Drug induced liver injury with analysis of alternative causes as confounding variables.

PubMed

Teschke, Rolf; Danan, Gaby

2018-04-01

Drug-induced liver injury (DILI) is rare compared to the worldwide frequent acute or chronic liver diseases. Therefore, patients included in series of suspected DILI are at high risk of not having DILI, whereby alternative causes may confound the DILI diagnosis. The aim of this review is to evaluate published case series of DILI for alternative causes. Relevant studies were identified using a computerized search of the Medline database for publications from 1993 through 30 October 2017. We used the following terms: drug hepatotoxicity, drug induced liver injury, hepatotoxic drugs combined with diagnosis, causality assessment and alternative causes. Alternative causes as variables confounding the DILI diagnosis emerged in 22 published DILI case series, ranging from 4 to 47%. Among 13 335 cases of suspected DILI, alternative causes were found to be more likely in 4555 patients (34.2%), suggesting that the suspected DILI was probably not DILI. Biliary diseases such as biliary obstruction, cholangitis, choledocholithiasis, primary biliary cholangitis and primary sclerosing cholangitis were among the most missed diagnoses. Alternative causes included hepatitis B, C and E, cytomegalovirus, Epstein-Barr virus, ischemic hepatitis, cardiac hepatopathy, autoimmune hepatitis, nonalcoholic fatty liver disease, nonalcoholic steatohepatitis, and alcoholic liver disease. In more than one-third of published global DILI case series, alternative causes as published in these reports confounded the DILI diagnosis. In the future, published DILI case series should include only patients with secured DILI diagnosis, preferentially established by prospective use of scored items provided by robust diagnostic algorithms such as the updated Roussel Uclaf causality assessment method. © 2018 The British Pharmacological Society.

The Honolulu Liver Disease Cluster at the Medical Center: Its Mysteries and Challenges

PubMed Central

Teschke, Rolf; Eickhoff, Axel

2016-01-01

In 2013, physicians at the Honolulu Queen’s Medical Center (QMC) noticed that seven liver disease patients reported the use of OxyELITE Pro (OEP), a widely consumed dietary supplement (DS). Assuming a temporal association between OEP use and disease, they argued that OEP was the cause of this mysterious cluster. Subsequent reexamination, however, has revealed that this QMC cohort is heterogeneous and not a cluster with a single agent causing a single disease. It is heterogeneous because patients used multiple DS’s and drugs and because patients appeared to have suffered from multiple liver diseases: liver cirrhosis, liver failure by acetaminophen, hepatotoxicity by non-steroidal antiinflammatory drugs (NSAIDs), resolving acute viral hepatitis by hepatitis B virus (HBV), herpes simplex virus (HSV), and varicella zoster virus (VZV), and suspected hepatitis E virus (HEV). Failing to exclude these confounders and to consider more viable diagnoses, the QMC physicians may have missed specific treatment options in some of their patients. The QMC physicians unjustifiably upgraded their Roussel Uclaf Causality Assessment Method (RUCAM) causality scores so that all patients would appear to be “probable” for OEP. However, subsequent RUCAM reassessments by our group demonstrated a lack of causality for OEP in the evaluated QMC cases. The QMC’s questionable approaches explain the extraordinary accumulation of suspected OEP cases at the QMC in Hawaii as single place, whereas similar cohorts were not published by any larger US liver center, substantiating that the problem is with the QMC. In this review article, we present and discuss new case data and critically evaluate upcoming developments of problematic regulatory assessments by the US Centers for Disease Control and Prevention (CDC), the Hawaii Department of Health (HDOH), and the Food and Drug Administration (FDA), as based on invalid QMC conclusions, clarifying now also basic facts and facilitating constructive discussions. PMID:27043544

A rare case of methimazole-induced cholestatic jaundice in an elderly man of Asian ethnicity with hyperthyroidism: A case report.

PubMed

Ji, Hongjian; Yue, Feng; Song, Jianxiang; Zhou, Xiaohua

2017-12-01

Methimazole is an antithyroid drug that is widely used for the treatment of hyperthyroidism. As an inhibitor of the enzyme thyroperoxidase, methimazole is generally well-tolerated. However, there have been increasing reports of methimazole-induced liver damage, although this effect of methimazole has been limited by the absence of objective diagnosis of the liver condition or the inappropriate use of the Naranjo scale. We present the case of an elderly man with hyperthyroidism, gastritis, and epilepsy who developed liver damage after administration of multiple drugs. Considering the low sensitivity of the Naranjo scale in detecting rare reactions associated with liver damage, we used the Roussel-Uclaf Causality Assessment Method scale, with a finding of cholestatic jaundice hepatitis induced by methimazole. The patient's liver enzyme levels improved after discontinuation of methimazole. Our case underlines the possible hepatoxicity associated with the use of methimazole. A review of the literature confirmed a selective hepatoxicity risk in individuals of Asian ethnicity, which has not been identified in Caucasian or Black populations. Physicians should be aware of the risk of hepatoxicity when prescribing oral methimazole to patients of Asian ethnicity.

A Case of Hepatotoxicity Induced by Adulterated "Tiger King", a Chinese Herbal Medicine Containing Sildenafil.

PubMed

Nissan, Ran; Poperno, Alina; Stein, Gideon Y; Shapira, Barak; Fuchs, Shmuel; Berkovitz, Ronny; Hess, Zipora; Arieli, Mickey

2016-01-01

Detection of Phosphodiesterase Type 5 (PDE-5) inhibitors and their analogues in "100% natural" or "herbal" supplements have been described in numerous reports. However, few reports have been published in relation to actual harm caused by counterfeit erectile dysfunction herbal supplements. We describe a case of a 65-year old male admitted to a tertiary hospital with acute liver toxicity, possibly induced by adulterated "Chinese herbal" supplement "Tiger King" for sexual enhancement. Chemical analysis of the tablets discovered the presence of therapeutic doses of sildenafil with no other herbal components. Other medications were excluded as potential causes of the hepatic impairment. According to the Naranjo adverse drug reaction scale and the Roussel Uclaf Causality Assessment Method (RUCAM) the probability of association of Hepatotoxicity with Sildenafil was "possible" and "probable" respectively (Naranjo score of 4, RUCAM score of 7). Within three days of admission, the patient's clinical status and liver function improved without any specific treatment. His liver function tests normalized 30 days post discharge. Further pharmacovigilance actions should be taken by regulatory authorities and pharmaceutical companies in order to determine the relation between sildenafil and hepatotoxicity. This case emphasizes the importance of raising public awareness on the potential dangers of "Tiger king" in particular, and other counterfeit medications or herbal supplements of unknown origin.

Multicenter study of trimethoprim/sulfamethoxazole-related hepatotoxicity: incidence and associated factors among HIV-infected patients treated for Pneumocystis jirovecii pneumonia.

PubMed

Yang, Jen-Jia; Huang, Chung-Hao; Liu, Chun-Eng; Tang, Hung-Jen; Yang, Chia-Jui; Lee, Yi-Chien; Lee, Kuan-Yeh; Tsai, Mao-Song; Lin, Shu-Wen; Chen, Yen-Hsu; Lu, Po-Liang; Hung, Chien-Ching

2014-01-01

The incidence of hepatotoxicity related to trimethoprim/sulfamethoxazole (TMP/SMX) administered at a therapeutic dose may vary among study populations of different ethnicities and hepatotoxic metabolites of TMP/SMX may be decreased by drug-drug interaction with fluconazole. We aimed to investigate the incidence of hepatotoxicity and the role of concomitant use of fluconazole in HIV-infected patients receiving TMP/SMX for Pneumocystis jirovecii pneumonia. We reviewed medical records to collect clinical characteristics and laboratory data of HIV-infected patients who received TMP/SMX for treatment of P. jirovecii pneumonia at 6 hospitals around Taiwan between September 2009 and February 2013. Hepatotoxicity was defined as 2-fold or greater increase of aminotransferase or total bilirubin level from baselines. Roussel UCLAF Causality Assessment Method (RUCAM) was used to analyze the causality of drug-induced liver injuries. NAT1 and NAT2 acetylator types were determined with the use of polymerase-chain-reaction (PCR) restriction fragment length polymorphism to differentiate common single-nucleotide polymorphisms (SNPs) predictive of the acetylator phenotypes in a subgroup of patients. During the study period, 286 courses of TMP/SMX treatment administered to 284 patients were analyzed. One hundred and fifty-two patients (53.1%) developed hepatotoxicity, and TMP/SMX was considered causative in 47 (16.4%) who had a RUCAM score of 6 or greater. In multivariate analysis, concomitant use of fluconazole for candidiasis was the only factor associated with reduced risk for hepatotoxicity (adjusted odds ratio, 0.372; 95% confidence interval, 0.145-0.957), while serostatus of hepatitis B or C virus, NAT1 and NAT2 acetylator types, or receipt of combination antiretroviral therapy was not. The incidence of hepatotoxicity decreased with an increasing daily dose of fluconazole up to 4.0 mg/kg. We conclude that the incidence of TMP/SMX-related hepatotoxicity was 16.4% in HIV-infected Taiwanese patients who received TMP/SMX for pneumocystosis. Concomitant use of fluconazole was associated with decreased risk for TMP/SMX-related hepatotoxicity.

Boycott threat forces French company to abandon RU486.

PubMed

Dorozynski, A

1997-04-19

Threatened boycotts by American anti-abortion groups have forced the French pharmaceutical company Roussel-Uclaf, a subsidiary of the German company Hoechst, to stop production and distribution of mifepristone (RU-486), which the protesters call "the abortion pill." All patent rights have been transferred, without charge, to Dr. Edouard Sarkiz, one of the pill's developers. Hoechst, which had acquired Marion Pharmaceuticals to form a new group, Hoechst-Marion-Roussel, had increased its share of the US pharmaceutical market from 1% to 4% in doing so and could not tolerate a boycott. RU-486, which was discovered by Professor Etienne Baulieu, was introduced in France in 1987 as an alternative to surgical abortion. Although Hoechst, then a majority stockholder of Roussel-Uclaf, had asked the French firm to interrupt production of the pill in 1988, the French minister of health and social affairs at that time, Claude Evin, ordered production to be continued. Approximately 25% of French women seeking abortion use RU-486; it is also used in Britain, Sweden, and China (women in China must pay for the drug, while surgical abortion is free). All American firms have refused to buy the drug from Roussel-Uclaf. An offer to the World Health Organization was ignored. The American Population Council obtained the right to use RU-486 in 1993. Dr. Sarkiz has formed Exelgyn, a small nonprofit company, to produce and distribute RU-486; research into other uses for the drug will also be conducted. There has been limited research into its use as an emergency contraceptive and as a treatment for endometriosis, uterine fibroma, and breast cancer. According to Professor Baulieu, the drug could be used in treating wounds and burns because of its antiglucocorticoid and immunosuppressive properties; preliminary research by the professor indicates the drug could also possibly be used as a reversible male contraceptive because of its action on the membranes of spermatozoa. The drug's use in abortion is due to its effect on the uterine mucus membrane.

Roussel-Uclaf to transfer RU 486 rights.

PubMed

1997-04-18

On April 8, the German pharmaceutical firm Hoechst, under pressure from anti-abortion groups that were boycotting its new allergy medication, Allegra, announced the transfer of the patent rights for the abortifacient mifepristone (RU-486), from Roussel-Uclaf, its subsidiary, to Dr. Edouard Sakiz, a former executive who had been involved in the development of the drug. Dr. Sakiz has established a new company, Exelgyn, to market the drug, which, due to strict company guidelines, is currently available only in France, Sweden, and the United Kingdom. Residency requirements prevent women from traveling to these countries for treatment. Other countries desiring access to RU-486 must meet standards established by Dr. Sakiz: the government must make a formal request and provide a secure means of distribution and good follow-up care. A European manufacturer or distributor has not yet been found. In the United States, the Population Council, a nonprofit organization, has been licensed to manufacture and distribute the drug; it should be available to the general public by the end of this year. Anti-abortion groups continue to boycott all Hoechst products. The Allegra boycott was launched with an April 2 press conference; the groups, which include the National Right to Life Committee, bought full-page ads in "USA Today" and "The Washington Post."

An Update on Drug-induced Liver Injury.

PubMed

Devarbhavi, Harshad

2012-09-01

Idiosyncratic drug-induced liver injury (DILI) is an important cause of morbidity and mortality following drugs taken in therapeutic doses. Hepatotoxicity is a leading cause of attrition in drug development, or withdrawal or restricted use after marketing. No age is exempt although adults and the elderly are at increased risk. DILI spans the entire spectrum ranging from asymptomatic elevation in transaminases to severe disease such as acute hepatitis leading to acute liver failure. The liver specific Roussel Uclaf Causality Assessment Method is the most validated and extensively used for determining the likelihood that an implicated drug caused DILI. Asymptomatic elevation in liver tests must be differentiated from adaptation. Drugs producing DILI have a signature pattern although no single pattern is characteristic. Antimicrobial and central nervous system agents including antiepileptic drugs are the leading causes of DILI worldwide. In the absence of a diagnostic test or a biomarker, the diagnosis rests on the evidence of absence of competing causes such as acute viral hepatitis, autoimmune hepatitis and others. Recent studies show that antituberculosis drugs given for active or latent disease are still a major cause of drug-induced liver injury in India and the West respectively. Presence of jaundice signifies a severe disease and entails a worse outcome. The pathogenesis is unclear and is due to a mix of host, drug metabolite and environmental factors. Research has evolved from incriminating candidate genes to genome wide analysis studies. Immediate cessation of the drug is key to prevent or minimize progressive damage. Treatment is largely supportive. N-acetylcysteine is the antidote for paracetamol toxicity. Carnitine has been tried in valproate injury whereas steroids and ursodeoxycholic acid may be used in DILI associated with hypersensitivity or cholestatic features respectively. This article provides an overview of the epidemiology, the patterns of hepatotoxicity, the pathogenesis and associated risk factors besides its clinical management.

Drug-Induced liver injury with hypersensitivity features has a better outcome: a single-center experience of 39 children and adolescents.

PubMed

Devarbhavi, Harshad; Karanth, Dheeraj; Prasanna, K S; Adarsh, C K; Patil, Mallikarjun

2011-10-01

Drug-induced liver injury (DILI) is rare in children and adolescents, and, consequently, data are remarkably limited. We analyzed the causes, clinical and biochemical features, natural history, and outcomes of children with DILI. Consecutive children with DILI from 1997 to 2004 (retrospective) and 2005 to 2010 (prospective) were studied based on standard criteria for DILI. Thirty-nine children constituted 8.7% of 450 cases of DILI. There were 22 boys and 17 girls. Median age was 16 years (range, 2.6-17). Combination antituberculous drugs were the most common cause (n = 22), followed by the anticonvulsants, phenytoin (n = 10) and carbamazepine (n = 6). All of the 16 children (41%) who developed hypersensitivity features, such as skin rashes, fever, lymphadenopathy, and/or eosinophilia, including the 3 with Stevens-Johnson syndrome, survived. Those with hypersensitivity presented earlier (24.5 versus 35 days; P = 0.24) had less severe disease (MELD, 16 versus 29; P = 0.01) and had no mortality (0/16 versus 12/23; P < 0.001), compared to those without hypersensitivity. The 12 fatalities were largely the result of antituberculous DILI (n = 11). The presence of encephalopathy and ascites were associated with mortality, along with hyperbilirubinemia, high international normalized ratio, and serum creatinine. According to the Roussel Uclaf Causality Assessment Method, 18 were highly probable, 14 probable, and 7 possible. Thirty-two children were hospitalized. DILI is not uncommon in children and accounts for 8.7% of all patients with DILI. Antituberculous drugs and anticonvulsants are the leading causes of DILI in India. Overall mortality is high (30.7%), largely accounted by antituberculous drugs. Children with DILI and hypersensitivity features present early, have less severe disease, and, consequently, a better prognosis, compared to those without, and are often associated with anticonvulsants or sulfonamides. Copyright © 2011 American Association for the Study of Liver Diseases.

Hepatic findings in long-term clinical trials of ximelagatran.

PubMed

Lee, William M; Larrey, Dominique; Olsson, Rolf; Lewis, James H; Keisu, Marianne; Auclert, Laurent; Sheth, Sunita

2005-01-01

In clinical trials, the efficacy and safety of the oral direct thrombin inhibitor ximelagatran have been evaluated in the prevention or treatment of thromboembolic conditions known to have high morbidity and mortality. In these studies, raised aminotransferase levels were observed during long-term use (>35 days). The aim of this analysis is to review the data regarding these hepatic findings in the long-term trials of ximelagatran. The prospective analysis included 6948 patients randomised to ximelagatran and 6230 patients randomised to comparator (warfarin, low-molecular weight heparin followed by warfarin or placebo). Of these, 6931 patients received ximelagatran for a mean of 357 days and 6216 patients received comparator for a mean of 389 days. An algorithm was developed for frequent testing of hepatic enzyme levels. A panel of four hepatologists analysed all cases of potential concern with regard to causal relation to ximelagatran treatment using an established evaluation tool (Roussel Uclaf Causality Assessment Method [RUCAM]). An elevated alanine aminotransferase (ALT) level of >3 x the upper limit of normal (ULN) was found in 7.9% of patients in the ximelagatran group versus 1.2% in the comparator group. The increase in ALT level occurred 1-6 months after initiation of therapy and data were available to confirm recovery of the ALT level to <2 x ULN in 96% of patients, whether they continued to receive ximelagatran or not. There was some variability in the incidence of ALT level elevation between indications, those with simultaneous acute illnesses (acute myocardial infarction or venous thromboembolism) having higher incidences. Combined elevations of ALT level of >3 x ULN and total bilirubin level of >2 x ULN (within 1 month of the ALT elevation), regardless of aetiology, were infrequent, occurring in 37 patients (0.5%) treated with ximelagatran, of whom one sustained a severe hepatic illness that appeared to be resolving when the patient died from a gastrointestinal haemorrhage. No death was observed directly related to hepatic failure caused by ximelagatran. Treatment with ximelagatran has been associated with mainly asymptomatic elevation of ALT levels in a mean of 7.9% of patients in the long-term clinical trial programme and nearly all of the cases occurred within the first 6 months of therapy. Rare symptomatic cases have been observed. An algorithm has been developed for testing ALT to ensure appropriate management of patients with elevated ALT levels. Regular ALT testing should allow the clinical benefits of ximelagatran to reach the widest population of patients while minimising the risk of hepatic adverse effects.

In Support of Clinical Case Reports: A System of Causality Assessment

PubMed Central

Hamre, Harald J.; Kienle, Gunver S.

2013-01-01

The usefulness of clinical research depends on an assessment of causality. This assessment determines what constitutes clinical evidence. Case reports are an example of evidence that is frequently overlooked because it is believed they cannot address causal links between treatment and outcomes. This may be a mistake. Clarity on the topic of causality and its assessment will be of benefit for researchers and clinicians. This article outlines an overall system of causality and causality assessment. The system proposed involves two dimensions: horizontal and vertical; each of these dimensions consists of three different types of causality and three corresponding types of causality assessment. Included in this system are diverse forms of case causality illustrated with examples from everyday life and clinical medicine. Assessing case causality can complement conventional clinical research in an era of personalized medicine. PMID:24416665

CADDIS Volume 1. Stressor Identification: About Causal Assessment

EPA Pesticide Factsheets

An introduction to the history of our approach to causal assessment, A chronology of causal history and philosophy, An introduction to causal history and philosophy, References for the Causal Assessment Background section of Stressor Identification

Assessing Understanding of Complex Causal Networks Using an Interactive Game

ERIC Educational Resources Information Center

Ross, Joel

2013-01-01

Assessing people's understanding of the causal relationships found in large-scale complex systems may be necessary for addressing many critical social concerns, such as environmental sustainability. Existing methods for assessing systems thinking and causal understanding frequently use the technique of cognitive causal mapping. However, the…

Drug and herb induced liver injury: Council for International Organizations of Medical Sciences scale for causality assessment

PubMed Central

Teschke, Rolf; Wolff, Albrecht; Frenzel, Christian; Schwarzenboeck, Alexander; Schulze, Johannes; Eickhoff, Axel

2014-01-01

Causality assessment of suspected drug induced liver injury (DILI) and herb induced liver injury (HILI) is hampered by the lack of a standardized approach to be used by attending physicians and at various subsequent evaluating levels. The aim of this review was to analyze the suitability of the liver specific Council for International Organizations of Medical Sciences (CIOMS) scale as a standard tool for causality assessment in DILI and HILI cases. PubMed database was searched for the following terms: drug induced liver injury; herb induced liver injury; DILI causality assessment; and HILI causality assessment. The strength of the CIOMS lies in its potential as a standardized scale for DILI and HILI causality assessment. Other advantages include its liver specificity and its validation for hepatotoxicity with excellent sensitivity, specificity and predictive validity, based on cases with a positive reexposure test. This scale allows prospective collection of all relevant data required for a valid causality assessment. It does not require expert knowledge in hepatotoxicity and its results may subsequently be refined. Weaknesses of the CIOMS scale include the limited exclusion of alternative causes and qualitatively graded risk factors. In conclusion, CIOMS appears to be suitable as a standard scale for attending physicians, regulatory agencies, expert panels and other scientists to provide a standardized, reproducible causality assessment in suspected DILI and HILI cases, applicable primarily at all assessing levels involved. PMID:24653791

Imputation of adverse drug reactions: Causality assessment in hospitals

PubMed Central

Mastroianni, Patricia de Carvalho

2017-01-01

Background & objectives Different algorithms have been developed to standardize the causality assessment of adverse drug reactions (ADR). Although most share common characteristics, the results of the causality assessment are variable depending on the algorithm used. Therefore, using 10 different algorithms, the study aimed to compare inter-rater and multi-rater agreement for ADR causality assessment and identify the most consistent to hospitals. Methods Using ten causality algorithms, four judges independently assessed the first 44 cases of ADRs reported during the first year of implementation of a risk management service in a medium complexity hospital in the state of Sao Paulo (Brazil). Owing to variations in the terminology used for causality, the equivalent imputation terms were grouped into four categories: definite, probable, possible and unlikely. Inter-rater and multi-rater agreement analysis was performed by calculating the Cohen´s and Light´s kappa coefficients, respectively. Results None of the algorithms showed 100% reproducibility in the causal imputation. Fair inter-rater and multi-rater agreement was found. Emanuele (1984) and WHO-UMC (2010) algorithms showed a fair rate of agreement between the judges (k = 0.36). Interpretation & conclusions Although the ADR causality assessment algorithms were poorly reproducible, our data suggest that WHO-UMC algorithm is the most consistent for imputation in hospitals, since it allows evaluating the quality of the report. However, to improve the ability of assessing the causality using algorithms, it is necessary to include criteria for the evaluation of drug-related problems, which may be related to confounding variables that underestimate the causal association. PMID:28166274

[Population Council responsible for RU486 clinical trials in USA].

PubMed

Aguillaume, C J

1993-04-01

As a result of the sudden political change that came with the Clinton Administration, RU-486's manufacturer, Roussel-Uclaf, and the Population Council agreed on April 20, 1992, on the manufacture and distribution of RU-486 in the US. In the US, there are less than 1.6 million induced abortions annually. From now on, US women will be able to have a choice between medical and surgical abortion. The Population Council and Roussel-Uclaf have had a contract since 1982. The Council is solely responsible for the phase 2 clinical trial of RU-486 in the US and other countries. It must present to the US Food and Drug Administration (FDA) an amendment allowing it to begin phase 3 clinical trials. The Council will also lead the US medical facilities in this study. It will identify partners for future production of RU-486 and its distribution in the US. It will also submit to FDA a New Drug Application (NDA). FDA will review the scientific literature on RU-486 and evaluate all data submitted by the Population Council. There are still obstacles to be surmounted. The Population Council must demonstrate good judgment when selecting the criteria for choosing a pharmaceutical firm before a Technical Committee which will be part of a group of players promoting women's health, scientific experts, and other interested parties. It must find the necessary funds to conduct the clinical trials and prepare the NDA. Phase 3 clinical trials in the US must have at least 2000 women. They will test RU-486's efficacy, safety, and acceptability among women choosing medical abortion over surgical abortion. Since the Council operates in almost all countries in the world, has innovated contraceptive research and development activities, and has been endorsed by the UN, product approval of RU-486 in the US will affect policy in all countries concerned about abortion.

RU 486 in France and England: corporate ethics and compulsory licensing.

PubMed

Boland, R

1992-01-01

Prospects for the introduction of RU-486 into the US in the foreseeable future are not good. The governments of France and England moved forward expeditiously with testing and approval of the drug. The legal developments surrounding the introduction of RU-486 in France and England as well as American, French, and English legal issues of corporate responsibility for licensing valuable drugs and compulsory licensing are outlined. The French government on October 28, 1988, ordered the company Roussel-Uclaf to resume plans to distribute RU-486 out of concern for public health and stated that RU-486 was the moral property of women. Roussel-Uclaf agreed to resume plans for distribution. RU-486 suits were finally decided in late 1990 and early 1991 by the State Council, France's highest administrative court, which issued a series of significant rulings. The French government issued new rules prohibiting the use of RU-486 by women who are heavy smokers or over 35 years old and modifying the dose of prostaglandin to be administered because of an RU-486-related death of an overweight 31-year old woman. In England, RU-486 was initially approved in July 1991. The conditions set were similar to those in France: the drug would have be used within 9 weeks of amenorrhea, as opposed to 7 in France; women over 35 or moderate to heavy smokers would be ineligible; and visits 36-48 hours later would be necessary to have a prostaglandin administered with check ups 7-10 days later. The hostility of the current US administration to the introduction of RU-486 blocks access to the drug. In 1989, the Food and Drug Administration placed reluctant to enter the American market. Under the Bush administration there is little possibility that the American government will act and take an active role in facilitating access to RU-486.

Accounting for respiration is necessary to reliably infer Granger causality from cardiovascular variability series.

PubMed

Porta, Alberto; Bassani, Tito; Bari, Vlasta; Pinna, Gian D; Maestri, Roberto; Guzzetti, Stefano

2012-03-01

This study was designed to demonstrate the need of accounting for respiration (R) when causality between heart period (HP) and systolic arterial pressure (SAP) is under scrutiny. Simulations generated according to a bivariate autoregressive closed-loop model were utilized to assess how causality changes as a function of the model parameters. An exogenous (X) signal was added to the bivariate autoregressive closed-loop model to evaluate the bias on causality induced when the X source was disregarded. Causality was assessed in the time domain according to a predictability improvement approach (i.e., Granger causality). HP and SAP variability series were recorded with R in 19 healthy subjects during spontaneous and controlled breathing at 10, 15, and 20 breaths/min. Simulations proved the importance of accounting for X signals. During spontaneous breathing, assessing causality without taking into consideration R leads to a significantly larger percentage of closed-loop interactions and a smaller fraction of unidirectional causality from HP to SAP. This finding was confirmed during paced breathing and it was independent of the breathing rate. These results suggest that the role of baroreflex cannot be correctly assessed without accounting for R.

Herbal hepatotoxicity: Challenges and pitfalls of causality assessment methods

PubMed Central

Teschke, Rolf; Frenzel, Christian; Schulze, Johannes; Eickhoff, Axel

2013-01-01

The diagnosis of herbal hepatotoxicity or herb induced liver injury (HILI) represents a particular clinical and regulatory challenge with major pitfalls for the causality evaluation. At the day HILI is suspected in a patient, physicians should start assessing the quality of the used herbal product, optimizing the clinical data for completeness, and applying the Council for International Organizations of Medical Sciences (CIOMS) scale for initial causality assessment. This scale is structured, quantitative, liver specific, and validated for hepatotoxicity cases. Its items provide individual scores, which together yield causality levels of highly probable, probable, possible, unlikely, and excluded. After completion by additional information including raw data, this scale with all items should be reported to regulatory agencies and manufacturers for further evaluation. The CIOMS scale is preferred as tool for assessing causality in hepatotoxicity cases, compared to numerous other causality assessment methods, which are inferior on various grounds. Among these disputed methods are the Maria and Victorino scale, an insufficiently qualified, shortened version of the CIOMS scale, as well as various liver unspecific methods such as the ad hoc causality approach, the Naranjo scale, the World Health Organization (WHO) method, and the Karch and Lasagna method. An expert panel is required for the Drug Induced Liver Injury Network method, the WHO method, and other approaches based on expert opinion, which provide retrospective analyses with a long delay and thereby prevent a timely assessment of the illness in question by the physician. In conclusion, HILI causality assessment is challenging and is best achieved by the liver specific CIOMS scale, avoiding pitfalls commonly observed with other approaches. PMID:23704820

Evaluation of the causal framework used for setting national ambient air quality standards.

PubMed

Goodman, Julie E; Prueitt, Robyn L; Sax, Sonja N; Bailey, Lisa A; Rhomberg, Lorenz R

2013-11-01

Abstract A scientifically sound assessment of the potential hazards associated with a substance requires a systematic, objective and transparent evaluation of the weight of evidence (WoE) for causality of health effects. We critically evaluated the current WoE framework for causal determination used in the United States Environmental Protection Agency's (EPA's) assessments of the scientific data on air pollutants for the National Ambient Air Quality Standards (NAAQS) review process, including its methods for literature searches; study selection, evaluation and integration; and causal judgments. The causal framework used in recent NAAQS evaluations has many valuable features, but it could be more explicit in some cases, and some features are missing that should be included in every WoE evaluation. Because of this, it has not always been applied consistently in evaluations of causality, leading to conclusions that are not always supported by the overall WoE, as we demonstrate using EPA's ozone Integrated Science Assessment as a case study. We propose additions to the NAAQS causal framework based on best practices gleaned from a previously conducted survey of available WoE frameworks. A revision of the NAAQS causal framework so that it more closely aligns with these best practices and the full and consistent application of the framework will improve future assessments of the potential health effects of criteria air pollutants by making the assessments more thorough, transparent, and scientifically sound.

Bayesian networks improve causal environmental assessments for evidence-based policy

EPA Science Inventory

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the p...

Application of the revised WHO causality assessment protocol for adverse events following immunization in India.

PubMed

Singh, Awnish Kumar; Wagner, Abram L; Joshi, Jyoti; Carlson, Bradley F; Aneja, Satinder; Boulton, Matthew L

2017-07-24

In 2013, the World Health Organization (WHO) and CIOMS introduced a revised Causality Assessment Protocol (CAP) for Adverse Events following Immunization (AEFI). India is one of the first countries to adopt the revised CAP. This study describes the application of the revised CAP in India. We describe use of CAP by India's AEFI surveillance program to assess reported AEFIs. Using publicly available results of causality assessment for reported AEFIs, we describe the results by demographic characteristics and review the trends for the results of the causality assessment. A total of 771 reports of AEFI between January 2012 and January 2015, completed causality review by August 2016. The cases were reported as belonging to a cluster (54%; n=302), hospitalized or requiring hospitalization (41%; n=270), death (25%; n=195), or resulting in disability (0.4%; n=3). The most common combinations of vaccines leading to report of an AEFI were DTwP, Hepatitis B, and OPV (14%; n=106), followed by Pentavalent and OPV (13%; n=103), and JE vaccine (13%; n=101). Using the WHO Algorithm, most AEFI reports (89%, n=683) were classifiable. Classifiable AEFI reports included those with a consistent causal association (53%; n=407), an inconsistent causal association (29%; n=226) or were indeterminate causal association with implicated vaccine(s) or vaccination process (6.5%; n=50) (Fig. 1); 88 reports remained unclassifiable. The revised CAP was informative and useful in classifying most of the reviewed AEFIs in India. Unclassifiable reports could be minimized with more complete information from health records. Improvements in causality assessment, and standardization in reporting between countries, can improve public confidence in vaccine system performance and identify important vaccine safety signals. Copyright © 2017 Elsevier Ltd. All rights reserved.

Causal modelling applied to the risk assessment of a wastewater discharge.

PubMed

Paul, Warren L; Rokahr, Pat A; Webb, Jeff M; Rees, Gavin N; Clune, Tim S

2016-03-01

Bayesian networks (BNs), or causal Bayesian networks, have become quite popular in ecological risk assessment and natural resource management because of their utility as a communication and decision-support tool. Since their development in the field of artificial intelligence in the 1980s, however, Bayesian networks have evolved and merged with structural equation modelling (SEM). Unlike BNs, which are constrained to encode causal knowledge in conditional probability tables, SEMs encode this knowledge in structural equations, which is thought to be a more natural language for expressing causal information. This merger has clarified the causal content of SEMs and generalised the method such that it can now be performed using standard statistical techniques. As it was with BNs, the utility of this new generation of SEM in ecological risk assessment will need to be demonstrated with examples to foster an understanding and acceptance of the method. Here, we applied SEM to the risk assessment of a wastewater discharge to a stream, with a particular focus on the process of translating a causal diagram (conceptual model) into a statistical model which might then be used in the decision-making and evaluation stages of the risk assessment. The process of building and testing a spatial causal model is demonstrated using data from a spatial sampling design, and the implications of the resulting model are discussed in terms of the risk assessment. It is argued that a spatiotemporal causal model would have greater external validity than the spatial model, enabling broader generalisations to be made regarding the impact of a discharge, and greater value as a tool for evaluating the effects of potential treatment plant upgrades. Suggestions are made on how the causal model could be augmented to include temporal as well as spatial information, including suggestions for appropriate statistical models and analyses.

Drug- and Herb-Induced Liver Injury in Clinical and Translational Hepatology: Causality Assessment Methods, Quo Vadis?

PubMed Central

Eickhoff, Axel; Schulze, Johannes

2013-01-01

Drug-induced liver injury (DILI) and herb-induced liver injury (HILI) are typical diseases of clinical and translational hepatology. Their diagnosis is complex and requires an experienced clinician to translate basic science into clinical judgment and identify a valid causality algorithm. To prospectively assess causality starting on the day DILI or HILI is suspected, the best approach for physicians is to use the Council for International Organizations of Medical Sciences (CIOMS) scale in its original or preferably its updated version. The CIOMS scale is validated, liver-specific, structured, and quantitative, providing final causality grades based on scores of specific items for individual patients. These items include latency period, decline in liver values after treatment cessation, risk factors, co-medication, alternative diagnoses, hepatotoxicity track record of the suspected product, and unintentional re-exposure. Provided causality is established as probable or highly probable, data of the CIOMS scale with all individual items, a short clinical report, and complete raw data should be transmitted to the regulatory agencies, manufacturers, expert panels, and possibly to the scientific community for further refinement of the causality evaluation in a setting of retrospective expert opinion. Good-quality case data combined with thorough CIOMS-based assessment as a standardized approach should avert subsequent necessity for other complex causality assessment methods that may have inter-rater problems because of poor-quality data. In the future, the CIOMS scale will continue to be the preferred tool to assess causality of DILI and HILI cases and should be used consistently, both prospectively by physicians, and retrospectively for subsequent expert opinion if needed. For comparability and international harmonization, all parties assessing causality in DILI and HILI cases should attempt this standardized approach using the updated CIOMS scale. PMID:26357608

Development and Inter-Rater Reliability of the Liverpool Adverse Drug Reaction Causality Assessment Tool

PubMed Central

Gallagher, Ruairi M.; Kirkham, Jamie J.; Mason, Jennifer R.; Bird, Kim A.; Williamson, Paula R.; Nunn, Anthony J.; Turner, Mark A.; Smyth, Rosalind L.; Pirmohamed, Munir

2011-01-01

Aim To develop and test a new adverse drug reaction (ADR) causality assessment tool (CAT). Methods A comparison between seven assessors of a new CAT, formulated by an expert focus group, compared with the Naranjo CAT in 80 cases from a prospective observational study and 37 published ADR case reports (819 causality assessments in total). Main Outcome Measures Utilisation of causality categories, measure of disagreements, inter-rater reliability (IRR). Results The Liverpool ADR CAT, using 40 cases from an observational study, showed causality categories of 1 unlikely, 62 possible, 92 probable and 125 definite (1, 62, 92, 125) and ‘moderate’ IRR (kappa 0.48), compared to Naranjo (0, 100, 172, 8) with ‘moderate’ IRR (kappa 0.45). In a further 40 cases, the Liverpool tool (0, 66, 81, 133) showed ‘good’ IRR (kappa 0.6) while Naranjo (1, 90, 185, 4) remained ‘moderate’. Conclusion The Liverpool tool assigns the full range of causality categories and shows good IRR. Further assessment by different investigators in different settings is needed to fully assess the utility of this tool. PMID:22194808

How Can Historical Understanding Best be Assessed? Use of Prediction Tasks To Assess How Students Understand the Role of Causal Factors that Produce Historical Events.

ERIC Educational Resources Information Center

Alonso-Tapia, Jesus; Villa, Jose Luis

1999-01-01

Examines the viability of using hypothetical problems that need the application of causal models for their solution as a method to assessing understanding in the social sciences. Explains that this method was used to describe how seventh-grade students understand causal factors affecting the "discovery and colonization of America." (CMK)

Causal explanations of distress and general practitioners' assessments of common mental disorder among punjabi and English attendees.

PubMed

Bhui, Kamaldeep; Bhugra, Dinesh; Goldberg, David

2002-01-01

The literature on the primary care assessment of mental distress among Indian subcontinent origin patients suggests frequent presentations to general practitioner, but rarely for recognisable psychiatric disorders. This study investigates whether cultural variations in patients' causal explanatory models account for cultural variations in the assessment of non-psychotic mental disorders in primary care. In a two-phase survey, 272 Punjabi and 269 English subjects were screened. The second phase was completed by 209 and 180 subjects, respectively. Causal explanatory models were elicited as explanations of two vignette scenarios. One of these emphasised a somatic presentation and the other anxiety symptoms. Psychiatric disorder was assessed by GPs on a Likert scale and by a psychiatrist on the Clinical Interview Schedule. Punjabis more commonly expressed medical/somatic and religious beliefs. General practitioners were more likely to assess any subject giving psychological explanations to vignette A and English subjects giving religious explanations to vignette B as having a significant psychiatric disorder. Where medical/somatic explanations of distress were most prevalent in response to the somatic vignette, psychological, religious and work explanations were less prevalent among Punjabis but not among English subjects. Causal explanations did not fully explain cultural differences in assessments. General practitioners' assessments and causal explanations are related and influenced by culture, but causal explanations do not fully explain cultural differences in assessments.

Causality Assessment of Olfactory and Gustatory Dysfunction Associated with Intranasal Fluticasone Propionate: Application of the Bradford Hill Criteria.

PubMed

Muganurmath, Chandrashekhar S; Curry, Amy L; Schindzielorz, Andrew H

2018-02-01

Causality assessment is crucial to post-marketing pharmacovigilance and helps optimize safe and appropriate use of medicines by patients in the real world. Self-reported olfactory and gustatory dysfunction are common in the general population as well as in patients with allergic rhinitis and nasal polyposis. Intranasal corticosteroids, including intranasal fluticasone propionate (INFP), are amongst the most effective drugs indicated in the treatment of allergic rhinitis and nasal polyposis. While intranasal corticosteroids are associated with olfactory and gustatory dysfunction and are currently labeled for these adverse events, causality assessment has not been performed to date. Although there is no single widely accepted method to assess causality in pharmacovigilance, the Bradford Hill criteria offer a robust and comprehensive approach because nine distinct aspects of an observed potential drug-event association are assessed. In this literature-based narrative review, Hill's criteria were applied to determine causal inference between INFP and olfactory and gustatory dysfunction.

Causal Inferences with Large Scale Assessment Data: Using a Validity Framework

ERIC Educational Resources Information Center

Rutkowski, David; Delandshere, Ginette

2016-01-01

To answer the calls for stronger evidence by the policy community, educational researchers and their associated organizations increasingly demand more studies that can yield causal inferences. International large scale assessments (ILSAs) have been targeted as a rich data sources for causal research. It is in this context that we take up a…

Inferring causal molecular networks: empirical assessment through a community-based effort

PubMed Central

Hill, Steven M.; Heiser, Laura M.; Cokelaer, Thomas; Unger, Michael; Nesser, Nicole K.; Carlin, Daniel E.; Zhang, Yang; Sokolov, Artem; Paull, Evan O.; Wong, Chris K.; Graim, Kiley; Bivol, Adrian; Wang, Haizhou; Zhu, Fan; Afsari, Bahman; Danilova, Ludmila V.; Favorov, Alexander V.; Lee, Wai Shing; Taylor, Dane; Hu, Chenyue W.; Long, Byron L.; Noren, David P.; Bisberg, Alexander J.; Mills, Gordon B.; Gray, Joe W.; Kellen, Michael; Norman, Thea; Friend, Stephen; Qutub, Amina A.; Fertig, Elana J.; Guan, Yuanfang; Song, Mingzhou; Stuart, Joshua M.; Spellman, Paul T.; Koeppl, Heinz; Stolovitzky, Gustavo; Saez-Rodriguez, Julio; Mukherjee, Sach

2016-01-01

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks. PMID:26901648

Strengthening of causality assessment of adverse events following immunization in the WHO South East Asia and Western Pacific regions: Lessons from the 2014 SEAR inter-country workshop.

PubMed

MacDonald, Noni E; Guichard, Stephane; Amarasinghe, Ananda; Balakrishnan, Madhava Ram

2015-11-27

Poorly managed AEFI undermine immunization programs. Improved surveillance in SEAR countries means more AEFIs but management varies. SEAR brought countries together to share AEFI experiences, and learn more about causality assessment. Three day 10 country workshop (9 SEAR; 1 WPR). Participants outlined county AEFI experiences, undertook causality assessment for 8 AEFIs using WHO methodology, critiqued the process by questionnaire and had a discussion. All 10 valued AEFI monitoring and causality assessment, and praised the opportunity to share experiences. Participants determined a range of AEFI and causality assessment needs in SEAR such as adapting WHO Algorithm, CIOMS/Brighton definitions, WHO verbal autopsy to fit context, requesting a practical guide--AEFI definition, time interval, rates of AEFI for different vaccines and evidence for vaccine related causes of death under 24h. LMIC need WHO AEFI tools adapted to better fit LMIC. Learning from each other builds capacity. Sharing AEFI experiences, case reviews help LMIC improve practices. Copyright © 2015. Published by Elsevier Ltd.

CADDIS Volume 5. Causal Databases: Home page (Duplicate?)

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

Reasoning with Causal Cycles

ERIC Educational Resources Information Center

Rehder, Bob

2017-01-01

This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…

CADDIS Volume 5. Causal Databases: Interactive Conceptual Diagrams (ICDs) User Guide

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

Formulating and Answering High-Impact Causal Questions in Physiologic Childbirth Science: Concepts and Assumptions.

PubMed

Snowden, Jonathan M; Tilden, Ellen L; Odden, Michelle C

2018-06-08

In this article, we conclude our 3-part series by focusing on several concepts that have proven useful for formulating causal questions and inferring causal effects. The process of causal inference is of key importance for physiologic childbirth science, so each concept is grounded in content related to women at low risk for perinatal complications. A prerequisite to causal inference is determining that the question of interest is causal rather than descriptive or predictive. Another critical step in defining a high-impact causal question is assessing the state of existing research for evidence of causality. We introduce 2 causal frameworks that are useful for this undertaking, Hill's causal considerations and the sufficient-component cause model. We then provide 3 steps to aid perinatal researchers in inferring causal effects in a given study. First, the researcher should formulate a rigorous and clear causal question. We introduce an example of epidural analgesia and labor progression to demonstrate this process, including the central role of temporality. Next, the researcher should assess the suitability of the given data set to answer this causal question. In randomized controlled trials, data are collected with the express purpose of answering the causal question. Investigators using observational data should also ensure that their chosen causal question is answerable with the available data. Finally, investigators should design an analysis plan that targets the causal question of interest. Some data structures (eg, time-dependent confounding by labor progress when estimating the effect of epidural analgesia on postpartum hemorrhage) require specific analytical tools to control for bias and estimate causal effects. The assumptions of consistency, exchangeability, and positivity may be especially useful in carrying out these steps. Drawing on appropriate causal concepts and considering relevant assumptions strengthens our confidence that research has reduced the likelihood of alternative explanations (eg bias, chance) and estimated a causal effect. © 2018 by the American College of Nurse-Midwives.

Perceived Causal Relations: Novel Methodology for Assessing Client Attributions about Causal Associations between Variables Including Symptoms and Functional Impairment

ERIC Educational Resources Information Center

Frewen, Paul A.; Allen, Samantha L.; Lanius, Ruth A.; Neufeld, Richard W. J.

2012-01-01

Researchers have argued that the investigation of causal interrelationships between symptoms may help explain the high comorbidity rate between certain psychiatric disorders. Clients' own attributions concerning the causal interrelationships linking the co-occurrence of their symptoms represent data that may inform their clinical case…

Causal Mediation in Educational Research: An Illustration Using International Assessment Data

ERIC Educational Resources Information Center

Caro, Daniel H.

2015-01-01

This paper applies the causal mediation framework proposed by Kosuke Imai and colleagues (Imai, Keele, & Tingley, 2010) to educational research by examining the causal mediating role of early literacy activities in parental education influences on reading performance. The paper argues that the study of causal mediation is particularly relevant…

Learning to make things happen: Infants' observational learning of social and physical causal events.

PubMed

Waismeyer, Anna; Meltzoff, Andrew N

2017-10-01

Infants learn about cause and effect through hands-on experience; however, they also can learn about causality simply from observation. Such observational causal learning is a central mechanism by which infants learn from and about other people. Across three experiments, we tested infants' observational causal learning of both social and physical causal events. Experiment 1 assessed infants' learning of a physical event in the absence of visible spatial contact between the causes and effects. Experiment 2 developed a novel paradigm to assess whether infants could learn about a social causal event from third-party observation of a social interaction between two people. Experiment 3 compared learning of physical and social events when the outcomes occurred probabilistically (happening some, but not all, of the time). Infants demonstrated significant learning in all three experiments, although learning about probabilistic cause-effect relations was most difficult. These findings about infant observational causal learning have implications for children's rapid nonverbal learning about people, things, and their causal relations. Copyright © 2017 Elsevier Inc. All rights reserved.

A Causal-Comparative Study of the Affects of Benchmark Assessments on Middle Grades Science Achievement Scores

ERIC Educational Resources Information Center

Galloway, Melissa Ritchie

2016-01-01

The purpose of this causal comparative study was to test the theory of assessment that relates benchmark assessments to the Georgia middle grades science Criterion Referenced Competency Test (CRCT) percentages, controlling for schools who do not administer benchmark assessments versus schools who do administer benchmark assessments for all middle…

CADDIS Volume 5. Causal Databases: Interactive Conceptual Diagrams (ICDs) Quick Start Instructions

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

Causal Analysis/Diagnosis Decision Information System (CADDIS)

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems to determine the cause of contamination.

Inferring causal molecular networks: empirical assessment through a community-based effort.

PubMed

Hill, Steven M; Heiser, Laura M; Cokelaer, Thomas; Unger, Michael; Nesser, Nicole K; Carlin, Daniel E; Zhang, Yang; Sokolov, Artem; Paull, Evan O; Wong, Chris K; Graim, Kiley; Bivol, Adrian; Wang, Haizhou; Zhu, Fan; Afsari, Bahman; Danilova, Ludmila V; Favorov, Alexander V; Lee, Wai Shing; Taylor, Dane; Hu, Chenyue W; Long, Byron L; Noren, David P; Bisberg, Alexander J; Mills, Gordon B; Gray, Joe W; Kellen, Michael; Norman, Thea; Friend, Stephen; Qutub, Amina A; Fertig, Elana J; Guan, Yuanfang; Song, Mingzhou; Stuart, Joshua M; Spellman, Paul T; Koeppl, Heinz; Stolovitzky, Gustavo; Saez-Rodriguez, Julio; Mukherjee, Sach

2016-04-01

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense.

Human Papilloma Viruses and Breast Cancer - Assessment of Causality.

PubMed

Lawson, James Sutherland; Glenn, Wendy K; Whitaker, Noel James

2016-01-01

High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case-control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is "specificity." HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers.

Human Papilloma Viruses and Breast Cancer – Assessment of Causality

PubMed Central

Lawson, James Sutherland; Glenn, Wendy K.; Whitaker, Noel James

2016-01-01

High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case–control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is “specificity.” HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers. PMID:27747193

Monitoring signals for vaccine safety: the assessment of individual adverse event reports by an expert advisory committee. Advisory Committee on Causality Assessment.

PubMed Central

Collet, J. P.; MacDonald, N.; Cashman, N.; Pless, R.

2000-01-01

Monitoring vaccine safety is a complex and shared responsibility. It can be carried out in many ways, one of which is the reporting of individual cases of adverse reactions thought to be due to vaccination. The task is difficult because ascribing causality to an individual case report is fraught with challenges. A standardized evaluation instrument--known as the causality assessment form--was therefore developed for use by an expert advisory committee to facilitate the process. By following the several sections in this form, the members of the committee are taken through a series of points to establish causality. These points include the basic criteria for causation such as biological plausibility, the time elapsed between the vaccine administration and the onset of the adverse event, and whether other factors (drugs, chemicals or underlying disease) could account for the adverse symptoms. The form concludes with a consensus assessment of causality, a commentary about the assessment, and advice for further study or follow-up. This method of assessing the more serious cases of adverse reaction reported to vaccination has proven useful in evaluating ongoing safety of vaccines in Canada. Through analyses such as this, new signals can be identified and investigated further. PMID:10743282

Causal Assessment of Biological Impairment in the Bogue Homo River, Mississippi Using the U.S. EPA’s Stressor Identification Methodology (Final)

EPA Science Inventory

EPA announced the availability of the final report, Causal Assessment of Biological Impairment in the Bogue Homo River, Mississippi Using the U.S. EPA’s Stressor Identification Methodology. This assessment is taken from more than 700 court ordered assessments of the cau...

Causality or Relatedness Assessment in Adverse Drug Reaction and Its Relevance in Dermatology.

PubMed

Pande, Sushil

2018-01-01

Causality assessment essentially means finding a causal association or relationship between a drug and drug reaction. Identifying the culprit drug or drugs can be lifesaving or helpful in preventing the further damage caused by the drug to our body systems. In dermatology practice, when it comes to cutaneous adverse drug reaction, this is much more important and relevant because many aetiologies can produce a similar cutaneous manifestation. There are multiple criteria or algorithms available as of now for establishing a causal relationship in cases of adverse drug reaction (ADR), indicating that none of them is specific or complete. Most of these causality assessment tools (CATs) use four cardinal principles of diagnosis of ADR such as temporal relationship of drug with the drug reaction, biological plausibility of the drug causing a reaction, dechallenge, and rechallenge. The present study reviews some of the established or commonly used CATs and its implications or relevance to dermatology in clinical practice.

Causality and causal inference in epidemiology: the need for a pluralistic approach

PubMed Central

Vandenbroucke, Jan P; Broadbent, Alex; Pearce, Neil

2016-01-01

Abstract Causal inference based on a restricted version of the potential outcomes approach reasoning is assuming an increasingly prominent place in the teaching and practice of epidemiology. The proposed concepts and methods are useful for particular problems, but it would be of concern if the theory and practice of the complete field of epidemiology were to become restricted to this single approach to causal inference. Our concerns are that this theory restricts the questions that epidemiologists may ask and the study designs that they may consider. It also restricts the evidence that may be considered acceptable to assess causality, and thereby the evidence that may be considered acceptable for scientific and public health decision making. These restrictions are based on a particular conceptual framework for thinking about causality. In Section 1, we describe the characteristics of the restricted potential outcomes approach (RPOA) and show that there is a methodological movement which advocates these principles, not just for solving particular problems, but as ideals for which epidemiology as a whole should strive. In Section 2, we seek to show that the limitation of epidemiology to one particular view of the nature of causality is problematic. In Section 3, we argue that the RPOA is also problematic with regard to the assessment of causality. We argue that it threatens to restrict study design choice, to wrongly discredit the results of types of observational studies that have been very useful in the past and to damage the teaching of epidemiological reasoning. Finally, in Section 4 we set out what we regard as a more reasonable ‘working hypothesis’ as to the nature of causality and its assessment: pragmatic pluralism. PMID:26800751

Causality and causal inference in epidemiology: the need for a pluralistic approach.

PubMed

Vandenbroucke, Jan P; Broadbent, Alex; Pearce, Neil

2016-12-01

Causal inference based on a restricted version of the potential outcomes approach reasoning is assuming an increasingly prominent place in the teaching and practice of epidemiology. The proposed concepts and methods are useful for particular problems, but it would be of concern if the theory and practice of the complete field of epidemiology were to become restricted to this single approach to causal inference. Our concerns are that this theory restricts the questions that epidemiologists may ask and the study designs that they may consider. It also restricts the evidence that may be considered acceptable to assess causality, and thereby the evidence that may be considered acceptable for scientific and public health decision making. These restrictions are based on a particular conceptual framework for thinking about causality. In Section 1, we describe the characteristics of the restricted potential outcomes approach (RPOA) and show that there is a methodological movement which advocates these principles, not just for solving particular problems, but as ideals for which epidemiology as a whole should strive. In Section 2, we seek to show that the limitation of epidemiology to one particular view of the nature of causality is problematic. In Section 3, we argue that the RPOA is also problematic with regard to the assessment of causality. We argue that it threatens to restrict study design choice, to wrongly discredit the results of types of observational studies that have been very useful in the past and to damage the teaching of epidemiological reasoning. Finally, in Section 4 we set out what we regard as a more reasonable 'working hypothesis' as to the nature of causality and its assessment: pragmatic pluralism. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

Analogy in causal inference: rethinking Austin Bradford Hill's neglected consideration.

PubMed

Weed, Douglas L

2018-05-01

The purpose of this article was to rethink and resurrect Austin Bradford Hill's "criterion" of analogy as an important consideration in causal inference. In epidemiology today, analogy is either completely ignored (e.g., in many textbooks), or equated with biologic plausibility or coherence, or aligned with the scientist's imagination. None of these examples, however, captures Hill's description of analogy. His words suggest that there may be something gained by contrasting two bodies of evidence, one from an established causal relationship, the other not. Coupled with developments in the methods of systematic assessments of evidence-including but not limited to meta-analysis-analogy can be restructured as a key component in causal inference. This new approach will require that a collection-a library-of known cases of causal inference (i.e., bodies of evidence involving established causal relationships) be developed. This library would likely include causal assessments by organizations such as the International Agency for Research on Cancer, the National Toxicology Program, and the United States Environmental Protection Agency. In addition, a process for describing key features of a causal relationship would need to be developed along with what will be considered paradigm cases of causation. Finally, it will be important to develop ways to objectively compare a "new" body of evidence with the relevant paradigm case of causation. Analogy, along with all other existing methods and causal considerations, may improve our ability to identify causal relationships. Copyright © 2018 Elsevier Inc. All rights reserved.

A qualitative study evaluating causality attribution for serious adverse events during early phase oncology clinical trials.

PubMed

Mukherjee, Som D; Coombes, Megan E; Levine, Mitch; Cosby, Jarold; Kowaleski, Brenda; Arnold, Andrew

2011-10-01

In early phase oncology trials, novel targeted therapies are increasingly being tested in combination with traditional agents creating greater potential for enhanced and new toxicities. When a patient experiences a serious adverse event (SAE), investigators must determine whether the event is attributable to the investigational drug or not. This study seeks to understand the clinical reasoning, tools used and challenges faced by the researchers who assign causality to SAE's. Thirty-two semi-structured interviews were conducted with medical oncologists and trial coordinators at six Canadian academic cancer centres. Interviews were recorded and transcribed verbatim. Individual interview content analysis was followed by thematic analysis across the interview set. Our study found that causality assessment tends to be a rather complex process, often without complete clinical and investigational data at hand. Researchers described using a common processing strategy whereby they gather pertinent information, eliminate alternative explanations, and consider whether or not the study drug resulted in the SAE. Many of the interviewed participants voiced concern that causality assessments are often conducted quickly and tend to be highly subjective. Many participants were unable to identify any useful tools to help in assigning causality and welcomed more objectivity in the overall process. Attributing causality to SAE's is a complex process. Clinical trial researchers apply a logical system of reasoning, but feel that the current method of assigning causality could be improved. Based on these findings, future research involving the development of a new causality assessment tool specifically for use in early phase oncology clinical trials may be useful.

A Causal Inference Analysis of the Effect of Wildland Fire ...

EPA Pesticide Factsheets

Wildfire smoke is a major contributor to ambient air pollution levels. In this talk, we develop a spatio-temporal model to estimate the contribution of fire smoke to overall air pollution in different regions of the country. We combine numerical model output with observational data within a causal inference framework. Our methods account for aggregation and potential bias of the numerical model simulation, and address uncertainty in the causal estimates. We apply the proposed method to estimation of ozone and fine particulate matter from wildland fires and the impact on health burden assessment. We develop a causal inference framework to assess contributions of fire to ambient PM in the presence of spatial interference.

Causality networks from multivariate time series and application to epilepsy.

PubMed

Siggiridou, Elsa; Koutlis, Christos; Tsimpiris, Alkiviadis; Kimiskidis, Vasilios K; Kugiumtzis, Dimitris

2015-08-01

Granger causality and variants of this concept allow the study of complex dynamical systems as networks constructed from multivariate time series. In this work, a large number of Granger causality measures used to form causality networks from multivariate time series are assessed. For this, realizations on high dimensional coupled dynamical systems are considered and the performance of the Granger causality measures is evaluated, seeking for the measures that form networks closest to the true network of the dynamical system. In particular, the comparison focuses on Granger causality measures that reduce the state space dimension when many variables are observed. Further, the linear and nonlinear Granger causality measures of dimension reduction are compared to a standard Granger causality measure on electroencephalographic (EEG) recordings containing episodes of epileptiform discharges.

Unified framework for information integration based on information geometry

PubMed Central

Oizumi, Masafumi; Amari, Shun-ichi

2016-01-01

Assessment of causal influences is a ubiquitous and important subject across diverse research fields. Drawn from consciousness studies, integrated information is a measure that defines integration as the degree of causal influences among elements. Whereas pairwise causal influences between elements can be quantified with existing methods, quantifying multiple influences among many elements poses two major mathematical difficulties. First, overestimation occurs due to interdependence among influences if each influence is separately quantified in a part-based manner and then simply summed over. Second, it is difficult to isolate causal influences while avoiding noncausal confounding influences. To resolve these difficulties, we propose a theoretical framework based on information geometry for the quantification of multiple causal influences with a holistic approach. We derive a measure of integrated information, which is geometrically interpreted as the divergence between the actual probability distribution of a system and an approximated probability distribution where causal influences among elements are statistically disconnected. This framework provides intuitive geometric interpretations harmonizing various information theoretic measures in a unified manner, including mutual information, transfer entropy, stochastic interaction, and integrated information, each of which is characterized by how causal influences are disconnected. In addition to the mathematical assessment of consciousness, our framework should help to analyze causal relationships in complex systems in a complete and hierarchical manner. PMID:27930289

Basic Language Skills and Young Children's Understanding of Causal Connections during Storytelling

ERIC Educational Resources Information Center

Brown, Danielle D.; Lile, Jacquelyn; Burns, Barbara M.

2011-01-01

The current study examined the role of basic language skills for individual differences in preschoolers' understanding of causal connections. Assessments of basic language skills, expressive vocabulary, phonological processing, and receptive language comprehension were examined in relation to the production of causal connections in a storytelling…

Causal Agency Theory: Reconceptualizing a Functional Model of Self-Determination

ERIC Educational Resources Information Center

Shogren, Karrie A.; Wehmeyer, Michael L.; Palmer, Susan B.; Forber-Pratt, Anjali J.; Little, Todd J.; Lopez, Shane

2015-01-01

This paper introduces Causal Agency Theory, an extension of the functional model of self-determination. Causal Agency Theory addresses the need for interventions and assessments pertaining to selfdetermination for all students and incorporates the significant advances in understanding of disability and in the field of positive psychology since the…

A Bayesian network approach for causal inferences in pesticide risk assessment and management

EPA Science Inventory

Pesticide risk assessment and management must balance societal benefits and ecosystem protection, based on quantified risks and the strength of the causal linkages between uses of the pesticide and socioeconomic and ecological endpoints of concern. A Bayesian network (BN) is a gr...

CAUSAL ANALYSIS OF BIOLOGICAL IMPAIRMENT IN LONG CREEK, A SANDY-BOTTOMED STREAM IN COASTAL SOUTHERN MAINE (Final Report)

EPA Science Inventory

This assessment presents results from a complex causal assessment of a biologically impaired, urbanized coastal watershed located primarily in South Portland, Maine, USA—the Long Creek watershed. This case study serves as an example implementation of U.S. Environmental Protectio...

CADDIS Publications

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

CADDIS Authors & Contributors

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

CADDIS Site Map

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

CADDIS Frequent Questions

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

CADDIS Related Links

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

CADDIS Recent Additions

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

CADDIS Basic Information

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

Earthquake prediction: the interaction of public policy and science.

PubMed Central

Jones, L M

1996-01-01

Earthquake prediction research has searched for both informational phenomena, those that provide information about earthquake hazards useful to the public, and causal phenomena, causally related to the physical processes governing failure on a fault, to improve our understanding of those processes. Neither informational nor causal phenomena are a subset of the other. I propose a classification of potential earthquake predictors of informational, causal, and predictive phenomena, where predictors are causal phenomena that provide more accurate assessments of the earthquake hazard than can be gotten from assuming a random distribution. Achieving higher, more accurate probabilities than a random distribution requires much more information about the precursor than just that it is causally related to the earthquake. PMID:11607656

Causal capture effects in chimpanzees (Pan troglodytes).

PubMed

Matsuno, Toyomi; Tomonaga, Masaki

2017-01-01

Extracting a cause-and-effect structure from the physical world is an important demand for animals living in dynamically changing environments. Human perceptual and cognitive mechanisms are known to be sensitive and tuned to detect and interpret such causal structures. In contrast to rigorous investigations of human causal perception, the phylogenetic roots of this perception are not well understood. In the present study, we aimed to investigate the susceptibility of nonhuman animals to mechanical causality by testing whether chimpanzees perceived an illusion called causal capture (Scholl & Nakayama, 2002). Causal capture is a phenomenon in which a type of bistable visual motion of objects is perceived as causal collision due to a bias from a co-occurring causal event. In our experiments, we assessed the susceptibility of perception of a bistable stream/bounce motion event to a co-occurring causal event in chimpanzees. The results show that, similar to in humans, causal "bounce" percepts were significantly increased in chimpanzees with the addition of a task-irrelevant causal bounce event that was synchronously presented. These outcomes suggest that the perceptual mechanisms behind the visual interpretation of causal structures in the environment are evolutionarily shared between human and nonhuman animals. Copyright © 2016 Elsevier B.V. All rights reserved.

Bayesian Networks Improve Causal Environmental Assessments for Evidence-Based Policy.

PubMed

Carriger, John F; Barron, Mace G; Newman, Michael C

2016-12-20

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on valued ecological resources. These aspects are demonstrated through hypothetical problem scenarios that explore some major benefits of using Bayesian networks for reasoning and making inferences in evidence-based policy.

Combined Functional and Causal Connectivity Analyses of Language Networks in Children: A Feasibility Study

ERIC Educational Resources Information Center

Wilke, Marko; Lidzba, Karen; Krageloh-Mann, Ingeborg

2009-01-01

Instead of assessing activation in distinct brain regions, approaches to investigating the networks underlying distinct brain functions have come into the focus of neuroscience research. Here, we provide a completely data-driven framework for assessing functional and causal connectivity in functional magnetic resonance imaging (fMRI) data,…

On the origin of Hill's causal criteria.

PubMed

Morabia, A

1991-09-01

The rules to assess causation formulated by the eighteenth century Scottish philosopher David Hume are compared to Sir Austin Bradford Hill's causal criteria. The strength of the analogy between Hume's rules and Hill's causal criteria suggests that, irrespective of whether Hume's work was known to Hill or Hill's predecessors, Hume's thinking expresses a point of view still widely shared by contemporary epidemiologists. The lack of systematic experimental proof to causal inferences in epidemiology may explain the analogy of Hume's and Hill's, as opposed to Popper's, logic.

Assessing Command and Control System Vulnerabilities in Underdeveloped, Degraded and Denied Operational Environments

DTIC Science & Technology

2013-06-01

simulation of complex systems (Sterman 2000, Meadows 2008): a) Causal Loop Diagrams. A Causal Loop Diagram ( CLD ) is used to represent the feedback...structure of the dynamic system. CLDs consist of variables in the system being connected by arrows to show their causal influences and relationships. It is...distribution of orders will be included in the model. 6.4.2 Causal Loop Diagrams The CLD , as seen in Figure 5, is derived from the WDA constructs for the

CADDIS Document: Using Data From Other Sources

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System, or CADDIS, is a website developed to help scientists and engineers in the Regions, States, and Tribes conduct causal assessments in aquatic systems.

Mendelian randomization analyses in cardiometabolic disease: challenges in evaluating causality

PubMed Central

Holmes, Michael V; Ala-Korpela, Mika; Davey Smith, George

2017-01-01

Mendelian randomization (MR) is a burgeoning field that involves the use of genetic variants to assess causal relationships between exposures and outcomes. MR studies can be straightforward; for example, genetic variants within or near the encoding locus that is associated with protein concentrations can help to assess their causal role in disease. However, a more complex relationship between the genetic variants and an exposure can make findings from MR more difficult to interpret. In this Review, we describe some of these challenges in interpreting MR analyses, including those from studies using genetic variants to assess causality of multiple traits (such as branched-chain amino acids and risk of diabetes mellitus); studies describing pleiotropic variants (for example, C-reactive protein and its contribution to coronary heart disease); and those investigating variants that disrupt normal function of an exposure (for example, HDL cholesterol or IL-6 and coronary heart disease). Furthermore, MR studies on variants that encode enzymes responsible for the metabolism of an exposure (such as alcohol) are discussed, in addition to those assessing the effects of variants on time-dependent exposures (extracellular superoxide dismutase), cumulative exposures (LDL cholesterol), and overlapping exposures (triglycerides and non-HDL cholesterol). We elaborate on the molecular features of each relationship, and provide explanations for the likely causal associations. In doing so, we hope to contribute towards more reliable evaluations of MR findings. PMID:28569269

Repeated causal decision making.

PubMed

Hagmayer, York; Meder, Björn

2013-01-01

Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in such situations and how they use their knowledge to adapt to changes in the decision context. Our studies show that decision makers' behavior is strongly contingent on their causal beliefs and that people exploit their causal knowledge to assess the consequences of changes in the decision problem. A high consistency between hypotheses about causal structure, causally expected values, and actual choices was observed. The experiments show that (a) existing causal hypotheses guide the interpretation of decision feedback, (b) consequences of decisions are used to revise existing causal beliefs, and (c) decision makers use the experienced feedback to induce a causal model of the choice situation even when they have no initial causal hypotheses, which (d) enables them to adapt their choices to changes of the decision problem. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Causal Inference and Omitted Variable Bias in Financial Aid Research: Assessing Solutions

ERIC Educational Resources Information Center

Riegg, Stephanie K.

2008-01-01

This article highlights the problem of omitted variable bias in research on the causal effect of financial aid on college-going. I first describe the problem of self-selection and the resulting bias from omitted variables. I then assess and explore the strengths and weaknesses of random assignment, multivariate regression, proxy variables, fixed…

Preliminary Findings on the Computer-Administered Multiple-Choice Online Causal Comprehension Assessment, a Diagnostic Reading Comprehension Test

ERIC Educational Resources Information Center

Davison, Mark L.; Biancarosa, Gina; Carlson, Sarah E.; Seipel, Ben; Liu, Bowen

2018-01-01

The computer-administered Multiple-Choice Online Causal Comprehension Assessment (MOCCA) for Grades 3 to 5 has an innovative, 40-item multiple-choice structure in which each distractor corresponds to a comprehension process upon which poor comprehenders have been shown to rely. This structure requires revised thinking about measurement issues…

A critical assessment of the association between postnatal toxoplasmosis and epilepsy in immune-competent patients.

PubMed

Uzorka, J W; Arend, S M

2017-07-01

While postnatal toxoplasmosis in immune-competent patients is generally considered a self-limiting and mild illness, it has been associated with a variety of more severe clinical manifestations. The causal relation with some manifestations, e.g. myocarditis, has been microbiologically proven, but this is not unequivocally so for other reported associations, such as with epilepsy. We aimed to systematically assess causality between postnatal toxoplasmosis and epilepsy in immune-competent patients. A literature search was performed. The Bradford Hill criteria for causality were used to score selected articles for each component of causality. Using an arbitrary but defined scoring system, the maximal score was 15 points (13 for case reports). Of 704 articles, five case reports or series and five case-control studies were selected. The strongest evidence for a causal relation was provided by two case reports and one case-control study, with a maximal causality score of, respectively, 9/13, 10/13 and 10/15. The remaining studies had a median causality score of 7 (range 5-9). No selection bias was identified, but 6/10 studies contained potential confounders (it was unsure whether the infection was pre- or postnatal acquired, or immunodeficiency was not specifically excluded). Based on the evaluation of the available literature, although scanty and of limited quality, a causal relationship between postnatal toxoplasmosis and epilepsy seems possible. More definite proof requires further research, e.g. by performing Toxoplasma serology in all de novo epilepsy cases.

Bayesian networks improve causal environmental ...

EPA Pesticide Factsheets

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value

Causation in risk assessment and management: models, inference, biases, and a microbial risk-benefit case study.

PubMed

Cox, L A; Ricci, P F

2005-04-01

Causal inference of exposure-response relations from data is a challenging aspect of risk assessment with important implications for public and private risk management. Such inference, which is fundamentally empirical and based on exposure (or dose)-response models, seldom arises from a single set of data; rather, it requires integrating heterogeneous information from diverse sources and disciplines including epidemiology, toxicology, and cell and molecular biology. The causal aspects we discuss focus on these three aspects: drawing sound inferences about causal relations from one or more observational studies; addressing and resolving biases that can affect a single multivariate empirical exposure-response study; and applying the results from these considerations to the microbiological risk management of human health risks and benefits of a ban on antibiotic use in animals, in the context of banning enrofloxacin or macrolides, antibiotics used against bacterial illnesses in poultry, and the effects of such bans on changing the risk of human food-borne campylobacteriosis infections. The purposes of this paper are to describe novel causal methods for assessing empirical causation and inference; exemplify how to deal with biases that routinely arise in multivariate exposure- or dose-response modeling; and provide a simplified discussion of a case study of causal inference using microbial risk analysis as an example. The case study supports the conclusion that the human health benefits from a ban are unlikely to be greater than the excess human health risks that it could create, even when accounting for uncertainty. We conclude that quantitative causal analysis of risks is a preferable to qualitative assessments because it does not involve unjustified loss of information and is sound under the inferential use of risk results by management.

Structural nested mean models for assessing time-varying effect moderation.

PubMed

Almirall, Daniel; Ten Have, Thomas; Murphy, Susan A

2010-03-01

This article considers the problem of assessing causal effect moderation in longitudinal settings in which treatment (or exposure) is time varying and so are the covariates said to moderate its effect. Intermediate causal effects that describe time-varying causal effects of treatment conditional on past covariate history are introduced and considered as part of Robins' structural nested mean model. Two estimators of the intermediate causal effects, and their standard errors, are presented and discussed: The first is a proposed two-stage regression estimator. The second is Robins' G-estimator. The results of a small simulation study that begins to shed light on the small versus large sample performance of the estimators, and on the bias-variance trade-off between the two estimators are presented. The methodology is illustrated using longitudinal data from a depression study.

Causality Assessment of Serious Neurologic Adverse Events Following 2009 H1N1 Vaccination

PubMed Central

Williams, S Elizabeth; Pahud, Barbara A; Vellozzi, Claudia; Donofrio, Peter D; Dekker, Cornelia L; Halsey, Neal; Klein, Nicola P; Baxter, Roger P; Marchant, Colin D; LaRussa, Philip S; Barnett, Elizabeth D; Tokars, Jerome I; McGeeney, Brian E; Sparks, Robert C; Aukes, Laurie L.; Jakob, Kathleen; Coronel, Silvia; Sejvar, James J; Slade, Barbara A; Edwards, Kathryn M

2016-01-01

Background Adverse events occurring after vaccination are routinely reported to the Vaccine Adverse Event Reporting System (VAERS). We studied serious adverse events (SAEs) of a neurologic nature reported after receipt of influenza A (H1N1) 2009 monovalent vaccine during the 2009–10 influenza season. Investigators in the Clinical Immunization Safety Assessment (CISA) Network sought to characterize these SAEs and to assess their possible causal relationship to vaccination. Methods Centers for Disease Control and Prevention (CDC) and Food and Drug Administration (FDA) physicians reviewed all SAE reports (as defined by the Code of Federal Regulations, 21CFR§314.80) after receipt of H1N1 vaccine reported to VAERS between October 1st 2009 and March 31st 2010. Non-fatal SAE reports with neurologic presentation were referred to CISA investigators, who requested and reviewed additional medical records and clinical information as available. CISA investigators assessed the causal relationship between vaccination and the event using modified WHO criteria as defined. Results 212 VAERS reports of non-fatal serious neurological events were referred for CISA review. Case reports were equally distributed by gender (50.9% female) with an age range of 6 months to 83 years (median 38 years). The most frequent diagnoses reviewed were: Guillain-Barré Syndrome (37.3%), seizures (10.8%), cranial neuropathy (5.7%), and acute disseminated encephalomyelitis (3.8%). Causality assessment resulted in classification of 72 events as “possibly” related (33%), 108 as “unlikely” related (51%), and 20 as “unrelated” (9%) to H1N1 vaccination; none were classified as “probable” or “definite” and 12 were unclassifiable (6%). Conclusion The absence of a specific test to indicate whether a vaccine component contributes to the pathogenesis of an event occurring within a biologically plausible time period makes assessing causality difficult. The development of standardized protocols for providers to use in evaluation of adverse events following immunization, and rapid identification and follow-up of VAERS reports could improve causality assessment. PMID:21893148

Causal inference in biology networks with integrated belief propagation.

PubMed

Chang, Rui; Karr, Jonathan R; Schadt, Eric E

2015-01-01

Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.

Assessing Causality in a Complex Security Environment

DTIC Science & Technology

2015-01-01

social sciences that could genuinely benefit those students. Causality is one of these critical issues. Causality has many definitions, but we might...protests (Ivan Bandura ) Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated...relatively simple theory of what leads to a stable deter- rent relationship between two states. Mearsheimer argued that when State A fields a

Comparison Groups in Short Interrupted Time-Series: An Illustration Evaluating No Child Left Behind

ERIC Educational Resources Information Center

Wong, Manyee; Cook, Thomas D.; Steiner, Peter M.

2009-01-01

Interrupted time-series (ITS) are often used to assess the causal effect of a planned or even unplanned shock introduced into an on-going process. The pre-intervention slope is supposed to index the causal counterfactual, and deviations from it in mean, slope or variance are used to indicate an effect. However, a secure causal inference is only…

A Causal-Comparative Study of Third Grade Reading Achievement and the Use of Commercial Reading Programs to Promote Literacy

ERIC Educational Resources Information Center

McDonald, Wendy E.

2013-01-01

This quantitative, causal-comparative study examined the reading achievement of third grade students to ascertain the reading health of elementary students as measured through South Carolina's standardized assessment, the Palmetto Assessment of State Standards (PASS). The purpose of this study was to determine if there was a significant difference…

Assessing Causality in the Relationship between Adolescents' Risky Sexual Online Behavior and Their Perceptions of This Behavior

ERIC Educational Resources Information Center

Baumgartner, Susanne E.; Valkenburg, Patti M.; Peter, Jochen

2010-01-01

The main aim of this study was to investigate the causal nature of the relationship between adolescents' risky sexual behavior on the internet and their perceptions of this behavior. Engagement in the following online behaviors was assessed: searching online for someone to talk about sex, searching online for someone to have sex, sending intimate…

Assessing Causality and Persistence in Associations between Family Dinners and Adolescent Well-Being

ERIC Educational Resources Information Center

Musick, Kelly; Meier, Ann

2012-01-01

Adolescents who share meals with their parents score better on a range of well-being indicators. Using 3 waves of the National Longitudinal Survey of Adolescent Health (N = 17,977), the authors assessed the causal nature of these associations and the extent to which they persist into adulthood. They examined links between family dinners and…

Reducing Children’s Behavior Problems through Social Capital: A Causal Assessment

PubMed Central

López Turley, Ruth N.; Gamoran, Adam; McCarty, Alyn Turner; Fish, Rachel

2016-01-01

Behavior problems among young children have serious detrimental effects on short and long-term educational outcomes. An especially promising prevention strategy may be one that focuses on strengthening the relationships among families in schools, or social capital. However, empirical research on social capital has been constrained by conceptual and causal ambiguity. This study attempts to construct a more focused conceptualization of social capital and aims to determine the causal effects of social capital on children’s behavior. Using data from a cluster randomized trial of 52 elementary schools, we apply several multilevel models to assess the causal relationship, including intent to treat and treatment on the treated analyses. Taken together, these analyses provide stronger evidence than previous studies that social capital improves children’s behavioral outcomes and that these improvements are not simply a result of selection into social relations but result from the social relations themselves. PMID:27886729

ASSESSING CAUSALITY AND PERSISTENCE IN ASSOCIATIONS BETWEEN FAMILY DINNERS AND ADOLESCENT WELL-BEING

PubMed Central

Musick, Kelly; Meier, Ann

2013-01-01

Adolescents who share meals with their parents score better on a range of well-being indicators. Using three waves of the National Longitudinal Survey of Adolescent Health (N = 17,977), we assessed the causal nature of these associations and the extent to which they persist into adulthood. We examined links between family dinners and adolescent mental health, substance use, and delinquency at wave 1, accounting for detailed measures of the family environment to test whether family meals simply proxy for other family processes. As a more stringent test of causality, we estimated fixed effects models from waves 1 and 2, and we used wave 3 to explore persistence in the influence of family dinners. Associations between family dinners and adolescent well-being remained significant, net of controls, and some held up to stricter tests of causality. Beyond indirect benefits via earlier well-being, however, family dinners associations did not persist into adulthood. PMID:23794750

ASSESSING CAUSALITY AND PERSISTENCE IN ASSOCIATIONS BETWEEN FAMILY DINNERS AND ADOLESCENT WELL-BEING.

PubMed

Musick, Kelly; Meier, Ann

2012-06-01

Adolescents who share meals with their parents score better on a range of well-being indicators. Using three waves of the National Longitudinal Survey of Adolescent Health ( N = 17,977), we assessed the causal nature of these associations and the extent to which they persist into adulthood. We examined links between family dinners and adolescent mental health, substance use, and delinquency at wave 1, accounting for detailed measures of the family environment to test whether family meals simply proxy for other family processes. As a more stringent test of causality, we estimated fixed effects models from waves 1 and 2, and we used wave 3 to explore persistence in the influence of family dinners. Associations between family dinners and adolescent well-being remained significant, net of controls, and some held up to stricter tests of causality. Beyond indirect benefits via earlier well-being, however, family dinners associations did not persist into adulthood.

Should herbs take all the blame? Causality assessment of a serious thrombocytopenia event.

PubMed

Lai, Jung-Nien; Hsieh, Shu-Ching; Chen, Pau-Chung; Chen, Huey-Jen; Wang, Jung-Der

2010-11-01

With the increasing use of herbal medicines, the causality assessment of adverse drug-related reactions becomes more complicated because of the concomitant use of herbs and conventional medications. Epidemiological causal inference can be a central feature of such judgment but may be insufficient. Other scientific considerations include study design, bias, confounding, and measurement issues. The approach of this study is to establish an active safety surveillance system for finished herbal products (FHPs) and to review each adverse event regularly. A single case of serious thrombocytopenia was found in 136 subjects taking FHPs on a clinical trial for 12 weeks, for which the cause was sought. Because at the end of the first month the patient's platelet counts were normal and the thrombocytopenia developed after the co-medication with conventional drugs, it was suspected that the thrombocytopenia might not be attributed to the use of FHP. This report summarizes the criteria of causality assessment under mixed use of herbs and conventional medicine and recommends a feasible process for careful evaluation of adverse drug reactions related to all herbal medicine.

Supporting shared hypothesis testing in the biomedical domain.

PubMed

Agibetov, Asan; Jiménez-Ruiz, Ernesto; Ondrésik, Marta; Solimando, Alessandro; Banerjee, Imon; Guerrini, Giovanna; Catalano, Chiara E; Oliveira, Joaquim M; Patanè, Giuseppe; Reis, Rui L; Spagnuolo, Michela

2018-02-08

Pathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pathogenesis outcomes to the observed conditions. And to prove such causal hypotheses we would need to have the full understanding of the causal relationships, and we would have to provide all the necessary evidences to support our claims. In practice, however, we might not possess all the background knowledge on the causality relationships, and we might be unable to collect all the evidence to prove our hypotheses. In this work we propose a methodology for the translation of biological knowledge on causality relationships of biological processes and their effects on conditions to a computational framework for hypothesis testing. The methodology consists of two main points: hypothesis graph construction from the formalization of the background knowledge on causality relationships, and confidence measurement in a causality hypothesis as a normalized weighted path computation in the hypothesis graph. In this framework, we can simulate collection of evidences and assess confidence in a causality hypothesis by measuring it proportionally to the amount of available knowledge and collected evidences. We evaluate our methodology on a hypothesis graph that represents both contributing factors which may cause cartilage degradation and the factors which might be caused by the cartilage degradation during osteoarthritis. Hypothesis graph construction has proven to be robust to the addition of potentially contradictory information on the simultaneously positive and negative effects. The obtained confidence measures for the specific causality hypotheses have been validated by our domain experts, and, correspond closely to their subjective assessments of confidences in investigated hypotheses. Overall, our methodology for a shared hypothesis testing framework exhibits important properties that researchers will find useful in literature review for their experimental studies, planning and prioritizing evidence collection acquisition procedures, and testing their hypotheses with different depths of knowledge on causal dependencies of biological processes and their effects on the observed conditions.

Framework for assessing causality of air pollution-related health effects for reviews of the National Ambient Air Quality Standards.

PubMed

Owens, Elizabeth Oesterling; Patel, Molini M; Kirrane, Ellen; Long, Thomas C; Brown, James; Cote, Ila; Ross, Mary A; Dutton, Steven J

2017-08-01

To inform regulatory decisions on the risk due to exposure to ambient air pollution, consistent and transparent communication of the scientific evidence is essential. The United States Environmental Protection Agency (U.S. EPA) develops the Integrated Science Assessment (ISA), which contains evaluations of the policy-relevant science on the effects of criteria air pollutants and conveys critical science judgments to inform decisions on the National Ambient Air Quality Standards. This article discusses the approach and causal framework used in the ISAs to evaluate and integrate various lines of scientific evidence and draw conclusions about the causal nature of air pollution-induced health effects. The framework has been applied to diverse pollutants and cancer and noncancer effects. To demonstrate its flexibility, we provide examples of causality judgments on relationships between health effects and pollutant exposures, drawing from recent ISAs for ozone, lead, carbon monoxide, and oxides of nitrogen. U.S. EPA's causal framework has increased transparency by establishing a structured process for evaluating and integrating various lines of evidence and uniform approach for determining causality. The framework brings consistency and specificity to the conclusions in the ISA, and the flexibility of the framework makes it relevant for evaluations of evidence across media and health effects. Published by Elsevier Inc.

Herbalife hepatotoxicity: Evaluation of cases with positive reexposure tests.

PubMed

Teschke, Rolf; Frenzel, Christian; Schulze, Johannes; Schwarzenboeck, Alexander; Eickhoff, Axel

2013-07-27

To analyze the validity of applied test criteria and causality assessment methods in assumed Herbalife hepatotoxicity with positive reexposure tests. We searched the Medline database for suspected cases of Herbalife hepatotoxicity and retrieved 53 cases including eight cases with a positive unintentional reexposure and a high causality level for Herbalife. First, analysis of these eight cases focused on the data quality of the positive reexposure cases, requiring a baseline value of alanine aminotransferase (ALT) < 5 upper limit of normal (N) before reexposure, with N as the upper limit of normal, and a doubling of the ALT value at reexposure as compared to the ALT value at baseline prior to reexposure. Second, reported methods to assess causality in the eight cases were evaluated, and then the liver specific Council for International Organizations of Medical Sciences (CIOMS) scale validated for hepatotoxicity cases was used for quantitative causality reevaluation. This scale consists of various specific elements with scores provided through the respective case data, and the sum of the scores yields a causality grading for each individual case of initially suspected hepatotoxicity. Details of positive reexposure test conditions and their individual results were scattered in virtually all cases, since reexposures were unintentional and allowed only retrospective rather than prospective assessments. In 1/8 cases, criteria for a positive reexposure were fulfilled, whereas in the remaining cases the reexposure test was classified as negative (n = 1), or the data were considered as uninterpretable due to missing information to comply adequately with the criteria (n = 6). In virtually all assessed cases, liver unspecific causality assessment methods were applied rather than a liver specific method such as the CIOMS scale. Using this scale, causality gradings for Herbalife in these eight cases were probable (n = 1), unlikely (n = 4), and excluded (n = 3). Confounding variables included low data quality, alternative diagnoses, poor exclusion of important other causes, and comedication by drugs and herbs in 6/8 cases. More specifically, problems were evident in some cases regarding temporal association, daily doses, exact start and end dates of product use, actual data of laboratory parameters such as ALT, and exact dechallenge characteristics. Shortcomings included scattered exclusion of hepatitis A-C, cytomegalovirus and Epstein Barr virus infection with only globally presented or lacking parameters. Hepatitis E virus infection was considered in one single patient and found positive, infections by herpes simplex virus and varicella zoster virus were excluded in none. Only one case fulfilled positive reexposure test criteria in initially assumed Herbalife hepatotoxicity, with lower CIOMS based causality gradings for the other cases than hitherto proposed.

Extended causal modeling to assess Partial Directed Coherence in multiple time series with significant instantaneous interactions.

PubMed

Faes, Luca; Nollo, Giandomenico

2010-11-01

The Partial Directed Coherence (PDC) and its generalized formulation (gPDC) are popular tools for investigating, in the frequency domain, the concept of Granger causality among multivariate (MV) time series. PDC and gPDC are formalized in terms of the coefficients of an MV autoregressive (MVAR) model which describes only the lagged effects among the time series and forsakes instantaneous effects. However, instantaneous effects are known to affect linear parametric modeling, and are likely to occur in experimental time series. In this study, we investigate the impact on the assessment of frequency domain causality of excluding instantaneous effects from the model underlying PDC evaluation. Moreover, we propose the utilization of an extended MVAR model including both instantaneous and lagged effects. This model is used to assess PDC either in accordance with the definition of Granger causality when considering only lagged effects (iPDC), or with an extended form of causality, when we consider both instantaneous and lagged effects (ePDC). The approach is first evaluated on three theoretical examples of MVAR processes, which show that the presence of instantaneous correlations may produce misleading profiles of PDC and gPDC, while ePDC and iPDC derived from the extended model provide here a correct interpretation of extended and lagged causality. It is then applied to representative examples of cardiorespiratory and EEG MV time series. They suggest that ePDC and iPDC are better interpretable than PDC and gPDC in terms of the known cardiovascular and neural physiologies.

Influence analysis for high-dimensional time series with an application to epileptic seizure onset zone detection

PubMed Central

Flamm, Christoph; Graef, Andreas; Pirker, Susanne; Baumgartner, Christoph; Deistler, Manfred

2013-01-01

Granger causality is a useful concept for studying causal relations in networks. However, numerical problems occur when applying the corresponding methodology to high-dimensional time series showing co-movement, e.g. EEG recordings or economic data. In order to deal with these shortcomings, we propose a novel method for the causal analysis of such multivariate time series based on Granger causality and factor models. We present the theoretical background, successfully assess our methodology with the help of simulated data and show a potential application in EEG analysis of epileptic seizures. PMID:23354014

MINIMIZING COGNITIVE ERRORS IN SITE-SPECIFIC CAUSAL ASSESSMENT

EPA Science Inventory

Interest in causal investigations in aquatic systems has been a natural outgrowth of the increased use of biological monitoring to characterize the condition of resources. Although biological monitoring approaches are critical tools for detecting whether effects are occurring, t...

Electrophysiological difference between the representations of causal judgment and associative judgment in semantic memory.

PubMed

Chen, Qingfei; Liang, Xiuling; Lei, Yi; Li, Hong

2015-05-01

Causally related concepts like "virus" and "epidemic" and general associatively related concepts like "ring" and "emerald" are represented and accessed separately. The Evoked Response Potential (ERP) procedure was used to examine the representations of causal judgment and associative judgment in semantic memory. Participants were required to remember a task cue (causal or associative) presented at the beginning of each trial, and assess whether the relationship between subsequently presented words matched the initial task cue. The ERP data showed that an N400 effect (250-450 ms) was more negative for unrelated words than for all related words. Furthermore, the N400 effect elicited by causal relations was more positive than for associative relations in causal cue condition, whereas no significant difference was found in the associative cue condition. The centrally distributed late ERP component (650-750 ms) elicited by the causal cue condition was more positive than for the associative cue condition. These results suggested that the processing of causal judgment and associative judgment in semantic memory recruited different degrees of attentional and executive resources. Copyright © 2015 Elsevier B.V. All rights reserved.

Contours of a causal feedback mechanism between adaptive personality and psychosocial function in patients with personality disorders: a secondary analysis from a randomized clinical trial.

PubMed

Klungsøyr, Ole; Antonsen, Bjørnar; Wilberg, Theresa

2017-06-05

Patients with personality disorders commonly exhibit impairment in psychosocial function that persists over time even with diagnostic remission. Further causal knowledge may help to identify and assess factors with a potential to alleviate this impairment. Psychosocial function is associated with personality functioning which describes personality disorder severity in DSM-5 (section III) and which can reportedly be improved by therapy. The reciprocal association between personality functioning and psychosocial function was assessed, in 113 patients with different personality disorders, in a secondary longitudinal analysis of data from a randomized clinical trial, over six years. Personality functioning was represented by three domains of the Severity Indices of Personality Problems: Relational Capacity, Identity Integration, and Self-control. Psychosocial function was measured by Global Assessment of Functioning. The marginal structural model was used for estimation of causal effects of the three personality functioning domains on psychosocial function, and vice versa. The attractiveness of this model lies in the ability to assess an effect of a time - varying exposure on an outcome, while adjusting for time - varying confounding. Strong causal effects were found. A hypothetical intervention to increase Relational Capacity by one standard deviation, both at one and two time-points prior to assessment of psychosocial function, would increase psychosocial function by 3.5 standard deviations (95% CI: 2.0, 4.96). Significant effects of Identity Integration and Self-control on psychosocial function, and from psychosocial function on all three domains of personality functioning, although weaker, were also found. This study indicates that persistent impairment in psychosocial function can be addressed through a causal pathway of personality functioning, with interventions of at least 18 months duration.

MIIC online: a web server to reconstruct causal or non-causal networks from non-perturbative data.

PubMed

Sella, Nadir; Verny, Louis; Uguzzoni, Guido; Affeldt, Séverine; Isambert, Hervé

2018-07-01

We present a web server running the MIIC algorithm, a network learning method combining constraint-based and information-theoretic frameworks to reconstruct causal, non-causal or mixed networks from non-perturbative data, without the need for an a priori choice on the class of reconstructed network. Starting from a fully connected network, the algorithm first removes dispensable edges by iteratively subtracting the most significant information contributions from indirect paths between each pair of variables. The remaining edges are then filtered based on their confidence assessment or oriented based on the signature of causality in observational data. MIIC online server can be used for a broad range of biological data, including possible unobserved (latent) variables, from single-cell gene expression data to protein sequence evolution and outperforms or matches state-of-the-art methods for either causal or non-causal network reconstruction. MIIC online can be freely accessed at https://miic.curie.fr. Supplementary data are available at Bioinformatics online.

Causal beliefs about depression in different cultural groups—what do cognitive psychological theories of causal learning and reasoning predict?

PubMed Central

Hagmayer, York; Engelmann, Neele

2014-01-01

Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analyzed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given. PMID:25505432

Tool to assess causality of direct and indirect adverse events associated with therapeutic interventions.

PubMed

Zorzela, Liliane; Mior, Silvano; Boon, Heather; Gross, Anita; Yager, Jeromy; Carter, Rose; Vohra, Sunita

2018-03-01

To develop and test a tool to assess the causality of direct and indirect adverse events associated with therapeutic interventions. The intervention was one or more drugs and/or natural health products, a device, or practice (professional delivering the intervention). Through the assessment of causality of adverse events, we can learn about factors contributing to the harm and consider what modification may prevent its reoccurrence. Existing scales (WHO-UMC, Naranjo and Horn) were adapted to develop a tool (algorithm and table) to evaluate cases of serious harmful events reported through a national surveillance study. We also incorporated a novel approach that assesses indirect harm (caused by the delay in diagnosis/treatment) and the health provider delivering the intervention (practice). The tool was tested, revised and then implemented to assess all reported cases of serious events resulting from use of complementary therapies. The use of complementary therapies was the trigger to report the event. Each case was evaluated by two assessors, out of a panel of five, representing different health care professionals. The tool was used in assessment of eight serious adverse events. Each event was independently evaluated by two assessors. The algorithm facilitated assessment of a serious direct or indirect harm. Assessors agreed in the final score on seven of eight cases (weighted kappa coefficient of 0.75). A tool to support the assessment of causality of adverse events was developed and tested. We propose a novel method to assess direct and indirect harms related to product(s), device(s), practice or a combination of the previous. Further research will probably help evaluate this approach across different settings and interventions.

Assessing the causal role of adiposity on disordered eating in childhood, adolescence, and adulthood: a Mendelian randomization analysis

PubMed Central

2017-01-01

Background: Observational studies have shown that higher body mass index (BMI) is associated with increased risk of developing disordered eating patterns. However, the causal direction of this relation remains ambiguous. Objective: We used Mendelian randomization (MR) to infer the direction of causality between BMI and disordered eating in childhood, adolescence, and adulthood. Design: MR analyses were conducted with a genetic score as an instrumental variable for BMI to assess the causal effect of BMI at age 7 y on disordered eating patterns at age 13 y with the use of data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 4473). To examine causality in the reverse direction, MR analyses were used to estimate the effect of the same disordered eating patterns at age 13 y on BMI at age 17 y via a split-sample approach in the ALSPAC. We also investigated the causal direction of the association between BMI and eating disorders (EDs) in adults via a two-sample MR approach and publically available genome-wide association study data. Results: MR results indicated that higher BMI at age 7 y likely causes higher levels of binge eating and overeating, weight and shape concerns, and weight-control behavior patterns in both males and females and food restriction in males at age 13 y. Furthermore, results suggested that higher levels of binge eating and overeating in males at age 13 y likely cause higher BMI at age 17 y. We showed no evidence of causality between BMI and EDs in adulthood in either direction. Conclusions: This study provides evidence to suggest a causal effect of higher BMI in childhood and increased risk of disordered eating at age 13 y. Furthermore, higher levels of binge eating and overeating may cause higher BMI in later life. These results encourage an exploration of the ways to break the causal chain between these complex phenotypes, which could inform and prevent disordered eating problems in adolescence. PMID:28747331

Assessing the causal role of adiposity on disordered eating in childhood, adolescence, and adulthood: a Mendelian randomization analysis.

PubMed

Reed, Zoe E; Micali, Nadia; Bulik, Cynthia M; Davey Smith, George; Wade, Kaitlin H

2017-09-01

Background: Observational studies have shown that higher body mass index (BMI) is associated with increased risk of developing disordered eating patterns. However, the causal direction of this relation remains ambiguous. Objective: We used Mendelian randomization (MR) to infer the direction of causality between BMI and disordered eating in childhood, adolescence, and adulthood. Design: MR analyses were conducted with a genetic score as an instrumental variable for BMI to assess the causal effect of BMI at age 7 y on disordered eating patterns at age 13 y with the use of data from the Avon Longitudinal Study of Parents and Children (ALSPAC) ( n = 4473). To examine causality in the reverse direction, MR analyses were used to estimate the effect of the same disordered eating patterns at age 13 y on BMI at age 17 y via a split-sample approach in the ALSPAC. We also investigated the causal direction of the association between BMI and eating disorders (EDs) in adults via a two-sample MR approach and publically available genome-wide association study data. Results: MR results indicated that higher BMI at age 7 y likely causes higher levels of binge eating and overeating, weight and shape concerns, and weight-control behavior patterns in both males and females and food restriction in males at age 13 y. Furthermore, results suggested that higher levels of binge eating and overeating in males at age 13 y likely cause higher BMI at age 17 y. We showed no evidence of causality between BMI and EDs in adulthood in either direction. Conclusions: This study provides evidence to suggest a causal effect of higher BMI in childhood and increased risk of disordered eating at age 13 y. Furthermore, higher levels of binge eating and overeating may cause higher BMI in later life. These results encourage an exploration of the ways to break the causal chain between these complex phenotypes, which could inform and prevent disordered eating problems in adolescence.

Consequences of bullying victimization in childhood and adolescence: A systematic review and meta-analysis

PubMed Central

Moore, Sophie E; Norman, Rosana E; Suetani, Shuichi; Thomas, Hannah J; Sly, Peter D; Scott, James G

2017-01-01

AIM To identify health and psychosocial problems associated with bullying victimization and conduct a meta-analysis summarizing the causal evidence. METHODS A systematic review was conducted using PubMed, EMBASE, ERIC and PsycINFO electronic databases up to 28 February 2015. The study included published longitudinal and cross-sectional articles that examined health and psychosocial consequences of bullying victimization. All meta-analyses were based on quality-effects models. Evidence for causality was assessed using Bradford Hill criteria and the grading system developed by the World Cancer Research Fund. RESULTS Out of 317 articles assessed for eligibility, 165 satisfied the predetermined inclusion criteria for meta-analysis. Statistically significant associations were observed between bullying victimization and a wide range of adverse health and psychosocial problems. The evidence was strongest for causal associations between bullying victimization and mental health problems such as depression, anxiety, poor general health and suicidal ideation and behaviours. Probable causal associations existed between bullying victimization and tobacco and illicit drug use. CONCLUSION Strong evidence exists for a causal relationship between bullying victimization, mental health problems and substance use. Evidence also exists for associations between bullying victimization and other adverse health and psychosocial problems, however, there is insufficient evidence to conclude causality. The strong evidence that bullying victimization is causative of mental illness highlights the need for schools to implement effective interventions to address bullying behaviours. PMID:28401049

Assessing the strength of cardiac and sympathetic baroreflex controls via transfer entropy during orthostatic challenge

NASA Astrophysics Data System (ADS)

Porta, Alberto; Marchi, Andrea; Bari, Vlasta; De Maria, Beatrice; Esler, Murray; Lambert, Elisabeth; Baumert, Mathias

2017-05-01

The study assesses the strength of the causal relation along baroreflex (BR) in humans during an incremental postural challenge soliciting the BR. Both cardiac BR (cBR) and sympathetic BR (sBR) were characterized via BR sequence approaches from spontaneous fluctuations of heart period (HP), systolic arterial pressure (SAP), diastolic arterial pressure (DAP) and muscle sympathetic nerve activity (MSNA). A model-based transfer entropy method was applied to quantify the strength of the coupling from SAP to HP and from DAP to MSNA. The confounding influences of respiration were accounted for. Twelve young healthy subjects (20-36 years, nine females) were sequentially tilted at 0°, 20°, 30° and 40°. We found that (i) the strength of the causal relation along the cBR increases with tilt table inclination, while that along the sBR is unrelated to it; (ii) the strength of the causal coupling is unrelated to the gain of the relation; (iii) transfer entropy indexes are significantly and positively associated with simplified causality indexes derived from BR sequence analysis. The study proves that causality indexes are complementary to traditional characterization of the BR and suggests that simple markers derived from BR sequence analysis might be fruitfully exploited to estimate causality along the BR. This article is part of the themed issue `Mathematical methods in medicine: neuroscience, cardiology and pathology'.

Functional ability loss in sensory impaired and sensory unimpaired very old adults: analyzing causal relations with positive affect across four years.

PubMed

Wahl, Hans-Werner; Drapaniotis, Philipp M; Heyl, Vera

2014-11-01

This paper focuses on the relationship between functional ability (FA) and positive affect (PA), a major component of well-being, in sensory impaired very old adults (SI) compared with sensory unimpaired individuals (UI). Previous research mostly suggests a robust causal impact of FA on PA. However, some research, drawing from Fredrickson's broaden-and-build theory, also points to the possibility of an inverse causality between FA and PA. We examine in this paper both of these causal directions in SI as well as UI individuals across a 4year observation period. Additionally, we checked for the role of negative affect (NA). The T1-T2 sample comprised 81 out of 237 SI individuals (visually or hearing impaired) assessed at T1, with a mean age at T1 of 81.8years, and 87 UI individuals out of 150 assessed at T1, with a mean age at T1 of 81.5years. Established scales were used to assess FA, PA, and NA. Using cross-lagged panel analysis to examine the direction of causality, our findings indicate that FA has significant impact on PA in both the SI and the UI group, whereas the alternative causal pathway was not confirmed. Both cross-lagged relationships between FA and NA were non-significant. No group differences in path strengths between SI and UI were present. Our study provides evidence that FA is a key competence for successful emotional aging in vulnerable groups of very old adults such as SI as well as in UI adults in advanced old age. Copyright © 2014 Elsevier Inc. All rights reserved.

An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation

PubMed Central

Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander

2016-01-01

Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894

The psychophysical law of speed estimation in Michotte's causal events.

PubMed

Parovel, Giulia; Casco, Clara

2006-11-01

Observers saw an event in which a computer-animated square moved up to and made contact with another, which after a short delay moved off, its motion appearing to be caused by launch by the first square. Observers chose whether the second (launched) square was faster in this causal event than when presented following a long delay (non-causal event). The speed of the second object in causal events was overestimated for a wide range of speeds of the first object (launcher), but accurately assessed in non-causal events. Experiments 2 and 3 showed that overestimation occurred also in other causal displays in which the trajectories were overlapping, successive, spatially separated or inverted but did not occurred with consecutive speeds that did not produce causal percepts. We also found that if the first object in a causal event was faster, then Weber's law holds and overestimation of the launched object speed was proportional to the speed of the launcher. In contrast, if the second object was faster, overestimation was constant, i.e. independent of the launcher. We propose that the particular speed integration of causal display results in overestimation and that the way overestimation depends on V1 phenomenally affects the attribution of the source of V2 motion: either in V1 (in launching) or in V2 (in triggering).

Evaluating Candidate Principal Surrogate Endpoints

PubMed Central

Gilbert, Peter B.; Hudgens, Michael G.

2009-01-01

Summary Frangakis and Rubin (2002, Biometrics 58, 21–29) proposed a new definition of a surrogate endpoint (a “principal” surrogate) based on causal effects. We introduce an estimand for evaluating a principal surrogate, the causal effect predictiveness (CEP) surface, which quantifies how well causal treatment effects on the biomarker predict causal treatment effects on the clinical endpoint. Although the CEP surface is not identifiable due to missing potential outcomes, it can be identified by incorporating a baseline covariate(s) that predicts the biomarker. Given case–cohort sampling of such a baseline predictor and the biomarker in a large blinded randomized clinical trial, we develop an estimated likelihood method for estimating the CEP surface. This estimation assesses the “surrogate value” of the biomarker for reliably predicting clinical treatment effects for the same or similar setting as the trial. A CEP surface plot provides a way to compare the surrogate value of multiple biomarkers. The approach is illustrated by the problem of assessing an immune response to a vaccine as a surrogate endpoint for infection. PMID:18363776

Assessing causality in drug policy analyses: How useful are the Bradford Hill criteria in analysing take-home naloxone programs?

PubMed

Olsen, Anna; McDonald, David; Lenton, Simon; Dietze, Paul M

2018-05-01

The Bradford Hill criteria for assessing causality are useful in assembling evidence, including within complex policy analyses. In this paper, we argue that the implementation of take-home naloxone (THN) programs in Australia and elsewhere reflects sensible, evidence-based public health policy, despite the absence of randomised controlled trials. However, we also acknowledge that the debate around expanding access to THN would benefit from a careful consideration of causal inference and health policy impact of THN program implementation. Given the continued debate around expanding access to THN, and the relatively recent access to new data from implementation studies, two research groups independently conducted Bradford Hill analyses in order to carefully consider causal inference and health policy impact. Hill's criteria offer a useful analytical tool for interpreting current evidence on THN programs and making decisions about the (un)certainty of THN program safety and effectiveness. © 2017 Australasian Professional Society on Alcohol and other Drugs.

A decision analysis tool for the assessment of posterior fossa tumour surgery outcomes in children--the "Liverpool Neurosurgical Complication Causality Assessment Tool".

PubMed

Zakaria, Rasheed; Ellenbogen, Jonathan; Graham, Catherine; Pizer, Barry; Mallucci, Conor; Kumar, Ram

2013-08-01

Complications may occur following posterior fossa tumour surgery in children. Such complications are subjectively and inconsistently reported even though they may have significant long-term behavioural and cognitive consequences for the child. This makes comparison of surgeons, programmes and treatments problematic. We have devised a causality tool for assessing if an adverse event after surgery can be classified as a surgical complication using a series of simple questions, based on a tool used in assessing adverse drug reactions. This tool, which we have called the "Liverpool Neurosurgical Complication Causality Assessment Tool", was developed by reviewing a series of ten posterior fossa tumour cases with a panel of neurosurgery, neurology, oncology and neuropsychology specialists working in a multidisciplinary paediatric tumour treatment programme. We have demonstrated its use and hope that it may improve reliability between different assessors both in evaluating the outcomes of existing programmes and treatments as well as aiding in trials which may directly compare the effects of surgical and medical treatments.

Herbalife hepatotoxicity: Evaluation of cases with positive reexposure tests

PubMed Central

Teschke, Rolf; Frenzel, Christian; Schulze, Johannes; Schwarzenboeck, Alexander; Eickhoff, Axel

2013-01-01

AIM: To analyze the validity of applied test criteria and causality assessment methods in assumed Herbalife hepatotoxicity with positive reexposure tests. METHODS: We searched the Medline database for suspected cases of Herbalife hepatotoxicity and retrieved 53 cases including eight cases with a positive unintentional reexposure and a high causality level for Herbalife. First, analysis of these eight cases focused on the data quality of the positive reexposure cases, requiring a baseline value of alanine aminotransferase (ALT) < 5 upper limit of normal (N) before reexposure, with N as the upper limit of normal, and a doubling of the ALT value at reexposure as compared to the ALT value at baseline prior to reexposure. Second, reported methods to assess causality in the eight cases were evaluated, and then the liver specific Council for International Organizations of Medical Sciences (CIOMS) scale validated for hepatotoxicity cases was used for quantitative causality reevaluation. This scale consists of various specific elements with scores provided through the respective case data, and the sum of the scores yields a causality grading for each individual case of initially suspected hepatotoxicity. RESULTS: Details of positive reexposure test conditions and their individual results were scattered in virtually all cases, since reexposures were unintentional and allowed only retrospective rather than prospective assessments. In 1/8 cases, criteria for a positive reexposure were fulfilled, whereas in the remaining cases the reexposure test was classified as negative (n = 1), or the data were considered as uninterpretable due to missing information to comply adequately with the criteria (n = 6). In virtually all assessed cases, liver unspecific causality assessment methods were applied rather than a liver specific method such as the CIOMS scale. Using this scale, causality gradings for Herbalife in these eight cases were probable (n = 1), unlikely (n = 4), and excluded (n = 3). Confounding variables included low data quality, alternative diagnoses, poor exclusion of important other causes, and comedication by drugs and herbs in 6/8 cases. More specifically, problems were evident in some cases regarding temporal association, daily doses, exact start and end dates of product use, actual data of laboratory parameters such as ALT, and exact dechallenge characteristics. Shortcomings included scattered exclusion of hepatitis A-C, cytomegalovirus and Epstein Barr virus infection with only globally presented or lacking parameters. Hepatitis E virus infection was considered in one single patient and found positive, infections by herpes simplex virus and varicella zoster virus were excluded in none. CONCLUSION: Only one case fulfilled positive reexposure test criteria in initially assumed Herbalife hepatotoxicity, with lower CIOMS based causality gradings for the other cases than hitherto proposed. PMID:23898368

Causality

NASA Astrophysics Data System (ADS)

Pearl, Judea

2000-03-01

Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.

Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease

PubMed Central

Relton, Caroline L; Davey Smith, George

2012-01-01

The burgeoning interest in the field of epigenetics has precipitated the need to develop approaches to strengthen causal inference when considering the role of epigenetic mediators of environmental exposures on disease risk. Epigenetic markers, like any other molecular biomarker, are vulnerable to confounding and reverse causation. Here, we present a strategy, based on the well-established framework of Mendelian randomization, to interrogate the causal relationships between exposure, DNA methylation and outcome. The two-step approach first uses a genetic proxy for the exposure of interest to assess the causal relationship between exposure and methylation. A second step then utilizes a genetic proxy for DNA methylation to interrogate the causal relationship between DNA methylation and outcome. The rationale, origins, methodology, advantages and limitations of this novel strategy are presented. PMID:22422451

An assessment of predominant causal factors of pilot deviations that contribute to runway incursions

NASA Astrophysics Data System (ADS)

Campbell, Denado M.

The aim of this study was to identify predominant causal factors of pilot deviations in runway incursions over a two-year period. Runway incursion reports were obtained from NASA's Aviation Safety Reporting System (ASRS), and a qualitative method was used by classifying and coding each report to a specific causal factor(s). The causal factors that were used were substantiated by research from the Aircraft Owner's and Pilot's Association that found that these causal factors were the most common in runway incursion incidents and accidents. An additional causal factor was also utilized to determine the significance of pilot training in relation to runway incursions. From the reports examined, it was found that miscommunication and situational awareness have the greatest impact on pilots and are most often the major causes of runway incursions. This data can be used to assist airports, airlines, and the FAA to understand trends in pilot deviations, and to find solutions for specific problem areas in runway incursion incidents.

Could Plasmodium vivax malaria trigger malnutrition? Revisiting the Bradford Hill criteria to assess a causal relationship between two neglected problems.

PubMed

Monteiro, Wuelton Marcelo; Alexandre, Márcia Araújo; Siqueira, André; Melo, Gisely; Romero, Gustavo Adolfo Sierra; d'Ávila, Efrem; Benzecry, Silvana Gomes; Leite, Heitor Pons; Lacerda, Marcus Vinícius Guimarães

2016-01-01

The benign characteristics formerly attributed to Plasmodium vivax infections have recently changed owing to the increasing number of reports of severe vivax malaria resulting in a broad spectrum of clinical complications, probably including undernutrition. Causal inference is a complex process, and arriving at a tentative inference of the causal or non-causal nature of an association is a subjective process limited by the existing evidence. Applying classical epidemiology principles, such as the Bradford Hill criteria, may help foster an understanding of causality and lead to appropriate interventions being proposed that may improve quality of life and decrease morbidity in neglected populations. Here, we examined these criteria in the context of the available data suggesting that vivax malaria may substantially contribute to childhood malnutrition. We found the data supported a role for P. vivax in the etiology of undernutrition in endemic areas. Thus, the application of modern causal inference tools, in future studies, may be useful in determining causation.

Children's Concepts of How People Get Babies

ERIC Educational Resources Information Center

Bernstein, Anne C.; Cowan, Philip A.

1975-01-01

Twenty children, 3-12 years old, were given a newly constructed interview on their concepts of human reproduction (social causality), in conjunction with Piaget-type tasks assessing physical conservation-identity, physical causality, and a new social identity task. The children's concepts of human reproduction appeared to proceed through a…

Robotics: Assessing Its Role in Improving Mathematics Skills for Grades 4 to 5

ERIC Educational Resources Information Center

Laughlin, Sara Rose

2013-01-01

Inspiring and motivating students to pursue science, technology, engineering, and mathematics education continues to be an important educational focus in the United States. Robotics programs are one strategy developed to accomplish this goal. This causal comparative study focused on investigating whether a causal relationship exists between…

Magical Thinking in Formal Operational Adults.

ERIC Educational Resources Information Center

Lesser, R.; Paisner, M.

1985-01-01

Female adult members of a spiritual community denying the existence of chance were matched by age and educational level with adult female nonmembers. Level of development of logical operations and causal belief systems were assessed. Findings indicate that personally charged, magical concepts of causality can develop into maturity and exist…

Causal uncertainty, claimed and behavioural self-handicapping.

PubMed

Thompson, Ted; Hepburn, Jonathan

2003-06-01

Causal uncertainty beliefs involve doubts about the causes of events, and arise as a consequence of non-contingent evaluative feedback: feedback that leaves the individual uncertain about the causes of his or her achievement outcomes. Individuals high in causal uncertainty are frequently unable to confidently attribute their achievement outcomes, experience anxiety in achievement situations and as a consequence are likely to engage in self-handicapping behaviour. Accordingly, we sought to establish links between trait causal uncertainty, claimed and behavioural self-handicapping. Participants were N=72 undergraduate students divided equally between high and low causally uncertain groups. We used a 2 (causal uncertainty status: high, low) x 3 (performance feedback condition: success, non-contingent success, non-contingent failure) between-subjects factorial design to examine the effects of causal uncertainty on achievement behaviour. Following performance feedback, participants completed 20 single-solution anagrams and 12 remote associate tasks serving as performance measures, and 16 unicursal tasks to assess practice effort. Participants also completed measures of claimed handicaps, state anxiety and attributions. Relative to low causally uncertain participants, high causally uncertain participants claimed more handicaps prior to performance on the anagrams and remote associates, reported higher anxiety, attributed their failure to internal, stable factors, and reduced practice effort on the unicursal tasks, evident in fewer unicursal tasks solved. These findings confirm links between trait causal uncertainty and claimed and behavioural self-handicapping, highlighting the need for educators to facilitate means by which students can achieve surety in the manner in which they attribute the causes of their achievement outcomes.

A pilot randomised controlled trial to assess the utility of an e-learning package that trains users in adverse drug reaction causality.

PubMed

Conroy, Elizabeth J; Kirkham, Jamie J; Bellis, Jennifer R; Peak, Matthew; Smyth, Rosalind L; Williamson, Paula R; Pirmohamed, Munir

2015-12-01

Causality assessment of adverse drug reactions (ADRs) by healthcare professionals is often informal which can lead to inconsistencies in practice. The Liverpool Causality Assessment Tool (LCAT) offers a systematic approach. An interactive, web-based, e-learning package, the Liverpool ADR Causality Assessment e-learning Package (LACAeP), was designed to improve causality assessment using the LCAT. This study aimed to (1) get feedback on usability and usefulness on the LACAeP, identify areas for improvement and development, and generate data on effect size to inform a larger scale study; and (2) test the usability and usefulness of the LCAT. A pilot, single-blind, parallel-group, randomised controlled trial hosted by the University of Liverpool was undertaken. Participants were paediatric medical trainees at specialty training level 1+ within the Mersey and North-West England Deaneries. Participants were randomised (1 : 1) access to the LACAeP or no training. The primary efficacy outcome was score by correct classification, predefined by a multidisciplinary panel of experts. Following participation, feedback on both the LCAT and the LACAeP was obtained, via a built in survey, from participants. Of 57 randomised, 35 completed the study. Feedback was mainly positive although areas for improvement were identified. Seventy-four per cent of participants found the LCAT easy to use and 78% found the LACAeP training useful. Sixty-one per cent would be unlikely to recommend the training. Scores ranged from 4 to 13 out of 20. The LACAeP increased scores by 1.3, but this was not significant. Improving the LACAeP before testing it in an appropriately powered trial, informed by the differences observed, is required. Rigorous evaluation will enable a quality resource that will be of value in healthcare professional training. © 2015 The Authors. International Journal of Pharmacy Practice published by John Wiley & Sons Ltd on behalf of Royal Pharmaceutical Society.

A pilot randomised controlled trial to assess the utility of an e‐learning package that trains users in adverse drug reaction causality

PubMed Central

Kirkham, Jamie J.; Bellis, Jennifer R.; Peak, Matthew; Smyth, Rosalind L.; Williamson, Paula R.; Pirmohamed, Munir

2015-01-01

Abstract Objectives Causality assessment of adverse drug reactions (ADRs) by healthcare professionals is often informal which can lead to inconsistencies in practice. The Liverpool Causality Assessment Tool (LCAT) offers a systematic approach. An interactive, web‐based, e‐learning package, the Liverpool ADR Causality Assessment e‐learning Package (LACAeP), was designed to improve causality assessment using the LCAT. This study aimed to (1) get feedback on usability and usefulness on the LACAeP, identify areas for improvement and development, and generate data on effect size to inform a larger scale study; and (2) test the usability and usefulness of the LCAT. Methods A pilot, single‐blind, parallel‐group, randomised controlled trial hosted by the University of Liverpool was undertaken. Participants were paediatric medical trainees at specialty training level 1+ within the Mersey and North‐West England Deaneries. Participants were randomised (1 : 1) access to the LACAeP or no training. The primary efficacy outcome was score by correct classification, predefined by a multidisciplinary panel of experts. Following participation, feedback on both the LCAT and the LACAeP was obtained, via a built in survey, from participants. Key findings Of 57 randomised, 35 completed the study. Feedback was mainly positive although areas for improvement were identified. Seventy‐four per cent of participants found the LCAT easy to use and 78% found the LACAeP training useful. Sixty‐one per cent would be unlikely to recommend the training. Scores ranged from 4 to 13 out of 20. The LACAeP increased scores by 1.3, but this was not significant. Conclusions Improving the LACAeP before testing it in an appropriately powered trial, informed by the differences observed, is required. Rigorous evaluation will enable a quality resource that will be of value in healthcare professional training. PMID:26032626

Fear of cancer recurrence and psychological well-being in women with breast cancer: The role of causal cancer attributions and optimism.

PubMed

Dumalaon-Canaria, J A; Prichard, I; Hutchinson, A D; Wilson, C

2018-01-01

This study aims to examine the association between cancer causal attributions, fear of cancer recurrence (FCR) and psychological well-being and the possible moderating effect of optimism among women with a previous diagnosis of breast cancer. Participants (N = 314) completed an online self-report assessment of causal attributions for their own breast cancer, FCR, psychological well-being and optimism. Simultaneous multiple regression analyses were conducted to explore the overall contribution of causal attributions to FCR and psychological well-being separately. Hierarchical multiple regression analyses were also utilised to examine the potential moderating influence of dispositional optimism on the relationship between causal attributions and FCR and psychological well-being. Causal attributions of environmental exposures, family history and stress were significantly associated with higher FCR. The attribution of stress was also significantly associated with lower psychological well-being. Optimism did not moderate the relationship between causal attributions and FCR or well-being. The observed relationships between causal attributions for breast cancer and FCR and psychological well-being suggest that the inclusion of causal attributions in screening for FCR is potentially important. Health professionals may need to provide greater psychological support to women who attribute their cancer to non-modifiable causes and consequently continue to experience distress. © 2016 John Wiley & Sons Ltd.

Zika Virus Infection as a Cause of Congenital Brain Abnormalities and Guillain-Barré Syndrome: Systematic Review.

PubMed

Krauer, Fabienne; Riesen, Maurane; Reveiz, Ludovic; Oladapo, Olufemi T; Martínez-Vega, Ruth; Porgo, Teegwendé V; Haefliger, Anina; Broutet, Nathalie J; Low, Nicola

2017-01-01

The World Health Organization (WHO) stated in March 2016 that there was scientific consensus that the mosquito-borne Zika virus was a cause of the neurological disorder Guillain-Barré syndrome (GBS) and of microcephaly and other congenital brain abnormalities based on rapid evidence assessments. Decisions about causality require systematic assessment to guide public health actions. The objectives of this study were to update and reassess the evidence for causality through a rapid and systematic review about links between Zika virus infection and (a) congenital brain abnormalities, including microcephaly, in the foetuses and offspring of pregnant women and (b) GBS in any population, and to describe the process and outcomes of an expert assessment of the evidence about causality. The study had three linked components. First, in February 2016, we developed a causality framework that defined questions about the relationship between Zika virus infection and each of the two clinical outcomes in ten dimensions: temporality, biological plausibility, strength of association, alternative explanations, cessation, dose-response relationship, animal experiments, analogy, specificity, and consistency. Second, we did a systematic review (protocol number CRD42016036693). We searched multiple online sources up to May 30, 2016 to find studies that directly addressed either outcome and any causality dimension, used methods to expedite study selection, data extraction, and quality assessment, and summarised evidence descriptively. Third, WHO convened a multidisciplinary panel of experts who assessed the review findings and reached consensus statements to update the WHO position on causality. We found 1,091 unique items up to May 30, 2016. For congenital brain abnormalities, including microcephaly, we included 72 items; for eight of ten causality dimensions (all except dose-response relationship and specificity), we found that more than half the relevant studies supported a causal association with Zika virus infection. For GBS, we included 36 items, of which more than half the relevant studies supported a causal association in seven of ten dimensions (all except dose-response relationship, specificity, and animal experimental evidence). Articles identified nonsystematically from May 30 to July 29, 2016 strengthened the review findings. The expert panel concluded that (a) the most likely explanation of available evidence from outbreaks of Zika virus infection and clusters of microcephaly is that Zika virus infection during pregnancy is a cause of congenital brain abnormalities including microcephaly, and (b) the most likely explanation of available evidence from outbreaks of Zika virus infection and GBS is that Zika virus infection is a trigger of GBS. The expert panel recognised that Zika virus alone may not be sufficient to cause either congenital brain abnormalities or GBS but agreed that the evidence was sufficient to recommend increased public health measures. Weaknesses are the limited assessment of the role of dengue virus and other possible cofactors, the small number of comparative epidemiological studies, and the difficulty in keeping the review up to date with the pace of publication of new research. Rapid and systematic reviews with frequent updating and open dissemination are now needed both for appraisal of the evidence about Zika virus infection and for the next public health threats that will emerge. This systematic review found sufficient evidence to say that Zika virus is a cause of congenital abnormalities and is a trigger of GBS.

Zika Virus Infection as a Cause of Congenital Brain Abnormalities and Guillain–Barré Syndrome: Systematic Review

PubMed Central

Reveiz, Ludovic; Oladapo, Olufemi T.; Martínez-Vega, Ruth; Haefliger, Anina

2017-01-01

Background The World Health Organization (WHO) stated in March 2016 that there was scientific consensus that the mosquito-borne Zika virus was a cause of the neurological disorder Guillain–Barré syndrome (GBS) and of microcephaly and other congenital brain abnormalities based on rapid evidence assessments. Decisions about causality require systematic assessment to guide public health actions. The objectives of this study were to update and reassess the evidence for causality through a rapid and systematic review about links between Zika virus infection and (a) congenital brain abnormalities, including microcephaly, in the foetuses and offspring of pregnant women and (b) GBS in any population, and to describe the process and outcomes of an expert assessment of the evidence about causality. Methods and Findings The study had three linked components. First, in February 2016, we developed a causality framework that defined questions about the relationship between Zika virus infection and each of the two clinical outcomes in ten dimensions: temporality, biological plausibility, strength of association, alternative explanations, cessation, dose–response relationship, animal experiments, analogy, specificity, and consistency. Second, we did a systematic review (protocol number CRD42016036693). We searched multiple online sources up to May 30, 2016 to find studies that directly addressed either outcome and any causality dimension, used methods to expedite study selection, data extraction, and quality assessment, and summarised evidence descriptively. Third, WHO convened a multidisciplinary panel of experts who assessed the review findings and reached consensus statements to update the WHO position on causality. We found 1,091 unique items up to May 30, 2016. For congenital brain abnormalities, including microcephaly, we included 72 items; for eight of ten causality dimensions (all except dose–response relationship and specificity), we found that more than half the relevant studies supported a causal association with Zika virus infection. For GBS, we included 36 items, of which more than half the relevant studies supported a causal association in seven of ten dimensions (all except dose–response relationship, specificity, and animal experimental evidence). Articles identified nonsystematically from May 30 to July 29, 2016 strengthened the review findings. The expert panel concluded that (a) the most likely explanation of available evidence from outbreaks of Zika virus infection and clusters of microcephaly is that Zika virus infection during pregnancy is a cause of congenital brain abnormalities including microcephaly, and (b) the most likely explanation of available evidence from outbreaks of Zika virus infection and GBS is that Zika virus infection is a trigger of GBS. The expert panel recognised that Zika virus alone may not be sufficient to cause either congenital brain abnormalities or GBS but agreed that the evidence was sufficient to recommend increased public health measures. Weaknesses are the limited assessment of the role of dengue virus and other possible cofactors, the small number of comparative epidemiological studies, and the difficulty in keeping the review up to date with the pace of publication of new research. Conclusions Rapid and systematic reviews with frequent updating and open dissemination are now needed both for appraisal of the evidence about Zika virus infection and for the next public health threats that will emerge. This systematic review found sufficient evidence to say that Zika virus is a cause of congenital abnormalities and is a trigger of GBS. PMID:28045901

[Causality link in criminal law: role of epidemiology].

PubMed

Zocchetti, C; Riboldi, L

2003-01-01

This paper focusses on the role of epidemiology in demonstrating causality in criminal trials of toxic tort litigation. First of all, consideration is given of the specificity of the criminal trial and of the role of the epidemiologist as expert witness. As a second step the concept of causality is examined separating general from specific (individual level) causality. As regards general causality, strategies based on some criteria (example: Bradford-Hill criteria) are contrasted with approaches that do not consider causality a matter of science but one of health policy; and specific methods frequently used (meta-analysis, risk assessment, International Boards evaluation,....) are discussed, with special reference to the adoption of high-level standards and to the context of cross-examination. As regards individual level causality the difficulties of the epidemiologic approach to such evaluation are stressed, with special reference to topics like expected value, attributable risk, and probability of causation. All examples are taken from Italian court trials. A general comment on the difficulties of using the criminal trial (dominated by the "but for" rule) for toxic tort litigation and on the opportunity to switch to trials (civil, administrative) with less stringent causal rules ("more probable than not") is offered, with a consideration also of what are called "class actions".

Cross-species coherence in effects and modes of action in support of causality determinations in the U.S. Environmental Protection Agency's Integrated Science Assessment for Lead.

PubMed

Lassiter, Meredith Gooding; Owens, Elizabeth Oesterling; Patel, Molini M; Kirrane, Ellen; Madden, Meagan; Richmond-Bryant, Jennifer; Hines, Erin Pias; Davis, J Allen; Vinikoor-Imler, Lisa; Dubois, Jean-Jacques

2015-04-01

The peer-reviewed literature on the health and ecological effects of lead (Pb) indicates common effects and underlying modes of action across multiple organisms for several endpoints. Based on such observations, the United States (U.S.) Environmental Protection Agency (EPA) applied a cross-species approach in the 2013 Integrated Science Assessment (ISA) for Lead for evaluating the causality of relationships between Pb exposure and specific endpoints that are shared by humans, laboratory animals, and ecological receptors (i.e., hematological effects, reproductive and developmental effects, and nervous system effects). Other effects of Pb (i.e., cardiovascular, renal, and inflammatory responses) are less commonly assessed in aquatic and terrestrial wildlife limiting the application of cross-species comparisons. Determinations of causality in ISAs are guided by a framework for classifying the weight of evidence across scientific disciplines and across related effects by considering aspects such as biological plausibility and coherence. As illustrated for effects of Pb where evidence across species exists, the integration of coherent effects and common underlying modes of action can serve as a means to substantiate conclusions regarding the causal nature of the health and ecological effects of environmental toxicants. Published by Elsevier Ireland Ltd.

Granger Causality Testing with Intensive Longitudinal Data.

PubMed

Molenaar, Peter C M

2018-06-01

The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.

'Mendelian randomization': an approach for exploring causal relations in epidemiology.

PubMed

Gupta, V; Walia, G K; Sachdeva, M P

2017-04-01

To assess the current status of Mendelian randomization (MR) approach in effectively influencing the observational epidemiology for examining causal relationships. Narrative review on studies related to principle, strengths, limitations, and achievements of MR approach. Observational epidemiological studies have repeatedly produced several beneficiary associations which were discarded when tested by standard randomized controlled trials (RCTs). The technique which is more feasible, highly similar to RCTs, and has the potential to establish a causal relationship between modifiable exposures and disease outcomes is known as MR. The technique uses genetic variants related to modifiable traits/exposures as instruments for detecting causal and directional associations with outcomes. In the last decade, the approach of MR has methodologically developed and progressed to a stage of high acceptance among the epidemiologists and is gradually expanding the landscape of causal relationships in non-communicable chronic diseases. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Productivity in Academia: An Assessment of Causal Linkages between Output and Outcome Indicators

ERIC Educational Resources Information Center

Wamala, Robert; Ssembatya, Vincent A.

2015-01-01

Purpose: The purpose of this paper is to investigate causal linkages between output and outcome indicators of productivity in academia. Design/methodology/approach: The duration of teaching service and the number of graduate students supervised to completion were adopted as output indicators of productivity. Equivalent outcome indicators were the…

The Causal Effects of Grade Retention on Behavioral Outcomes

ERIC Educational Resources Information Center

Martorell, Paco; Mariano, Louis T.

2018-01-01

This study examines the impact of grade retention on behavioral outcomes under a comprehensive assessment-based student promotion policy in New York City. To isolate the causal effect of grade retention, we implement a fuzzy regression discontinuity (RD) design that exploits the fact that grade retention is largely determined by whether a student…

The Children's Perceived Locus of Causality Scale for Physical Education

ERIC Educational Resources Information Center

Pannekoek, Linda; Piek, Jan P.; Hagger, Martin S.

2014-01-01

A mixed methods design was applied to evaluate the application of the Perceived Locus of Causality scale (PLOC) to preadolescent samples in physical education settings. Subsequent to minor item adaptations to accommodate the assessment of younger samples, qualitative pilot tests were performed (N = 15). Children's reports indicated the need…

Assessing the causal effect of policies: an example using stochastic interventions.

PubMed

Díaz, Iván; van der Laan, Mark J

2013-11-19

Assessing the causal effect of an exposure often involves the definition of counterfactual outcomes in a hypothetical world in which the stochastic nature of the exposure is modified. Although stochastic interventions are a powerful tool to measure the causal effect of a realistic intervention that intends to alter the population distribution of an exposure, their importance to answer questions about plausible policy interventions has been obscured by the generalized use of deterministic interventions. In this article, we follow the approach described in Díaz and van der Laan (2012) to define and estimate the effect of an intervention that is expected to cause a truncation in the population distribution of the exposure. The observed data parameter that identifies the causal parameter of interest is established, as well as its efficient influence function under the non-parametric model. Inverse probability of treatment weighted (IPTW), augmented IPTW and targeted minimum loss-based estimators (TMLE) are proposed, their consistency and efficiency properties are determined. An extension to longitudinal data structures is presented and its use is demonstrated with a real data example.

Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review.

PubMed

Haber, Noah; Smith, Emily R; Moscoe, Ellen; Andrews, Kathryn; Audy, Robin; Bell, Winnie; Brennan, Alana T; Breskin, Alexander; Kane, Jeremy C; Karra, Mahesh; McClure, Elizabeth S; Suarez, Elizabeth A

2018-01-01

The pathway from evidence generation to consumption contains many steps which can lead to overstatement or misinformation. The proliferation of internet-based health news may encourage selection of media and academic research articles that overstate strength of causal inference. We investigated the state of causal inference in health research as it appears at the end of the pathway, at the point of social media consumption. We screened the NewsWhip Insights database for the most shared media articles on Facebook and Twitter reporting about peer-reviewed academic studies associating an exposure with a health outcome in 2015, extracting the 50 most-shared academic articles and media articles covering them. We designed and utilized a review tool to systematically assess and summarize studies' strength of causal inference, including generalizability, potential confounders, and methods used. These were then compared with the strength of causal language used to describe results in both academic and media articles. Two randomly assigned independent reviewers and one arbitrating reviewer from a pool of 21 reviewers assessed each article. We accepted the most shared 64 media articles pertaining to 50 academic articles for review, representing 68% of Facebook and 45% of Twitter shares in 2015. Thirty-four percent of academic studies and 48% of media articles used language that reviewers considered too strong for their strength of causal inference. Seventy percent of academic studies were considered low or very low strength of inference, with only 6% considered high or very high strength of causal inference. The most severe issues with academic studies' causal inference were reported to be omitted confounding variables and generalizability. Fifty-eight percent of media articles were found to have inaccurately reported the question, results, intervention, or population of the academic study. We find a large disparity between the strength of language as presented to the research consumer and the underlying strength of causal inference among the studies most widely shared on social media. However, because this sample was designed to be representative of the articles selected and shared on social media, it is unlikely to be representative of all academic and media work. More research is needed to determine how academic institutions, media organizations, and social network sharing patterns impact causal inference and language as received by the research consumer.

Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review

PubMed Central

Smith, Emily R.; Moscoe, Ellen; Audy, Robin; Bell, Winnie; Brennan, Alana T.; Breskin, Alexander; Kane, Jeremy C.; Suarez, Elizabeth A.

2018-01-01

Background The pathway from evidence generation to consumption contains many steps which can lead to overstatement or misinformation. The proliferation of internet-based health news may encourage selection of media and academic research articles that overstate strength of causal inference. We investigated the state of causal inference in health research as it appears at the end of the pathway, at the point of social media consumption. Methods We screened the NewsWhip Insights database for the most shared media articles on Facebook and Twitter reporting about peer-reviewed academic studies associating an exposure with a health outcome in 2015, extracting the 50 most-shared academic articles and media articles covering them. We designed and utilized a review tool to systematically assess and summarize studies’ strength of causal inference, including generalizability, potential confounders, and methods used. These were then compared with the strength of causal language used to describe results in both academic and media articles. Two randomly assigned independent reviewers and one arbitrating reviewer from a pool of 21 reviewers assessed each article. Results We accepted the most shared 64 media articles pertaining to 50 academic articles for review, representing 68% of Facebook and 45% of Twitter shares in 2015. Thirty-four percent of academic studies and 48% of media articles used language that reviewers considered too strong for their strength of causal inference. Seventy percent of academic studies were considered low or very low strength of inference, with only 6% considered high or very high strength of causal inference. The most severe issues with academic studies’ causal inference were reported to be omitted confounding variables and generalizability. Fifty-eight percent of media articles were found to have inaccurately reported the question, results, intervention, or population of the academic study. Conclusions We find a large disparity between the strength of language as presented to the research consumer and the underlying strength of causal inference among the studies most widely shared on social media. However, because this sample was designed to be representative of the articles selected and shared on social media, it is unlikely to be representative of all academic and media work. More research is needed to determine how academic institutions, media organizations, and social network sharing patterns impact causal inference and language as received by the research consumer. PMID:29847549

Three Cs in measurement models: causal indicators, composite indicators, and covariates.

PubMed

Bollen, Kenneth A; Bauldry, Shawn

2011-09-01

In the last 2 decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that one can classify indicators into 2 categories: effect (reflective) indicators and causal (formative) indicators. We argue that the dichotomous view is too simple. Instead, there are effect indicators and 3 types of variables on which a latent variable depends: causal indicators, composite (formative) indicators, and covariates (the "Three Cs"). Causal indicators have conceptual unity, and their effects on latent variables are structural. Covariates are not concept measures, but are variables to control to avoid bias in estimating the relations between measures and latent variables. Composite (formative) indicators form exact linear combinations of variables that need not share a concept. Their coefficients are weights rather than structural effects, and composites are a matter of convenience. The failure to distinguish the Three Cs has led to confusion and questions, such as, Are causal and formative indicators different names for the same indicator type? Should an equation with causal or formative indicators have an error term? Are the coefficients of causal indicators less stable than effect indicators? Distinguishing between causal and composite indicators and covariates goes a long way toward eliminating this confusion. We emphasize the key role that subject matter expertise plays in making these distinctions. We provide new guidelines for working with these variable types, including identification of models, scaling latent variables, parameter estimation, and validity assessment. A running empirical example on self-perceived health illustrates our major points.

Perceived causal relations between anxiety, posttraumatic stress and depression: extension to moderation, mediation, and network analysis.

PubMed

Frewen, Paul A; Schmittmann, Verena D; Bringmann, Laura F; Borsboom, Denny

2013-01-01

Previous research demonstrates that posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame are frequently co-occurring problems that may be causally related. The present study utilized Perceived Causal Relations (PCR) scaling in order to assess participants' own attributions concerning whether and to what degree these co-occurring problems may be causally interrelated. 288 young adults rated the frequency and respective PCR scores associating their symptoms of posttraumatic reexperiencing, depression, anxiety, and guilt-shame. PCR scores were found to moderate associations between the frequency of posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame. Network analyses showed that the number of feedback loops between PCR scores was positively associated with symptom frequencies. Results tentatively support the interpretation of PCR scores as moderators of the association between different psychological problems, and lend support to the hypothesis that increased symptom frequencies are observed in the presence of an increased number of causal feedback loops between symptoms. Additionally, a perceived causal role for the reexperiencing of traumatic memories in exacerbating emotional disturbance was identified.

Using the Aesop's fable paradigm to investigate causal understanding of water displacement by New Caledonian crows.

PubMed

Jelbert, Sarah A; Taylor, Alex H; Cheke, Lucy G; Clayton, Nicola S; Gray, Russell D

2014-01-01

Understanding causal regularities in the world is a key feature of human cognition. However, the extent to which non-human animals are capable of causal understanding is not well understood. Here, we used the Aesop's fable paradigm--in which subjects drop stones into water to raise the water level and obtain an out of reach reward--to assess New Caledonian crows' causal understanding of water displacement. We found that crows preferentially dropped stones into a water-filled tube instead of a sand-filled tube; they dropped sinking objects rather than floating objects; solid objects rather than hollow objects, and they dropped objects into a tube with a high water level rather than a low one. However, they failed two more challenging tasks which required them to attend to the width of the tube, and to counter-intuitive causal cues in a U-shaped apparatus. Our results indicate that New Caledonian crows possess a sophisticated, but incomplete, understanding of the causal properties of displacement, rivalling that of 5-7 year old children.

Using the Aesop's Fable Paradigm to Investigate Causal Understanding of Water Displacement by New Caledonian Crows

PubMed Central

Jelbert, Sarah A.; Taylor, Alex H.; Cheke, Lucy G.; Clayton, Nicola S.; Gray, Russell D.

2014-01-01

Understanding causal regularities in the world is a key feature of human cognition. However, the extent to which non-human animals are capable of causal understanding is not well understood. Here, we used the Aesop's fable paradigm – in which subjects drop stones into water to raise the water level and obtain an out of reach reward – to assess New Caledonian crows' causal understanding of water displacement. We found that crows preferentially dropped stones into a water-filled tube instead of a sand-filled tube; they dropped sinking objects rather than floating objects; solid objects rather than hollow objects, and they dropped objects into a tube with a high water level rather than a low one. However, they failed two more challenging tasks which required them to attend to the width of the tube, and to counter-intuitive causal cues in a U-shaped apparatus. Our results indicate that New Caledonian crows possess a sophisticated, but incomplete, understanding of the causal properties of displacement, rivalling that of 5–7 year old children. PMID:24671252

Educational Outcomes of Synchronous and Asynchronous High School Students: A Quantitative Causal-Comparative Study of Online Algebra 1

ERIC Educational Resources Information Center

Berry, Sharon

2017-01-01

This study used a quantitative, causal-comparative design. It compared educational outcome data from online Algebra 1 courses to determine if a significant difference existed between synchronous and asynchronous students for end-of-course grades, state assessments scores, and student perceptions of their course. The study found that synchronous…

Relations among Parental Causal Attributions and Children's Math Performance and Task Persistence

ERIC Educational Resources Information Center

Tõeväli, Paula-Karoliina; Kikas, Eve

2017-01-01

The present longitudinal study examined the cross-lagged relations between parental causal attributions of children's math success to children's ability, parental help, children's math performance and task persistence. A total of 735 children, their mothers, fathers and teachers were assessed twice--at the end of the second and the third grades.…

Development of VNTR Markers to Assess Genetic Diversity of Mycosphaerella Fijiensis, the Causal Agent of Black Leaf Streak Disease in Bananas (Musa spp.)

USDA-ARS?s Scientific Manuscript database

Mycosphaerella fijiensis is the causal agent of black leaf streak (BLS) disease in bananas. This pathogen threatens global banana production as the main export cultivars are highly susceptible. As a consequence, commercial banana plantations must be protected chemically with fungicides; up to 40 app...

Propensity Score Techniques and the Assessment of Measured Covariate Balance to Test Causal Associations in Psychological Research

ERIC Educational Resources Information Center

Harder, Valerie S.; Stuart, Elizabeth A.; Anthony, James C.

2010-01-01

There is considerable interest in using propensity score (PS) statistical techniques to address questions of causal inference in psychological research. Many PS techniques exist, yet few guidelines are available to aid applied researchers in their understanding, use, and evaluation. In this study, the authors give an overview of available…

Compared to What? The Effectiveness of Synthetic Control Methods for Causal Inference in Educational Assessment

ERIC Educational Resources Information Center

Johnson, Clay Stephen

2013-01-01

Synthetic control methods are an innovative matching technique first introduced within the economics and political science literature that have begun to find application in educational research as well. Synthetic controls create an aggregate-level, time-series comparison for a single treated unit of interest for causal inference with observational…

Assessing the Generalizability of Estimates of Causal Effects from Regression Discontinuity Designs

ERIC Educational Resources Information Center

Bloom, Howard S.; Porter, Kristin E.

2012-01-01

In recent years, the regression discontinuity design (RDD) has gained widespread recognition as a quasi-experimental method that when used correctly, can produce internally valid estimates of causal effects of a treatment, a program or an intervention (hereafter referred to as treatment effects). In an RDD study, subjects or groups of subjects…

Interpreting findings from Mendelian randomization using the MR-Egger method.

PubMed

Burgess, Stephen; Thompson, Simon G

2017-05-01

Mendelian randomization-Egger (MR-Egger) is an analysis method for Mendelian randomization using summarized genetic data. MR-Egger consists of three parts: (1) a test for directional pleiotropy, (2) a test for a causal effect, and (3) an estimate of the causal effect. While conventional analysis methods for Mendelian randomization assume that all genetic variants satisfy the instrumental variable assumptions, the MR-Egger method is able to assess whether genetic variants have pleiotropic effects on the outcome that differ on average from zero (directional pleiotropy), as well as to provide a consistent estimate of the causal effect, under a weaker assumption-the InSIDE (INstrument Strength Independent of Direct Effect) assumption. In this paper, we provide a critical assessment of the MR-Egger method with regard to its implementation and interpretation. While the MR-Egger method is a worthwhile sensitivity analysis for detecting violations of the instrumental variable assumptions, there are several reasons why causal estimates from the MR-Egger method may be biased and have inflated Type 1 error rates in practice, including violations of the InSIDE assumption and the influence of outlying variants. The issues raised in this paper have potentially serious consequences for causal inferences from the MR-Egger approach. We give examples of scenarios in which the estimates from conventional Mendelian randomization methods and MR-Egger differ, and discuss how to interpret findings in such cases.

Normalizing the causality between time series.

PubMed

Liang, X San

2015-08-01

Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

Normalizing the causality between time series

NASA Astrophysics Data System (ADS)

Liang, X. San

2015-08-01

Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

Does sufficient evidence exist to support a causal association between vitamin D status and cardiovascular disease risk? An assessment using Hill's criteria for causality.

PubMed

Weyland, Patricia G; Grant, William B; Howie-Esquivel, Jill

2014-09-02

Serum 25-hydroxyvitamin D (25(OH)D) levels have been found to be inversely associated with both prevalent and incident cardiovascular disease (CVD) risk factors; dyslipidemia, hypertension and diabetes mellitus. This review looks for evidence of a causal association between low 25(OH)D levels and increased CVD risk. We evaluated journal articles in light of Hill's criteria for causality in a biological system. The results of our assessment are as follows. Strength of association: many randomized controlled trials (RCTs), prospective and cross-sectional studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Consistency of observed association: most studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors in various populations, locations and circumstances. Temporality of association: many RCTs and prospective studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Biological gradient (dose-response curve): most studies assessing 25(OH)D levels and CVD risk found an inverse association exhibiting a linear biological gradient. Plausibility of biology: several plausible cellular-level causative mechanisms and biological pathways may lead from a low 25(OH)D level to increased risk for CVD with mediators, such as dyslipidemia, hypertension and diabetes mellitus. Experimental evidence: some well-designed RCTs found increased CVD risk factors with decreasing 25(OH)D levels. Analogy: the association between serum 25(OH)D levels and CVD risk is analogous to that between 25(OH)D levels and the risk of overall cancer, periodontal disease, multiple sclerosis and breast cancer. all relevant Hill criteria for a causal association in a biological system are satisfied to indicate a low 25(OH)D level as a CVD risk factor.

A Causal Model for Joint Evaluation of Placebo and Treatment-Specific Effects in Clinical Trials

PubMed Central

Zhang, Zhiwei; Kotz, Richard M.; Wang, Chenguang; Ruan, Shiling; Ho, Martin

2014-01-01

Summary Evaluation of medical treatments is frequently complicated by the presence of substantial placebo effects, especially on relatively subjective endpoints, and the standard solution to this problem is a randomized, double-blinded, placebo-controlled clinical trial. However, effective blinding does not guarantee that all patients have the same belief or mentality about which treatment they have received (or treatmentality, for brevity), making it difficult to interpret the usual intent-to-treat effect as a causal effect. We discuss the causal relationships among treatment, treatmentality and the clinical outcome of interest, and propose a causal model for joint evaluation of placebo and treatment-specific effects. The model highlights the importance of measuring and incorporating patient treatmentality and suggests that each treatment group should be considered a separate observational study with a patient's treatmentality playing the role of an uncontrolled exposure. This perspective allows us to adapt existing methods for dealing with confounding to joint estimation of placebo and treatment-specific effects using measured treatmentality data, commonly known as blinding assessment data. We first apply this approach to the most common type of blinding assessment data, which is categorical, and illustrate the methods using an example from asthma. We then propose that blinding assessment data can be collected as a continuous variable, specifically when a patient's treatmentality is measured as a subjective probability, and describe analytic methods for that case. PMID:23432119

Herbal hepatotoxicity: a critical review

PubMed Central

Teschke, Rolf; Frenzel, Christian; Glass, Xaver; Schulze, Johannes; Eickhoff, Axel

2013-01-01

This review deals with herbal hepatotoxicity, identical to herb induced liver injury (HILI), and critically summarizes the pitfalls associated with the evaluation of assumed HILI cases. Analysis of the relevant publications reveals that several dozens of different herbs and herbal products have been implicated to cause toxic liver disease, but major quality issues limit the validity of causality attribution. In most of these reports, discussions around quality specifications regarding herbal products, case data presentations and causality assessment methods prevail. Though the production of herbal drugs is under regulatory surveillance and quality aspects are normally not a matter of concern, low quality of the less regulated herbal supplements may be a critical issue considering product batch variability, impurities, adulterants and herb misidentifications. Regarding case data presentation, essential diagnostic information is often lacking, as is the use of valid and liver specific causality assessment methods that also consider alternative diseases. At present, causality is best assessed by using the Council for International Organizations of Medical Sciences scale ( CIOMS) in its original or updated form, which should primarily be applied prospectively by the treating physician when evaluating a patient rather than retrospectively by regulatory agencies. To cope with these problems, a common quality approach by manufacturers, physicians and regulatory agencies should strive for the best quality. We propose steps for improvements with impact on future cases of liver injury by herbs, herbal drugs and herbal supplements. PMID:22831551

Standardization of Nomenclature and Causality Assessment in Drug-Induced Liver Injury: Summary of a Clinical Research Workshop

PubMed Central

Fontana, Robert J.; Seeff, Leonard B.; Andrade, Raúl J.; Björnsson, Einar; Day, Christopher P.; Serrano, Jose; Hoofnagle, Jay H.

2013-01-01

Idiosyncratic drug-induced liver injury (DILI) is an important but relatively infrequent cause of potentially severe acute and chronic liver injury. The aim of this clinical research workshop was to review and attempt to standardize the current nomenclature and terminology used in DILI research. Because DILI is a diagnosis of exclusion, selected elements of the medical history, laboratory tests, and previous reports were proposed to improve causality assessment. Definitions and diagnostic criteria regarding the onset of DILI, evolution of liver injury, risk factors, and mandatory testing versus optional testing for competing causes were reviewed. In addition, the role of intentional and inadvertent rechallenge, liver histology, and host genetic polymorphisms in establishing the diagnosis and prognosis of DILI were reviewed. Consensus was established regarding the need to develop a web-of-knowledge database that provides concise, reliable, and updated information on cases of liver injury due to drugs and herbal and dietary supplements. In addition, the need to develop drug-specific computerized causality assessment methods that are derived from prospectively phenotyped cases was a high priority. Proposed scales for grading DILI severity and assessing the likelihood of an agent causing DILI and written criteria for improving the reliability, accuracy, and reproducibility of expert opinion were reviewed. Finally, the unique challenges of assessing causality in children, patients with underlying liver disease, and subjects taking herbal and dietary supplements were discussed. Conclusion: Workshop participants concluded that multicenter referral networks enrolling patients with suspected DILI according to standardized methodologies are needed. These networks should also collect biological samples that may provide crucial insights into the mechanism(s) of DILI with the ultimate aim of preventing future cases of DILI. PMID:20564754

Three Cs in Measurement Models: Causal Indicators, Composite Indicators, and Covariates

PubMed Central

Bollen, Kenneth A.; Bauldry, Shawn

2013-01-01

In the last two decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that we can classify indicators into two categories, effect (reflective) indicators and causal (formative) indicators. This paper argues that the dichotomous view is too simple. Instead, there are effect indicators and three types of variables on which a latent variable depends: causal indicators, composite (formative) indicators, and covariates (the “three Cs”). Causal indicators have conceptual unity and their effects on latent variables are structural. Covariates are not concept measures, but are variables to control to avoid bias in estimating the relations between measures and latent variable(s). Composite (formative) indicators form exact linear combinations of variables that need not share a concept. Their coefficients are weights rather than structural effects and composites are a matter of convenience. The failure to distinguish the “three Cs” has led to confusion and questions such as: are causal and formative indicators different names for the same indicator type? Should an equation with causal or formative indicators have an error term? Are the coefficients of causal indicators less stable than effect indicators? Distinguishing between causal and composite indicators and covariates goes a long way toward eliminating this confusion. We emphasize the key role that subject matter expertise plays in making these distinctions. We provide new guidelines for working with these variable types, including identification of models, scaling latent variables, parameter estimation, and validity assessment. A running empirical example on self-perceived health illustrates our major points. PMID:21767021

Assessment of causal associations between illness and criminal acts in those who are acquitted by reason of insanity.

PubMed

Skeie, Christian Aarup; Rasmussen, Kirsten

2015-02-24

The court proceedings after the terrorist attacks on 22 July 2011 reignited the debate on the justification for having a rule that regulates the insanity defence exclusively on the basis of a medical condition – the medical principle. The psychological principle represents an alternative that requires a causal relationship between the psychosis and the acts committed. In this article we investigate rulings made by the courts of appeal where the accused have been found legally insane at the time of the act, and elucidate the extent to which a causal relationship between the illness and the act appears to be in evidence. Data have been retrieved from rulings by the courts of appeal published at lovdata.no, which include anonymised rulings. Searches were made for cases under Section 39 (verdict of special sanctions) and Section 44 (acquittal by reason of insanity) of the General Civil Penal Code. Court rulings in which a possible causal relationship could be considered were included. The included rulings were carefully assessed with regard to whether a causal relationship existed between the mental disorder of the accused at the time and the criminal act. The search returned a total of 373 rulings, of which 75 were included. The vast majority of the charges referred to serious crimes. Diagnoses under ICD-10 category codes F20-29 (schizophrenia, schizotypal and delusional disorders) were the most frequently occurring type. In 17 of the 75 rulings (23%), it was judged that no causal relationship between the illness and the act existed. In 25 of 26 cases that involved homicide, a causal relationship between the illness and the act was judged to be evident. The data may indicate that the medical principle results in impunity in a considerable number of rulings where the illness of the accused apparently has had no effect on the acts committed.

What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts.

PubMed

Brion, Marie-Jo A; Lawlor, Debbie A; Matijasevich, Alicia; Horta, Bernardo; Anselmi, Luciana; Araújo, Cora L; Menezes, Ana Maria B; Victora, Cesar G; Smith, George Davey

2011-06-01

A novel approach is explored for improving causal inference in observational studies by comparing cohorts from high-income with low- or middle-income countries (LMIC), where confounding structures differ. This is applied to assessing causal effects of breastfeeding on child blood pressure (BP), body mass index (BMI) and intelligence quotient (IQ). Standardized approaches for assessing the confounding structure of breastfeeding by socio-economic position were applied to the British Avon Longitudinal Study of Parents and Children (ALSPAC) (N ≃ 5000) and Brazilian Pelotas 1993 cohorts (N ≃ 1000). This was used to improve causal inference regarding associations of breastfeeding with child BP, BMI and IQ. Analyses were extended to include results from a meta-analysis of five LMICs (N ≃ 10 000) and compared with a randomized trial of breastfeeding promotion. Findings Although higher socio-economic position was strongly associated with breastfeeding in ALSPAC, there was little such patterning in Pelotas. In ALSPAC, breastfeeding was associated with lower BP, lower BMI and higher IQ, adjusted for confounders, but in the directions expected if due to socioeconomic patterning. In contrast, in Pelotas, breastfeeding was not strongly associated with BP or BMI but was associated with higher IQ. Differences in associations observed between ALSPAC and the LMIC meta-analysis were in line with those observed between ALSPAC and Pelotas, but with robust evidence of heterogeneity detected between ALSPAC and the LMIC meta-analysis associations. Trial data supported the conclusions inferred by the cross-cohort comparisons, which provided evidence for causal effects on IQ but not for BP or BMI. While reported associations of breastfeeding with child BP and BMI are likely to reflect residual confounding, breastfeeding may have causal effects on IQ. Comparing associations between populations with differing confounding structures can be used to improve causal inference in observational studies.

Paracetamol in therapeutic dosages and acute liver injury: causality assessment in a prospective case series

PubMed Central

2011-01-01

Background Acute liver injury (ALI) induced by paracetamol overdose is a well known cause of emergency hospital admission and death. However, there is debate regarding the risk of ALI after therapeutic dosages of the drug. The aim is to describe the characteristics of patients admitted to hospital with jaundice who had previous exposure to therapeutic doses of paracetamol. An assessment of the causality role of paracetamol was performed in each case. Methods Based on the evaluation of prospectively gathered cases of ALI with detailed clinical information, thirty-two cases of ALI in non-alcoholic patients exposed to therapeutic doses of paracetamol were identified. Two authors assessed all drug exposures by using the CIOMS/RUCAM scale. Each case was classified into one of five categories based on the causality score for paracetamol. Results In four cases the role of paracetamol was judged to be unrelated, in two unlikely, and these were excluded from evaluation. In seven of the remaining 26 cases, the RUCAM score associated with paracetamol was higher than that associated with other concomitant medications. The estimated incidence of ALI related to the use of paracetamol in therapeutic dosages was 0.4 per million inhabitants older than 15 years of age and per year (99%CI, 0.2-0.8) and of 10 per million paracetamol users-year (95% CI 4.3-19.4). Conclusions Our results indicate that paracetamol in therapeutic dosages may be considered in the causality assessment in non-alcoholic patients with liver injury, even if the estimated incidence of ALI related to paracetamol appears to be low. PMID:21762481

Overview of the Clinical Consult Case Review of Adverse Events Following Immunization: Clinical Immunization Safety Assessment Network (CISA) 2004-2009

PubMed Central

Williams, S Elizabeth; Klein, Nicola P; Halsey, Neal; Dekker, Cornelia L; Baxter, Roger P; Marchant, Colin D; LaRussa, Philip S; Sparks, Robert C; Tokars, Jerome I; Pahud, Barbara A; Aukes, Laurie; Jakob, Kathleen; Coronel, Silvia; Choi, Howard; Slade, Barbara A; Edwards, Kathryn M

2016-01-01

Background In 2004 the Clinical Consult Case Review (CCCR) working group was formed within the CDC-funded Clinical immunization Safety Assessment (CISA) Network to review individual cases of adverse events following immunizations (AEFI). Methods Cases were referred by practitioners, health departments, or CDC employees. Vaccine Adverse Event Reporting System (VAERS) searches and literature reviews for similar cases were performed prior to review. After CCCR discussion, AEFI were assessed for a causal relationship with vaccination and recommendations regarding future immunizations were relayed back to the referring physicians. In 2010, surveys were sent to referring physicians to determine the utility and effectiveness of the CCCR service. Results CISA investigators reviewed 76 cases during 68 conference calls between April 2004 and December 2009. Almost half of cases (35/76) were neurological in nature. Similar AEFI for the specific vaccines received were discovered for 63 cases through VAERS searches and for 38 cases through PubMed searches. Causality assessment using the modified WHO criteria resulted in classifying 3 cases as definitely related to vaccine administration, 12 as probably related, 16 as possibly related, 18 as unlikely related, 10 as unrelated, and 17 had insufficient information to assign causality. The physician satisfaction survey was returned by 30 (57.7%) of those surveyed and a majority of respondents (93.3%) felt that the CCCR service was useful. Conclusions The CCCR provides advice about AEFI to practitioners, assigns potential causality, and contributes to an improved understanding of adverse health events following immunizations. PMID:21801776

Executive Emotional System Disruption as Causal Agent in Frontal Lobishness among Abused Children

ERIC Educational Resources Information Center

Naude, H.; Du Preez, C. S.; Pretorius, E.

2004-01-01

This article aims to explore Executive Emotional System (EES) disruption as causal agent in frontal lobishness among abused children. The "Revised Senior South African Individual Scale" (SSAIS-R) was used to assess a sample population of seventy-five male and female subjects between the ages of 8 years 0 months and 16 years 11 months who were…

ACSPRI 2014 4th International Social Science Methodology Conference Report

DTIC Science & Technology

2015-04-01

Validity, trustworthiness and rigour: quality and the idea of qualitative research . Journal of Advanced Nursing, 304-310. Spencer, L., Ritchie, J...increasing data quality; the Total Survey Error framework; multi-modal on-line surveying, quality frameworks for assessing qualitative research ; and...provided an overview of the current perspectives on causal claims in qualitative research . Three approaches to generating plausible causal

The Well-Being of Children Born to Teen Mothers: Multiple Approaches to Assessing the Causal Links. JCPR Working Paper.

ERIC Educational Resources Information Center

Levine, Judith A.; Pollack, Harold

This study used linked maternal-child data from the 1997-1998 National Longitudinal Survey of Youth to explore the wellbeing of children born to teenage mothers. Two econometric techniques explored the causal impact of early childbearing on subsequent child and adolescent outcomes. First, a fixed-effect, cousin-comparison analysis controlled for…

Assessing causal mechanistic interactions: a peril ratio index of synergy based on multiplicativity.

PubMed

Lee, Wen-Chung

2013-01-01

The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction as a genuine mechanistic interaction. The author adopts an alternative metric system for risk, the 'peril'. A peril is an exponentiated cumulative rate, or simply, the inverse of a survival (risk complement) or one plus an odds. The author proposes a new index based on multiplicativity of peril ratios, the 'peril ratio index of synergy based on multiplicativity' (PRISM). Under the assumption of no redundancy, PRISM can be used to assess synergisms in sufficient cause sense, i.e., causal co-actions or causal mechanistic interactions. It has a less stringent threshold to detect a synergy as compared to a previous index of 'relative excess risk due to interaction'. Using the new PRISM criterion, many situations in which there is not evidence of interaction judged by the traditional indices are in fact corresponding to bona fide positive or negative synergisms.

Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity

PubMed Central

Lee, Wen-Chung

2013-01-01

The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction as a genuine mechanistic interaction. The author adopts an alternative metric system for risk, the ‘peril’. A peril is an exponentiated cumulative rate, or simply, the inverse of a survival (risk complement) or one plus an odds. The author proposes a new index based on multiplicativity of peril ratios, the ‘peril ratio index of synergy based on multiplicativity’ (PRISM). Under the assumption of no redundancy, PRISM can be used to assess synergisms in sufficient cause sense, i.e., causal co-actions or causal mechanistic interactions. It has a less stringent threshold to detect a synergy as compared to a previous index of ‘relative excess risk due to interaction’. Using the new PRISM criterion, many situations in which there is not evidence of interaction judged by the traditional indices are in fact corresponding to bona fide positive or negative synergisms. PMID:23826299

The Russo-Williamson Theses in the social sciences: causal inference drawing on two types of evidence.

PubMed

Claveau, François

2012-12-01

This article examines two theses formulated by Russo and Williamson (2007) in their study of causal inference in the health sciences. The two theses are assessed against evidence from a specific case in the social sciences, i.e., research on the institutional determinants of the aggregate unemployment rate. The first Russo-Williamson Thesis is that a causal claim can only be established when it is jointly supported by difference-making and mechanistic evidence. This thesis is shown not to hold. While researchers in my case study draw extensively on both types of evidence, one causal claim out of the three analyzed is established even though it is exclusively supported by mechanistic evidence. The second Russo-Williamson Thesis is that standard accounts of causality fail to handle the dualist epistemology highlighted in the first Thesis. I argue that a counterfactual-manipulationist account of causality--which is endorsed by many philosophers as well as many social scientists--can perfectly make sense of the typical strategy in my case study to draw on both difference-making and mechanistic evidence; it is just an instance of the common strategy of increasing evidential variety. Copyright © 2012 Elsevier Ltd. All rights reserved.

Beyond Markov: Accounting for independence violations in causal reasoning.

PubMed

Rehder, Bob

2018-06-01

Although many theories of causal cognition are based on causal graphical models, a key property of such models-the independence relations stipulated by the Markov condition-is routinely violated by human reasoners. This article presents three new accounts of those independence violations, accounts that share the assumption that people's understanding of the correlational structure of data generated from a causal graph differs from that stipulated by causal graphical model framework. To distinguish these models, experiments assessed how people reason with causal graphs that are larger than those tested in previous studies. A traditional common cause network (Y 1 ←X→Y 2 ) was extended so that the effects themselves had effects (Z 1 ←Y 1 ←X→Y 2 →Z 2 ). A traditional common effect network (Y 1 →X←Y 2 ) was extended so that the causes themselves had causes (Z 1 →Y 1 →X←Y 2 ←Z 2 ). Subjects' inferences were most consistent with the beta-Q model in which consistent states of the world-those in which variables are either mostly all present or mostly all absent-are viewed as more probable than stipulated by the causal graphical model framework. Substantial variability in subjects' inferences was also observed, with the result that substantial minorities of subjects were best fit by one of the other models (the dual prototype or a leaky gate models). The discrepancy between normative and human causal cognition stipulated by these models is foundational in the sense that they locate the error not in people's causal reasoning but rather in their causal representations. As a result, they are applicable to any cognitive theory grounded in causal graphical models, including theories of analogy, learning, explanation, categorization, decision-making, and counterfactual reasoning. Preliminary evidence that independence violations indeed generalize to other judgment types is presented. Copyright © 2018 Elsevier Inc. All rights reserved.

The Teacher, the Physician and the Person: Exploring Causal Connections between Teaching Performance and Role Model Types Using Directed Acyclic Graphs

PubMed Central

Boerebach, Benjamin C. M.; Lombarts, Kiki M. J. M. H.; Scherpbier, Albert J. J.; Arah, Onyebuchi A.

2013-01-01

Background In fledgling areas of research, evidence supporting causal assumptions is often scarce due to the small number of empirical studies conducted. In many studies it remains unclear what impact explicit and implicit causal assumptions have on the research findings; only the primary assumptions of the researchers are often presented. This is particularly true for research on the effect of faculty’s teaching performance on their role modeling. Therefore, there is a need for robust frameworks and methods for transparent formal presentation of the underlying causal assumptions used in assessing the causal effects of teaching performance on role modeling. This study explores the effects of different (plausible) causal assumptions on research outcomes. Methods This study revisits a previously published study about the influence of faculty’s teaching performance on their role modeling (as teacher-supervisor, physician and person). We drew eight directed acyclic graphs (DAGs) to visually represent different plausible causal relationships between the variables under study. These DAGs were subsequently translated into corresponding statistical models, and regression analyses were performed to estimate the associations between teaching performance and role modeling. Results The different causal models were compatible with major differences in the magnitude of the relationship between faculty’s teaching performance and their role modeling. Odds ratios for the associations between teaching performance and the three role model types ranged from 31.1 to 73.6 for the teacher-supervisor role, from 3.7 to 15.5 for the physician role, and from 2.8 to 13.8 for the person role. Conclusions Different sets of assumptions about causal relationships in role modeling research can be visually depicted using DAGs, which are then used to guide both statistical analysis and interpretation of results. Since study conclusions can be sensitive to different causal assumptions, results should be interpreted in the light of causal assumptions made in each study. PMID:23936020

Improving Causal Inferences in Meta-analyses of Longitudinal Studies: Spanking as an Illustration.

PubMed

Larzelere, Robert E; Gunnoe, Marjorie Lindner; Ferguson, Christopher J

2018-05-24

To evaluate and improve the validity of causal inferences from meta-analyses of longitudinal studies, two adjustments for Time-1 outcome scores and a temporally backwards test are demonstrated. Causal inferences would be supported by robust results across both adjustment methods, distinct from results run backwards. A systematic strategy for evaluating potential confounds is also introduced. The methods are illustrated by assessing the impact of spanking on subsequent externalizing problems (child age: 18 months to 11 years). Significant results indicated a small risk or a small benefit of spanking, depending on the adjustment method. These meta-analytic methods are applicable for research on alternatives to spanking and other developmental science topics. The underlying principles can also improve causal inferences in individual studies. © 2018 Society for Research in Child Development.

Therapists' causal attributions of clients' problems and selection of intervention strategies.

PubMed

Royce, W S; Muehlke, C V

1991-04-01

Therapists' choices of intervention strategies are influenced by many factors, including judgments about the bases of clients' problems. To assess the relationships between such causal attributions and the selection of intervention strategies, 196 counselors, psychologists, and social workers responded to the written transcript of a client's interview by answering two questionnaires, a 1982 scale (Causal Dimension Scale by Russell) which measured causal attribution of the client's problem, and another which measured preference for emotional, rational, and active intervention strategies in dealing with the client, based on the 1979 E-R-A taxonomy of Frey and Raming. A significant relationship was found between the two sets of variables, with internal attributions linked to rational intervention strategies and stable attributions linked to active strategies. The results support Halleck's 1978 hypothesis that theories of psychotherapy tie interventions to etiological considerations.

Guidelines for investigating causality of sequence variants in human disease

PubMed Central

MacArthur, D. G.; Manolio, T. A.; Dimmock, D. P.; Rehm, H. L.; Shendure, J.; Abecasis, G. R.; Adams, D. R.; Altman, R. B.; Antonarakis, S. E.; Ashley, E. A.; Barrett, J. C.; Biesecker, L. G.; Conrad, D. F.; Cooper, G. M.; Cox, N. J.; Daly, M. J.; Gerstein, M. B.; Goldstein, D. B.; Hirschhorn, J. N.; Leal, S. M.; Pennacchio, L. A.; Stamatoyannopoulos, J. A.; Sunyaev, S. R.; Valle, D.; Voight, B. F.; Winckler, W.; Gunter, C.

2014-01-01

The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development. PMID:24759409

EARLY, LATE OR NEVER? WHEN DOES PARENTAL EDUCATION IMPACT CHILD OUTCOMES?

PubMed Central

Dickson, Matt; Gregg, Paul; Robinson, Harriet

2017-01-01

We estimate the causal effect of parents’ education on their children’s education and examine the timing of the impact. We identify the causal effect by exploiting the exogenous shift in (parents’) education levels induced by the 1972 minimum school leaving age reform in England. Increasing parental education has a positive causal effect on children’s outcomes that is evident in preschool assessments at age 4 and continues to be visible up to and including high-stakes examinations taken at age 16. Children of parents affected by the reform attain results around 0.1 standard deviations higher than those whose parents were not impacted. PMID:28736454

Guidelines for investigating causality of sequence variants in human disease.

PubMed

MacArthur, D G; Manolio, T A; Dimmock, D P; Rehm, H L; Shendure, J; Abecasis, G R; Adams, D R; Altman, R B; Antonarakis, S E; Ashley, E A; Barrett, J C; Biesecker, L G; Conrad, D F; Cooper, G M; Cox, N J; Daly, M J; Gerstein, M B; Goldstein, D B; Hirschhorn, J N; Leal, S M; Pennacchio, L A; Stamatoyannopoulos, J A; Sunyaev, S R; Valle, D; Voight, B F; Winckler, W; Gunter, C

2014-04-24

The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.

The Effects of Intelligence, Self-Concept, and Attributional Style on Metamemory and Memory Behavior: A Developmental Study. Paper 1.

ERIC Educational Resources Information Center

Schneider, Wolfgang; And Others

The influence of intelligence, self-concept, and causal attributions on metamemory and the metamemory-memory behavior relationship in grade-school children was studied. Following the assessment of intelligence, self-concept, and causal attributions, 105 children each from grades 3, 5, and 7 were given a metamemory interview and a sort-recall task.…

Effects of Student-Generated Diagrams versus Student-Generated Summaries on Conceptual Understanding of Causal and Dynamic Knowledge in Plate Tectonics.

ERIC Educational Resources Information Center

Gobert, Janice D.; Clement, John J.

1999-01-01

Grade five students' (n=58) conceptual understanding of plate tectonics was measured by analysis of student-generated summaries and diagrams, and by posttest assessment of both the spatial/static and causal/dynamic aspects of the domain. The diagram group outperformed the summary and text-only groups on the posttest measures. Discusses the effects…

Implementation and Assessment of an Intervention to Debias Adolescents against Causal Illusions

PubMed Central

Barberia, Itxaso; Blanco, Fernando; Cubillas, Carmelo P.; Matute, Helena

2013-01-01

Researchers have warned that causal illusions are at the root of many superstitious beliefs and fuel many people’s faith in pseudoscience, thus generating significant suffering in modern society. Therefore, it is critical that we understand the mechanisms by which these illusions develop and persist. A vast amount of research in psychology has investigated these mechanisms, but little work has been done on the extent to which it is possible to debias individuals against causal illusions. We present an intervention in which a sample of adolescents was introduced to the concept of experimental control, focusing on the need to consider the base rate of the outcome variable in order to determine if a causal relationship exists. The effectiveness of the intervention was measured using a standard contingency learning task that involved fake medicines that typically produce causal illusions. Half of the participants performed the contingency learning task before participating in the educational intervention (the control group), and the other half performed the task after they had completed the intervention (the experimental group). The participants in the experimental group made more realistic causal judgments than did those in the control group, which served as a baseline. To the best of our knowledge, this is the first evidence-based educational intervention that could be easily implemented to reduce causal illusions and the many problems associated with them, such as superstitions and belief in pseudoscience. PMID:23967189

Herbal hepatotoxicity: a tabular compilation of reported cases.

PubMed

Teschke, Rolf; Wolff, Albrecht; Frenzel, Christian; Schulze, Johannes; Eickhoff, Axel

2012-11-01

Herbal hepatotoxicity is a field that has rapidly grown over the last few years along with increased use of herbal products worldwide. To summarize the various facets of this disease, we undertook a literature search for herbs, herbal drugs and herbal supplements with reported cases of herbal hepatotoxicity. A selective literature search was performed to identify published case reports, spontaneous case reports, case series and review articles regarding herbal hepatotoxicity. A total of 185 publications were identified and the results compiled. They show 60 different herbs, herbal drugs and herbal supplements with reported potential hepatotoxicity, additional information including synonyms of individual herbs, botanical names and cross references are provided. If known, details are presented for specific ingredients and chemicals in herbal products, and for references with authors that can be matched to each herbal product and to its effect on the liver. Based on stringent causality assessment methods and/or positive re-exposure tests, causality was highly probable or probable for Ayurvedic herbs, Chaparral, Chinese herbal mixture, Germander, Greater Celandine, green tea, few Herbalife products, Jin Bu Huan, Kava, Ma Huang, Mistletoe, Senna, Syo Saiko To and Venencapsan(®). In many other publications, however, causality was not properly evaluated by a liver-specific and for hepatotoxicity-validated causality assessment method such as the scale of CIOMS (Council for International Organizations of Medical Sciences). This compilation presents details of herbal hepatotoxicity, assisting thereby clinical assessment of involved physicians in the future. © 2012 John Wiley & Sons A/S.

[Hepatotoxicity associated with the use of Herbalife].

PubMed

Jóhannsson, Magnús; Ormarsdóttir, Sif; Olafsson, Sigurdur

2010-03-01

Many herbal products are known to be hepatotoxic. In a recent survey in Iceland concerning adverse reactions related to herbal medicines, Herbalife products were implicated in the majority of the reported cases of hepatotoxicity. The clinical presentations of five cases of Herbalife related liver injury during the period of 1999-2008 are analysed. Causality was assessed by using the WHO-UMC system for causality assessment and the RUCAM method. Of the five cases there were four females and one male; median age was 46 years (range 29-78). Herbalife had been used for 1 to 7 months prior to presentation. Four patients presented with a hepatocellular and one with a cholestatic reaction. Median values were for bilirubin 190 micromol/L (range: 26-311; ref. < 20 micromol/L), ALP 407 U/L (range: 149-712; ref. 35-105 U/L) and ALT 24 87 U/L (range: 456-2637; ref. 70 and 45 U/L for males and females, respectively). Liver biopsy was performed in 2 patients and was consistent with toxic hepatitis in both cases. Other causes of hepatitis were excluded by appropriate serological testing and ultrasound. Causality assessment according to RUCAM was probable in three cases and possible in two. Using the WHO-UMC criteria causality was certain in one case, probable in two and possible in two cases. Hepatotoxicity is probably associated with the use of Herbalife products. Hepatotoxicity due to herbal remedies is an important differential diagnosis in the diagnostic work-up of liver injury.

Academic procrastination: the relationship between causal attribution styles and behavioral postponement.

PubMed

Badri Gargari, Rahim; Sabouri, Hossein; Norzad, Fatemeh

2011-01-01

This research was conducted to study the relationship between attribution and academic procrastination in University Students. The subjects were 203 undergraduate students, 55 males and 148 females, selected from English and French language and literature students of Tabriz University. Data were gathered through Procrastination Assessment Scale-student (PASS) and Causal Dimension Scale (CDA) and were analyzed by multiple regression analysis (stepwise). The results showed that there was a meaningful and negative relation between the locus of control and controllability in success context and academic procrastination. Besides, a meaningful and positive relation was observed between the locus of control and stability in failure context and procrastination. It was also found that 17% of the variance of procrastination was accounted by linear combination of attributions. We believe that causal attribution is a key in understanding procrastination in academic settings and is used by those who have the knowledge of Causal Attribution styles to organize their learning.

Autoimmune chronic spontaneous urticaria: What we know and what we do not know.

PubMed

Kolkhir, Pavel; Church, Martin K; Weller, Karsten; Metz, Martin; Schmetzer, Oliver; Maurer, Marcus

2017-06-01

Chronic spontaneous urticaria (CSU) is a mast cell-driven skin disease characterized by the recurrence of transient wheals, angioedema, or both for more than 6 weeks. Autoimmunity is thought to be one of the most frequent causes of CSU. Type I and II autoimmunity (ie, IgE to autoallergens and IgG autoantibodies to IgE or its receptor, respectively) have been implicated in the etiology and pathogenesis of CSU. We analyzed the relevant literature and assessed the existing evidence in support of a role for type I and II autoimmunity in CSU with the help of Hill's criteria of causality. For each of these criteria (ie, strength of association, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy), we categorized the strength of evidence as "insufficient," "low," "moderate," or "high" and then assigned levels of causality for type I and II autoimmunity in patients with CSU from level 1 (causal relationship) to level 5 (causality not likely). Based on the evidence in support of Hill's criteria, type I autoimmunity in patients with CSU has level 3 causality (causal relationship suggested), and type II autoimmunity has level 2 causality (causal relationship likely). There are still many aspects of the pathologic mechanisms of CSU that need to be resolved, but it is becoming clear that there are at least 2 distinct pathways, type I and type II autoimmunity, that contribute to the pathogenesis of this complex disease. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Analogical and category-based inference: a theoretical integration with Bayesian causal models.

PubMed

Holyoak, Keith J; Lee, Hee Seung; Lu, Hongjing

2010-11-01

A fundamental issue for theories of human induction is to specify constraints on potential inferences. For inferences based on shared category membership, an analogy, and/or a relational schema, it appears that the basic goal of induction is to make accurate and goal-relevant inferences that are sensitive to uncertainty. People can use source information at various levels of abstraction (including both specific instances and more general categories), coupled with prior causal knowledge, to build a causal model for a target situation, which in turn constrains inferences about the target. We propose a computational theory in the framework of Bayesian inference and test its predictions (parameter-free for the cases we consider) in a series of experiments in which people were asked to assess the probabilities of various causal predictions and attributions about a target on the basis of source knowledge about generative and preventive causes. The theory proved successful in accounting for systematic patterns of judgments about interrelated types of causal inferences, including evidence that analogical inferences are partially dissociable from overall mapping quality.

Structure and Connectivity Analysis of Financial Complex System Based on G-Causality Network

NASA Astrophysics Data System (ADS)

Xu, Chuan-Ming; Yan, Yan; Zhu, Xiao-Wu; Li, Xiao-Teng; Chen, Xiao-Song

2013-11-01

The recent financial crisis highlights the inherent weaknesses of the financial market. To explore the mechanism that maintains the financial market as a system, we study the interactions of U.S. financial market from the network perspective. Applied with conditional Granger causality network analysis, network density, in-degree and out-degree rankings are important indicators to analyze the conditional causal relationships among financial agents, and further to assess the stability of U.S. financial systems. It is found that the topological structure of G-causality network in U.S. financial market changed in different stages over the last decade, especially during the recent global financial crisis. Network density of the G-causality model is much higher during the period of 2007-2009 crisis stage, and it reaches the peak value in 2008, the most turbulent time in the crisis. Ranked by in-degrees and out-degrees, insurance companies are listed in the top of 68 financial institutions during the crisis. They act as the hubs which are more easily influenced by other financial institutions and simultaneously influence others during the global financial disturbance.

Cannabis and psychosis: what is the link?

PubMed

Ben Amar, Mohamed; Potvin, Stéphane

2007-06-01

Growing evidence supports the hypothesis that cannabis consumption is a risk factor for the development of psychotic symptoms. Nonetheless, controversy remains about the causal nature of the association. This review takes the debate further through a critical appraisal of the evidence. An electronic search was performed, allowing to identify 622 studies published until June 1st 2005. Longitudinal studies and literature reviews were selected if they addressed specifically the issues of the cannabis/psychosis relationship or possible mechanisms involved. Ten epidemiological studies were relevant: three supported a causal relationship between cannabis use and diagnosed psychosis; five suggested that chronic cannabis intake increases the frequency of psychotic symptoms, but not of diagnosed psychosis; and two showed no causal relationship. Potential neurobiological mechanisms were also identified, involving dopamine, endocannabinoids, and brain growth factors. Although there is evidence that cannabis use increases the risk of developing psychotic symptoms, the causal nature of this association remains unclear. Contributing factors include heavy consumption, length and early age of exposure, and psychotic vulnerability. This conclusion should be mitigated by uncertainty arising from cannabis use assessment, psychosis measurement, reverse causality and control of residual confounding.

Preschool physics: Using the invisible property of weight in causal reasoning tasks

PubMed Central

Williamson, Rebecca A.; Meltzoff, Andrew N.

2018-01-01

Causal reasoning is an important aspect of scientific thinking. Even young human children can use causal reasoning to explain observations, make predictions, and design actions to bring about specific outcomes in the physical world. Weight is an interesting type of cause because it is an invisible property. Here, we tested preschool children with causal problem-solving tasks that assessed their understanding of weight. In an experimental setting, 2- to 5-year-old children completed three different tasks in which they had to use weight to produce physical effects—an object displacement task, a balance-scale task, and a tower-building task. The results showed that the children’s understanding of how to use object weight to produce specific object-to-object causal outcomes improved as a function of age, with 4- and 5-year-olds showing above-chance performance on all three tasks. The younger children’s performance was more variable. The pattern of results provides theoretical insights into which aspects of weight processing are particularly difficult for preschool children and why they find it difficult. PMID:29561840

Preschool physics: Using the invisible property of weight in causal reasoning tasks.

PubMed

Wang, Zhidan; Williamson, Rebecca A; Meltzoff, Andrew N

2018-01-01

Causal reasoning is an important aspect of scientific thinking. Even young human children can use causal reasoning to explain observations, make predictions, and design actions to bring about specific outcomes in the physical world. Weight is an interesting type of cause because it is an invisible property. Here, we tested preschool children with causal problem-solving tasks that assessed their understanding of weight. In an experimental setting, 2- to 5-year-old children completed three different tasks in which they had to use weight to produce physical effects-an object displacement task, a balance-scale task, and a tower-building task. The results showed that the children's understanding of how to use object weight to produce specific object-to-object causal outcomes improved as a function of age, with 4- and 5-year-olds showing above-chance performance on all three tasks. The younger children's performance was more variable. The pattern of results provides theoretical insights into which aspects of weight processing are particularly difficult for preschool children and why they find it difficult.

Moral asymmetries in judgments of agency withstand ludicrous causal deviance.

PubMed

Sousa, Paulo; Holbrook, Colin; Swiney, Lauren

2015-01-01

Americans have been shown to attribute greater intentionality to immoral than to amoral actions in cases of causal deviance, that is, cases where a goal is satisfied in a way that deviates from initially planned means (e.g., a gunman wants to hit a target and his hand slips, but the bullet ricochets off a rock into the target). However, past research has yet to assess whether this asymmetry persists in cases of extreme causal deviance. Here, we manipulated the level of mild to extreme causal deviance of an immoral versus amoral act. The asymmetry in attributions of intentionality was observed at all but the most extreme level of causal deviance, and, as we hypothesized, was mediated by attributions of blame/credit and judgments of action performance. These findings are discussed as they support a multiple-concepts interpretation of the asymmetry, wherein blame renders a naïve concept of intentional action (the outcome matches the intention) more salient than a composite concept (the outcome matches the intention and was brought about by planned means), and in terms of their implications for cross-cultural research on judgments of agency.

Upsampling to 400-ms Resolution for Assessing Effective Connectivity in Functional Magnetic Resonance Imaging Data with Granger Causality

PubMed Central

Kerr, Deborah L.; Nitschke, Jack B.

2013-01-01

Abstract Granger causality analysis of functional magnetic resonance imaging (fMRI) blood-oxygen-level-dependent signal data allows one to infer the direction and magnitude of influence that brain regions exert on one another. We employed a method for upsampling the time resolution of fMRI data that does not require additional interpolation beyond the interpolation that is regularly used for slice-timing correction. The mathematics for this new method are provided, and simulations demonstrate its viability. Using fMRI, 17 snake phobics and 19 healthy controls viewed snake, disgust, and neutral fish video clips preceded by anticipatory cues. Multivariate Granger causality models at the native 2-sec resolution and at the upsampled 400-ms resolution assessed directional associations of fMRI data among 13 anatomical regions of interest identified in prior research on anxiety and emotion. Superior sensitivity was observed for the 400-ms model, both for connectivity within each group and for group differences in connectivity. Context-dependent analyses for the 400-ms multivariate Granger causality model revealed the specific trial types showing group differences in connectivity. This is the first demonstration of effective connectivity of fMRI data using a method for achieving 400-ms resolution without sacrificing accuracy available at 2-sec resolution. PMID:23134194

Safety reports on the off-label use of baclofen for alcohol-dependence: recommendations to improve causality assessment.

PubMed

Rolland, Benjamin; Auffret, Marine; Franchitto, Nicolas

2016-06-01

The off-label use of high-dose baclofen (HDB) for alcohol-dependence has recently spread. However, HDB has been associated with numerous reports of adverse events (AEs). Pharmacovigilance reporting is supposed to differentiate AEs from adverse drug reactions (ADRs), for which the causality of the drug is determined using validated methods. Since 2010, we found 20 publications on baclofen-related AEs in alcohol dependence, in Medline-referenced journals or national pharmacovigilance reports. We focused on whether these reports used causality algorithms, and provided essential elements for determining baclofen causality and excluding the involvement of alcohol and other psychoactive substances or psychotropic drugs. In half of the cases, no causality algorithm was used. Detailed information on baclofen dosing was found in 17 out of 20 (85%) articles, whereas alcohol doses were given only in 10 (50%) publications. Other psychoactive substances and psychotropic drugs were broached in 14 (70%) publications. future publications reporting suspected HDB-induced ADRs should use validated causality algorithms and provide sufficient amount of contextual information for excluding other potential causes. For HDB, the psychiatric history, and the longitudinal description of alcohol consumptions and associated doses of psychoactive substances or psychotropic medications should be detailed for every reported case.

Causal attributions in Brazilian children's reasoning about health and illness.

PubMed

Boruchovitch, E; Mednick, B R

2000-10-01

At a time when a great number of diseases can be prevented by changing one's habits and life style, investigations have focused on understanding what adults and children believe to be desirable health practices and uncovering the factors associated with successful adherence to such practices. For these, causal attributions for health and illness were investigated among 96 Brazilian elementary school students. Ninety six subjects, aged 6 to 14, were interviewed individually and their causal attributions were assessed through 14 true-false items (e.g. people stay well [healthy] because they are lucky). The relationship between the children's causal attributions and demographic characteristics were also examined. Overall, the results were consistent with previous researches. "Taking care of oneself" was considered the most important cause of good health. "Viruses and germs" and "lack of self-care" were the most selected causes of illness. Analyses revealed significant relationship between subjects' causal attribution and their age, school grade level, socioeconomic status and gender. The study findings suggest that there may be more cross-cultural similarities than differences in children's causal attributions for health and illness. Finding ways to help individuals engage in appropriate preventive-maintenance health practices without developing an exaggerated notion that the individuals can control their own health and illness is a challenge which remains to be addressed by further research.

Subfertility factors rather than assisted conception factors affect cognitive and behavioural development of 4-year-old singletons.

PubMed

Schendelaar, Pamela; La Bastide-Van Gemert, Sacha; Heineman, Maas Jan; Middelburg, Karin J; Seggers, Jorien; Van den Heuvel, Edwin R; Hadders-Algra, Mijna

2016-12-01

Research on cognitive and behavioural development of children born after assisted conception is inconsistent. This prospective study aimed to explore underlying causal relationships between ovarian stimulation, in-vitro procedures, subfertility components and child cognition and behaviour. Participants were singletons born to subfertile couples after ovarian stimulation IVF (n = 63), modified natural cycle IVF (n = 53), natural conception (n = 79) and singletons born to fertile couples (reference group) (n = 98). At 4 years, cognition (Kaufmann-ABC-II; total IQ) and behaviour (Child Behavior Checklist; total problem T-score) were assessed. Causal inference search algorithms and structural equation modelling was applied to unravel causal mechanisms. Most children had typical cognitive and behavioural scores. No underlying causal effect was found between ovarian stimulation and the in-vitro procedure and outcome. Direct negative causal effects were found between severity of subfertility (time to pregnancy) and cognition and presence of subfertility and behaviour. Maternal age and maternal education acted as confounders. The study concludes that no causal effects were found between ovarian stimulation or in-vitro procedures and cognition and behaviour in childrenaged 4 years born to subfertile couples. Subfertility, especially severe subfertility, however, was associated with worse cognition and behaviour. Copyright © 2016 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

A review and assessment of drug-induced parotitis.

PubMed

Brooks, Krista G; Thompson, Dennis F

2012-12-01

To review the current literature on drug-induced parotitis. Literature was accessed through MEDLINE/PubMed (1980-May 2012), using the search terms sialadenitis/chemically induced and parotitis/chemically induced. EMBASE (1980-May 2012) was searched using the terms parotitis/diagnosis, sialadenitis/side effect, and parotitis/side effect. International Pharmaceutical Abstracts (1970-May 2012) was searched using the search terms parotitis and sialadenitis. All searches were limited to articles on humans written in English. Inclusion criteria were published letters, case reports, reviews, and clinical trials involving drugs that may be associated with parotitis. Articles pertaining to parotitis induced by iodine-containing drugs were excluded. References of all relevant articles were reviewed for additional citations. Review articles, clinical trials, background data, and case reports of drug-induced parotitis were collected and case reports were assessed for causality. Parotitis is an uncommon adverse effect; however, signs and symptoms of parotitis have been noted in case reports as an adverse drug reaction related to various medications. Assessing causality of an adverse drug reaction such as parotitis is challenging. To help determine the probability of causality for these events, algorithms such as the Naranjo probability scale have been developed. Eighty-four case reports of drug-induced parotitis from 40 different drugs were reviewed using a modified Naranjo probability scale that included criteria specific for parotitis. Medications that met the criteria for establishing causality included l-asparaginase with 7 case reports, clozapine with 13 case reports, and phenylbutazone with 13 case reports. Drug-induced parotitis is a rare adverse drug reaction. Based on the quantitative and qualitative evidence collected from the case reports, medications that are associated with drug-induced parotitis include l-asparaginase, clozapine, and phenylbutazone. Many other drugs have been implicated in the development of parotitis; however, the evidence supporting this association is insufficient to determine causality at this time.

Is there a causal link between knee loading and knee osteoarthritis progression? A systematic review and meta-analysis of cohort studies and randomised trials

PubMed Central

Henriksen, Marius; Creaby, Mark W; Lund, Hans; Juhl, Carsten; Christensen, Robin

2014-01-01

Objective We performed a systematic review, meta-analysis and assessed the evidence supporting a causal link between knee joint loading during walking and structural knee osteoarthritis (OA) progression. Design Systematic review, meta-analysis and application of Bradford Hill's considerations on causation. Data sources We searched MEDLINE, Scopus, AMED, CINAHL and SportsDiscus for prospective cohort studies and randomised controlled trials (RCTs) from 1950 through October 2013. Study eligibility criteria We selected cohort studies and RCTs in which estimates of knee joint loading during walking were used to predict structural knee OA progression assessed by X-ray or MRI. Data analyses Meta-analysis was performed to estimate the combined OR for structural disease progression with higher baseline loading. The likelihood of a causal link between knee joint loading and OA progression was assessed from cohort studies using the Bradford Hill guidelines to derive a 0–4 causation score based on four criteria and examined for confirmation in RCTs. Results Of the 1078 potentially eligible articles, 5 prospective cohort studies were included. The studies included a total of 452 patients relating joint loading to disease progression over 12–72 months. There were very serious limitations associated with the methodological quality of the included studies. The combined OR for disease progression was 1.90 (95% CI 0.85 to 4.25; I2=77%) for each one-unit increment in baseline knee loading. The combined causation score was 0, indicating no causal association between knee loading and knee OA progression. No RCTs were found to confirm or refute the findings from the cohort studies. Conclusions There is very limited and low-quality evidence to support for a causal link between knee joint loading during walking and structural progression of knee OA. Trial registration number CRD42012003253 PMID:25031196

Is there a causal link between knee loading and knee osteoarthritis progression? A systematic review and meta-analysis of cohort studies and randomised trials.

PubMed

Henriksen, Marius; Creaby, Mark W; Lund, Hans; Juhl, Carsten; Christensen, Robin

2014-07-15

We performed a systematic review, meta-analysis and assessed the evidence supporting a causal link between knee joint loading during walking and structural knee osteoarthritis (OA) progression. Systematic review, meta-analysis and application of Bradford Hill's considerations on causation. We searched MEDLINE, Scopus, AMED, CINAHL and SportsDiscus for prospective cohort studies and randomised controlled trials (RCTs) from 1950 through October 2013. We selected cohort studies and RCTs in which estimates of knee joint loading during walking were used to predict structural knee OA progression assessed by X-ray or MRI. Meta-analysis was performed to estimate the combined OR for structural disease progression with higher baseline loading. The likelihood of a causal link between knee joint loading and OA progression was assessed from cohort studies using the Bradford Hill guidelines to derive a 0-4 causation score based on four criteria and examined for confirmation in RCTs. Of the 1078 potentially eligible articles, 5 prospective cohort studies were included. The studies included a total of 452 patients relating joint loading to disease progression over 12-72 months. There were very serious limitations associated with the methodological quality of the included studies. The combined OR for disease progression was 1.90 (95% CI 0.85 to 4.25; I(2)=77%) for each one-unit increment in baseline knee loading. The combined causation score was 0, indicating no causal association between knee loading and knee OA progression. No RCTs were found to confirm or refute the findings from the cohort studies. There is very limited and low-quality evidence to support for a causal link between knee joint loading during walking and structural progression of knee OA. CRD42012003253. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Does Sufficient Evidence Exist to Support a Causal Association between Vitamin D Status and Cardiovascular Disease Risk? An Assessment Using Hill’s Criteria for Causality

PubMed Central

Weyland, Patricia G.; Grant, William B.; Howie-Esquivel, Jill

2014-01-01

Serum 25-hydroxyvitamin D (25(OH)D) levels have been found to be inversely associated with both prevalent and incident cardiovascular disease (CVD) risk factors; dyslipidemia, hypertension and diabetes mellitus. This review looks for evidence of a causal association between low 25(OH)D levels and increased CVD risk. We evaluated journal articles in light of Hill’s criteria for causality in a biological system. The results of our assessment are as follows. Strength of association: many randomized controlled trials (RCTs), prospective and cross-sectional studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Consistency of observed association: most studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors in various populations, locations and circumstances. Temporality of association: many RCTs and prospective studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Biological gradient (dose-response curve): most studies assessing 25(OH)D levels and CVD risk found an inverse association exhibiting a linear biological gradient. Plausibility of biology: several plausible cellular-level causative mechanisms and biological pathways may lead from a low 25(OH)D level to increased risk for CVD with mediators, such as dyslipidemia, hypertension and diabetes mellitus. Experimental evidence: some well-designed RCTs found increased CVD risk factors with decreasing 25(OH)D levels. Analogy: the association between serum 25(OH)D levels and CVD risk is analogous to that between 25(OH)D levels and the risk of overall cancer, periodontal disease, multiple sclerosis and breast cancer. Conclusion: all relevant Hill criteria for a causal association in a biological system are satisfied to indicate a low 25(OH)D level as a CVD risk factor. PMID:25184368

Assessing Learned Helplessness in Poor Readers.

ERIC Educational Resources Information Center

Winograd, Peter; Niquette, Garland

1988-01-01

Feelings of helplessness can impact on learning to read. This research review illustrates problems in assessing learned helplessness, including instrumentation inadequacies, lack of comprehensive causal schemes, context specificity, etc. Observations of and discussions with the child are recommended in the assessment process. Guidelines for…

Principal Stratification — Uses and Limitations

PubMed Central

VanderWeele, Tyler J

2011-01-01

Pearl (2011) asked for the causal inference community to clarify the role of the principal stratification framework in the analysis of causal effects. Here, I argue that the notion of principal stratification has shed light on problems of non-compliance, censoring-by-death, and the analysis of post-infection outcomes; that it may be of use in considering problems of surrogacy but further development is needed; that it is of some use in assessing “direct effects”; but that it is not the appropriate tool for assessing “mediation.” There is nothing within the principal stratification framework that corresponds to a measure of an “indirect” or “mediated” effect. PMID:21841939

Private schooling and admission to medicine: a case study using matched samples and causal mediation analysis.

PubMed

Houston, Muir; Osborne, Michael; Rimmer, Russell

2015-08-20

Are applicants from private schools advantaged in gaining entry to degrees in medicine? This is of international significance and there is continuing research in a range of nations including the USA, the UK, other English-speaking nations and EU countries. Our purpose is to seek causal explanations using a quantitative approach. We took as a case study admission to medicine in the UK and drew samples of those who attended private schools and those who did not, with sample members matched on background characteristics. Unlike other studies in the area, causal mediation analysis was applied to resolve private-school influence into direct and indirect effects. In so doing, we sought a benchmark, using data for 2004, against which the effectiveness of policies adopted over the past decade can be assessed. Private schooling improved admission likelihood. This did not occur indirectly via the effect of school type on academic performance; but arose directly from attending private schools. A sensitivity analysis suggests this finding is unlikely to be eliminated by the influence of an unobserved variable. Academic excellence is not a certain pathway into medicine at university; yet applying with good grades after attending private school is more certain. The results of our paper differ from those in an earlier observational study and find support in a later study. Consideration of sources of difference from the earlier observational study suggest the causal approach offers substantial benefits and the consequences in the causal study for gender, ethnicity, socio-economic classification and region of residence provide a benchmark for assessing policy in future research.

The serum uric acid concentration is not causally linked to diabetic nephropathy in type 1 diabetes.

PubMed

Ahola, Aila J; Sandholm, Niina; Forsblom, Carol; Harjutsalo, Valma; Dahlström, Emma; Groop, Per-Henrik

2017-05-01

Previous studies have shown a relationship between uric acid concentration and progression of renal disease. Here we studied causality between the serum uric acid concentration and progression of diabetic nephropathy in 3895 individuals with type 1 diabetes in the FinnDiane Study. The renal status was assessed with the urinary albumin excretion rate and estimated glomerular filtration rate (eGFR) at baseline and at the end of the follow-up. Based on previous genomewide association studies on serum uric acid concentration, 23 single nucleotide polymorphisms (SNPs) with good imputation quality were selected for the SNP score. This score was used to assess the causality between serum uric acid and renal complications using a Mendelian randomization approach. At baseline, the serum uric acid concentration was higher with worsening renal status. In multivariable Cox regression analyses, baseline serum uric acid concentration was not independently associated with progression of diabetic nephropathy over a mean follow-up of 7 years. However, over the same period, baseline serum uric acid was independently associated with the decline in eGFR. In the cross-sectional logistic regression analyses, the SNP score was associated with the serum uric acid concentration. Nevertheless, the Mendelian randomization showed no causality between uric acid and diabetic nephropathy, eGFR categories, or eGFR as a continuous variable. Thus, our results suggest that the serum uric acid concentration is not causally related to diabetic nephropathy but is a downstream marker of kidney damage. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Using causal maps to support ex-post assessment of social impacts of dams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aledo, Antonio, E-mail: Antonio.Aledo@ua.es; García-Andreu, Hugo, E-mail: Hugo.Andreu@ua.es; Pinese, José, E-mail: pinese@uel.br

- Highlights: • We defend the usefulness of causal maps (CM) for ex-post impact assessment of dams. • Political decisions are presented as unavoidable technical measures. • CM enable the identification of multiple causes involved in the dam impacts. • An alternative management of the dams is shown from the precise tracking of the causes. • Participatory CM better the quality of information and the governance of the research. This paper presents the results of an ex-post assessment of two important dams in Brazil. The study follows the principles of Social Impact Management, which offer a suitable framework for analyzingmore » the complex social transformations triggered by hydroelectric dams. In the implementation of this approach, participative causal maps were used to identify the ex-post social impacts of the Porto Primavera and Rosana dams on the community of Porto Rico, located along the High Paraná River. We found that in the operation of dams there are intermediate causes of a political nature, stemming from decisions based on values and interests not determined by neutral, exclusively technical reasons; and this insight opens up an area of action for managing the negative impacts of dams.« less

Knowledge Representation Standards and Interchange Formats for Causal Graphs

NASA Technical Reports Server (NTRS)

Throop, David R.; Malin, Jane T.; Fleming, Land

2005-01-01

In many domains, automated reasoning tools must represent graphs of causally linked events. These include fault-tree analysis, probabilistic risk assessment (PRA), planning, procedures, medical reasoning about disease progression, and functional architectures. Each of these fields has its own requirements for the representation of causation, events, actors and conditions. The representations include ontologies of function and cause, data dictionaries for causal dependency, failure and hazard, and interchange formats between some existing tools. In none of the domains has a generally accepted interchange format emerged. The paper makes progress towards interoperability across the wide range of causal analysis methodologies. We survey existing practice and emerging interchange formats in each of these fields. Setting forth a set of terms and concepts that are broadly shared across the domains, we examine the several ways in which current practice represents them. Some phenomena are difficult to represent or to analyze in several domains. These include mode transitions, reachability analysis, positive and negative feedback loops, conditions correlated but not causally linked and bimodal probability distributions. We work through examples and contrast the differing methods for addressing them. We detail recent work in knowledge interchange formats for causal trees in aerospace analysis applications in early design, safety and reliability. Several examples are discussed, with a particular focus on reachability analysis and mode transitions. We generalize the aerospace analysis work across the several other domains. We also recommend features and capabilities for the next generation of causal knowledge representation standards.

Reliability of Causality Assessment for Drug, Herbal and Dietary Supplement Hepatoxicity in the Drug-Induced Liver Injury Network (DILIN)

PubMed Central

Hayashi, Paul H.; Barnhart, Huiman X.; Fontana, Robert J.; Chalasani, Naga; Davern, Timothy J.; Talwalkar, Jayant A.; Reddy, K. Rajender; Stolz, Andrew A.; Hoofnagle, Jay H.; Rockey, Don C.

2014-01-01

Background Due to the lack of objective tests to diagnose drug induced liver injury (DILI), causality assessment is a matter of debate. Expert opinion is often used in research and industry but its test-retest reliability is unknown. Aims To determine the test-retest reliability of the expert opinion process used by the Drug-Induced Liver Injury Network (DILIN) Methods Three DILIN hepatologists adjudicate suspected hepatotoxicity cases to 1 of 5 categories representing levels of likelihood of DILI. Adjudication is based on retrospective assessment of gathered case data that includes prospective follow-up information. One hundred randomly selected DILIN cases were re-assessed using the same processes for initial assessment but by 3 different reviewers in 92% of cases. Results The median time between assessments was 938 days (range: 140–2352). Thirty-one cases involved >1 agent. Weighted kappa statistics for overall case and individual agent category agreement were 0.60 (95% CI: 0.50–0.71) and 0.60 (0.52–0.68), respectively. Overall case adjudications were within one category of each other 93% of the time, while 5% differed by 2 categories and 2% differed by 3 categories. Fourteen-percent crossed the 50% threshold of likelihood due to competing diagnoses or atypical timing between drug exposure and injury. Conclusions The DILIN expert opinion causality assessment method has moderate inter-observer reliability but very good agreement within 1 category. A small but important proportion of cases could not be reliably diagnosed as ≥ 50% likely to be DILI. PMID:24661785

Spatiotemporal causal modeling for the management of Dengue Fever

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Huang, Tailin; Lee, Chieh-Han

2015-04-01

Increasing climatic extremes have caused growing concerns about the health effects and disease outbreaks. The association between climate variation and the occurrence of epidemic diseases play an important role on a country's public health systems. Part of the impacts are direct casualties associated with the increasing frequency and intensity of typhoons, the proliferation of disease vectors and the short-term increase of clinic visits on gastro-intestinal discomforts, diarrhea, dermatosis, or psychological trauma. Other impacts come indirectly from the influence of disasters on the ecological and socio-economic systems, including the changes of air/water quality, living environment and employment condition. Previous risk assessment studies on dengue fever focus mostly on climatic and non-climatic factors and their association with vectors' reproducing pattern. The public-health implication may appear simple. Considering the seasonal changes and regional differences, however, the causality of the impacts is full of uncertainties. Without further investigation, the underlying dengue fever risk dynamics may not be assessed accurately. The objective of this study is to develop an epistemic framework for assessing dynamic dengue fever risk across space and time. The proposed framework integrates cross-departmental data, including public-health databases, precipitation data over time and various socio-economic data. We explore public-health issues induced by typhoon through literature review and spatiotemporal analytic techniques on public health databases. From those data, we identify relevant variables and possible causal relationships, and their spatiotemporal patterns derived from our proposed spatiotemporal techniques. Eventually, we create a spatiotemporal causal network and a framework for modeling dynamic dengue fever risk.

Functional neural circuits that underlie developmental stuttering

PubMed Central

Zhao, Guihu; Huo, Yuankai; Herder, Carl L.; Sikora, Chamonix O.; Peterson, Bradley S.

2017-01-01

The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS) and typically developing (TD) fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-state functional magnetic resonance imaging data in 44 PWS and 50 TD controls. We then used Independent Component Analysis (ICA) together with Hierarchical Partner Matching (HPM) to identify networks of robust, functionally connected brain regions that were highly reproducible across participants, and we assessed whether connectivity differed significantly across diagnostic groups. We then used Granger Causality (GC) to study the causal interactions (effective connectivity) between the regions that ICA and HPM identified. Finally, we used a kernel support vector machine to assess how well these measures of functional connectivity and granger causality discriminate PWS from TD controls. Functional connectivity was stronger in PWS compared with TD controls in the supplementary motor area (SMA) and primary motor cortices, but weaker in inferior frontal cortex (IFG, Broca’s area), caudate, putamen, and thalamus. Additionally, causal influences were significantly weaker in PWS from the IFG to SMA, and from the basal ganglia to IFG through the thalamus, compared to TD controls. ICA and GC indices together yielded an accuracy of 92.7% in classifying PWS from TD controls. Our findings suggest the presence of dysfunctional circuits that support speech planning and timing cues for the initiation and execution of motor sequences in PWS. Our high accuracy of classification further suggests that these aberrant brain features may serve as robust biomarkers for PWS. PMID:28759567

Functional neural circuits that underlie developmental stuttering.

PubMed

Qiao, Jianping; Wang, Zhishun; Zhao, Guihu; Huo, Yuankai; Herder, Carl L; Sikora, Chamonix O; Peterson, Bradley S

2017-01-01

The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS) and typically developing (TD) fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-state functional magnetic resonance imaging data in 44 PWS and 50 TD controls. We then used Independent Component Analysis (ICA) together with Hierarchical Partner Matching (HPM) to identify networks of robust, functionally connected brain regions that were highly reproducible across participants, and we assessed whether connectivity differed significantly across diagnostic groups. We then used Granger Causality (GC) to study the causal interactions (effective connectivity) between the regions that ICA and HPM identified. Finally, we used a kernel support vector machine to assess how well these measures of functional connectivity and granger causality discriminate PWS from TD controls. Functional connectivity was stronger in PWS compared with TD controls in the supplementary motor area (SMA) and primary motor cortices, but weaker in inferior frontal cortex (IFG, Broca's area), caudate, putamen, and thalamus. Additionally, causal influences were significantly weaker in PWS from the IFG to SMA, and from the basal ganglia to IFG through the thalamus, compared to TD controls. ICA and GC indices together yielded an accuracy of 92.7% in classifying PWS from TD controls. Our findings suggest the presence of dysfunctional circuits that support speech planning and timing cues for the initiation and execution of motor sequences in PWS. Our high accuracy of classification further suggests that these aberrant brain features may serve as robust biomarkers for PWS.

Thinking or feeling? An exploratory study of maternal scaffolding, child mental state talk, and emotion understanding in language-impaired and typically developing school-aged children.

PubMed

Yuill, Nicola; Little, Sarah

2018-06-01

Mother-child mental state talk (MST) supports children's developing social-emotional understanding. In typically developing (TD) children, family conversations about emotion, cognition, and causes have been linked to children's emotion understanding. Specific language impairment (SLI) may compromise developing emotion understanding and adjustment. We investigated emotion understanding in children with SLI and TD, in relation to mother-child conversation. Specifically, is cognitive, emotion, or causal MST more important for child emotion understanding and how might maternal scaffolding support this? Nine 5- to 9-year-old children with SLI and nine age-matched typically developing (TD) children, and their mothers. We assessed children's language, emotion understanding and reported behavioural adjustment. Mother-child conversations were coded for MST, including emotion, cognition, and causal talk, and for scaffolding of causal talk. Children with SLI scored lower than TD children on emotion understanding and adjustment. Mothers in each group provided similar amounts of cognitive, emotion, and causal talk, but SLI children used proportionally less cognitive and causal talk than TD children did, and more such child talk predicted better child emotion understanding. Child emotion talk did not differ between groups and did not predict emotion understanding. Both groups participated in maternal-scaffolded causal talk, but causal talk about emotion was more frequent in TD children, and such talk predicted higher emotion understanding. Cognitive and causal language scaffolded by mothers provides tools for articulating increasingly complex ideas about emotion, predicting children's emotion understanding. Our study provides a robust method for studying scaffolding processes for understanding causes of emotion. © 2017 The British Psychological Society.

Frequency distribution of causal connectivity in rat sensorimotor network: resting-state fMRI analyses.

PubMed

Shim, Woo H; Baek, Kwangyeol; Kim, Jeong Kon; Chae, Yongwook; Suh, Ji-Yeon; Rosen, Bruce R; Jeong, Jaeseung; Kim, Young R

2013-01-01

Resting-state functional MRI (fMRI) has emerged as an important method for assessing neural networks, enabling extensive connectivity analyses between multiple brain regions. Among the analysis techniques proposed, partial directed coherence (PDC) provides a promising tool to unveil causal connectivity networks in the frequency domain. Using the MRI time series obtained from the rat sensorimotor system, we applied PDC analysis to determine the frequency-dependent causality networks. In particular, we compared in vivo and postmortem conditions to establish the statistical significance of directional PDC values. Our results demonstrate that two distinctive frequency populations drive the causality networks in rat; significant, high-frequency causal connections clustered in the range of 0.2-0.4 Hz, and the frequently documented low-frequency connections <0.15 Hz. Frequency-dependence and directionality of the causal connection are characteristic between sensorimotor regions, implying the functional role of frequency bands to transport specific resting-state signals. In particular, whereas both intra- and interhemispheric causal connections between heterologous sensorimotor regions are robust over all frequency levels, the bilaterally homologous regions are interhemispherically linked mostly via low-frequency components. We also discovered a significant, frequency-independent, unidirectional connection from motor cortex to thalamus, indicating dominant cortical inputs to the thalamus in the absence of external stimuli. Additionally, to address factors underlying the measurement error, we performed signal simulations and revealed that the interactive MRI system noise alone is a likely source of the inaccurate PDC values. This work demonstrates technical basis for the PDC analysis of resting-state fMRI time series and the presence of frequency-dependent causality networks in the sensorimotor system.

Causal attributions in parents of babies with a cleft lip and/or palate and their association with psychological well-being.

PubMed

Nelson, Jonathan; O'Leary, Catherine; Weinman, John

2009-07-01

This study aimed to assess causal attributions of parents of babies with a cleft lip and/or palate. Evidence from causal attribution theory and attribution studies in other medical conditions led to the hypothesis that parents who make internal attributions (self-blame) will have poorer psychological well-being. A cross-sectional survey. Postal questionnaires were sent to parents of children under the care of the South Thames Cleft Service at Guy's Hospital. PARTICIPANTS were recruited if they had a baby between 12 and 24 months old with a cleft lip and/or palate. Of 204 parents, 42 responded. A semistructured questionnaire about causal beliefs was completed alongside validated questionnaires measuring anxiety, depression (Hospital Anxiety and Depression Scale), and perceived stress (Perceived Stress Scale). Causal attributions were grouped according to type (environmental, chance, self-blame, and no belief) and loci (external or internal). The most common attribution made was to external factors (54.4%), followed by no causal attribution (38.1%). Parents making an internal (self-blaming) attribution (16.7%) had significantly (p < .05) higher scores on the Hospital Anxiety and Depression Scale anxiety measure (r = .32) and Perceived Stress Scale (r = .33), but not on the Hospital Anxiety and Depression Scale depression measure (p = .283). The high number of parents making an external attribution can be explained by causal attribution theory. However, the percentage of parents making no causal attribution was higher than seen in previous research. Surprisingly, no parents blamed others. The main hypothesis was tentatively accepted because there were significantly higher anxiety and stress scores in parents who self-blamed; although, depression scores were not significantly higher.

Income and obesity: what is the direction of the relationship? A systematic review and meta-analysis

PubMed Central

Kim, Tae Jun; von dem Knesebeck, Olaf

2018-01-01

Objective It was repeatedly shown that lower income is associated with higher risks for subsequent obesity. However, the perspective of a potential reverse causality is often neglected, in which obesity is considered a cause for lower income, when obese people drift into lower-income jobs due to labour–market discrimination and public stigmatisation. This review was performed to explore the direction of the relation between income and obesity by specifically assessing the importance of social causation and reverse causality. Design Systematic review and meta-analysis. Methods A systematic literature search was conducted in January 2017. The databases Medline, PsycINFO, Sociological Abstracts, International Bibliography of Social Sciences and Sociological Index were screened to identify prospective cohort studies with quantitative data on the relation between income and obesity. Meta-analytic methods were applied using random-effect models, and the quality of studies assessed with the Newcastle-Ottawa Scale. Results In total, 21 studies were eligible for meta-analysis. All included studies originated from either the USA (n=16), the UK (n=3) or Canada (n=2). From these, 14 studies on causation and 7 studies on reverse causality were found. Meta-analyses revealed that lower income is associated with subsequent obesity (OR 1.27, 95% CI 1.10 to 1.47; risk ratio 1.52, 95% CI 1.08 to 2.13), though the statistical significance vanished once adjusted for publication bias. Studies on reverse causality indicated a more consistent relation between obesity and subsequent income, even after taking publication bias into account (standardised mean difference −0.15, 95% CI −0.30 to 0.01). Sensitivity analyses implied that the association is influenced by obesity measurement, gender, length of observation and study quality. Conclusions Findings suggest that there is more consistent evidence for reverse causality. Therefore, there is a need to examine reverse causality processes in more detail to understand the relation between income and obesity. PROSPERO registration number 42016041296. PMID:29306894

Training Basic Visual Attention Leads to Changes in Responsiveness to Social-Communicative Cues in 9-Month-Olds.

PubMed

Forssman, Linda; Wass, Sam V

2018-05-01

This study investigated transfer effects of gaze-interactive attention training to more complex social and cognitive skills in infancy. Seventy 9-month-olds were assigned to a training group (n = 35) or an active control group (n = 35). Before, after, and at 6-week follow-up both groups completed an assessment battery assessing transfer to nontrained aspects of attention control, including table top tasks assessing social attention in seminaturalistic contexts. Transfer effects were found on nontrained screen-based tasks but importantly also on a structured observation task assessing the infants' likelihood to respond to an adult's social-communication cues. The results causally link basic attention skills and more complex social-communicative skills and provide a principle for studying causal mechanisms of early development. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Detecting causal drivers and empirical prediction of the Indian Summer Monsoon

NASA Astrophysics Data System (ADS)

Di Capua, G.; Vellore, R.; Raghavan, K.; Coumou, D.

2017-12-01

The Indian summer monsoon (ISM) is crucial for the economy, society and natural ecosystems on the Indian peninsula. Predict the total seasonal rainfall at several months lead time would help to plan effective water management strategies, improve flood or drought protection programs and prevent humanitarian crisis. However, the complexity and strong internal variability of the ISM circulation system make skillful seasonal forecasting challenging. Moreover, to adequately identify the low-frequency, and far-away processes which influence ISM behavior novel tools are needed. We applied a Response-Guided Causal Precursor Detection (RGCPD) scheme, which is a novel empirical prediction method which unites a response-guided community detection scheme with a causal discovery algorithm (CEN). These tool allow us to assess causal pathways between different components of the ISM circulation system and with far-away regions in the tropics, mid-latitudes or Arctic. The scheme has successfully been used to identify causal precursors of the Stratospheric polar vortex enabling skillful predictions at (sub) seasonal timescales (Kretschmer et al. 2016, J.Clim., Kretschmer et al. 2017, GRL). We analyze observed ISM monthly rainfall over the monsoon trough region. Applying causal discovery techniques, we identify several causal precursor communities in the fields of 2m-temperature, sea level pressure and snow depth over Eurasia. Specifically, our results suggest that surface temperature conditions in both tropical and Arctic regions contribute to ISM variability. A linear regression prediction model based on the identified set of communities has good hindcasting skills with 4-5 months lead times. Further we separate El Nino, La Nina and ENSO-neutral years from each other and find that the causal precursors are different dependent on ENSO state. The ENSO-state dependent causal precursors give even higher skill, especially for La Nina years when the ISM is relatively strong. These findings are promising results that might ultimately contribute to both improved understanding of the ISM circulation system and help improving seasonal ISM forecasts.

Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

PubMed

Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S

2014-11-01

COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Detecting switching and intermittent causalities in time series

NASA Astrophysics Data System (ADS)

Zanin, Massimiliano; Papo, David

2017-04-01

During the last decade, complex network representations have emerged as a powerful instrument for describing the cross-talk between different brain regions both at rest and as subjects are carrying out cognitive tasks, in healthy brains and neurological pathologies. The transient nature of such cross-talk has nevertheless by and large been neglected, mainly due to the inherent limitations of some metrics, e.g., causality ones, which require a long time series in order to yield statistically significant results. Here, we present a methodology to account for intermittent causal coupling in neural activity, based on the identification of non-overlapping windows within the original time series in which the causality is strongest. The result is a less coarse-grained assessment of the time-varying properties of brain interactions, which can be used to create a high temporal resolution time-varying network. We apply the proposed methodology to the analysis of the brain activity of control subjects and alcoholic patients performing an image recognition task. Our results show that short-lived, intermittent, local-scale causality is better at discriminating both groups than global network metrics. These results highlight the importance of the transient nature of brain activity, at least under some pathological conditions.

Causal analysis of self-sustaining processes in the logarithmic layer of wall-bounded turbulence

NASA Astrophysics Data System (ADS)

Bae, H. J.; Encinar, M. P.; Lozano-Durán, A.

2018-04-01

Despite the large amount of information provided by direct numerical simulations of turbulent flows, their underlying dynamics remain elusive even in the most simple and canonical configurations. Most common approaches to investigate the turbulence phenomena do not provide a clear causal inference between events, which is essential to determine the dynamics of self-sustaining processes. In the present work, we examine the causal interactions between streaks, rolls and mean shear in the logarithmic layer of a minimal turbulent channel flow. Causality between structures is assessed in a non-intrusive manner by transfer entropy, i.e., how much the uncertainty of one structure is reduced by knowing the past states of the others. We choose to represent streaks by the first Fourier modes of the streamwise velocity, while rolls are defined by the wall-normal and spanwise velocity modes. The results show that the process is mainly unidirectional rather than cyclic, and that the log-layer motions are sustained by extracting energy from the mean shear which controls the dynamics and time-scales. The well-known lift-up effect is also identified, but shown to be of secondary importance in the causal network between shear, streaks and rolls.

Causal inference and longitudinal data: a case study of religion and mental health.

PubMed

VanderWeele, Tyler J; Jackson, John W; Li, Shanshan

2016-11-01

We provide an introduction to causal inference with longitudinal data and discuss the complexities of analysis and interpretation when exposures can vary over time. We consider what types of causal questions can be addressed with the standard regression-based analyses and what types of covariate control and control for the prior values of outcome and exposure must be made to reason about causal effects. We also consider newer classes of causal models, including marginal structural models, that can assess questions of the joint effects of time-varying exposures and can take into account feedback between the exposure and outcome over time. Such feedback renders cross-sectional data ineffective for drawing inferences about causation. The challenges are illustrated by analyses concerning potential effects of religious service attendance on depression, in which there may in fact be effects in both directions with service attendance preventing the subsequent depression, but depression itself leading to lower levels of the subsequent religious service attendance. Longitudinal designs, with careful control for prior exposures, outcomes, and confounders, and suitable methodology, will strengthen research on mental health, religion and health, and in the biomedical and social sciences generally.

Causal analysis of self-sustaining processes in the log-layer of wall-bounded turbulence

NASA Astrophysics Data System (ADS)

Lozano-Duran, Adrian; Bae, Hyunji Jane

2017-11-01

Despite the large amount of information provided by direct numerical simulations of turbulent flows, the underlying dynamics remain elusive even in the most simple and canonical configurations. Most standard methods used to investigate turbulence do not provide a clear causal inference between events, which is necessary to determine this dynamics, particularly in self-sustaning processes. In the present work, we examine the causal interactions between streaks and rolls in the logarithmic layer of minimal turbulent channel flow. Causality between structures is assessed in a non-intrusive manner by transfer entropy, i.e., how much the uncertainty of one structure is reduced by knowing the past states of the others. Streaks are represented by the first Fourier modes of the streamwise velocity, while rolls are defined by the wall-normal and spanwise velocities. The results show that the process is mainly unidirectional rather than cyclic, and that the log-layer motions are sustained by extracting energy from the mean shear, which controls the dynamics and time-scales. The well-known lift-up effect is shown to be not a key ingredient in the causal network between shear, streaks and rolls. Funded by ERC Coturb Madrid Summer Program.

Identification and Sensitivity Analysis for Average Causal Mediation Effects with Time-Varying Treatments and Mediators: Investigating the Underlying Mechanisms of Kindergarten Retention Policy.

PubMed

Park, Soojin; Steiner, Peter M; Kaplan, David

2018-06-01

Considering that causal mechanisms unfold over time, it is important to investigate the mechanisms over time, taking into account the time-varying features of treatments and mediators. However, identification of the average causal mediation effect in the presence of time-varying treatments and mediators is often complicated by time-varying confounding. This article aims to provide a novel approach to uncovering causal mechanisms in time-varying treatments and mediators in the presence of time-varying confounding. We provide different strategies for identification and sensitivity analysis under homogeneous and heterogeneous effects. Homogeneous effects are those in which each individual experiences the same effect, and heterogeneous effects are those in which the effects vary over individuals. Most importantly, we provide an alternative definition of average causal mediation effects that evaluates a partial mediation effect; the effect that is mediated by paths other than through an intermediate confounding variable. We argue that this alternative definition allows us to better assess at least a part of the mediated effect and provides meaningful and unique interpretations. A case study using ECLS-K data that evaluates kindergarten retention policy is offered to illustrate our proposed approach.

Comparison of six methods for the detection of causality in a bivariate time series

NASA Astrophysics Data System (ADS)

Krakovská, Anna; Jakubík, Jozef; Chvosteková, Martina; Coufal, David; Jajcay, Nikola; Paluš, Milan

2018-04-01

In this comparative study, six causality detection methods were compared, namely, the Granger vector autoregressive test, the extended Granger test, the kernel version of the Granger test, the conditional mutual information (transfer entropy), the evaluation of cross mappings between state spaces, and an assessment of predictability improvement due to the use of mixed predictions. Seven test data sets were analyzed: linear coupling of autoregressive models, a unidirectional connection of two Hénon systems, a unidirectional connection of chaotic systems of Rössler and Lorenz type and of two different Rössler systems, an example of bidirectionally connected two-species systems, a fishery model as an example of two correlated observables without a causal relationship, and an example of mediated causality. We tested not only 20 000 points long clean time series but also noisy and short variants of the data. The standard and the extended Granger tests worked only for the autoregressive models. The remaining methods were more successful with the more complex test examples, although they differed considerably in their capability to reveal the presence and the direction of coupling and to distinguish causality from mere correlation.

Moral asymmetries in judgments of agency withstand ludicrous causal deviance

PubMed Central

Sousa, Paulo; Holbrook, Colin; Swiney, Lauren

2015-01-01

Americans have been shown to attribute greater intentionality to immoral than to amoral actions in cases of causal deviance, that is, cases where a goal is satisfied in a way that deviates from initially planned means (e.g., a gunman wants to hit a target and his hand slips, but the bullet ricochets off a rock into the target). However, past research has yet to assess whether this asymmetry persists in cases of extreme causal deviance. Here, we manipulated the level of mild to extreme causal deviance of an immoral versus amoral act. The asymmetry in attributions of intentionality was observed at all but the most extreme level of causal deviance, and, as we hypothesized, was mediated by attributions of blame/credit and judgments of action performance. These findings are discussed as they support a multiple-concepts interpretation of the asymmetry, wherein blame renders a naïve concept of intentional action (the outcome matches the intention) more salient than a composite concept (the outcome matches the intention and was brought about by planned means), and in terms of their implications for cross-cultural research on judgments of agency. PMID:26441755

Causal evidence in risk and policy perceptions: Applying the covariation/mechanism framework.

PubMed

Baucum, Matt; John, Richard

2018-05-01

Today's information-rich society demands constant evaluation of cause-effect relationships; behaviors and attitudes ranging from medical choices to voting decisions to policy preferences typically entail some form of causal inference ("Will this policy reduce crime?", "Will this activity improve my health?"). Cause-effect relationships such as these can be thought of as depending on two qualitatively distinct forms of evidence: covariation-based evidence (e.g., "states with this policy have fewer homicides") or mechanism-based (e.g., "this policy will reduce crime by discouraging repeat offenses"). Some psychological work has examined how people process these two forms of causal evidence in instances of "everyday" causality (e.g., assessing why a car will not start), but it is not known how these two forms of evidence contribute to causal judgments in matters of public risk or policy. Three studies (n = 715) investigated whether judgments of risk and policy scenarios would be affected by covariation and mechanism evidence and whether the evidence types interacted with one another (as suggested by past studies). Results showed that causal judgments varied linearly with mechanism strength and logarithmically with covariation strength, and that the evidence types produced only additive effects (but no interaction). We discuss the results' implications for risk communication and policy information dissemination. Copyright © 2018 Elsevier B.V. All rights reserved.

On the factorial and construct validity of the Intrinsic Motivation Inventory: conceptual and operational concerns.

PubMed

Markland, D; Hardy, L

1997-03-01

The Intrinsic Motivation Inventory (IMI) has been gaining acceptance in the sport and exercise domain since the publication of research by McAuley, Duncan, and Tammen (1989) and McAuley, Wraith, and Duncan (1991), which reported confirmatory support for the factorial validity of a hierarchical model of intrinsic motivation. Authors of the present study argue that the results of these studies did not conclusively support the hierarchical model and that the model did not accurately reflect the tenets of cognitive evaluation theory (Deci & Ryan, 1985) from which the IMI is drawn. It is also argued that a measure of perceived locus of causality is required to model intrinsic motivation properly. The development of a perceived locus of causality for exercise scale is described, and alternative models, in which perceived competence and perceived locus of causality are held to have causal influences on intrinsic motivation, are compared with an oblique confirmatory factor analytic model in which the constructs are held at the same conceptual level. Structural equation modeling showed support for a causal model in which perceived locus of causality mediates the effects of perceived competence on pressure-tension, interest-enjoyment, and effort-importance. It is argued that conceptual and operational problems with the IMI, as currently used, should be addressed before it becomes established as the instrument of choice for assessing levels of intrinsic motivation.

Attributional "Tunnel Vision" in Patients With Borderline Personality Disorder.

PubMed

Schilling, Lisa; Moritz, Steffen; Schneider, Brooke; Bierbrodt, Julia; Nagel, Matthias

2015-12-01

We aimed to examine the profile of interpersonal attributions in BPD. We hypothesized that patients show more mono-causal and internal attributions than healthy controls. A revised version of the Internal, Personal, Situational and Attributions Questionnaire was assessed in 30 BPD patients and 30 healthy controls. BPD patients and controls differed significantly in their attributional pattern. Patients displayed more mono-causal inferences, that is, they had difficulties considering alternative explanatory factors. For negative events, patients made more internal attributions compared to healthy controls. We concluded that mono-causal "trapped" thinking might contribute to (interpersonal) problems in BPD patients by fostering impulsive consequential behaviors, for example, harming one's self or others. A self-blaming tendency likely promotes depressive symptoms and low self-esteem.

Assessing the Effectiveness of Cumulative Sum Normal- and Poisson-Based Tests for Detecting Rare Diseases

DTIC Science & Technology

2010-12-01

The Francisella tularensis is one of these and is the causal agent of the tularemia disease. Tularemia is used as the motivating problem to evaluate...PAGES 79 14. SUBJECT TERMS Biosurveillance, Rare Disease, Tularemia , Cumulative Sum, CUSUM 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...is one of these, and is the causal agent of the tularemia disease. Tularemia is used as the motivating problem to evaluate and compare the

Gang membership and substance use: guilt as a gendered causal pathway

PubMed Central

Coffman, Donna L.; Melde, Chris; Esbensen, Finn-Aage

2014-01-01

Objectives We examine whether anticipated guilt for substance use is a gendered mechanism underlying the noted enhancement effect of gang membership on illegal drug use. We also demonstrate a method for making stronger causal inferences when assessing mediation in the presence of moderation and time-varying confounding. Methods We estimate a series of inverse propensity weighted models to obtain unbiased estimates of mediation in the presence of confounding of the exposure (i.e., gang membership) and mediator (i.e., anticipated guilt) using three waves of data from a multi-site panel study of a law-related education program for youth (N=1,113). Results The onset of gang membership significantly decreased anticipated substance use guilt among both male and female respondents. This reduction was significantly associated with increased frequency of substance use only for female respondents, however, suggesting that gender moderates the mechanism through which gang membership influences substance use. Conclusions Criminologists are often concerned with identifying causal pathways for antisocial and/or delinquent behavior, but confounders of the exposure, mediator, and outcome often interfere with efforts to assess mediation. Many new approaches have been proposed for strengthening causal inference for mediation effects. After controlling for confounding using inverse propensity weighting, our results suggest that interventions aimed at reducing substance use by current and former female gang members should focus on the normative aspects of these behaviors. PMID:26190954

Gang membership and substance use: guilt as a gendered causal pathway.

PubMed

Coffman, Donna L; Melde, Chris; Esbensen, Finn-Aage

2015-03-01

We examine whether anticipated guilt for substance use is a gendered mechanism underlying the noted enhancement effect of gang membership on illegal drug use. We also demonstrate a method for making stronger causal inferences when assessing mediation in the presence of moderation and time-varying confounding. We estimate a series of inverse propensity weighted models to obtain unbiased estimates of mediation in the presence of confounding of the exposure (i.e., gang membership) and mediator (i.e., anticipated guilt) using three waves of data from a multi-site panel study of a law-related education program for youth ( N =1,113). The onset of gang membership significantly decreased anticipated substance use guilt among both male and female respondents. This reduction was significantly associated with increased frequency of substance use only for female respondents, however, suggesting that gender moderates the mechanism through which gang membership influences substance use. Criminologists are often concerned with identifying causal pathways for antisocial and/or delinquent behavior, but confounders of the exposure, mediator, and outcome often interfere with efforts to assess mediation. Many new approaches have been proposed for strengthening causal inference for mediation effects. After controlling for confounding using inverse propensity weighting, our results suggest that interventions aimed at reducing substance use by current and former female gang members should focus on the normative aspects of these behaviors.

Financial networks based on Granger causality: A case study

NASA Astrophysics Data System (ADS)

Papana, Angeliki; Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

2017-09-01

Connectivity analysis is performed on a long financial record of 21 international stock indices employing a linear and a nonlinear causality measure, the conditional Granger causality index (CGCI) and the partial mutual information on mixed embedding (PMIME), respectively. Both measures aim to specify the direction of the interrelationships among the international stock indexes and portray the links of the resulting networks, by the presence of direct couplings between variables exploiting all available information. However, their differences are assessed due to the presence of nonlinearity. The weighted networks formed with respect to the causality measures are transformed to binary ones using a significance test. The financial networks are formed on sliding windows in order to examine the network characteristics and trace changes in the connectivity structure. Subsequently, two statistical network quantities are calculated; the average degree and the average shortest path length. The empirical findings reveal interesting time-varying properties of the constructed network, which are clearly dependent on the nature of the financial cycle.

Evaluating ritual efficacy: evidence from the supernatural.

PubMed

Legare, Cristine H; Souza, André L

2012-07-01

Rituals pose a cognitive paradox: although widely used to treat problems, rituals are causally opaque (i.e., they lack a causal explanation for their effects). How is the efficacy of ritual action evaluated in the absence of causal information? To examine this question using ecologically valid content, three studies (N=162) were conducted in Brazil, a cultural context in which rituals called simpatias are used to treat a great variety of problems ranging from asthma to infidelity. Using content from existing simpatias, experimental simpatias were designed to manipulate the kinds of information that influences perceptions of efficacy. A fourth study (N=68) with identical stimuli was conducted with a US sample to assess the generalizability of the findings across two different cultural contexts. The results provide evidence that information reflecting intuitive causal principles (i.e., repetition of procedures, number of procedural steps) and transcendental influence (i.e., presence of religious icons) affects how people evaluate ritual efficacy. Copyright © 2012 Elsevier B.V. All rights reserved.

Academic Procrastination: The Relationship Between Causal Attribution Styles and Behavioral Postponement

PubMed Central

Badri Gargari, Rahim; Sabouri, Hossein; Norzad, Fatemeh

2011-01-01

Objective: This research was conducted to study the relationship between attribution and academic procrastination in University Students. Methods: The subjects were 203 undergraduate students, 55 males and 148 females, selected from English and French language and literature students of Tabriz University. Data were gathered through Procrastination Assessment Scale-student (PASS) and Causal Dimension Scale (CDA) and were analyzed by multiple regression analysis (stepwise). Results: The results showed that there was a meaningful and negative relation between the locus of control and controllability in success context and academic procrastination. Besides, a meaningful and positive relation was observed between the locus of control and stability in failure context and procrastination. It was also found that 17% of the variance of procrastination was accounted by linear combination of attributions. Conclusion: We believe that causal attribution is a key in understanding procrastination in academic settings and is used by those who have the knowledge of Causal Attribution styles to organize their learning. PMID:24644450

What is learned from longitudinal studies of advertising and youth drinking and smoking? A critical assessment.

PubMed

Nelson, Jon P

2010-03-01

This paper assesses the methodology employed in longitudinal studies of advertising and youth drinking and smoking behaviors. These studies often are given a causal interpretation in the psychology and public health literatures. Four issues are examined from the perspective of econometrics. First, specification and validation of empirical models. Second, empirical issues associated with measures of advertising receptivity and exposure. Third, potential endogeneity of receptivity and exposure variables. Fourth, sample selection bias in baseline and follow-up surveys. Longitudinal studies reviewed include 20 studies of youth drinking and 26 studies of youth smoking. Substantial shortcomings are found in the studies, which preclude a causal interpretation.

What is Learned from Longitudinal Studies of Advertising and Youth Drinking and Smoking? A Critical Assessment

PubMed Central

Nelson, Jon P

2010-01-01

This paper assesses the methodology employed in longitudinal studies of advertising and youth drinking and smoking behaviors. These studies often are given a causal interpretation in the psychology and public health literatures. Four issues are examined from the perspective of econometrics. First, specification and validation of empirical models. Second, empirical issues associated with measures of advertising receptivity and exposure. Third, potential endogeneity of receptivity and exposure variables. Fourth, sample selection bias in baseline and follow-up surveys. Longitudinal studies reviewed include 20 studies of youth drinking and 26 studies of youth smoking. Substantial shortcomings are found in the studies, which preclude a causal interpretation. PMID:20617009

Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors.

PubMed

Burgess, Stephen; Scott, Robert A; Timpson, Nicholas J; Davey Smith, George; Thompson, Simon G

2015-07-01

Finding individual-level data for adequately-powered Mendelian randomization analyses may be problematic. As publicly-available summarized data on genetic associations with disease outcomes from large consortia are becoming more abundant, use of published data is an attractive analysis strategy for obtaining precise estimates of the causal effects of risk factors on outcomes. We detail the necessary steps for conducting Mendelian randomization investigations using published data, and present novel statistical methods for combining data on the associations of multiple (correlated or uncorrelated) genetic variants with the risk factor and outcome into a single causal effect estimate. A two-sample analysis strategy may be employed, in which evidence on the gene-risk factor and gene-outcome associations are taken from different data sources. These approaches allow the efficient identification of risk factors that are suitable targets for clinical intervention from published data, although the ability to assess the assumptions necessary for causal inference is diminished. Methods and guidance are illustrated using the example of the causal effect of serum calcium levels on fasting glucose concentrations. The estimated causal effect of a 1 standard deviation (0.13 mmol/L) increase in calcium levels on fasting glucose (mM) using a single lead variant from the CASR gene region is 0.044 (95 % credible interval -0.002, 0.100). In contrast, using our method to account for the correlation between variants, the corresponding estimate using 17 genetic variants is 0.022 (95 % credible interval 0.009, 0.035), a more clearly positive causal effect.

Individuals Who Believe in the Paranormal Expose Themselves to Biased Information and Develop More Causal Illusions than Nonbelievers in the Laboratory.

PubMed

Blanco, Fernando; Barberia, Itxaso; Matute, Helena

2015-01-01

In the reasoning literature, paranormal beliefs have been proposed to be linked to two related phenomena: a biased perception of causality and a biased information-sampling strategy (believers tend to test fewer hypotheses and prefer confirmatory information). In parallel, recent contingency learning studies showed that, when two unrelated events coincide frequently, individuals interpret this ambiguous pattern as evidence of a causal relationship. Moreover, the latter studies indicate that sampling more cause-present cases than cause-absent cases strengthens the illusion. If paranormal believers actually exhibit a biased exposure to the available information, they should also show this bias in the contingency learning task: they would in fact expose themselves to more cause-present cases than cause-absent trials. Thus, by combining the two traditions, we predicted that believers in the paranormal would be more vulnerable to developing causal illusions in the laboratory than nonbelievers because there is a bias in the information they experience. In this study, we found that paranormal beliefs (measured using a questionnaire) correlated with causal illusions (assessed by using contingency judgments). As expected, this correlation was mediated entirely by the believers' tendency to expose themselves to more cause-present cases. The association between paranormal beliefs, biased exposure to information, and causal illusions was only observed for ambiguous materials (i.e., the noncontingent condition). In contrast, the participants' ability to detect causal relationships which did exist (i.e., the contingent condition) was unaffected by their susceptibility to believe in paranormal phenomena.

Children's beliefs about causes of childhood depression and ADHD: a study of stigmatization.

PubMed

Coleman, Daniel; Walker, Janet S; Lee, Junghee; Friesen, Barbara J; Squire, Peter N

2009-07-01

Children's causal attributions about childhood mental health problems were examined in a national sample for prevalence; relative stigmatization; variation by age, race and ethnicity, and gender; and self-report of a diagnosis of depression or attention-deficit hyperactivity disorder (ADHD). A national sample of 1,091 children were randomly assigned to read vignettes about a peer with depression, ADHD, or asthma and respond to an online survey. Causal attributions and social distance were assessed, and correlations were examined. Logistic regression models for each causal item tested main effects and interaction terms for conditions, demographic characteristics, and self-reported diagnosis. The beliefs that parenting, substance abuse, and low effort caused the condition were all strongly intercorrelated and were moderately correlated with social distance. The depression condition was the strongest predictor of endorsement of the most stigmatizing causal beliefs. Stigmatizing causal beliefs were evident for ADHD, but with more modest effects. Children who reported a diagnosis were more likely to endorse parenting and substance abuse as causes (attenuated for ADHD). Modest to moderate effects were found for variation in causal beliefs across ethnic groups. This study demonstrated a consistent presence of stigmatization in children's beliefs about the causes of childhood mental health problems. Low effort, parenting, and substance abuse together tapped a moralistic and blaming view of mental health problems. The results reinforce the need to address stigmatization of mental disorders and the relative stigmatization of different causal beliefs. The findings of variation by ethnicity and diagnosis can inform and target antistigmatization efforts.

Individuals Who Believe in the Paranormal Expose Themselves to Biased Information and Develop More Causal Illusions than Nonbelievers in the Laboratory

PubMed Central

Blanco, Fernando; Barberia, Itxaso; Matute, Helena

2015-01-01

In the reasoning literature, paranormal beliefs have been proposed to be linked to two related phenomena: a biased perception of causality and a biased information-sampling strategy (believers tend to test fewer hypotheses and prefer confirmatory information). In parallel, recent contingency learning studies showed that, when two unrelated events coincide frequently, individuals interpret this ambiguous pattern as evidence of a causal relationship. Moreover, the latter studies indicate that sampling more cause-present cases than cause-absent cases strengthens the illusion. If paranormal believers actually exhibit a biased exposure to the available information, they should also show this bias in the contingency learning task: they would in fact expose themselves to more cause-present cases than cause-absent trials. Thus, by combining the two traditions, we predicted that believers in the paranormal would be more vulnerable to developing causal illusions in the laboratory than nonbelievers because there is a bias in the information they experience. In this study, we found that paranormal beliefs (measured using a questionnaire) correlated with causal illusions (assessed by using contingency judgments). As expected, this correlation was mediated entirely by the believers' tendency to expose themselves to more cause-present cases. The association between paranormal beliefs, biased exposure to information, and causal illusions was only observed for ambiguous materials (i.e., the noncontingent condition). In contrast, the participants' ability to detect causal relationships which did exist (i.e., the contingent condition) was unaffected by their susceptibility to believe in paranormal phenomena. PMID:26177025

IMPROVING THE TMDL PROCESS USING WATERSHED RISK ASSESSMENT PRINCIPLES

EPA Science Inventory

Watershed ecological risk assessment (WERA) evaluates potential causal relationships between multiple sources and stressors and impacts on valued ecosystem components. This has many similarities tothe placed-based analuses that are undertaken to develop total maximum daily loads...

Assessment of resampling methods for causality testing: A note on the US inflation behavior

PubMed Central

Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

2017-01-01

Different resampling methods for the null hypothesis of no Granger causality are assessed in the setting of multivariate time series, taking into account that the driving-response coupling is conditioned on the other observed variables. As appropriate test statistic for this setting, the partial transfer entropy (PTE), an information and model-free measure, is used. Two resampling techniques, time-shifted surrogates and the stationary bootstrap, are combined with three independence settings (giving a total of six resampling methods), all approximating the null hypothesis of no Granger causality. In these three settings, the level of dependence is changed, while the conditioning variables remain intact. The empirical null distribution of the PTE, as the surrogate and bootstrapped time series become more independent, is examined along with the size and power of the respective tests. Additionally, we consider a seventh resampling method by contemporaneously resampling the driving and the response time series using the stationary bootstrap. Although this case does not comply with the no causality hypothesis, one can obtain an accurate sampling distribution for the mean of the test statistic since its value is zero under H0. Results indicate that as the resampling setting gets more independent, the test becomes more conservative. Finally, we conclude with a real application. More specifically, we investigate the causal links among the growth rates for the US CPI, money supply and crude oil. Based on the PTE and the seven resampling methods, we consistently find that changes in crude oil cause inflation conditioning on money supply in the post-1986 period. However this relationship cannot be explained on the basis of traditional cost-push mechanisms. PMID:28708870

Assessment of resampling methods for causality testing: A note on the US inflation behavior.

PubMed

Papana, Angeliki; Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

2017-01-01

Different resampling methods for the null hypothesis of no Granger causality are assessed in the setting of multivariate time series, taking into account that the driving-response coupling is conditioned on the other observed variables. As appropriate test statistic for this setting, the partial transfer entropy (PTE), an information and model-free measure, is used. Two resampling techniques, time-shifted surrogates and the stationary bootstrap, are combined with three independence settings (giving a total of six resampling methods), all approximating the null hypothesis of no Granger causality. In these three settings, the level of dependence is changed, while the conditioning variables remain intact. The empirical null distribution of the PTE, as the surrogate and bootstrapped time series become more independent, is examined along with the size and power of the respective tests. Additionally, we consider a seventh resampling method by contemporaneously resampling the driving and the response time series using the stationary bootstrap. Although this case does not comply with the no causality hypothesis, one can obtain an accurate sampling distribution for the mean of the test statistic since its value is zero under H0. Results indicate that as the resampling setting gets more independent, the test becomes more conservative. Finally, we conclude with a real application. More specifically, we investigate the causal links among the growth rates for the US CPI, money supply and crude oil. Based on the PTE and the seven resampling methods, we consistently find that changes in crude oil cause inflation conditioning on money supply in the post-1986 period. However this relationship cannot be explained on the basis of traditional cost-push mechanisms.

Arsenic metabolism efficiency has a causal role in arsenic toxicity: Mendelian randomization and gene-environment interaction.

PubMed

Pierce, Brandon L; Tong, Lin; Argos, Maria; Gao, Jianjun; Farzana, Jasmine; Roy, Shantanu; Paul-Brutus, Rachelle; Rahaman, Ronald; Rakibuz-Zaman, Muhammad; Parvez, Faruque; Ahmed, Alauddin; Quasem, Iftekhar; Hore, Samar K; Alam, Shafiul; Islam, Tariqul; Harjes, Judith; Sarwar, Golam; Slavkovich, Vesna; Gamble, Mary V; Chen, Yu; Yunus, Mohammad; Rahman, Mahfuzar; Baron, John A; Graziano, Joseph H; Ahsan, Habibul

2013-12-01

Arsenic exposure through drinking water is a serious global health issue. Observational studies suggest that individuals who metabolize arsenic efficiently are at lower risk for toxicities such as arsenical skin lesions. Using two single nucleotide polymorphisms(SNPs) in the 10q24.32 region (near AS3MT) that show independent associations with metabolism efficiency, Mendelian randomization can be used to assess whether the association between metabolism efficiency and skin lesions is likely to be causal. Using data on 2060 arsenic-exposed Bangladeshi individuals, we estimated associations for two 10q24.32 SNPs with relative concentrations of three urinary arsenic species (representing metabolism efficiency): inorganic arsenic (iAs), monomethylarsonic acid(MMA) and dimethylarsinic acid (DMA). SNP-based predictions of iAs%, MMA% and DMA% were tested for association with skin lesion status among 2483 cases and 2857 controls. Causal odds ratios for skin lesions were 0.90 (95% confidence interval[CI]: 0.87, 0.95), 1.19 (CI: 1.10, 1.28) and 1.23 (CI: 1.12, 1.36)for a one standard deviation increase in DMA%, MMA% and iAs%,respectively. We demonstrated genotype-arsenic interaction, with metabolism-related variants showing stronger associations with skin lesion risk among individuals with high arsenic exposure (synergy index: 1.37; CI: 1.11, 1.62). We provide strong evidence for a causal relationship between arsenic metabolism efficiency and skin lesion risk. Mendelian randomization can be used to assess the causal role of arsenic exposure and metabolism in a wide array of health conditions.exposure and metabolism in a wide array of health conditions.Developing interventions that increase arsenic metabolism efficiency are likely to reduce the impact of arsenic exposure on health.

The Effects of Write Score Formative Assessment on Student Achievement

ERIC Educational Resources Information Center

Fox, Janice M.

2013-01-01

In an "ex post facto" causal-comparative research design, this study investigated the effectiveness of a formative writing assessment program, Write Score, on increasing student writing achievement. Tennessee Comprehensive Assessment Program (TCAP) reading language arts and writing scores from 2012 were utilized for this study. The…

Somatization revisited: diagnosis and perceived causes of common mental disorders.

PubMed

Henningsen, Peter; Jakobsen, Thorsten; Schiltenwolf, Marcus; Weiss, Mitchell G

2005-02-01

The assessment of somatoform disorders is complicated by persistent theoretical and practical questions of classification and assessment. Critical rethinking of professional concepts of somatization suggests the value of complementary assessment of patients' illness explanatory models of somatoform and other common mental disorders. We undertook this prospective study to assess medically unexplained somatic symptoms and their patient-perceived causes of illness and to show how patients' explanatory models relate to professional diagnoses of common mental disorders and how they may predict the short-term course of illness. Tertiary care patients (N=186) with prominent somatoform symptoms were evaluated with the Structured Clinical Interview for DSM-IV, a locally adapted Explanatory Model Interview to elicit patients' illness experience (priority symptoms) and perceived causes, and clinical self-report questionnaires. The self-report questionnaires were administered at baseline and after 6 months. Diagnostic overlap between somatoform, depressive, and anxiety disorders occurred frequently (79.6%). Patients explained pure somatoform disorders mainly with organic causal attributions; they explained pure depressive and/or anxiety disorders mainly with psychosocial perceived causes, and patients in the diagnostic overlap group typically reported mixed causal attributions. In this last group, among patients with similar levels of symptom severity, organic perceived causes were related to a lower physical health sum score on the MOS Short Form, and psychosocial perceived causes were related to less severe depressive symptoms, assessed with the Hospital Anxiety and Depression Scale at 6 months. Among patients meeting criteria for comorbid somatoform with anxiety and/or depressive disorders, complementary assessment of patient-perceived causes, a key element of illness explanatory models, was related to levels of functional impairment and short-term prognosis. For such patients, causal attributions may be particularly useful to clarify clinically significant features of common mental disorders and thereby contribute to clinical assessment.

Understanding Lay Assessments of Alcohol Use Disorder: Need for Treatment and Associated Stigma.

PubMed

Weine, Erienne R; Kim, Nancy S; Lincoln, Alisa K

2016-01-01

Three-quarters of people with an alcohol use disorder in the USA never receive treatment. Our understandings of who receives care are informed by sociological perspectives, theories and models, each of which discuss the role of lay people's understanding of illness. However, comparatively little work has been done to unpack the cognitive processes underlying lay assessment. In the context of the Framework Integrating Normative Influences on Stigma (FINIS), we aim to understand key factors guiding lay people's stigmatizing attitudes, perceptions and assessments of alcohol use disorder behaviors. Lay people read a vignette depicting a male or female adult with a diagnosable alcohol use disorder, along with either a causal life-event explanation for the alcohol use disorder behaviors or no explanation. They then made judgments of the need for treatment, psychological abnormality and the stigma they felt toward the person depicted. Causal life-event explanations decreased lay judgments of the need for treatment, psychological abnormality and stigma. The results suggest that the availability of a causal life-event explanation may have a complex effect on lay judgments, decreasing the likelihood of recommending treatment for alcohol use disorders, yet simultaneously reducing stigmatizing perceptions (and presumably social distance). © The Author 2015. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Surrogacy Assessment Using Principal Stratification and a Gaussian Copula Model

PubMed Central

Taylor, J.M.G.; Elliott, M.R.

2014-01-01

In clinical trials, a surrogate outcome (S) can be measured before the outcome of interest (T) and may provide early information regarding the treatment (Z) effect on T. Many methods of surrogacy validation rely on models for the conditional distribution of T given Z and S. However, S is a post-randomization variable, and unobserved, simultaneous predictors of S and T may exist, resulting in a non-causal interpretation. Frangakis and Rubin1 developed the concept of principal surrogacy, stratifying on the joint distribution of the surrogate marker under treatment and control to assess the association between the causal effects of treatment on the marker and the causal effects of treatment on the clinical outcome. Working within the principal surrogacy framework, we address the scenario of an ordinal categorical variable as a surrogate for a censored failure time true endpoint. A Gaussian copula model is used to model the joint distribution of the potential outcomes of T, given the potential outcomes of S. Because the proposed model cannot be fully identified from the data, we use a Bayesian estimation approach with prior distributions consistent with reasonable assumptions in the surrogacy assessment setting. The method is applied to data from a colorectal cancer clinical trial, previously analyzed by Burzykowski et al..2 PMID:24947559

Surrogacy assessment using principal stratification and a Gaussian copula model.

PubMed

Conlon, Asc; Taylor, Jmg; Elliott, M R

2017-02-01

In clinical trials, a surrogate outcome ( S) can be measured before the outcome of interest ( T) and may provide early information regarding the treatment ( Z) effect on T. Many methods of surrogacy validation rely on models for the conditional distribution of T given Z and S. However, S is a post-randomization variable, and unobserved, simultaneous predictors of S and T may exist, resulting in a non-causal interpretation. Frangakis and Rubin developed the concept of principal surrogacy, stratifying on the joint distribution of the surrogate marker under treatment and control to assess the association between the causal effects of treatment on the marker and the causal effects of treatment on the clinical outcome. Working within the principal surrogacy framework, we address the scenario of an ordinal categorical variable as a surrogate for a censored failure time true endpoint. A Gaussian copula model is used to model the joint distribution of the potential outcomes of T, given the potential outcomes of S. Because the proposed model cannot be fully identified from the data, we use a Bayesian estimation approach with prior distributions consistent with reasonable assumptions in the surrogacy assessment setting. The method is applied to data from a colorectal cancer clinical trial, previously analyzed by Burzykowski et al.

Microrandomized trials: An experimental design for developing just-in-time adaptive interventions.

PubMed

Klasnja, Predrag; Hekler, Eric B; Shiffman, Saul; Boruvka, Audrey; Almirall, Daniel; Tewari, Ambuj; Murphy, Susan A

2015-12-01

This article presents an experimental design, the microrandomized trial, developed to support optimization of just-in-time adaptive interventions (JITAIs). JITAIs are mHealth technologies that aim to deliver the right intervention components at the right times and locations to optimally support individuals' health behaviors. Microrandomized trials offer a way to optimize such interventions by enabling modeling of causal effects and time-varying effect moderation for individual intervention components within a JITAI. The article describes the microrandomized trial design, enumerates research questions that this experimental design can help answer, and provides an overview of the data analyses that can be used to assess the causal effects of studied intervention components and investigate time-varying moderation of those effects. Microrandomized trials enable causal modeling of proximal effects of the randomized intervention components and assessment of time-varying moderation of those effects. Microrandomized trials can help researchers understand whether their interventions are having intended effects, when and for whom they are effective, and what factors moderate the interventions' effects, enabling creation of more effective JITAIs. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Causal assessment of surrogacy in a meta-analysis of colorectal cancer trials

PubMed Central

Li, Yun; Taylor, Jeremy M.G.; Elliott, Michael R.; Sargent, Daniel J.

2011-01-01

When the true end points (T) are difficult or costly to measure, surrogate markers (S) are often collected in clinical trials to help predict the effect of the treatment (Z). There is great interest in understanding the relationship among S, T, and Z. A principal stratification (PS) framework has been proposed by Frangakis and Rubin (2002) to study their causal associations. In this paper, we extend the framework to a multiple trial setting and propose a Bayesian hierarchical PS model to assess surrogacy. We apply the method to data from a large collection of colon cancer trials in which S and T are binary. We obtain the trial-specific causal measures among S, T, and Z, as well as their overall population-level counterparts that are invariant across trials. The method allows for information sharing across trials and reduces the nonidentifiability problem. We examine the frequentist properties of our model estimates and the impact of the monotonicity assumption using simulations. We also illustrate the challenges in evaluating surrogacy in the counterfactual framework that result from nonidentifiability. PMID:21252079

Micro-Randomized Trials: An Experimental Design for Developing Just-in-Time Adaptive Interventions

PubMed Central

Klasnja, Predrag; Hekler, Eric B.; Shiffman, Saul; Boruvka, Audrey; Almirall, Daniel; Tewari, Ambuj; Murphy, Susan A.

2015-01-01

Objective This paper presents an experimental design, the micro-randomized trial, developed to support optimization of just-in-time adaptive interventions (JITAIs). JITAIs are mHealth technologies that aim to deliver the right intervention components at the right times and locations to optimally support individuals’ health behaviors. Micro-randomized trials offer a way to optimize such interventions by enabling modeling of causal effects and time-varying effect moderation for individual intervention components within a JITAI. Methods The paper describes the micro-randomized trial design, enumerates research questions that this experimental design can help answer, and provides an overview of the data analyses that can be used to assess the causal effects of studied intervention components and investigate time-varying moderation of those effects. Results Micro-randomized trials enable causal modeling of proximal effects of the randomized intervention components and assessment of time-varying moderation of those effects. Conclusions Micro-randomized trials can help researchers understand whether their interventions are having intended effects, when and for whom they are effective, and what factors moderate the interventions’ effects, enabling creation of more effective JITAIs. PMID:26651463

Final Technical Report on Quantifying Dependability Attributes of Software Based Safety Critical Instrumentation and Control Systems in Nuclear Power Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smidts, Carol; Huang, Funqun; Li, Boyuan

With the current transition from analog to digital instrumentation and control systems in nuclear power plants, the number and variety of software-based systems have significantly increased. The sophisticated nature and increasing complexity of software raises trust in these systems as a significant challenge. The trust placed in a software system is typically termed software dependability. Software dependability analysis faces uncommon challenges since software systems’ characteristics differ from those of hardware systems. The lack of systematic science-based methods for quantifying the dependability attributes in software-based instrumentation as well as control systems in safety critical applications has proved itself to be amore » significant inhibitor to the expanded use of modern digital technology in the nuclear industry. Dependability refers to the ability of a system to deliver a service that can be trusted. Dependability is commonly considered as a general concept that encompasses different attributes, e.g., reliability, safety, security, availability and maintainability. Dependability research has progressed significantly over the last few decades. For example, various assessment models and/or design approaches have been proposed for software reliability, software availability and software maintainability. Advances have also been made to integrate multiple dependability attributes, e.g., integrating security with other dependability attributes, measuring availability and maintainability, modeling reliability and availability, quantifying reliability and security, exploring the dependencies between security and safety and developing integrated analysis models. However, there is still a lack of understanding of the dependencies between various dependability attributes as a whole and of how such dependencies are formed. To address the need for quantification and give a more objective basis to the review process -- therefore reducing regulatory uncertainty -- measures and methods are needed to assess dependability attributes early on, as well as throughout the life-cycle process of software development. In this research, extensive expert opinion elicitation is used to identify the measures and methods for assessing software dependability. Semi-structured questionnaires were designed to elicit expert knowledge. A new notation system, Causal Mechanism Graphing, was developed to extract and represent such knowledge. The Causal Mechanism Graphs were merged, thus, obtaining the consensus knowledge shared by the domain experts. In this report, we focus on how software contributes to dependability. However, software dependability is not discussed separately from the context of systems or socio-technical systems. Specifically, this report focuses on software dependability, reliability, safety, security, availability, and maintainability. Our research was conducted in the sequence of stages found below. Each stage is further examined in its corresponding chapter. Stage 1 (Chapter 2): Elicitation of causal maps describing the dependencies between dependability attributes. These causal maps were constructed using expert opinion elicitation. This chapter describes the expert opinion elicitation process, the questionnaire design, the causal map construction method and the causal maps obtained. Stage 2 (Chapter 3): Elicitation of the causal map describing the occurrence of the event of interest for each dependability attribute. The causal mechanisms for the “event of interest” were extracted for each of the software dependability attributes. The “event of interest” for a dependability attribute is generally considered to be the “attribute failure”, e.g. security failure. The extraction was based on the analysis of expert elicitation results obtained in Stage 1. Stage 3 (Chapter 4): Identification of relevant measurements. Measures for the “events of interest” and their causal mechanisms were obtained from expert opinion elicitation for each of the software dependability attributes. The measures extracted are presented in this chapter. Stage 4 (Chapter 5): Assessment of the coverage of the causal maps via measures. Coverage was assessed to determine whether the measures obtained were sufficient to quantify software dependability, and what measures are further required. Stage 5 (Chapter 6): Identification of “missing” measures and measurement approaches for concepts not covered. New measures, for concepts that had not been covered sufficiently as determined in Stage 4, were identified using supplementary expert opinion elicitation as well as literature reviews. Stage 6 (Chapter 7): Building of a detailed quantification model based on the causal maps and measurements obtained. Ability to derive such a quantification model shows that the causal models and measurements derived from the previous stages (Stage 1 to Stage 5) can form the technical basis for developing dependability quantification models. Scope restrictions have led us to prioritize this demonstration effort. The demonstration was focused on a critical system, i.e. the reactor protection system. For this system, a ranking of the software dependability attributes by nuclear stakeholders was developed. As expected for this application, the stakeholder ranking identified safety as the most critical attribute to be quantified. A safety quantification model limited to the requirements phase of development was built. Two case studies were conducted for verification. A preliminary control gate for software safety for the requirements stage was proposed and applied to the first case study. The control gate allows a cost effective selection of the duration of the requirements phase.« less

The Mediation Formula: A Guide to the Assessment of Causal Pathways in Nonlinear Models

DTIC Science & Technology

2011-10-27

through (25), (26) and (27), rather than going through (23) ( van der Laan and Rubin, 2006). 29 values, though disparities in parameters may not...graphs. Epidemiology 22 378–381. Petersen, M., Sinisi, S. and van der Laan, M. (2006). Estimation of direct causal effects. Epidemiology 17 276–284...and J. Halpern, eds.). College Publications, UK, 415–444. van der Laan, M. J. and Rubin, D. (2006). Targeted maximum likelihood learning. The

Using genetics to test the causal relationship of total adiposity and periodontitis: Mendelian randomization analyses in the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium

PubMed Central

Shungin, Dmitry; Cornelis, Marilyn C; Divaris, Kimon; Holtfreter, Birte; Shaffer, John R; Yu, Yau-Hua; Barros, Silvana P; Beck, James D; Biffar, Reiner; Boerwinkle, Eric A; Crout, Richard J.; Ganna, Andrea; Hallmans, Goran; Hindy, George; Hu, Frank B; Kraft, Peter; McNeil, Daniel W; Melander, Olle; Moss, Kevin L; North, Kari E; Orho-Melander, Marju; Pedersen, Nancy L; Ridker, Paul M; Rimm, Eric B; Rose, Lynda M; Rukh, Gull; Teumer, Alexander; Weyant, Robert J; Chasman, Daniel I; Joshipura, Kaumudi; Kocher, Thomas; Magnusson, Patrik KE; Marazita, Mary L; Nilsson, Peter; Offenbacher, Steve; Davey Smith, George; Lundberg, Pernilla; Palmer, Tom M; Timpson, Nicholas J; Johansson, Ingegerd; Franks, Paul W

2015-01-01

Background: The observational relationship between obesity and periodontitis is widely known, yet causal evidence is lacking. Our objective was to investigate causal associations between periodontitis and body mass index (BMI). Methods: We performed Mendelian randomization analyses with BMI-associated loci combined in a genetic risk score (GRS) as the instrument for BMI. All analyses were conducted within the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium in 13 studies from Europe and the USA, including 49 066 participants with clinically assessed (seven studies, 42.1% of participants) and self-reported (six studies, 57.9% of participants) periodontitis and genotype data (17 672/31 394 with/without periodontitis); 68 761 participants with BMI and genotype data; and 57 871 participants (18 881/38 990 with/without periodontitis) with data on BMI and periodontitis. Results: In the observational meta-analysis of all participants, the pooled crude observational odds ratio (OR) for periodontitis was 1.13 [95% confidence interval (CI): 1.03, 1.24] per standard deviation increase of BMI. Controlling for potential confounders attenuated this estimate (OR = 1.08; 95% CI:1.03, 1.12). For clinically assessed periodontitis, corresponding ORs were 1.25 (95% CI: 1.10, 1.42) and 1.13 (95% CI: 1.10, 1.17), respectively. In the genetic association meta-analysis, the OR for periodontitis was 1.01 (95% CI: 0.99, 1.03) per GRS unit (per one effect allele) in all participants and 1.00 (95% CI: 0.97, 1.03) in participants with clinically assessed periodontitis. The instrumental variable meta-analysis of all participants yielded an OR of 1.05 (95% CI: 0.80, 1.38) per BMI standard deviation, and 0.90 (95% CI: 0.56, 1.46) in participants with clinical data. Conclusions: Our study does not support total adiposity as a causal risk factor for periodontitis, as the point estimate is very close to the null in the causal inference analysis, with wide confidence intervals. PMID:26050256

Causal Attribution and Coping Maxims Differences between Immigrants and Non-Immigrants Suffering from Back Pain in Switzerland.

PubMed

Mantwill, Sarah; Schulz, Peter J

2016-01-01

This study aimed at investigating the relationship between causal attributions and coping maxims in people suffering from back pain. Further, it aimed at identifying in how far causal attributions and related coping maxims would defer between immigrants and non-immigrants in Switzerland. Data for this study came from a larger survey study that was conducted among immigrant populations in the German- and Italian-speaking part of Switzerland. Included in the analyses were native Swiss participants, as well as Albanian- and Serbian-speaking immigrants, who had indicated to have suffered from back pain within the last 12 months prior to the study. Data was analyzed for overall 495 participants. Items for causal attributions and coping maxims were subject to factor analyses. Cultural differences were assessed with ANOVA and regression analyses. Interaction terms were included to investigate whether the relationship between causal attributions and coping maxims would differ with cultural affiliation. For both immigrant groups the physician's influence on the course of their back pain was more important than for Swiss participants (p <.05). With regard to coping, both immigrant groups were more likely to agree with maxims that were related to the improvement of the back pain, as well as the acceptance of the current situation (p <.05). The only consistent interaction effect that was found indicated that being Albanian-speaking negatively moderated the relationship between physical activity as an attributed cause of back pain and all three identified coping maxims. The study shows that differences in causal attribution and coping maxims between immigrants and non-immigrants exist. Further, the results support the assumption of an association between causal attribution and coping maxims. However cultural affiliation did not considerably moderate this relationship.

Causal Attribution and Coping Maxims Differences between Immigrants and Non-Immigrants Suffering from Back Pain in Switzerland

PubMed Central

2016-01-01

Objectives This study aimed at investigating the relationship between causal attributions and coping maxims in people suffering from back pain. Further, it aimed at identifying in how far causal attributions and related coping maxims would defer between immigrants and non-immigrants in Switzerland. Methods Data for this study came from a larger survey study that was conducted among immigrant populations in the German- and Italian-speaking part of Switzerland. Included in the analyses were native Swiss participants, as well as Albanian- and Serbian-speaking immigrants, who had indicated to have suffered from back pain within the last 12 months prior to the study. Data was analyzed for overall 495 participants. Items for causal attributions and coping maxims were subject to factor analyses. Cultural differences were assessed with ANOVA and regression analyses. Interaction terms were included to investigate whether the relationship between causal attributions and coping maxims would differ with cultural affiliation. Results For both immigrant groups the physician’s influence on the course of their back pain was more important than for Swiss participants (p <.05). With regard to coping, both immigrant groups were more likely to agree with maxims that were related to the improvement of the back pain, as well as the acceptance of the current situation (p <.05). The only consistent interaction effect that was found indicated that being Albanian-speaking negatively moderated the relationship between physical activity as an attributed cause of back pain and all three identified coping maxims. Conclusion The study shows that differences in causal attribution and coping maxims between immigrants and non-immigrants exist. Further, the results support the assumption of an association between causal attribution and coping maxims. However cultural affiliation did not considerably moderate this relationship. PMID:27583445

What Can Causal Networks Tell Us about Metabolic Pathways?

PubMed Central

Blair, Rachael Hageman; Kliebenstein, Daniel J.; Churchill, Gary A.

2012-01-01

Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies. PMID:22496633

Herbal hepatotoxicity and WHO global introspection method.

PubMed

Teschke, Rolf; Eickhoff, Axel; Wolff, Albrecht; Frenzel, Christian; Schulze, Johannes

2013-01-01

Herbal hepatotoxicity is a rare but highly disputed disease because numerous confounding variables may complicate accurate causality assessment. Case evaluation is even more difficult when the WHO global introspection method (WHO method) is applied as diagnostic algorithm. This method lacks liver specificity, hepatotoxicity validation, and quantitative items, basic qualifications required for a sound evaluation of hepatotoxicity cases. Consequently, there are no data available for reliability, sensitivity, specificity, positive and negative predictive value. Its scope is also limited by the fact that it cannot discriminate between a positive and a negative causality attribution, thereby stimulating case overdiagnosing and overreporting. The WHO method ignores uncertainties regarding daily dose, temporal association, start, duration, and end of herbal use, time to onset of the adverse reaction, and course of liver values after herb discontinuation. Insufficiently considered or ignored are comedications, preexisting liver diseases, alternative explanations upon clinical assessment, and exclusion of infections by hepatitis A-C, cytomegalovirus (CMV), Epstein-Barr virus (EBV), herpes simplex virus (HSV), and varicella zoster virus (VZV). We clearly prefer as alternative the scale of CIOMS (Council for International Organizations of Medical Sciences) which is structured, quantitative, liver specific, and validated for hepatotoxicity. In conclusion, causality of herbal hepatotoxicity is best assessed by the liver specific CIOMS scale validated for hepatotoxicity rather than the obsolete WHO method that is liver unspecific and not validated for hepatotoxicity. CIOMS based assessments will ensure the correct diagnosis and exclude alternative diagnosis that may require other specific therapies.

Burnout Study of Clinical Nurses in Vietnam: Development of Job Burnout Model Based on Leiter and Maslach's Theory.

PubMed

Nguyen, Huong Thi Thu; Kitaoka, Kazuyo; Sukigara, Masune; Thai, Anh Lan

2018-03-01

This study aimed to create a Vietnamese version of both the Maslach Burnout Inventory-General Survey (MBI-GS) and Areas of Worklife Scale (AWS) to assess the burnout state of Vietnamese clinical nurses and to develop a causal model of burnout of clinical nurses. We conducted a descriptive design using a cross-sectional survey. The questionnaire was hand divided directly by nursing departments to 500 clinical nurses in three hospitals. Vietnamese MBI-GS and AWS were then examined for reliability and validity. We used the revised exhaustion +1 burnout classification to access burnout state. We performed path analysis to develop a Vietnamese causal model based on the original model by Leiter and Maslach's theory. We found that both scales were reliable and valid for assessing burnout. Among nurse participants, the percentage of severe burnout was 0.7% and burnout was 15.8%, and 17.2% of nurses were exhausted. The best predictor of burnout was "on-duty work schedule" that clinical nurses have to work for 24 hours. In the causal model, we also found similarity and difference pathways in comparison with the original model. Vietnamese MBI-GS and AWS were applicable to research on occupational stress. Nearly one-fifth of Vietnamese clinical nurses were working in burnout state. The causal model suggested a range of factors resulting in burnout, and it is necessary to consider the specific solution to prevent burnout problem. Copyright © 2018. Published by Elsevier B.V.

Overcoming confirmation bias in causal attribution: a case study of antibiotic resistance risks.

PubMed

Cox, Louis Anthony Tony; Popken, Douglas A

2008-10-01

When they do not use formal quantitative risk assessment methods, many scientists (like other people) make mistakes and exhibit biases in reasoning about causation, if-then relations, and evidence. Decision-related conclusions or causal explanations are reached prematurely based on narrative plausibility rather than adequate factual evidence. Then, confirming evidence is sought and emphasized, but disconfirming evidence is ignored or discounted. This tendency has serious implications for health-related public policy discussions and decisions. We provide examples occurring in antimicrobial health risk assessments, including a case study of a recently reported positive relation between virginiamycin (VM) use in poultry and risk of resistance to VM-like (streptogramin) antibiotics in humans. This finding has been used to argue that poultry consumption causes increased resistance risks, that serious health impacts may result, and therefore use of VM in poultry should be restricted. However, the original study compared healthy vegetarians to hospitalized poultry consumers. Our examination of the same data using conditional independence tests for potential causality reveals that poultry consumption acted as a surrogate for hospitalization in this study. After accounting for current hospitalization status, no evidence remains supporting a causal relationship between poultry consumption and increased streptogramin resistance. This example emphasizes both the importance and the practical possibility of analyzing and presenting quantitative risk information using data analysis techniques (such as Bayesian model averaging (BMA) and conditional independence tests) that are as free as possible from potential selection, confirmation, and modeling biases.

Frequency and Pathological Phenotype of Bovine Astrovirus CH13/NeuroS1 Infection in Neurologically-Diseased Cattle: Towards Assessment of Causality.

PubMed

Selimovic-Hamza, Senija; Boujon, Céline L; Hilbe, Monika; Oevermann, Anna; Seuberlich, Torsten

2017-01-18

Next-generation sequencing (NGS) has opened up the possibility of detecting new viruses in unresolved diseases. Recently, astrovirus brain infections have been identified in neurologically diseased humans and animals by NGS, among them bovine astrovirus (BoAstV) CH13/NeuroS1, which has been found in brain tissues of cattle with non-suppurative encephalitis. Only a few studies are available on neurotropic astroviruses and a causal relationship between BoAstV CH13/NeuroS1 infections and neurological disease has been postulated, but remains unproven. Aiming at making a step forward towards assessing the causality, we collected brain samples of 97 cases of cattle diagnosed with unresolved non-suppurative encephalitis, and analyzed them by in situ hybridization and immunohistochemistry, to determine the frequency and neuropathological distribution of the BoAstV CH13/NeuroS1 and its topographical correlation to the pathology. We detected BoAstV CH13/NeuroS1 RNA or proteins in neurons throughout all parts of the central nervous system (CNS) in 34% of all cases, but none were detected in cattle of the control group. In general, brain lesions had a high correlation with the presence of the virus. These findings show that a substantial proportion of cattle with non-suppurative encephalitis are infected with BoAstV CH13/NeuroS1 and further substantiate the causal relationship between neurological disease and astrovirus infections.

Frequency and Pathological Phenotype of Bovine Astrovirus CH13/NeuroS1 Infection in Neurologically-Diseased Cattle: Towards Assessment of Causality

PubMed Central

Selimovic-Hamza, Senija; Boujon, Céline L.; Hilbe, Monika; Oevermann, Anna; Seuberlich, Torsten

2017-01-01

Next-generation sequencing (NGS) has opened up the possibility of detecting new viruses in unresolved diseases. Recently, astrovirus brain infections have been identified in neurologically diseased humans and animals by NGS, among them bovine astrovirus (BoAstV) CH13/NeuroS1, which has been found in brain tissues of cattle with non-suppurative encephalitis. Only a few studies are available on neurotropic astroviruses and a causal relationship between BoAstV CH13/NeuroS1 infections and neurological disease has been postulated, but remains unproven. Aiming at making a step forward towards assessing the causality, we collected brain samples of 97 cases of cattle diagnosed with unresolved non-suppurative encephalitis, and analyzed them by in situ hybridization and immunohistochemistry, to determine the frequency and neuropathological distribution of the BoAstV CH13/NeuroS1 and its topographical correlation to the pathology. We detected BoAstV CH13/NeuroS1 RNA or proteins in neurons throughout all parts of the central nervous system (CNS) in 34% of all cases, but none were detected in cattle of the control group. In general, brain lesions had a high correlation with the presence of the virus. These findings show that a substantial proportion of cattle with non-suppurative encephalitis are infected with BoAstV CH13/NeuroS1 and further substantiate the causal relationship between neurological disease and astrovirus infections. PMID:28106800

Assessing the use of cognitive heuristic representativeness in clinical reasoning.

PubMed

Payne, Velma L; Crowley, Rebecca S; Crowley, Rebecca

2008-11-06

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors.

Assessing Use of Cognitive Heuristic Representativeness in Clinical Reasoning

PubMed Central

Payne, Velma L.; Crowley, Rebecca S.

2008-01-01

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors. PMID:18999140

Vector Autoregressive Models and Granger Causality in Time Series Analysis in Nursing Research: Dynamic Changes Among Vital Signs Prior to Cardiorespiratory Instability Events as an Example.

PubMed

Bose, Eliezer; Hravnak, Marilyn; Sereika, Susan M

Patients undergoing continuous vital sign monitoring (heart rate [HR], respiratory rate [RR], pulse oximetry [SpO2]) in real time display interrelated vital sign changes during situations of physiological stress. Patterns in this physiological cross-talk could portend impending cardiorespiratory instability (CRI). Vector autoregressive (VAR) modeling with Granger causality tests is one of the most flexible ways to elucidate underlying causal mechanisms in time series data. The purpose of this article is to illustrate the development of patient-specific VAR models using vital sign time series data in a sample of acutely ill, monitored, step-down unit patients and determine their Granger causal dynamics prior to onset of an incident CRI. CRI was defined as vital signs beyond stipulated normality thresholds (HR = 40-140/minute, RR = 8-36/minute, SpO2 < 85%) and persisting for 3 minutes within a 5-minute moving window (60% of the duration of the window). A 6-hour time segment prior to onset of first CRI was chosen for time series modeling in 20 patients using a six-step procedure: (a) the uniform time series for each vital sign was assessed for stationarity, (b) appropriate lag was determined using a lag-length selection criteria, (c) the VAR model was constructed, (d) residual autocorrelation was assessed with the Lagrange Multiplier test, (e) stability of the VAR system was checked, and (f) Granger causality was evaluated in the final stable model. The primary cause of incident CRI was low SpO2 (60% of cases), followed by out-of-range RR (30%) and HR (10%). Granger causality testing revealed that change in RR caused change in HR (21%; i.e., RR changed before HR changed) more often than change in HR causing change in RR (15%). Similarly, changes in RR caused changes in SpO2 (15%) more often than changes in SpO2 caused changes in RR (9%). For HR and SpO2, changes in HR causing changes in SpO2 and changes in SpO2 causing changes in HR occurred with equal frequency (18%). Within this sample of acutely ill patients who experienced a CRI event, VAR modeling indicated that RR changes tend to occur before changes in HR and SpO2. These findings suggest that contextual assessment of RR changes as the earliest sign of CRI is warranted. Use of VAR modeling may be helpful in other nursing research applications based on time series data.

Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience.

PubMed

Matiasz, Nicholas J; Wood, Justin; Wang, Wei; Silva, Alcino J; Hsu, William

2017-01-01

Computers help neuroscientists to analyze experimental results by automating the application of statistics; however, computer-aided experiment planning is far less common, due to a lack of similar quantitative formalisms for systematically assessing evidence and uncertainty. While ontologies and other Semantic Web resources help neuroscientists to assimilate required domain knowledge, experiment planning requires not only ontological but also epistemological (e.g., methodological) information regarding how knowledge was obtained. Here, we outline how epistemological principles and graphical representations of causality can be used to formalize experiment planning toward causal discovery. We outline two complementary approaches to experiment planning: one that quantifies evidence per the principles of convergence and consistency, and another that quantifies uncertainty using logical representations of constraints on causal structure. These approaches operationalize experiment planning as the search for an experiment that either maximizes evidence or minimizes uncertainty. Despite work in laboratory automation, humans must still plan experiments and will likely continue to do so for some time. There is thus a great need for experiment-planning frameworks that are not only amenable to machine computation but also useful as aids in human reasoning.

Causal cognition in a non-human primate: field playback experiments with Diana monkeys.

PubMed

Zuberbühler, K

2000-09-14

Crested guinea fowls (Guttera pucherani) living in West African rainforests give alarm calls to leopards (Panthera pardus) and sometimes humans (Homo sapiens), two main predators of sympatric Diana monkeys (Cercopithecus diana). When hearing these guinea fowl alarm calls, Diana monkeys respond as if a leopard were present, suggesting that by default the monkeys associate guinea fowl alarm calls with the presence of a leopard. To assess the monkeys' level of causal understanding, I primed monkeys to the presence of either a leopard or a human, before exposing them to playbacks of guinea fowl alarm calls. There were significant differences in the way leopard-primed groups and human-primed groups responded to guinea fowl alarm calls, suggesting that the monkeys' response was not directly driven by the alarm calls themselves but by the calls' underlying cause, i.e. the predator most likely to have caused the calls. Results are discussed with respect to three possible cognitive mechanisms - associative learning, specialized learning programs, and causal reasoning - that could have led to causal knowledge in Diana monkeys.

Applying survival analysis to a large-scale forest inventory for assessment of tree mortality in Minnesota

Treesearch

C.W. Woodall; P.L. Grambsch; W. Thomas

2005-01-01

Tree mortality has traditionally been assessed in forest inventories through summaries of mortality by location, species, and causal agents. Although these methods have historically constituted the majority of tree mortality summarizations, they have had limited use in assessing mortality trends and dynamics. This study proposed a novel method of applying survival...

What matters most: quantifying an epidemiology of consequence

PubMed Central

Keyes, Katherine; Galea, Sandro

2015-01-01

Risk factor epidemiology has contributed to substantial public health success. In this essay, we argue, however, that the focus on risk factor epidemiology has led epidemiology to ever increasing focus on the estimation of precise causal effects of exposures on an outcome at the expense of engagement with the broader causal architecture that produces population health. To conduct an epidemiology of consequence, a systematic effort is needed to engage our science in a critical reflection both about how well and under what conditions or assumptions we can assess causal effects and also on what will truly matter most for changing population health. Such an approach changes the priorities and values of the discipline and requires reorientation of how we structure the questions we ask and the methods we use, as well as how we teach epidemiology to our emerging scholars. PMID:25749559

The Causal Effects of Father Absence

PubMed Central

McLanahan, Sara; Tach, Laura; Schneider, Daniel

2014-01-01

The literature on father absence is frequently criticized for its use of cross-sectional data and methods that fail to take account of possible omitted variable bias and reverse causality. We review studies that have responded to this critique by employing a variety of innovative research designs to identify the causal effect of father absence, including studies using lagged dependent variable models, growth curve models, individual fixed effects models, sibling fixed effects models, natural experiments, and propensity score matching models. Our assessment is that studies using more rigorous designs continue to find negative effects of father absence on offspring well-being, although the magnitude of these effects is smaller than what is found using traditional cross-sectional designs. The evidence is strongest and most consistent for outcomes such as high school graduation, children’s social-emotional adjustment, and adult mental health. PMID:24489431

The complex spine: the multidimensional system of causal pathways for low-back disorders.

PubMed

Marras, William S

2012-12-01

The aim of this study was to examine the logic behind the knowledge of low-back problem causal pathways. Low-back pain and low-back disorders (LBDs) continue to represent the major musculoskeletal risk problem in the workplace,with the prevalence and costs of such disorders increasing over time. In recent years, there has been much criticism of the ability of ergonomics methods to control the risk of LBDs. Logical assessment of the systems logic associated with our understanding and prevention of LBDs. Current spine loading as well as spine tolerance research efforts are bringing the field to the point where there is a better systems understanding of the inextricable link between the musculoskeletal system and the cognitive system. Loading is influenced by both the physical environment factors as well as mental demands, whereas tolerances are defined by both physical tissue tolerance and biochemically based tissue sensitivities to pain. However, the logic used in many low-back risk assessment tools may be overly simplistic, given what is understood about causal pathways. Current tools typically assess only load or position in a very cursory manner. Efforts must work toward satisfying both the physical environment and the cognitive environment for the worker if one is to reliably lower the risk of low-back problems. This systems representation of LBD development may serve as a guide to identify gaps in our understanding of LBDs.

Causality in cancer epidemiology.

PubMed

Lagiou, Pagona; Adami, Hans-Olov; Trichopoulos, Dimitrios

2005-01-01

In this review, issues of causality in epidemiologic research with emphasis on the aetiology of human cancer are considered. Principles of assessing causation in epidemiological studies of cancer are distinguished into those concerning an individual study, several studies and a particular person. Strengths and weaknesses of various approaches of documenting carcinogenicity in humans are examined and lists of major established causes of human cancer are presented. The review concludes with estimates of mortality from cancer around the world that can be attributed to specific factors under the light of the current scientific knowledge.

Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic.

PubMed

Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R

2016-12-01

: MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We demonstrate our proposed approach for a two-sample summary data MR analysis to estimate the causal effect of low-density lipoprotein on heart disease risk. A high value of IGX2 close to 1 indicates that dilution does not materially affect the standard MR-Egger analyses for these data. : Care must be taken to assess the NOME assumption via the IGX2 statistic before implementing standard MR-Egger regression in the two-sample summary data context. If IGX2 is sufficiently low (less than 90%), inferences from the method should be interpreted with caution and adjustment methods considered. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

Phone-based safety monitoring of the first year of baclofen treatment for alcohol use disorder: the BACLOPHONE cohort study protocol.

PubMed

Rolland, Benjamin; Auffret, Marine; Labreuche, Julien; Lapeyre-Mestre, Maryse; Dib, Malek; Kemkem, Aomar; Grit, Isabelle; Drelon, Marie; Duhamel, Alain; Cabe, Nicolas; Vabret, François; Guillin, Olivier; Baguet, Alexandre; Masquelier, Céline; Dervaux, Alain; Deheul, Sylvie; Bordet, Régis; Carton, Louise; Cottencin, Olivier; Jardri, Renaud; Gautier, Sophie

2017-02-01

In France, baclofen is frequently used off-label for alcohol use disorder (AUD). Baclofen has been associated with diverse adverse events (AEs), but the causality of these AEs has never been properly assessed. BACLOPHONE is a prospective multicenter cohort study conducted in the Hauts-de-France and Normandie French regions. BACLOPHONE consists of the phone-based monitoring of 792 patients during their first year of baclofen treatment for AUD. Two initial phone interviews assess the medical history, current medications, and substance use as well as complete the alcohol use identification test (AUDIT) and severity of alcohol dependence questionnaire (SADQ). Daily alcohol use and baclofen doses are noted throughout the follow-up. For every reported AE, additional phone interviews determine the seriousness of the AE, the causality of baclofen using validated causality algorithms, and the final outcome. The main objective of the study is to determine the rate of patients who stop baclofen due to an AE during the first year of treatment. BACLOPHONE will provide important safety data on baclofen as a complement to the forthcoming efficacy data of randomized clinical trials.

Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data

PubMed Central

Havlicek, Martin; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.

2015-01-01

Increasing interest in understanding dynamic interactions of brain neural networks leads to formulation of sophisticated connectivity analysis methods. Recent studies have applied Granger causality based on standard multivariate autoregressive (MAR) modeling to assess the brain connectivity. Nevertheless, one important flaw of this commonly proposed method is that it requires the analyzed time series to be stationary, whereas such assumption is mostly violated due to the weakly nonstationary nature of functional magnetic resonance imaging (fMRI) time series. Therefore, we propose an approach to dynamic Granger causality in the frequency domain for evaluating functional network connectivity in fMRI data. The effectiveness and robustness of the dynamic approach was significantly improved by combining a forward and backward Kalman filter that improved estimates compared to the standard time-invariant MAR modeling. In our method, the functional networks were first detected by independent component analysis (ICA), a computational method for separating a multivariate signal into maximally independent components. Then the measure of Granger causality was evaluated using generalized partial directed coherence that is suitable for bivariate as well as multivariate data. Moreover, this metric provides identification of causal relation in frequency domain, which allows one to distinguish the frequency components related to the experimental paradigm. The procedure of evaluating Granger causality via dynamic MAR was demonstrated on simulated time series as well as on two sets of group fMRI data collected during an auditory sensorimotor (SM) or auditory oddball discrimination (AOD) tasks. Finally, a comparison with the results obtained from a standard time-invariant MAR model was provided. PMID:20561919

Toxicology and Epidemiology: Improving the Science with a Framework for Combining Toxicological and Epidemiological Evidence to Establish Causal Inference

PubMed Central

Adami, Hans-Olov; Berry, Sir Colin L.; Breckenridge, Charles B.; Smith, Lewis L.; Swenberg, James A.; Trichopoulos, Dimitrios; Weiss, Noel S.; Pastoor, Timothy P.

2011-01-01

Historically, toxicology has played a significant role in verifying conclusions drawn on the basis of epidemiological findings. Agents that were suggested to have a role in human diseases have been tested in animals to firmly establish a causative link. Bacterial pathogens are perhaps the oldest examples, and tobacco smoke and lung cancer and asbestos and mesothelioma provide two more recent examples. With the advent of toxicity testing guidelines and protocols, toxicology took on a role that was intended to anticipate or predict potential adverse effects in humans, and epidemiology, in many cases, served a role in verifying or negating these toxicological predictions. The coupled role of epidemiology and toxicology in discerning human health effects by environmental agents is obvious, but there is currently no systematic and transparent way to bring the data and analysis of the two disciplines together in a way that provides a unified view on an adverse causal relationship between an agent and a disease. In working to advance the interaction between the fields of toxicology and epidemiology, we propose here a five-step “Epid-Tox” process that would focus on: (1) collection of all relevant studies, (2) assessment of their quality, (3) evaluation of the weight of evidence, (4) assignment of a scalable conclusion, and (5) placement on a causal relationship grid. The causal relationship grid provides a clear view of how epidemiological and toxicological data intersect, permits straightforward conclusions with regard to a causal relationship between agent and effect, and can show how additional data can influence conclusions of causality. PMID:21561883

Do causal concentration-response functions exist? A critical review of associational and causal relations between fine particulate matter and mortality.

PubMed

Cox, Louis Anthony Tony

2017-08-01

Concentration-response (C-R) functions relating concentrations of pollutants in ambient air to mortality risks or other adverse health effects provide the basis for many public health risk assessments, benefits estimates for clean air regulations, and recommendations for revisions to existing air quality standards. The assumption that C-R functions relating levels of exposure and levels of response estimated from historical data usefully predict how future changes in concentrations would change risks has seldom been carefully tested. This paper critically reviews literature on C-R functions for fine particulate matter (PM2.5) and mortality risks. We find that most of them describe historical associations rather than valid causal models for predicting effects of interventions that change concentrations. The few papers that explicitly attempt to model causality rely on unverified modeling assumptions, casting doubt on their predictions about effects of interventions. A large literature on modern causal inference algorithms for observational data has been little used in C-R modeling. Applying these methods to publicly available data from Boston and the South Coast Air Quality Management District around Los Angeles shows that C-R functions estimated for one do not hold for the other. Changes in month-specific PM2.5 concentrations from one year to the next do not help to predict corresponding changes in average elderly mortality rates in either location. Thus, the assumption that estimated C-R relations predict effects of pollution-reducing interventions may not be true. Better causal modeling methods are needed to better predict how reducing air pollution would affect public health.

Children's Understanding of Emotions and Interpersonal Causality.

ERIC Educational Resources Information Center

Hamsher, J. Herbert

The specific purpose of the research discussed was to develop an instrument which would permit assessment of individual and developmental differences in the acquisition of abilities to understand and utilize emotional and psychological facets of interpersonal behavior. Emotional insight was assessed in 81 male and female children between the ages…

The Casual Effects of Emotion on Couples' Cognition and Behavior

ERIC Educational Resources Information Center

Tashiro, Ty; Frazier, Patricia

2007-01-01

The authors conducted 2 translational studies that assessed the causal effects of emotion on maladaptive cognitions and behaviors in couples. Specifically, the authors examined whether negative emotions increased and positive emotions decreased partner attributions and demand-withdraw behaviors. Study 1 (N=164) used video clips to assess the…

The AOP framework and causality: Meeting chemical risk assessment challenges in the 21st century

EPA Science Inventory

Chemical safety assessments are expanding from a focus on a few chemicals (or chemical mixtures) to the broader “universe” of thousands, if not hundreds of thousands of substances that potentially could impact humans or the environment. This is exemplified in ...

Has reducing fine particulate matter and ozone caused reduced mortality rates in the United States?

PubMed

Cox, Louis Anthony Tony; Popken, Douglas A

2015-03-01

Between 2000 and 2010, air pollutant levels in counties throughout the United States changed significantly, with fine particulate matter (PM2.5) declining over 30% in some counties and ozone (O3) exhibiting large variations from year to year. This history provides an opportunity to compare county-level changes in average annual ambient pollutant levels to corresponding changes in all-cause (AC) and cardiovascular disease (CVD) mortality rates over the course of a decade. Past studies have demonstrated associations and subsequently either interpreted associations causally or relied on subjective judgments to infer causation. This article applies more quantitative methods to assess causality. This article examines data from these "natural experiments" of changing pollutant levels for 483 counties in the 15 most populated US states using quantitative methods for causal hypothesis testing, such as conditional independence and Granger causality tests. We assessed whether changes in historical pollution levels helped to predict and explain changes in CVD and AC mortality rates. A causal relation between pollutant concentrations and AC or CVD mortality rates cannot be inferred from these historical data, although a statistical association between them is well supported. There were no significant positive associations between changes in PM2.5 or O3 levels and corresponding changes in disease mortality rates between 2000 and 2010, nor for shorter time intervals of 1 to 3 years. These findings suggest that predicted substantial human longevity benefits resulting from reducing PM2.5 and O3 may not occur or may be smaller than previously estimated. Our results highlight the potential for heterogeneity in air pollution health effects across regions, and the high potential value of accountability research comparing model-based predictions of health benefits from reducing air pollutants to historical records of what actually occurred. Copyright © 2015 Elsevier Inc. All rights reserved.

Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder.

PubMed

Wittenborn, A K; Rahmandad, H; Rick, J; Hosseinichimeh, N

2016-02-01

Depression is a complex public health problem with considerable variation in treatment response. The systemic complexity of depression, or the feedback processes among diverse drivers of the disorder, contribute to the persistence of depression. This paper extends prior attempts to understand the complex causal feedback mechanisms that underlie depression by presenting the first broad boundary causal loop diagram of depression dynamics. We applied qualitative system dynamics methods to map the broad feedback mechanisms of depression. We used a structured approach to identify candidate causal mechanisms of depression in the literature. We assessed the strength of empirical support for each mechanism and prioritized those with support from validation studies. Through an iterative process, we synthesized the empirical literature and created a conceptual model of major depressive disorder. The literature review and synthesis resulted in the development of the first causal loop diagram of reinforcing feedback processes of depression. It proposes candidate drivers of illness, or inertial factors, and their temporal functioning, as well as the interactions among drivers of depression. The final causal loop diagram defines 13 key reinforcing feedback loops that involve nine candidate drivers of depression. Future research is needed to expand upon this initial model of depression dynamics. Quantitative extensions may result in a better understanding of the systemic syndrome of depression and contribute to personalized methods of evaluation, prevention and intervention.

Global drivers of the stratospheric polar vortex via nonlinear causal discovery

NASA Astrophysics Data System (ADS)

Kretschmer, M.; Runge, J.; Coumou, D.

2016-12-01

The stratospheric polar vortex plays a major role in the Northern Hemisphere midlatitudes, especially in driving extreme weather conditions. Many different global drivers, from Arctic sea ice to tropical climate patterns, are hypothesized to influence its stability, including linear and nonlinear mechanisms. Here a novel causal discovery approach, extending previous work [1], that is adapted to the particular challenges posed by such a high-dimensional dataset comprised of multiple, possibly nonlinearly coupled time series is demonstrated. While links in the reconstructed network can be called causal only with respect to the set of analyzed variables, the absence of causal links allows to assess where physical mechanisms are unlikely.The present work confirms recent results obtained with a similar, but linear, approach [2], regarding the impact of Barents and Kara sea ice concentrations, and extends the analysis also to tropical drivers to cover more proposed mechanisms. [1] Jakob Runge, Vladimir Petoukhov, and Jürgen Kurths, 2014: Quantifying the Strength and Delay of Climatic Interactions: The Ambiguities of Cross Correlation and a Novel Measure Based on Graphical Models. J. Climate 27, 720-739, doi: 10.1175/JCLI-D-13-00159.1.[2] Marlene Kretschmer, Dim Coumou, Jonathan F. Donges, and Jakob Runge, 2016: Using Causal Effect Networks to Analyze Different Arctic Drivers of Midlatitude Winter Circulation. J. Climate 29, 4069-4081, doi: 10.1175/JCLI-D-15-0654.1.

Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder

PubMed Central

Wittenborn, A. K.; Rahmandad, H.; Rick, J.; Hosseinichimeh, N.

2016-01-01

Background Depression is a complex public health problem with considerable variation in treatment response. The systemic complexity of depression, or the feedback processes among diverse drivers of the disorder, contribute to the persistence of depression. This paper extends prior attempts to understand the complex causal feedback mechanisms that underlie depression by presenting the first broad boundary causal loop diagram of depression dynamics. Method We applied qualitative system dynamics methods to map the broad feedback mechanisms of depression. We used a structured approach to identify candidate causal mechanisms of depression in the literature. We assessed the strength of empirical support for each mechanism and prioritized those with support from validation studies. Through an iterative process, we synthesized the empirical literature and created a conceptual model of major depressive disorder. Results The literature review and synthesis resulted in the development of the first causal loop diagram of reinforcing feedback processes of depression. It proposes candidate drivers of illness, or inertial factors, and their temporal functioning, as well as the interactions among drivers of depression. The final causal loop diagram defines 13 key reinforcing feedback loops that involve nine candidate drivers of depression. Conclusions Future research is needed to expand upon this initial model of depression dynamics. Quantitative extensions may result in a better understanding of the systemic syndrome of depression and contribute to personalized methods of evaluation, prevention and intervention. PMID:26621339

The Mental Health Outcomes of Drought: A Systematic Review and Causal Process Diagram

PubMed Central

Vins, Holly; Bell, Jesse; Saha, Shubhayu; Hess, Jeremy J.

2015-01-01

Little is understood about the long term, indirect health consequences of drought (a period of abnormally dry weather). In particular, the implications of drought for mental health via pathways such as loss of livelihood, diminished social support, and rupture of place bonds have not been extensively studied, leaving a knowledge gap for practitioners and researchers alike. A systematic review of literature was performed to examine the mental health effects of drought. The systematic review results were synthesized to create a causal process diagram that illustrates the pathways linking drought effects to mental health outcomes. Eighty-two articles using a variety of methods in different contexts were gathered from the systematic review. The pathways in the causal process diagram with greatest support in the literature are those focusing on the economic and migratory effects of drought. The diagram highlights the complexity of the relationships between drought and mental health, including the multiple ways that factors can interact and lead to various outcomes. The systematic review and resulting causal process diagram can be used in both practice and theory, including prevention planning, public health programming, vulnerability and risk assessment, and research question guidance. The use of a causal process diagram provides a much needed avenue for integrating the findings of diverse research to further the understanding of the mental health implications of drought. PMID:26506367

DNA Methylation and BMI: Investigating Identified Methylation Sites at HIF3A in a Causal Framework

PubMed Central

Richmond, Rebecca C.; Ward, Mary E.; Fraser, Abigail; Lyttleton, Oliver; McArdle, Wendy L.; Ring, Susan M.; Gaunt, Tom R.; Lawlor, Debbie A.; Davey Smith, George; Relton, Caroline L.

2016-01-01

Multiple differentially methylated sites and regions associated with adiposity have now been identified in large-scale cross-sectional studies. We tested for replication of associations between previously identified CpG sites at HIF3A and adiposity in ∼1,000 mother-offspring pairs from the Avon Longitudinal Study of Parents and Children (ALSPAC). Availability of methylation and adiposity measures at multiple time points, as well as genetic data, allowed us to assess the temporal associations between adiposity and methylation and to make inferences regarding causality and directionality. Overall, our results were discordant with those expected if HIF3A methylation has a causal effect on BMI and provided more evidence for causality in the reverse direction (i.e., an effect of BMI on HIF3A methylation). These results are based on robust evidence from longitudinal analyses and were also partially supported by Mendelian randomization analysis, although this latter analysis was underpowered to detect a causal effect of BMI on HIF3A methylation. Our results also highlight an apparent long-lasting intergenerational influence of maternal BMI on offspring methylation at this locus, which may confound associations between own adiposity and HIF3A methylation. Further work is required to replicate and uncover the mechanisms underlying the direct and intergenerational effect of adiposity on DNA methylation. PMID:26861784

D.B.H. and Survival Analysis: A New Methodology for Assessing Forest Inventory Mortality

Treesearch

Christopher W. Woodall; Patricia L. Grambsch; William Thomas

2005-01-01

Tree mortality has typically been assessed in Forest Inventory and Analysis (FIA) studies through summaries of mortality by location, species, and causal agents. Although these methods have historically been used for most of FIA's tree mortality analyses, they are inadequate for robust assessment of mortality trends and dynamics. To offer a new method of analyzing...

A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors.

PubMed

Ren, J; Jenkinson, I; Wang, J; Xu, D L; Yang, J B

2008-01-01

Focusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships. The methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason's "Swiss cheese" model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Trigger events level, Incidents level, Accidents level, and Consequences level. To analyze and model a specified offshore installation safety, a BN model was established following the guideline of the proposed five-level framework. A range of events was specified, and the related prior and conditional probabilities regarding the BN model were assigned based on the inherent characteristics of each event. This paper shows that Reason's "Swiss cheese" model and BN can be jointly used in offshore safety assessment. On the one hand, the five-level conceptual model is enhanced by BNs that are capable of providing graphical demonstration of inter-relationships as well as calculating numerical values of occurrence likelihood for each failure event. Bayesian inference mechanism also makes it possible to monitor how a safety situation changes when information flow travel forwards and backwards within the networks. On the other hand, BN modeling relies heavily on experts' personal experiences and is therefore highly domain specific. "Swiss cheese" model is such a theoretic framework that it is based on solid behavioral theory and therefore can be used to provide industry with a roadmap for BN modeling and implications. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorized vessels caused by human and organizational factors (HOFs) during operations is used to illustrate an industrial application of the proposed methodology.

Telling the Tale and Living Well: Adolescent Narrative Identity, Personality Traits, and Well-Being Across Cultures.

PubMed

Reese, Elaine; Myftari, Ella; McAnally, Helena M; Chen, Yan; Neha, Tia; Wang, Qi; Jack, Fiona; Robertson, Sarah-Jane

2017-03-01

This study explored links between narrative identity, personality traits, and well-being for 263 adolescents (age 12-21) from three New Zealand cultures: Māori, Chinese, and European. Turning-point narratives were assessed for autobiographical reasoning (causal coherence), local thematic coherence, emotional expressivity, and topic. Across cultures, older adolescents with higher causal coherence reported better well-being. Younger adolescents with higher causal coherence instead reported poorer well-being. Personal development topics were positively linked to well-being for New Zealand European adolescents only, and thematic coherence was positively linked to well-being for Māori adolescents only. Negative expressivity, neuroticism, conscientiousness, and openness were also linked to well-being. Implications of these cultural similarities and differences are considered for theories of narrative identity, personality, and adolescent well-being. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

What matters most: quantifying an epidemiology of consequence.

PubMed

Keyes, Katherine; Galea, Sandro

2015-05-01

Risk factor epidemiology has contributed to substantial public health success. In this essay, we argue, however, that the focus on risk factor epidemiology has led epidemiology to ever increasing focus on the estimation of precise causal effects of exposures on an outcome at the expense of engagement with the broader causal architecture that produces population health. To conduct an epidemiology of consequence, a systematic effort is needed to engage our science in a critical reflection both about how well and under what conditions or assumptions we can assess causal effects and also on what will truly matter most for changing population health. Such an approach changes the priorities and values of the discipline and requires reorientation of how we structure the questions we ask and the methods we use, as well as how we teach epidemiology to our emerging scholars. Copyright © 2015 Elsevier Inc. All rights reserved.

Causal assessment of occupational pushing or pulling and low back pain: results of a systematic review.

PubMed

Roffey, Darren M; Wai, Eugene K; Bishop, Paul; Kwon, Brian K; Dagenais, Simon

2010-06-01

Low back pain (LBP) is a prevalent and expensive musculoskeletal condition that predominantly occurs in working-age individuals of industrialized nations. Although numerous occupational physical activities have been implicated in its etiology, determining the causation of occupational LBP still remains a challenge. To conduct a systematic review evaluating the causal relationship between occupational pushing or pulling and LBP. Systematic review of the literature. Studies reporting an association between occupational pushing or pulling and LBP. Numerical association between exposure to pushing or pulling and the presence of LBP. A systematic review was performed to identify, evaluate, and summarize the literature related to establishing a causal relationship, according to Bradford-Hill criteria for causation for occupational pushing or pulling and LBP. A search was conducted using Medline, EMBASE, CINAHL, Cochrane Library, and OSH-ROM, gray literature, hand-searching occupational health journals, reference lists of included studies, and expert knowledge. Methodological quality was assessed using a modified Newcastle-Ottawa Scale. This search yielded 2,766 citations. Thirteen studies met the inclusion criteria. Eight were high-quality studies and five were low-quality studies. There was conflicting evidence with one high-quality study demonstrating a positive association between occupational pushing or pulling and LBP and five studies showing no relationship. One study reported a nonstatistically significant dose-response trend, four studies discussed temporality of which one indicated a positive finding, two studies discussed the biological plausibility of a causal link between occupational pushing or pulling and LBP, and no evidence was uncovered to assess the experiment criterion. A qualitative summary of existing studies was not able to find any high-quality studies that fully satisfied any of the Bradford-Hill causation criteria for occupational pushing or pulling and LBP. Based on the evidence reviewed, it is unlikely that occupational pushing or pulling is independently causative of LBP in the populations of workers studied. Copyright 2010 Elsevier Inc. All rights reserved.

Etiologic effects and optimal intakes of foods and nutrients for risk of cardiovascular diseases and diabetes: Systematic reviews and meta-analyses from the Nutrition and Chronic Diseases Expert Group (NutriCoDE)

PubMed Central

Peñalvo, Jose L.; Khatibzadeh, Shahab; Singh, Gitanjali M.; Rao, Mayuree; Fahimi, Saman; Powles, John; Mozaffarian, Dariush

2017-01-01

Background Dietary habits are major contributors to coronary heart disease, stroke, and diabetes. However, comprehensive evaluation of etiologic effects of dietary factors on cardiometabolic outcomes, their quantitative effects, and corresponding optimal intakes are not well-established. Objective To systematically review the evidence for effects of dietary factors on cardiometabolic diseases, including comprehensively assess evidence for causality; estimate magnitudes of etiologic effects; evaluate heterogeneity and potential for bias in these etiologic effects; and determine optimal population intake levels. Methods We utilized Bradford-Hill criteria to assess probable or convincing evidence for causal effects of multiple diet-cardiometabolic disease relationships. Etiologic effects were quantified from published or de novo meta-analyses of prospective studies or randomized clinical trials, incorporating standardized units, dose-response estimates, and heterogeneity by age and other characteristics. Potential for bias was assessed in validity analyses. Optimal intakes were determined by levels associated with lowest disease risk. Results We identified 10 foods and 7 nutrients with evidence for causal cardiometabolic effects, including protective effects of fruits, vegetables, beans/legumes, nuts/seeds, whole grains, fish, yogurt, fiber, seafood omega-3s, polyunsaturated fats, and potassium; and harms of unprocessed red meats, processed meats, sugar-sweetened beverages, glycemic load, trans-fats, and sodium. Proportional etiologic effects declined with age, but did not generally vary by sex. Established optimal population intakes were generally consistent with observed national intakes and major dietary guidelines. In validity analyses, the identified effects of individual dietary components were similar to quantified effects of dietary patterns on cardiovascular risk factors and hard endpoints. Conclusions These novel findings provide a comprehensive summary of causal evidence, quantitative etiologic effects, heterogeneity, and optimal intakes of major dietary factors for cardiometabolic diseases, informing disease impact estimation and policy planning and priorities. PMID:28448503

Drug-disease association and drug-repositioning predictions in complex diseases using causal inference-probabilistic matrix factorization.

PubMed

Yang, Jihong; Li, Zheng; Fan, Xiaohui; Cheng, Yiyu

2014-09-22

The high incidence of complex diseases has become a worldwide threat to human health. Multiple targets and pathways are perturbed during the pathological process of complex diseases. Systematic investigation of complex relationship between drugs and diseases is necessary for new association discovery and drug repurposing. For this purpose, three causal networks were constructed herein for cardiovascular diseases, diabetes mellitus, and neoplasms, respectively. A causal inference-probabilistic matrix factorization (CI-PMF) approach was proposed to predict and classify drug-disease associations, and further used for drug-repositioning predictions. First, multilevel systematic relations between drugs and diseases were integrated from heterogeneous databases to construct causal networks connecting drug-target-pathway-gene-disease. Then, the association scores between drugs and diseases were assessed by evaluating a drug's effects on multiple targets and pathways. Furthermore, PMF models were learned based on known interactions, and associations were then classified into three types by trained models. Finally, therapeutic associations were predicted based upon the ranking of association scores and predicted association types. In terms of drug-disease association prediction, modified causal inference included in CI-PMF outperformed existing causal inference with a higher AUC (area under receiver operating characteristic curve) score and greater precision. Moreover, CI-PMF performed better than single modified causal inference in predicting therapeutic drug-disease associations. In the top 30% of predicted associations, 58.6% (136/232), 50.8% (31/61), and 39.8% (140/352) hit known therapeutic associations, while precisions obtained by the latter were only 10.2% (231/2264), 8.8% (36/411), and 9.7% (189/1948). Clinical verifications were further conducted for the top 100 newly predicted therapeutic associations. As a result, 21, 12, and 32 associations have been studied and many treatment effects of drugs on diseases were investigated for cardiovascular diseases, diabetes mellitus, and neoplasms, respectively. Related chains in causal networks were extracted for these 65 clinical-verified associations, and we further illustrated the therapeutic role of etodolac in breast cancer by inferred chains. Overall, CI-PMF is a useful approach for associating drugs with complex diseases and provides potential values for drug repositioning.

Causal interpretation of correlational studies - Analysis of medical news on the website of the official journal for German physicians.

PubMed

Buhse, Susanne; Rahn, Anne Christin; Bock, Merle; Mühlhauser, Ingrid

2018-01-01

Media frequently draws inappropriate causal statements from observational studies. We analyzed the reporting of study results in the Medical News section of the German medical journal Deutsches Ärzteblatt (DÄ). Study design: Retrospective quantitative content analysis of randomly selected news reports and related original journal articles and press releases. A medical news report was selected if headlines comprised at least two linked variables. Two raters independently categorized the headline and text of each news report, conclusions of the abstract and full text of the related journal article, and the press release. The assessment instrument comprised five categories from 'neutral' to 'unconditionally causal'. Outcome measures: degree of matching between 1) news headlines and conclusions of the journal article, 2) headlines and text of news reports, 3) text and conclusions, and 4) headlines and press releases. We analyzed whether news headlines rated as unconditionally causal based on randomized controlled trials (RCTs). One-thousand eighty-seven medical news reports were published between April 2015 and May 2016. The final random sample comprised 176 news reports and 100 related press releases. Degree of matching: 1) 45% (79/176) for news headlines and journal article conclusions, 2) 55% (97/176) for headlines and text, 3) 53% (93/176) for text and conclusions, and 4) 41% (41/100) for headlines and press releases. Exaggerations were found in 45% (80/176) of the headlines compared to the conclusions of the related journal article. Sixty-five of 137 unconditionally causal statements of the news headlines were phrased more weakly in the subsequent news text body. Only 52 of 137 headlines (38%) categorized as unconditionally causal reported RCTs. Reporting of medical news in the DÄ medical journal is misleading. Most headlines that imply causal associations were not based on RCTs. Medical journalists should follow standards of reporting scientific study results.

Problem formulation, metrics, open government, and on-line collaboration

NASA Astrophysics Data System (ADS)

Ziegler, C. R.; Schofield, K.; Young, S.; Shaw, D.

2010-12-01

Problem formulation leading to effective environmental management, including synthesis and application of science by government agencies, may benefit from collaborative on-line environments. This is illustrated by two interconnected projects: 1) literature-based evidence tools that support causal assessment and problem formulation, and 2) development of output, outcome, and sustainability metrics for tracking environmental conditions. Specifically, peer-production mechanisms allow for global contribution to science-based causal evidence databases, and subsequent crowd-sourced development of causal networks supported by that evidence. In turn, science-based causal networks may inform problem formulation and selection of metrics or indicators to track environmental condition (or problem status). Selecting and developing metrics in a collaborative on-line environment may improve stakeholder buy-in, the explicit relevance of metrics to planning, and the ability to approach problem apportionment or accountability, and to define success or sustainability. Challenges include contribution governance, data-sharing incentives, linking on-line interfaces to data service providers, and the intersection of environmental science and social science. Degree of framework access and confidentiality may vary by group and/or individual, but may ultimately be geared at demonstrating connections between science and decision making and supporting a culture of open government, by fostering transparency, public engagement, and collaboration.

THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...

EPA Pesticide Factsheets

CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc

Intolerance of uncertainty, causal uncertainty, causal importance, self-concept clarity and their relations to generalized anxiety disorder.

PubMed

Kusec, Andrea; Tallon, Kathleen; Koerner, Naomi

2016-06-01

Although numerous studies have provided support for the notion that intolerance of uncertainty plays a key role in pathological worry (the hallmark feature of generalized anxiety disorder (GAD)), other uncertainty-related constructs may also have relevance for the understanding of individuals who engage in pathological worry. Three constructs from the social cognition literature, causal uncertainty, causal importance, and self-concept clarity, were examined in the present study to assess the degree to which these explain unique variance in GAD, over and above intolerance of uncertainty. N = 235 participants completed self-report measures of trait worry, GAD symptoms, and uncertainty-relevant constructs. A subgroup was subsequently classified as low in GAD symptoms (n = 69) or high in GAD symptoms (n = 54) based on validated cut scores on measures of trait worry and GAD symptoms. In logistic regressions, only elevated intolerance of uncertainty and lower self-concept clarity emerged as unique correlates of high (vs. low) GAD symptoms. The possible role of self-concept uncertainty in GAD and the utility of integrating social cognition theories and constructs into clinical research on intolerance of uncertainty are discussed.

Assessing the Positive Influence of Music Activities in Community Development Programs

ERIC Educational Resources Information Center

Dillon, Steve

2006-01-01

This article describes a framework for assessing the positive influence of music activities in community development programs. It examines hybrid music, health and rich media approaches to creative case study with the purpose of developing more compelling evidence based advocacy that examines the claims of a causal link. This preliminary study…

Computer-Based Assessment of Complex Problem Solving: Concept, Implementation, and Application

ERIC Educational Resources Information Center

Greiff, Samuel; Wustenberg, Sascha; Holt, Daniel V.; Goldhammer, Frank; Funke, Joachim

2013-01-01

Complex Problem Solving (CPS) skills are essential to successfully deal with environments that change dynamically and involve a large number of interconnected and partially unknown causal influences. The increasing importance of such skills in the 21st century requires appropriate assessment and intervention methods, which in turn rely on adequate…

Small Learning Communities Sense of Belonging to Reach At-Risk Students of Promise

ERIC Educational Resources Information Center

Hackney, Debbie

2011-01-01

The research design is a quantitative causal comparative method. The Florida Comprehensive Assessment Test (FCAT) which measures student scores included assessments in mathematics and reading. The design study called for an examination of how type of small learning community (SLC) or the type non-SLC high school environment affected student…

Assessing Mediation Using Marginal Structural Models in the Presence of Confounding and Moderation

ERIC Educational Resources Information Center

Coffman, Donna L.; Zhong, Wei

2012-01-01

This article presents marginal structural models with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW…

Sedentary behaviour and adiposity in youth: a systematic review of reviews and analysis of causality.

PubMed

Biddle, Stuart J H; García Bengoechea, Enrique; Wiesner, Glen

2017-03-28

Sedentary behaviour (sitting time) has becoming a very popular topic for research and translation since early studies on TV viewing in children in the 1980s. The most studied area for sedentary behaviour health outcomes has been adiposity in young people. However, the literature is replete with inconsistencies. We conducted a systematic review of systematic reviews and meta-analyses to provide a comprehensive analysis of evidence and state-of-the-art synthesis on whether sedentary behaviours are associated with adiposity in young people, and to what extent any association can be considered 'causal'. Searches yielded 29 systematic reviews of over 450 separate papers. We analysed results by observational (cross-sectional and longitudinal) and intervention designs. Small associations were reported for screen time and adiposity from cross-sectional evidence, but associations were less consistent from longitudinal studies. Studies using objective accelerometer measures of sedentary behaviour yielded null associations. Most studies assessed BMI/BMI-z. Interventions to reduce sedentary behaviour produced modest effects for weight status and adiposity. Accounting for effects from sedentary behaviour reduction alone is difficult as many interventions included additional changes in behaviour, such as physical activity and dietary intake. Analysis of causality guided by the classic Bradford Hill criteria concluded that there is no evidence for a causal association between sedentary behaviour and adiposity in youth, although a small dose-response association exists. Associations between sedentary behaviour and adiposity in children and adolescents are small to very small and there is little to no evidence that this association is causal. This remains a complex field with different exposure and outcome measures and research designs. But claims for 'clear' associations between sedentary behaviour and adiposity in youth, and certainly for causality, are premature or misguided.

Splenomegaly - Diagnostic validity, work-up, and underlying causes.

PubMed

Curovic Rotbain, Emelie; Lund Hansen, Dennis; Schaffalitzky de Muckadell, Ove; Wibrand, Flemming; Meldgaard Lund, Allan; Frederiksen, Henrik

2017-01-01

Our aim was to assess the validity of the ICD-10 code for splenomegaly in the Danish National Registry of Patients (DNRP), as well as to investigate which underlying diseases explained the observed splenomegaly. Splenomegaly is a common finding in patients referred to an internal medical department and can be caused by a large spectrum of diseases, including haematological diseases and liver cirrhosis. However, some patients remain without a causal diagnosis, despite extensive medical work-up. We identified 129 patients through the DNRP, that had been given the ICD-10 splenomegaly diagnosis code in 1994-2013 at Odense University Hospital, Denmark, excluding patients with prior splenomegaly, malignant haematological neoplasia or liver cirrhosis. Medical records were reviewed for validity of the splenomegaly diagnosis, diagnostic work-up, and the underlying disease was determined. The positive predictive value (PPV) with 95% confidence interval (CI) was calculated for the splenomegaly diagnosis code. Patients with idiopathic splenomegaly in on-going follow-up were also invited to be investigated for Gaucher disease. The overall PPV was 92% (95% CI: 85, 96). Haematological diseases were the underlying causal diagnosis in 39%; hepatic diseases in 18%, infectious disease in 10% and other diseases in 8%. 25% of patients with splenomegaly remained without a causal diagnosis. Lymphoma was the most common haematological causal diagnosis and liver cirrhosis the most common hepatic causal diagnosis. None of the investigated patients with idiopathic splenomegaly had Gaucher disease. Our findings show that the splenomegaly diagnosis in the DNRP is valid and can be used in registry-based studies. However, because of suspected significant under-coding, it should be considered if supplementary data sources should be used in addition, in order to attain a more representative population. Haematological diseases were the most common cause, however in a large fraction of patients no causal diagnosis was found.

Reflections of a Vaccinologist: Lessons Learned About What We Can Do to Improve Trust in Vaccines and Vaccine Programsa.

PubMed

Halsey, Neal A

2017-03-01

Public trust can be improved by learning from past mistakes, by establishing a standing forum for review of new concerns as they arise, and by maintaining a robust vaccine safety system. Developing standard guidelines for reporting causality assessment in case reports would help educate physicians and prevent future unnecessary concerns based on false assumptions of causal relationships. © The Author 2015. Published by Oxford University Press on behalf of The Journal of the Pediatric Infectious Diseases Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Comparative assessment of crash causal factors and IVHS countermeasures

DOT National Transportation Integrated Search

1994-01-01

The National Highway Traffic Safety Administrations Office of Crash Avoidance Research, in : conjunction with the Research and Special Programs Administrations Volpe National : Transportation Systems Center, has underway a multi-disciplinary pr...

Vector Autoregressive (VAR) Models and Granger Causality in Time Series Analysis in Nursing Research: Dynamic Changes Among Vital Signs Prior to Cardiorespiratory Instability Events as an Example

PubMed Central

Bose, Eliezer; Hravnak, Marilyn; Sereika, Susan M.

2016-01-01

Background Patients undergoing continuous vital sign monitoring (heart rate [HR], respiratory rate [RR], pulse oximetry [SpO2]) in real time display inter-related vital sign changes during situations of physiologic stress. Patterns in this physiological cross-talk could portend impending cardiorespiratory instability (CRI). Vector autoregressive (VAR) modeling with Granger causality tests is one of the most flexible ways to elucidate underlying causal mechanisms in time series data. Purpose The purpose of this article is to illustrate development of patient-specific VAR models using vital sign time series (VSTS) data in a sample of acutely ill, monitored, step-down unit (SDU) patients, and determine their Granger causal dynamics prior to onset of an incident CRI. Approach CRI was defined as vital signs beyond stipulated normality thresholds (HR = 40–140/minute, RR = 8–36/minute, SpO2 < 85%) and persisting for 3 minutes within a 5-minute moving window (60% of the duration of the window). A 6-hour time segment prior to onset of first CRI was chosen for time series modeling in 20 patients using a six-step procedure: (a) the uniform time series for each vital sign was assessed for stationarity; (b) appropriate lag was determined using a lag-length selection criteria; (c) the VAR model was constructed; (d) residual autocorrelation was assessed with the Lagrange Multiplier test; (e) stability of the VAR system was checked; and (f) Granger causality was evaluated in the final stable model. Results The primary cause of incident CRI was low SpO2 (60% of cases), followed by out-of-range RR (30%) and HR (10%). Granger causality testing revealed that change in RR caused change in HR (21%) (i.e., RR changed before HR changed) more often than change in HR causing change in RR (15%). Similarly, changes in RR caused changes in SpO2 (15%) more often than changes in SpO2 caused changes in RR (9%). For HR and SpO2, changes in HR causing changes in SpO2 and changes in SpO2 causing changes in HR occurred with equal frequency (18%). Discussion Within this sample of acutely ill patients who experienced a CRI event, VAR modeling indicated that RR changes tend to occur before changes in HR and SpO2. These findings suggest that contextual assessment of RR changes as the earliest sign of CRI is warranted. Use of VAR modeling may be helpful in other nursing research applications based on time series data. PMID:27977564

Smoking and multiple sclerosis: A systematic review and meta-analysis using the Bradford Hill criteria for causation.

PubMed

Degelman, Michelle L; Herman, Katya M

2017-10-01

Despite being one of the most common neurological disorders globally, the cause(s) of multiple sclerosis (MS) remain unknown. Cigarette smoking has been studied with regards to both the development and progression of MS. The Bradford Hill criteria for causation can contribute to a more comprehensive evaluation of a potentially causal risk factor-disease outcome relationship. The objective of this systematic review and meta-analysis was to assess the relationship between smoking and both MS risk and MS progression, subsequently applying Hill's criteria to further evaluate the likelihood of causal associations. The Medline, EMBASE, CINAHL, PsycInfo, and Cochrane Library databases were searched for relevant studies up until July 28, 2015. A random-effects meta-analysis was conducted for three outcomes: MS risk, conversion from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS), and progression from relapsing-remitting multiple sclerosis (RRMS) to secondary-progressive multiple sclerosis (SPMS). Dose-response relationships and risk factor interactions, and discussions of mechanisms and analogous associations were noted. Hill's criteria were applied to assess causality of the relationships between smoking and each outcome. The effect of second-hand smoke exposure was also briefly reviewed. Smoking had a statistically significant association with both MS risk (conservative: OR/RR 1.54, 95% CI [1.46-1.63]) and SPMS risk (HR 1.80, 95% CI [1.04-3.10]), but the association with progression from CIS to CDMS was non-significant (HR 1.13, 95% CI [0.73-1.76]). Using Hill's criteria, there was strong evidence of a causal role of smoking in MS risk, but only moderate evidence of a causal association between smoking and MS progression. Heterogeneity in study designs and target populations, inconsistent results, and an overall scarcity of studies point to the need for more research on second-hand smoke exposure in relation to MS prior to conducting a detailed meta-analysis. This first review to supplement systematic review and meta-analytic methods with Hill's criteria to analyze the smoking-MS association provides evidence supporting the causal involvement of smoking in the development and progression of MS. Smoking prevention and cessation programs and policies should consider MS as an additional health risk when aiming to reduce smoking prevalence in the population. Copyright © 2017 Elsevier B.V. All rights reserved.

How to establish causality in epilepsy surgery.

PubMed

Asano, Eishi; Brown, Erik C; Juhász, Csaba

2013-09-01

Focality in electro-clinical or neuroimaging data often motivates epileptologists to consider epilepsy surgery in patients with medically-uncontrolled seizures, while not all focal findings are causally associated with the generation of epileptic seizures. With the help of Hill's criteria, we have discussed how to establish causality in the context of the presurgical evaluation of epilepsy. The strengths of EEG include the ability to determine the temporal relationship between cerebral activities and clinical events; thus, scalp video-EEG is necessary in the evaluation of the majority of surgical candidates. The presence of associated ictal discharges can confirm the epileptic nature of a particular spell and whether an observed neuroimaging abnormality is causally associated with the epileptic seizure. Conversely, one should be aware that scalp EEG has a limited spatial resolution and sometimes exhibits propagated epileptiform discharges more predominantly than in situ discharges generated at the seizure-onset zone. Intraoperative or extraoperative electrocorticography (ECoG) is utilized when noninvasive presurgical evaluation, including anatomical and functional neuroimaging, fails to determine the margin between the presumed epileptogenic zone and eloquent cortex. Retrospective as well as prospective studies have reported that complete resection of the seizure-onset zone on ECoG was associated with a better seizure outcome, but not all patients became seizure-free following such resective surgery. Some retrospective studies suggested that resection of sites showing high-frequency oscillations (HFOs) at >80Hz on interictal or ictal ECoG was associated with a better seizure outcome. Others reported that functionally-important areas may generate HFOs of a physiological nature during rest as well as sensorimotor and cognitive tasks. Resection of sites showing task-related augmentation of HFOs has been reported to indeed result in functional loss following surgery. Thus, some but not all sites showing interictal HFOs are causally associated with seizure generation. Furthermore, evidence suggests that some task-related HFOs can be transiently suppressed by the prior occurrence of interictal spikes. The significance of interictal HFOs should be assessed by taking into account the eloquent cortex, seizure-onset zone, and cortical lesions. Video-EEG and ECoG generally provide useful but still limited information to establish causality in presurgical evaluation. A comprehensive assessment of data derived from multiple modalities is ultimately required for successful management. Copyright © 2013 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

How to establish causality in epilepsy surgery

PubMed Central

Asano, Eishi; Brown, Erik C; Juhász, Csaba

2013-01-01

Focality in electro-clinical or neuroimaging data often motivates epileptologists to consider epilepsy surgery in patients with medically-uncontrolled seizures, while not all focal findings are causally associated with the generation of epileptic seizures. With the help of Hill's criteria, we have discussed how to establish causality in the context of the presurgical evaluation of epilepsy. The strengths of EEG include the ability to determine the temporal relationship between cerebral activities and clinical events; thus, scalp video-EEG is necessary in the evaluation of the majority of surgical candidates. The presence of associated ictal discharges can confirm the epileptic nature of a particular spell and whether an observed neuroimaging abnormality is causally associated with the epileptic seizure. Conversely, one should be aware that scalp EEG has a limited spatial resolution and sometimes exhibits propagated epileptiform discharges more predominantly than in situ discharges generated at the seizure-onset zone. Intraoperative or extraoperative electrocorticography (ECoG) is utilized when noninvasive presurgical evaluation, including anatomical and functional neuroimaging, fails to determine the margin between the presumed epileptogenic zone and eloquent cortex. Retrospective as well as prospective studies have reported that complete resection of the seizure-onset zone on ECoG was associated with a better seizure outcome, but not all patients became seizure-free following such resective surgery. Some retrospective studies suggested that resection of sites showing high-frequency oscillations (HFOs) at >80 Hz on interictal or ictal ECoG was associated with a better seizure outcome. Others reported that functionally-important areas may generate HFOs of a physiological nature during rest as well as sensorimotor and cognitive tasks. Resection of sites showing task-related augmentation of HFOs has been reported to indeed result in functional loss following surgery. Thus, some but not all sites showing interictal HFOs are causally associated with seizure generation. Furthermore, evidence suggests that some task-related HFOs can be transiently suppressed by the prior occurrence of interictal spikes. The significance of interictal HFOs should be assessed by taking into account the eloquent cortex, seizure-onset zone, and cortical lesions. Video-EEG and ECoG generally provide useful but still limited information to establish causality in presurgical evaluation. A comprehensive assessment of data derived from multiple modalities is ultimately required for successful management. PMID:23684007

Profiling neuronal ion channelopathies with non-invasive brain imaging and dynamic causal models: Case studies of single gene mutations

PubMed Central

Gilbert, Jessica R.; Symmonds, Mkael; Hanna, Michael G.; Dolan, Raymond J.; Friston, Karl J.; Moran, Rosalyn J.

2016-01-01

Clinical assessments of brain function rely upon visual inspection of electroencephalographic waveform abnormalities in tandem with functional magnetic resonance imaging. However, no current technology proffers in vivo assessments of activity at synapses, receptors and ion-channels, the basis of neuronal communication. Using dynamic causal modeling we compared electrophysiological responses from two patients with distinct monogenic ion channelopathies and a large cohort of healthy controls to demonstrate the feasibility of assaying synaptic-level channel communication non-invasively. Synaptic channel abnormality was identified in both patients (100% sensitivity) with assay specificity above 89%, furnishing estimates of neurotransmitter and voltage-gated ion throughput of sodium, calcium, chloride and potassium. This performance indicates a potential novel application as an adjunct for clinical assessments in neurological and psychiatric settings. More broadly, these findings indicate that biophysical models of synaptic channels can be estimated non-invasively, having important implications for advancing human neuroimaging to the level of non-invasive ion channel assays. PMID:26342528

A Difference-in-Differences Approach to Assess the Effect of a Heat Action Plan on Heat-Related Mortality, and Differences in Effectiveness According to Sex, Age, and Socioeconomic Status (Montreal, Quebec).

PubMed

Benmarhnia, Tarik; Bailey, Zinzi; Kaiser, David; Auger, Nathalie; King, Nicholas; Kaufman, Jay S

2016-11-01

The impact of heat waves on mortality and health inequalities is well documented. Very few studies have assessed the effectiveness of heat action plans (HAPs) on health, and none has used quasi-experimental methods to estimate causal effects of such programs. We developed a quasi-experimental method to estimate the causal effects associated with HAPs that allows the identification of heterogeneity across subpopulations, and to apply this method specifically to the case of the Montreal (Quebec, Canada) HAP. A difference-in-differences approach was undertaken using Montreal death registry data for the summers of 2000-2007 to assess the effectiveness of the Montreal HAP, implemented in 2004, on mortality. To study equity in the effect of HAP implementation, we assessed whether the program effects were heterogeneous across sex (male vs. female), age (≥ 65 years vs. < 65 years), and neighborhood education levels (first vs. third tertile). We conducted sensitivity analyses to assess the validity of the estimated causal effect of the HAP program. We found evidence that the HAP contributed to reducing mortality on hot days, and that the mortality reduction attributable to the program was greater for elderly people and people living in low-education neighborhoods. These findings show promise for programs aimed at reducing the impact of extreme temperatures and health inequities. We propose a new quasi-experimental approach that can be easily applied to evaluate the impact of any program or intervention triggered when daily thresholds are reached. Citation: Benmarhnia T, Bailey Z, Kaiser D, Auger N, King N, Kaufman J. 2016. A difference-in-differences approach to assess the effect of a heat action plan on heat-related mortality, and differences in effectiveness according to sex, age, and socioeconomic status (Montreal, Quebec). Environ Health Perspect 124:1694-1699; http://dx.doi.org/10.1289/EHP203.

Herbal does not mean innocuous: ten cases of severe hepatotoxicity associated with dietary supplements from Herbalife products.

PubMed

Schoepfer, Alain M; Engel, Antoinette; Fattinger, Karin; Marbet, Urs A; Criblez, Dominique; Reichen, Juerg; Zimmermann, Arthur; Oneta, Carl M

2007-10-01

Herbal agents are popular and perceived as safe because they are supposedly 'natural'. We report 10 cases of toxic hepatitis implicating Herbalife products. To determine the prevalence and outcome of hepatotoxicity due to Herbalife products. A questionnaire was sent to all public Swiss hospitals. Reported cases were subjected to causality assessment using the CIOMS criteria. Twelve cases of toxic hepatitis implicating Herbalife preparations (1998-2004) were retrieved, 10 sufficiently documented to permit causality analysis. Median age of patients was 51 years (range 30-69) and latency to onset was 5 months (0.5-144). Liver biopsy (7/10) showed hepatic necrosis, marked lymphocytic/eosinophilic infiltration and cholestasis in five patients. One patient with fulminant liver failure was successfully transplanted; the explant showed giant cell hepatitis. Sinusoidal obstruction syndrome was observed in one case. Three patients without liver biopsy presented with hepatocellular (2) or mixed (1) liver injury. Causality assessment of adverse drug reaction was classified as certain in two, probable in seven and possible in one case(s), respectively. We present a case series of toxic hepatitis implicating Herbalife products. Liver toxicity may be severe. A more detailed declaration of components and pro-active role of regulatory agencies would be desirable.

Intraoperative neuromonitoring alerts that reverse with intervention: treatment paradox and what to do about it.

PubMed

Skinner, Stanley A; Holdefer, Robert N

2014-04-01

Intervention-mediated recovery from adversely changed evoked potential recordings may provide evidence for improved outcomes during neurophysiological intraoperative monitoring. However, these reversible signal changes (RSCs) are ambiguous because the patient's neurologic status cannot be known either at signal decline or after intervention. This article describes methods to reduce this ambiguity. Randomized control trials are not always possible or ethical. Recent thought on grading evidence has acknowledged that guidelines first described by Sir Austin Bradford Hill may support evidence for causation. Causality guidelines identified RSCs most likely to be truly positive in three reported studies. Diagnostic statistics were revised accordingly. A range of revised positive predictive values and likelihood ratios was calculated in the three studies, using causality guidelines. The revised data were similar to those reported for other diagnostic tests used in medicine. The RSCs may be assessed using causality guidelines for more accurate reporting of diagnostic statistics while preserving information related to surgical intervention and recovery that is lost with end of surgery diagnostics or when RSCs are ignored. A method is described for including RSCs in diagnostic statistics. This approach will more readily permit assessment of the value of neurophysiological intraoperative monitoring in prediction and prevention of neurologic deficits.

Effective Connectivity Analysis of the Brain Network in Drivers during Actual Driving Using Near-Infrared Spectroscopy

PubMed Central

Liu, Zhian; Zhang, Ming; Xu, Gongcheng; Huo, Congcong; Tan, Qitao; Li, Zengyong; Yuan, Quan

2017-01-01

Driving a vehicle is a complex activity that requires high-level brain functions. This study aimed to assess the change in effective connectivity (EC) between the prefrontal cortex (PFC), motor-related areas (MA) and vision-related areas (VA) in the brain network among the resting, simple-driving and car-following states. Twelve young male right-handed adults were recruited to participate in an actual driving experiment. The brain delta [HbO2] signals were continuously recorded using functional near infrared spectroscopy (fNIRS) instruments. The conditional Granger causality (GC) analysis, which is a data-driven method that can explore the causal interactions among different brain areas, was performed to evaluate the EC. The results demonstrated that the hemodynamic activity level of the brain increased with an increase in the cognitive workload. The connection strength among PFC, MA and VA increased from the resting state to the simple-driving state, whereas the connection strength relatively decreased during the car-following task. The PFC in EC appeared as the causal target, while the MA and VA appeared as the causal sources. However, l-MA turned into causal targets with the subtask of car-following. These findings indicate that the hemodynamic activity level of the cerebral cortex increases linearly with increasing cognitive workload. The EC of the brain network can be strengthened by a cognitive workload, but also can be weakened by a superfluous cognitive workload such as driving with subtasks. PMID:29163083

AOP: An R Package For Sufficient Causal Analysis in Pathway ...

EPA Pesticide Factsheets

Summary: How can I quickly find the key events in a pathway that I need to monitor to predict that a/an beneficial/adverse event/outcome will occur? This is a key question when using signaling pathways for drug/chemical screening in pharma-cology, toxicology and risk assessment. By identifying these sufficient causal key events, we have fewer events to monitor for a pathway, thereby decreasing assay costs and time, while maximizing the value of the information. I have developed the “aop” package which uses backdoor analysis of causal net-works to identify these minimal sets of key events that are suf-ficient for making causal predictions. Availability and Implementation: The source and binary are available online through the Bioconductor project (http://www.bioconductor.org/) as an R package titled “aop”. The R/Bioconductor package runs within the R statistical envi-ronment. The package has functions that can take pathways (as directed graphs) formatted as a Cytoscape JSON file as input, or pathways can be represented as directed graphs us-ing the R/Bioconductor “graph” package. The “aop” package has functions that can perform backdoor analysis to identify the minimal set of key events for making causal predictions.Contact: burgoon.lyle@epa.gov This paper describes an R/Bioconductor package that was developed to facilitate the identification of key events within an AOP that are the minimal set of sufficient key events that need to be tested/monit

A genetically informative developmental study of the relationship between conduct disorder and peer deviance in males

PubMed Central

Kendler, K. S.; Jacobson, K.; Myers, J. M.; Eaves, L. J.

2014-01-01

Background Conduct disorder (CD) and peer deviance (PD) both powerfully predict future externalizing behaviors. Although levels of CD and PD are strongly correlated, the causal relationship between them has remained controversial and has not been examined by a genetically informative study. Method Levels of CD and PD were assessed in 746 adult male–male twin pairs at personal interview for ages 8–11, 12–14 and 15–17 years using a life history calendar. Model fitting was performed using the Mx program. Results The best-fit model indicated an active developmental relationship between CD and PD including forward transmission of both traits over time and strong causal relationships between CD and PD within time periods. The best-fit model indicated that the causal relationship for genetic risk factors was from CD to PD and was constant over time. For common environmental factors, the causal pathways ran from PD to CD and were stronger in earlier than later age periods. Conclusions A genetically informative model revealed causal pathways difficult to elucidate by other methods. Genes influence risk for CD, which, through social selection, impacts on the deviance of peers. Shared environment, through family and community processes, encourages or discourages adolescent deviant behavior, which, via social influence, alters risk for CD. Social influence is more important than social selection in childhood, but by late adolescence social selection becomes predominant. These findings have implications for prevention efforts for CD and associated externalizing disorders. PMID:17935643

Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment

ERIC Educational Resources Information Center

Johnson, Samuel G. B.; Ahn, Woo-kyoung

2015-01-01

Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge--an interconnected causal "network," where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms--causal "islands"--such that events in different…

Vaccination and 30-Day Mortality Risk in Children, Adolescents, and Young Adults.

PubMed

McCarthy, Natalie L; Gee, Julianne; Sukumaran, Lakshmi; Weintraub, Eric; Duffy, Jonathan; Kharbanda, Elyse O; Baxter, Roger; Irving, Stephanie; King, Jennifer; Daley, Matthew F; Hechter, Rulin; McNeil, Michael M

2016-03-01

This study evaluates the potential association of vaccination and death in the Vaccine Safety Datalink (VSD). The study cohort included individuals ages 9 to 26 years with deaths between January 1, 2005, and December 31, 2011. We implemented a case-centered method to estimate a relative risk (RR) for death in days 0 to 30 after vaccination.Deaths due to external causes (accidents, homicides, and suicides) were excluded from the primary analysis. In a secondary analysis, we included all deaths regardless of cause. A team of physicians reviewed available medical records and coroner's reports to confirm cause of death and assess the causal relationship between death and vaccination. Of the 1100 deaths identified during the study period, 76 (7%) occurred 0 to 30 days after vaccination. The relative risks for deaths after any vaccination and influenza vaccination were significantly lower for deaths due to nonexternal causes (RR 0.57, 95% confidence interval [CI] 0.38-0.83, and RR 0.44, 95% CI 0.24-0.80, respectively) and deaths due to all causes (RR 0.72, 95% CI 0.56-0.91, and RR 0.44, 95% CI 0.28-0.65). No other individual vaccines were significantly associated with death. Among deaths reviewed, 1 cause of death was unknown, 25 deaths were due to nonexternal causes, and 34 deaths were due to external causes. The causality assessment found no evidence of a causal association between vaccination and death. Risk of death was not increased during the 30 days after vaccination, and no deaths were found to be causally associated with vaccination. Copyright © 2016 by the American Academy of Pediatrics.

Mediation Effect of Locus of Control on the Causal Relationship between Students' Perceived Teachers' Expectancy and Self-Esteem

ERIC Educational Resources Information Center

Prihadi, Kususanto; Hairul, Nizam Ismail; Hazri, Jamil

2012-01-01

Introduction: Symbolic interaction theorists maintained that general self-esteem, defined as the way individuals assess themselves, is based on the individual's perception on the way others assess them (we are what we think other people think we are). Accordingly, studies in school settings indicated that students' perceived teachers' expectancy…

Assessing Sensitivity to Unmeasured Confounding Using a Simulated Potential Confounder

ERIC Educational Resources Information Center

Carnegie, Nicole Bohme; Harada, Masataka; Hill, Jennifer L.

2016-01-01

A major obstacle to developing evidenced-based policy is the difficulty of implementing randomized experiments to answer all causal questions of interest. When using a nonexperimental study, it is critical to assess how much the results could be affected by unmeasured confounding. We present a set of graphical and numeric tools to explore the…

Classification Agreement Analysis of Cross-Battery Assessment in the Identification of Specific Learning Disorders in Children and Youth

ERIC Educational Resources Information Center

Kranzler, John H.; Floyd, Randy G.; Benson, Nicholas; Zaboski, Brian; Thibodaux, Lia

2016-01-01

The Cross-Battery Assessment (XBA) approach to identifying a specific learning disorder (SLD) is based on the postulate that deficits in cognitive abilities in the presence of otherwise average general intelligence are causally related to academic achievement weaknesses. To examine this postulate, we conducted a classification agreement analysis…

Mapping rare and common causal alleles for complex human diseases

PubMed Central

Raychaudhuri, Soumya

2011-01-01

Advances in genotyping and sequencing technologies have revolutionized the genetics of complex disease by locating rare and common variants that influence an individual’s risk for diseases, such as diabetes, cancers, and psychiatric disorders. However, to capitalize on this data for prevention and therapies requires the identification of causal alleles and a mechanistic understanding for how these variants contribute to the disease. After discussing the strategies currently used to map variants for complex diseases, this Primer explores how variants may be prioritized for follow-up functional studies and the challenges and approaches for assessing the contributions of rare and common variants to disease phenotypes. PMID:21962507

Quasi-experimental study designs series-paper 7: assessing the assumptions.

PubMed

Bärnighausen, Till; Oldenburg, Catherine; Tugwell, Peter; Bommer, Christian; Ebert, Cara; Barreto, Mauricio; Djimeu, Eric; Haber, Noah; Waddington, Hugh; Rockers, Peter; Sianesi, Barbara; Bor, Jacob; Fink, Günther; Valentine, Jeffrey; Tanner, Jeffrey; Stanley, Tom; Sierra, Eduardo; Tchetgen, Eric Tchetgen; Atun, Rifat; Vollmer, Sebastian

2017-09-01

Quasi-experimental designs are gaining popularity in epidemiology and health systems research-in particular for the evaluation of health care practice, programs, and policy-because they allow strong causal inferences without randomized controlled experiments. We describe the concepts underlying five important quasi-experimental designs: Instrumental Variables, Regression Discontinuity, Interrupted Time Series, Fixed Effects, and Difference-in-Differences designs. We illustrate each of the designs with an example from health research. We then describe the assumptions required for each of the designs to ensure valid causal inference and discuss the tests available to examine the assumptions. Copyright © 2017 Elsevier Inc. All rights reserved.

30 YEARS OF THE MINERALOCORTICOID RECEPTOR: Mineralocorticoid receptor antagonists: 60 years of research and development

PubMed Central

Bärfacker, Lars

2017-01-01

The cDNA of the mineralocorticoid receptor (MR) was cloned 30 years ago, in 1987. At that time, spirolactone, the first generation of synthetic steroid-based MR antagonists (MRAs), which was identified in preclinical in vivo models, had already been in clinical use for 30 years. Subsequent decades of research and development by Searle & Co., Ciba-Geigy, Roussel Uclaf and Schering AG toward identifying a second generation of much more specific steroidal MRAs were all based on the initial 17-spirolactone construct. The salient example is eplerenone, first described in 1987, coincidentally with the cloning of MR cDNA. Its launch on the market in 2003 paralleled intensive drug discovery programs for a new generation of non-steroidal MRAs. Now, 30 years after the cDNA cloning of MR and 60 years of clinical use of steroidal MRAs, novel non-steroidal MRAs such as apararenone, esaxerenone and finerenone are in late-stage clinical trials in patients with heart failure, chronic kidney disease (CKD), hypertension and liver disease. Finerenone has already been studied in over 2000 patients with heart failure plus chronic kidney disease and/or diabetes, and in patients with diabetic kidney disease, in five phase II clinical trials. Here, we reflect on the history of the various generations of MRAs and review characteristics of the most important steroidal and non-steroidal MRAs. PMID:28634268

DEVELOPMENT PLAN FOR THE CAUSAL ANALYSIS ...

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System (CADDIS) is a web-based system that provides technical support for states, tribes and other users of the Office of Water's Stressor Identification Guidance. The Stressor Identification Guidance provides a rigorous and scientifically defensible method for determining the causes of biological impairments of aquatic ecosystems. It is being used by states as part of the TMDL process and is being applied to other impaired ecosystems such as Superfund sites. However, because of the complexity of causal relationships in ecosystems, and because the guidance includes a strength-of-evidence analysis which uses multiple causal considerations, the process is complex and information intensive. CADDIS helps users deal with that inherent complexity. Increasingly, the regulatory, remedial, and restoration actions taken to manage impaired environments are based on measurement and analysis of the biotic community. When an aquatic assemblage has been identified as impaired, an accurate and defensible assessment of the cause can help ensure that appropriate actions are taken. The U.S. EPA's Stressor Identification Guidance describes a methodology for identifying the most likely causes of observed impairments in aquatic systems. Stressor identification requires extensive knowledge of the mechanisms, symptoms, and stressor-response relationships for various specific stressors as well as the ability to use that knowledge in a

The stochastic system approach for estimating dynamic treatments effect.

PubMed

Commenges, Daniel; Gégout-Petit, Anne

2015-10-01

The problem of assessing the effect of a treatment on a marker in observational studies raises the difficulty that attribution of the treatment may depend on the observed marker values. As an example, we focus on the analysis of the effect of a HAART on CD4 counts, where attribution of the treatment may depend on the observed marker values. This problem has been treated using marginal structural models relying on the counterfactual/potential response formalism. Another approach to causality is based on dynamical models, and causal influence has been formalized in the framework of the Doob-Meyer decomposition of stochastic processes. Causal inference however needs assumptions that we detail in this paper and we call this approach to causality the "stochastic system" approach. First we treat this problem in discrete time, then in continuous time. This approach allows incorporating biological knowledge naturally. When working in continuous time, the mechanistic approach involves distinguishing the model for the system and the model for the observations. Indeed, biological systems live in continuous time, and mechanisms can be expressed in the form of a system of differential equations, while observations are taken at discrete times. Inference in mechanistic models is challenging, particularly from a numerical point of view, but these models can yield much richer and reliable results.

Interdependence of stroke survivors' recovery and their relatives' attitudes and health: a contribution to investigating the causal effects.

PubMed

Barskova, Tatjana; Wilz, Gabriele

2007-10-15

One goal of the study was to test specific hypotheses concerning the interdependence of the stroke survivors' recovery and their caregiving partners' attitudes and health. The other aim was to find an applicable method for investigating causal effects on the rehabilitation of chronically sick persons in longitudinal studies with medium-sized samples. The recovery of 81 stroke survivors regarding the physical and mental functioning in everyday life and their caregiving partners' health and attitudes were assessed twice, once after the patients left the hospital and again one year later. We applied the structure equation modeling and the cross-lagged partial correlation analysis (CLPC) for testing causal effects. Particularly stroke victims' cognitive and emotional recovery seems to be influenced by psychosocial factors such as the caregiving partners' acceptance of a post-stroke life-situation. In contrast to this, the research suggests that the patients' recovery regarding physical functioning is not substantially affected by the partners, rather the patients' difficulties with motor functioning influence their partners' health. Caregivers merit attention as part of rehabilitation interventions. We recommend the CLPC for investigating causal effects in the complex interdependence of chronically sick persons' convalescence and their family members' health and state of mind in medium-sized samples.

Granger causal time-dependent source connectivity in the somatosensory network

NASA Astrophysics Data System (ADS)

Gao, Lin; Sommerlade, Linda; Coffman, Brian; Zhang, Tongsheng; Stephen, Julia M.; Li, Dichen; Wang, Jue; Grebogi, Celso; Schelter, Bjoern

2015-05-01

Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess.

A causal loop analysis of the sustainability of integrated community case management in Rwanda.

PubMed

Sarriot, Eric; Morrow, Melanie; Langston, Anne; Weiss, Jennifer; Landegger, Justine; Tsuma, Laban

2015-04-01

Expansion of community health services in Rwanda has come with the national scale up of integrated Community Case Management (iCCM) of malaria, pneumonia and diarrhea. We used a sustainability assessment framework as part of a large-scale project evaluation to identify factors affecting iCCM sustainability (2011). We then (2012) used causal-loop analysis to identify systems determinants of iCCM sustainability from a national systems perspective. This allows us to develop three high-probability future scenarios putting the achievements of community health at risk, and to recommend mitigating strategies. Our causal loop diagram highlights both balancing and reinforcing loops of cause and effect in the national iCCM system. Financial, political and technical scenarios carry high probability for threatening the sustainability through: (1) reduction in performance-based financing resources, (2) political shocks and erosion of political commitment for community health, and (3) insufficient progress in resolving district health systems--"building blocks"--performance gaps. In a complex health system, the consequences of choices may be delayed and hard to predict precisely. Causal loop analysis and scenario mapping make explicit complex cause-and-effects relationships and high probability risks, which need to be anticipated and mitigated. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Assessing natural direct and indirect effects through multiple pathways.

PubMed

Lange, Theis; Rasmussen, Mette; Thygesen, Lau Caspar

2014-02-15

Within the fields of epidemiology, interventions research and social sciences researchers are often faced with the challenge of decomposing the effect of an exposure into different causal pathways working through defined mediator variables. The goal of such analyses is often to understand the mechanisms of the system or to suggest possible interventions. The case of a single mediator, thus implying only 2 causal pathways (direct and indirect) from exposure to outcome, has been extensively studied. By using the framework of counterfactual variables, researchers have established theoretical properties and developed powerful tools. However, in practical problems, it is not uncommon to have several distinct causal pathways from exposure to outcome operating through different mediators. In this article, we suggest a widely applicable approach to quantifying and ranking different causal pathways. The approach is an extension of the natural effect models proposed by Lange et al. (Am J Epidemiol. 2012;176(3):190-195). By allowing the analysis of distinct multiple pathways, the suggested approach adds to the capabilities of modern mediation techniques. Furthermore, the approach can be implemented using standard software, and we have included with this article implementation examples using R (R Foundation for Statistical Computing, Vienna, Austria) and Stata software (StataCorp LP, College Station, Texas).

Non-Separability and Synchronicity: Pauli, Jung and a New Historical, Philosophical Perspective on Quantum Physics

NASA Astrophysics Data System (ADS)

Giannetto, E. A.; Pozzi, F.

We would like to discuss the historical emergence of quantum physics and quantum non-separability, by analysing Pauli's point of view in relation to Jung's ideas. Recent inquiries on EPR shows that quantum non-separability indicates an a-causal connection of the "quantum reality" for space-like intervals ("simultaneity region ") of world (measurement) events: this non-causal connection is the physical counterpart of what Jung called "synchronicity " with an assessment given also by Pauli. This does not imply any violation of mechanical causality by any introduction of action-at-a-distance. From a physical point of view a-causal connections can be interpreted as implying a particular quantum topology of space-time, which leads to a non-mechanistic conception of nature and which could be related to a holistic quantum dynamical reality of the world like Bohm's "holomovement" or "light". This kind of non-mechanistic conception of nature as well as the idea of non-separability of the world and of synchronicity, as stated by Jung itself, was developed by Leibnitz: from this point of view, we can look at quantum physics (as well as for relativity it was shown) as related to a new emergence of concepts belonging to the Leibnitzian (anti-Newtonian) tradition.

Juvenile-onset inflammatory arthritis: a study of adolescents’ beliefs about underlying cause

PubMed Central

Cordingley, Lis; Vracas, Tiffany; Baildam, Eileen; Chieng, Alice; Davidson, Joyce; Foster, Helen E.; Gardner-Medwin, Janet; Wedderburn, Lucy R.; Thomson, Wendy

2012-01-01

Objective. Patients’ beliefs regarding the cause of illness may influence treatment adherence and long-term outcome. Little is known of adolescents’ beliefs regarding the cause of JIA. This study aims to identify adolescents’ beliefs about the underlying cause of their arthritis at first presentation to the paediatric rheumatology department. Methods. One hundred and twenty-two adolescents aged ≥11 years participating in the larger prospective Childhood Arthritis Prospective Study, an inception cohort of childhood-onset inflammatory arthritis, were asked to complete a questionnaire regarding underlying beliefs about their arthritis. The top-listed causes were identified, and associations between beliefs and characteristics of the adolescents and their arthritis were compared across the different causal beliefs. Results. The most common causal beliefs were genetics (27.1%), the immune system (21.3%), accident or injury (15.6%) and infection (13.1%). Association between causal beliefs and gender, disease duration, International League Against Rheumatism subtype and source of referral was observed, although small numbers prevented robust statistical comparisons. Conclusion. This first report on adolescents’ beliefs about the cause of their juvenile arthritis found the most common causal beliefs to be related to genes or the immune system. Brief assessments of adolescents’ beliefs at presentation will enable providers to modify or adapt potentially unhelpful beliefs and provide age-appropriate information regarding arthritis. PMID:22942401

Environment degradation, economic growth and energy consumption nexus: A wavelet-windowed cross correlation approach

NASA Astrophysics Data System (ADS)

Jammazi, Rania; Aloui, Chaker

2015-10-01

This paper analyzes the interactive linkages between carbon dioxide (CO2) emissions, energy consumption (EC) and economic growth (EG) using a novel approach namely wavelet windowed cross correlation (WWCC) for six oil-exporting countries from the GCC (Gulf Cooperation Council) region over the period 1980-2012. Our empirical results show that there exists a bidirectional causal relationship between EC and EG. However, the results support the occurrence of unidirectional causality from EC to CO2 emissions without any feedback effects, and there exists a bidirectional causal relationship between EG and CO2 emissions for the region as a whole. The study suggests that environmental and energy policies should recognize the differences in the nexus between EC and EG in order to maintain sustainable EG in the GCC region. Our findings will be useful for GCC countries to better evaluate its situation in the future climate negotiations. The overall findings will help GCC countries assess its position better in future climate change negotiations.

Lending to Parents and Insuring Children: Is There a Role for Microcredit in Complementing Health Insurance in Rural China?

PubMed

You, Jing

2016-05-01

This paper assesses the causal impact on child health of borrowing formal microcredit for Chinese rural households by exploiting a panel dataset (2000 and 2004) in a poor northwest province. Endogenous borrowing is controlled for in a dynamic regression-discontinuity design creating a quasi-experimental environment for causal inferences. There is causal relationship running from formal microcredit to improved child health in the short term, while past borrowing behaviour has no protracted impact on subsequent child health outcomes. Moreover, formal microcredit appears to be a complement to health insurance in improving child health through two mechanisms-it enhances affordability for out-of-pocket health care expenditure and helps buffer consumption against adverse health shocks and financial risk incurred by current health insurance arrangements. Government efforts in expanding health insurance for rural households would be more likely to achieve its optimal goals of improving child health outcomes if combined with sufficient access to formal microcredit. Copyright © 2015 John Wiley & Sons, Ltd.

An information-theoretic approach for the evaluation of surrogate endpoints based on causal inference.

PubMed

Alonso, Ariel; Van der Elst, Wim; Molenberghs, Geert; Buyse, Marc; Burzykowski, Tomasz

2016-09-01

In this work a new metric of surrogacy, the so-called individual causal association (ICA), is introduced using information-theoretic concepts and a causal inference model for a binary surrogate and true endpoint. The ICA has a simple and appealing interpretation in terms of uncertainty reduction and, in some scenarios, it seems to provide a more coherent assessment of the validity of a surrogate than existing measures. The identifiability issues are tackled using a two-step procedure. In the first step, the region of the parametric space of the distribution of the potential outcomes, compatible with the data at hand, is geometrically characterized. Further, in a second step, a Monte Carlo approach is proposed to study the behavior of the ICA on the previous region. The method is illustrated using data from the Collaborative Initial Glaucoma Treatment Study. A newly developed and user-friendly R package Surrogate is provided to carry out the evaluation exercise. © 2016, The International Biometric Society.

Selection and explosive growth alter genetic architecture and hamper the detection of causal rare variants

PubMed Central

Zaitlen, Noah A.; Ye, Chun Jimmie; Witte, John S.

2016-01-01

The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature. PMID:27197206

A Longitudinal Analysis of the Causal Factors in Major Maritime Accidents in the USA and Canada (1996-2006)

NASA Technical Reports Server (NTRS)

Johnson, C. W.; Holloway, C, M.

2007-01-01

Accident reports provide important insights into the causes and contributory factors leading to particular adverse events. In contrast, this paper provides an analysis that extends across the findings presented over ten years investigations into maritime accidents by both the US National Transportation Safety Board (NTSB) and Canadian Transportation Safety Board (TSB). The purpose of the study was to assess the comparative frequency of a range of causal factors in the reporting of adverse events. In order to communicate our findings, we introduce J-H graphs as a means of representing the proportion of causes and contributory factors associated with human error, equipment failure and other high level classifications in longitudinal studies of accident reports. Our results suggest the proportion of causal and contributory factors attributable to direct human error may be very much smaller than has been suggested elsewhere in the human factors literature. In contrast, more attention should be paid to wider systemic issues, including the managerial and regulatory context of maritime operations.

The MR-Base platform supports systematic causal inference across the human phenome

PubMed Central

Wade, Kaitlin H; Haberland, Valeriia; Baird, Denis; Laurin, Charles; Burgess, Stephen; Bowden, Jack; Langdon, Ryan; Tan, Vanessa Y; Yarmolinsky, James; Shihab, Hashem A; Timpson, Nicholas J; Evans, David M; Relton, Caroline; Martin, Richard M; Davey Smith, George

2018-01-01

Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies. PMID:29846171

Infant acetylcholine, dopamine, and melatonin dysregulation: Neonatal biomarkers and causal factors for ASD and ADHD phenotypes.

PubMed

Hellmer, Kahl; Nyström, Pär

2017-03-01

Autism spectrum disorders (ASD) and ADHD are common neurodevelopmental disorders that benefit from early intervention but currently suffer from late detection and diagnosis: neurochemical dysregulations are extant already at birth but clinical phenotypes are not distinguishable until preschool age or later. The vast heterogeneity between subjects' phenotypes relates to interaction between multiple unknown factors, making research on factor causality insurmountable. To unlock this situation we pose the hypothesis that atypical pupillary light responses from rods, cones, and the recently discovered ipRGC system reflect early acetylcholine, melatonin, and dopamine dysregulation that are sufficient but not necessary factors for developing ASD and/or ADHD disorders. Current technology allows non-invasive cost-efficient assessment already from the first postnatal month. The benefits of the current proposal are: identification of clinical subgroups based on cause rather than phenotypes; facilitation of research on other causal factors; neonatal prediction of later diagnoses; and guidance for targeted therapeutical intervention. Copyright © 2017 Elsevier Ltd. All rights reserved.

A new pressure ulcer conceptual framework.

PubMed

Coleman, Susanne; Nixon, Jane; Keen, Justin; Wilson, Lyn; McGinnis, Elizabeth; Dealey, Carol; Stubbs, Nikki; Farrin, Amanda; Dowding, Dawn; Schols, Jos M G A; Cuddigan, Janet; Berlowitz, Dan; Jude, Edward; Vowden, Peter; Schoonhoven, Lisette; Bader, Dan L; Gefen, Amit; Oomens, Cees W J; Nelson, E Andrea

2014-10-01

This paper discusses the critical determinants of pressure ulcer development and proposes a new pressure ulcer conceptual framework. Recent work to develop and validate a new evidence-based pressure ulcer risk assessment framework was undertaken. This formed part of a Pressure UlceR Programme Of reSEarch (RP-PG-0407-10056), funded by the National Institute for Health Research. The foundation for the risk assessment component incorporated a systematic review and a consensus study that highlighted the need to propose a new conceptual framework. Discussion Paper. The new conceptual framework links evidence from biomechanical, physiological and epidemiological evidence, through use of data from a systematic review (search conducted March 2010), a consensus study (conducted December 2010-2011) and an international expert group meeting (conducted December 2011). A new pressure ulcer conceptual framework incorporating key physiological and biomechanical components and their impact on internal strains, stresses and damage thresholds is proposed. Direct and key indirect causal factors suggested in a theoretical causal pathway are mapped to the physiological and biomechanical components of the framework. The new proposed conceptual framework provides the basis for understanding the critical determinants of pressure ulcer development and has the potential to influence risk assessment guidance and practice. It could also be used to underpin future research to explore the role of individual risk factors conceptually and operationally. By integrating existing knowledge from epidemiological, physiological and biomechanical evidence, a theoretical causal pathway and new conceptual framework are proposed with potential implications for practice and research. © 2014 The Authors. Journal of Advanced Nursing Published by John Wiley & Sons Ltd.

Evaluating causality for occupational cancers: the example of firefighters.

PubMed

Guidotti, Tee L

2007-10-01

The evaluation of causality in cancers associated with firefighting presents problems common to other applications of occupational epidemiology in adjudication of individual claims for workers' compensation. A trend in Canada to establish legislated presumptions for compensation of firefighters created an opportunity to re-evaluate the literature applying medicolegal standards of certainty. To evaluate causality in selected cancer categories for firefighters using the criteria applied in tort litigation and workers' compensation, which is based on the weight of evidence and which is required to take into account individual factors. The epidemiological literature on cancer risk among firefighters was reviewed based on the weight of evidence rather than scientific certainty. Generalizable frameworks were formulated to define recurrent issues in assessing the evidence from epidemiological studies. The evidence for latency and for a threshold effect with duration of employment was also examined in order to provide practical guidelines. Presumption is justified for the following cancers: bladder, kidney, testicular and brain, and lung cancer among non-smokers. Non-Hodgkin lymphoma, leukaemia and myeloma (each as a class) not only present particular problems in assessment but also merit an assumption of presumption. Four analytical frameworks describe the problems in analysis encountered. The preponderance of evidence supports the presumption of causation for certain cancer, mostly rare. These frameworks are applicable to other problems of adjudication that rest on interpretation of epidemiological data. The named cancers, taking into account the special assessment issues described by each framework, are supported by sufficient evidence to conclude that a presumption is warranted but not necessarily sufficient evidence to accept as proof by a scientific standard.

Development of an automated assessment tool for MedWatch reports in the FDA adverse event reporting system.

PubMed

Han, Lichy; Ball, Robert; Pamer, Carol A; Altman, Russ B; Proestel, Scott

2017-09-01

As the US Food and Drug Administration (FDA) receives over a million adverse event reports associated with medication use every year, a system is needed to aid FDA safety evaluators in identifying reports most likely to demonstrate causal relationships to the suspect medications. We combined text mining with machine learning to construct and evaluate such a system to identify medication-related adverse event reports. FDA safety evaluators assessed 326 reports for medication-related causality. We engineered features from these reports and constructed random forest, L1 regularized logistic regression, and support vector machine models. We evaluated model accuracy and further assessed utility by generating report rankings that represented a prioritized report review process. Our random forest model showed the best performance in report ranking and accuracy, with an area under the receiver operating characteristic curve of 0.66. The generated report ordering assigns reports with a higher probability of medication-related causality a higher rank and is significantly correlated to a perfect report ordering, with a Kendall's tau of 0.24 ( P  = .002). Our models produced prioritized report orderings that enable FDA safety evaluators to focus on reports that are more likely to contain valuable medication-related adverse event information. Applying our models to all FDA adverse event reports has the potential to streamline the manual review process and greatly reduce reviewer workload. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the United States.

Treatment of Congenital Toxoplasmosis: Safety of the Sulfadoxine-Pyrimethamine Combination in Children Based on a Method of Causality Assessment.

PubMed

Teil, Julie; Dupont, Damien; Charpiat, Bruno; Corvaisier, Stéphane; Vial, Thierry; Leboucher, Gilles; Wallon, Martine; Peyron, François

2016-06-01

The treatment of newborns and infants with congenital toxoplasmosis is standard practice. Some observational studies have examined safety in newborns, but most of these failed to provide sufficient details for a provisional assessment of causality. The aim of this study was to evaluate the clinical and biological adverse effects of the combination of sulfadoxine-pyrimethamine. Sixty-five children treated for 1 year with a combination of sulfadoxine-pyrimethamine (1 dose every 10 days) for congenital toxoplasmosis were followed up to evaluate abnormal hematological values and potential adverse events using a standardized method of causality assessment. Nine patients (13.8%) presented at least 1 adverse clinical event that was nonspecific, such as diarrhea on the day of drug administration, vomiting and agitation. In 1 patient, erythema appeared at the end of the treatment and resolved within 10 days. None of these events was attributed to the treatment. Six patients (9.2%) developed an adverse hematological event (neutropenia, n = 3; eosinophilia, n = 2 and both anemia and eosinophilia, n = 1) that was considered to be possibly related to the sulfadoxine-pyrimethamine combination. Four treatments were temporarily interrupted, and toxicity was observed after readministration of treatment in 1 case only. However, none of these adverse events was life threatening. According to our results and previously published data, the combination of sulfadoxine-pyrimethamine seems to be well tolerated. However, the sample size of our study was too small to rule out the risk of less frequent, but nevertheless severe, reactions and, in particular, of hypersensitivity reactions.

A new pressure ulcer conceptual framework

PubMed Central

Coleman, Susanne; Nixon, Jane; Keen, Justin; Wilson, Lyn; McGinnis, Elizabeth; Dealey, Carol; Stubbs, Nikki; Farrin, Amanda; Dowding, Dawn; Schols, Jos MGA; Cuddigan, Janet; Berlowitz, Dan; Jude, Edward; Vowden, Peter; Schoonhoven, Lisette; Bader, Dan L; Gefen, Amit; Oomens, Cees WJ; Nelson, E Andrea

2014-01-01

Aim This paper discusses the critical determinants of pressure ulcer development and proposes a new pressure ulcer conceptual framework. Background Recent work to develop and validate a new evidence-based pressure ulcer risk assessment framework was undertaken. This formed part of a Pressure UlceR Programme Of reSEarch (RP-PG-0407-10056), funded by the National Institute for Health Research. The foundation for the risk assessment component incorporated a systematic review and a consensus study that highlighted the need to propose a new conceptual framework. Design Discussion Paper. Data Sources The new conceptual framework links evidence from biomechanical, physiological and epidemiological evidence, through use of data from a systematic review (search conducted March 2010), a consensus study (conducted December 2010–2011) and an international expert group meeting (conducted December 2011). Implications for Nursing A new pressure ulcer conceptual framework incorporating key physiological and biomechanical components and their impact on internal strains, stresses and damage thresholds is proposed. Direct and key indirect causal factors suggested in a theoretical causal pathway are mapped to the physiological and biomechanical components of the framework. The new proposed conceptual framework provides the basis for understanding the critical determinants of pressure ulcer development and has the potential to influence risk assessment guidance and practice. It could also be used to underpin future research to explore the role of individual risk factors conceptually and operationally. Conclusion By integrating existing knowledge from epidemiological, physiological and biomechanical evidence, a theoretical causal pathway and new conceptual framework are proposed with potential implications for practice and research. PMID:24684197

Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment.

PubMed

Johnson, Samuel G B; Ahn, Woo-kyoung

2015-09-01

Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge—an interconnected causal network, where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms—causal islands—such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we tested whether people make transitive judgments about causal chains by inferring, given A causes B and B causes C, that A causes C. Specifically, causal chains schematized as one chunk or mechanism in semantic memory (e.g., exercising, becoming thirsty, drinking water) led to transitive causal judgments. On the other hand, chains schematized as multiple chunks (e.g., having sex, becoming pregnant, becoming nauseous) led to intransitive judgments despite strong intermediate links ((Experiments 1-3). Normative accounts of causal intransitivity could not explain these intransitive judgments (Experiments 4 and 5). Copyright © 2015 Cognitive Science Society, Inc.

Assessment of disruptive effects associated with urban transportation tunnel construction

DOT National Transportation Integrated Search

1976-06-01

Social, economic, and environmental impacts resulting from tunnels' being constructed for mass transportation purposes in urban areas are identified. A matrix is constructed identifying the locus of costs to affected groups by four kinds of causal ag...

Causal reasoning with forces

PubMed Central

Wolff, Phillip; Barbey, Aron K.

2015-01-01

Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed. PMID:25653611

Causal Analysis of Self-tracked Time Series Data Using a Counterfactual Framework for N-of-1 Trials.

PubMed

Daza, Eric J

2018-02-01

Many of an individual's historically recorded personal measurements vary over time, thereby forming a time series (e.g., wearable-device data, self-tracked fitness or nutrition measurements, regularly monitored clinical events or chronic conditions). Statistical analyses of such n-of-1 (i.e., single-subject) observational studies (N1OSs) can be used to discover possible cause-effect relationships to then self-test in an n-of-1 randomized trial (N1RT). However, a principled way of determining how and when to interpret an N1OS association as a causal effect (e.g., as if randomization had occurred) is needed.Our goal in this paper is to help bridge the methodological gap between risk-factor discovery and N1RT testing by introducing a basic counterfactual framework for N1OS design and personalized causal analysis.We introduce and characterize what we call the average period treatment effect (APTE), i.e., the estimand of interest in an N1RT, and build an analytical framework around it that can accommodate autocorrelation and time trends in the outcome, effect carryover from previous treatment periods, and slow onset or decay of the effect. The APTE is loosely defined as a contrast (e.g., difference, ratio) of averages of potential outcomes the individual can theoretically experience under different treatment levels during a given treatment period. To illustrate the utility of our framework for APTE discovery and estimation, two common causal inference methods are specified within the N1OS context. We then apply the framework and methods to search for estimable and interpretable APTEs using six years of the author's self-tracked weight and exercise data, and report both the preliminary findings and the challenges we faced in conducting N1OS causal discovery.Causal analysis of an individual's time series data can be facilitated by an N1RT counterfactual framework. However, for inference to be valid, the veracity of certain key assumptions must be assessed critically, and the hypothesized causal models must be interpretable and meaningful. Schattauer GmbH.

Different Approaches to Assessing the Quality of Explanations Following a Multiple-Document Inquiry Activity in Science

ERIC Educational Resources Information Center

Wiley, Jennifer; Hastings, Peter; Blaum, Dylan; Jaeger, Allison J.; Hughes, Simon; Wallace, Patricia; Griffin, Thomas D.; Britt, M. Anne

2017-01-01

This article describes several approaches to assessing student understanding using written explanations that students generate as part of a multiple-document inquiry activity on a scientific topic (global warming). The current work attempts to capture the causal structure of student explanations as a way to detect the quality of the students'…

Single-Participant Assessment of Treatment Mediators: Strategy Description and Examples from a Behavioral Activation Intervention for Depressed Adolescents

ERIC Educational Resources Information Center

Gaynor, Scott T.; Harris, Amanda

2008-01-01

Determining the means by which effective psychotherapy works is critical. A generally recommended strategy for identifying the potential causal variables is to conduct group-level statistical tests of treatment mediators. Herein the case is made for also assessing mediators of treatment outcome at the level of the individual participant.…

The Relation between Mother-Infant Interactional Characteristics in Early Infancy and Later Attachment as Assessed in the Strange Situation.

ERIC Educational Resources Information Center

Kanaya, Yuko; Miyake, Kazuo

Maternal and infant interactional characteristics in early infancy were investigated in order to examine their causal relationship with later attachment as assessed in the Strange Situation. Although the results of rating for maternal variables at four months of age exhibited significant differences between the set (S1) composed of attachment type…

Understanding causal associations between self-rated health and personal relationships in older adults: A review of evidence from longitudinal studies.

PubMed

Craigs, Cheryl L; Twiddy, Maureen; Parker, Stuart G; West, Robert M

2014-01-01

As we age we experience many life changes in our health, personal relationships, work, or home life which can impact on other aspects of our life. There is compelling evidence that how we feel about our health influences, or is influenced by, the personal relationships we experience with friends and relatives. Currently the direction this association takes is unclear. To assess the level of published evidence available on causal links between self-rated health and personal relationships in older adults. MEDLINE, CINAHL, and PsycINFO searches from inception to June 2012 and hand searches of publication lists, reference lists and citations were used to identify primary studies utilizing longitudinal data to investigate self-rated health and personal relationships in older adults. Thirty-one articles were identified. Only three articles employed methods suitable to explore causal associations between changes in self-rated health and changes in personal relationships. Two of these articles suggested that widowhood leads to a reduction in self-rated health in the short term, while the remaining article suggested a causal relationship between self-rated health and negative emotional support from family or friends, but this was complex and mediated by self-esteem and sense of control. While there is an abundance of longitudinal aging cohorts available which can be used to investigate self-rated health and personal relationships over time the potential for these databases to be used to investigate causal associations is currently not being recognized. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

DNA Methylation and BMI: Investigating Identified Methylation Sites at HIF3A in a Causal Framework.

PubMed

Richmond, Rebecca C; Sharp, Gemma C; Ward, Mary E; Fraser, Abigail; Lyttleton, Oliver; McArdle, Wendy L; Ring, Susan M; Gaunt, Tom R; Lawlor, Debbie A; Davey Smith, George; Relton, Caroline L

2016-05-01

Multiple differentially methylated sites and regions associated with adiposity have now been identified in large-scale cross-sectional studies. We tested for replication of associations between previously identified CpG sites at HIF3A and adiposity in ∼1,000 mother-offspring pairs from the Avon Longitudinal Study of Parents and Children (ALSPAC). Availability of methylation and adiposity measures at multiple time points, as well as genetic data, allowed us to assess the temporal associations between adiposity and methylation and to make inferences regarding causality and directionality. Overall, our results were discordant with those expected if HIF3A methylation has a causal effect on BMI and provided more evidence for causality in the reverse direction (i.e., an effect of BMI on HIF3A methylation). These results are based on robust evidence from longitudinal analyses and were also partially supported by Mendelian randomization analysis, although this latter analysis was underpowered to detect a causal effect of BMI on HIF3A methylation. Our results also highlight an apparent long-lasting intergenerational influence of maternal BMI on offspring methylation at this locus, which may confound associations between own adiposity and HIF3A methylation. Further work is required to replicate and uncover the mechanisms underlying the direct and intergenerational effect of adiposity on DNA methylation. © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Precautionary principles: a jurisdiction-free framework for decision-making under risk.

PubMed

Ricci, Paolo F; Cox, Louis A; MacDonald, Thomas R

2004-12-01

Fundamental principles of precaution are legal maxims that ask for preventive actions, perhaps as contingent interim measures while relevant information about causality and harm remains unavailable, to minimize the societal impact of potentially severe or irreversible outcomes. Such principles do not explain how to make choices or how to identify what is protective when incomplete and inconsistent scientific evidence of causation characterizes the potential hazards. Rather, they entrust lower jurisdictions, such as agencies or authorities, to make current decisions while recognizing that future information can contradict the scientific basis that supported the initial decision. After reviewing and synthesizing national and international legal aspects of precautionary principles, this paper addresses the key question: How can society manage potentially severe, irreversible or serious environmental outcomes when variability, uncertainty, and limited causal knowledge characterize their decision-making? A decision-analytic solution is outlined that focuses on risky decisions and accounts for prior states of information and scientific beliefs that can be updated as subsequent information becomes available. As a practical and established approach to causal reasoning and decision-making under risk, inherent to precautionary decision-making, these (Bayesian) methods help decision-makers and stakeholders because they formally account for probabilistic outcomes, new information, and are consistent and replicable. Rational choice of an action from among various alternatives--defined as a choice that makes preferred consequences more likely--requires accounting for costs, benefits and the change in risks associated with each candidate action. Decisions under any form of the precautionary principle reviewed must account for the contingent nature of scientific information, creating a link to the decision-analytic principle of expected value of information (VOI), to show the relevance of new information, relative to the initial (and smaller) set of data on which the decision was based. We exemplify this seemingly simple situation using risk management of BSE. As an integral aspect of causal analysis under risk, the methods developed in this paper permit the addition of non-linear, hormetic dose-response models to the current set of regulatory defaults such as the linear, non-threshold models. This increase in the number of defaults is an important improvement because most of the variants of the precautionary principle require cost-benefit balancing. Specifically, increasing the set of causal defaults accounts for beneficial effects at very low doses. We also show and conclude that quantitative risk assessment dominates qualitative risk assessment, supporting the extension of the set of default causal models.

Causal knowledge and the development of inductive reasoning.

PubMed

Bright, Aimée K; Feeney, Aidan

2014-06-01

We explored the development of sensitivity to causal relations in children's inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey→predator) or diagnostic (predator→prey), and the property that participants reasoned about established either a taxonomic or causal context. There was a causal asymmetry effect across all age groups, with more causal choices when the causal link was predictive than when it was diagnostic. Furthermore, context-sensitive causal reasoning showed a curvilinear development, with causal choices being most frequent for 8-year-olds regardless of context. Causal inductions decreased thereafter because 12-year-olds and adults made more taxonomic choices when reasoning in the taxonomic context. These findings suggest that simple causal relations may often be the default knowledge structure in young children's inductive reasoning, that sensitivity to causal direction is present early on, and that children over-generalize their causal knowledge when reasoning. Copyright © 2013 Elsevier Inc. All rights reserved.

Optimal causal inference: estimating stored information and approximating causal architecture.

PubMed

Still, Susanne; Crutchfield, James P; Ellison, Christopher J

2010-09-01

We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.

Health locus of control as manifested in individuals attending a state-run medical dispensary in northern India.

PubMed

Berg, Michael B; Anshika, Avi

2017-04-01

To investigate the health locus of control (HLOC) beliefs of patients and visitors at a free, state-run medical clinic in Faridabad, India, in order to establish a norm for this population and to explore potential associations between the different categories of causal health beliefs. Participants (110 men, 96 women) were interviewed in Hindi and asked a shortened version of the Multidimensional Health Locus of Control Scale assessing both internal HLOC and three aspects of external HLOC (chance, powerful others, and God). Additional variables of interest included a Traditional Values Scale, a measure of spirituality, an assessment of health status, and demographic information including gender, age, employment status, and religion. Participants rated the external-God factor as a stronger determinant of their health than the internal or other external HLOC factors. Internal HLOC was positively correlated with external HLOC in terms of chance and the role of powerful others and these associations were strongest for the most interdependent participants (i.e. women and the unemployed). For patients and visitors at the Faridabad clinic, religion played a significant role in their causal health beliefs. In addition, internal HLOC was positively associated with aspects of external locus of control, suggesting that causal health beliefs were viewed in a holistic, integrated fashion. Interventions based on these findings are suggested.

Adverse Outcome Pathways and Extrapolation Tools to Advance the Three Rs in Ecotoxicology

EPA Science Inventory

Adverse outcome pathways (AOPs) are conceptual frameworks for identifying and organizing predictive and causal linkages between cellular-level responses and endpoints conventionally considered in ecological risk assessment (e.g., effects on survival, growth/development, and repro...

The selective power of causality on memory errors.

PubMed

Marsh, Jessecae K; Kulkofsky, Sarah

2015-01-01

We tested the influence of causal links on the production of memory errors in a misinformation paradigm. Participants studied a set of statements about a person, which were presented as either individual statements or pairs of causally linked statements. Participants were then provided with causally plausible and causally implausible misinformation. We hypothesised that studying information connected with causal links would promote representing information in a more abstract manner. As such, we predicted that causal information would not provide an overall protection against memory errors, but rather would preferentially help in the rejection of misinformation that was causally implausible, given the learned causal links. In two experiments, we measured whether the causal linkage of information would be generally protective against all memory errors or only selectively protective against certain types of memory errors. Causal links helped participants reject implausible memory lures, but did not protect against plausible lures. Our results suggest that causal information may promote an abstract storage of information that helps prevent only specific types of memory errors.

Learning to learn causal models.

PubMed

Kemp, Charles; Goodman, Noah D; Tenenbaum, Joshua B

2010-09-01

Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. Copyright © 2010 Cognitive Science Society, Inc.

Experimental verification of an indefinite causal order

PubMed Central

Rubino, Giulia; Rozema, Lee A.; Feix, Adrien; Araújo, Mateus; Zeuner, Jonas M.; Procopio, Lorenzo M.; Brukner, Časlav; Walther, Philip

2017-01-01

Investigating the role of causal order in quantum mechanics has recently revealed that the causal relations of events may not be a priori well defined in quantum theory. Although this has triggered a growing interest on the theoretical side, creating processes without a causal order is an experimental task. We report the first decisive demonstration of a process with an indefinite causal order. To do this, we quantify how incompatible our setup is with a definite causal order by measuring a “causal witness.” This mathematical object incorporates a series of measurements that are designed to yield a certain outcome only if the process under examination is not consistent with any well-defined causal order. In our experiment, we perform a measurement in a superposition of causal orders—without destroying the coherence—to acquire information both inside and outside of a “causally nonordered process.” Using this information, we experimentally determine a causal witness, demonstrating by almost 7 SDs that the experimentally implemented process does not have a definite causal order. PMID:28378018

Fine-Scale Mapping at 9p22.2 Identifies Candidate Causal Variants That Modify Ovarian Cancer Risk in BRCA1 and BRCA2 Mutation Carriers

PubMed Central

Vigorito, Elena; Kuchenbaecker, Karoline B.; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A.; Andrulis, Irene L.; Arun, Banu K.; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A.; Campbell, Ian; Chan, Salina B.; Claes, Kathleen B. M.; Cohn, David E.; Cook, Jackie; Daly, Mary B.; Damiola, Francesca; Davidson, Rosemarie; de Pauw, Antoine; Delnatte, Capucine; Diez, Orland; Domchek, Susan M.; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F.; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D. Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D.; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A.; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K.; Goldgar, David E.; Hake, Christopher R.; Hansen, Thomas V. O.; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B. L.; Houdayer, Claude; Hulick, Peter J.; Imyanitov, Evgeny N.; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M.; Vijai, Joseph; Karlan, Beth Y.; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L.; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R.; Montagna, Marco; Nathanson, Katherine L.; Neuhausen, Susan L.; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I.; Ong, Kai-ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M.; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C.; Rookus, Matti A.; Ross, Eric A.; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F.; Slavin, Thomas P.; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I.; Tea, Muy-Kheng; Teixeira, Manuel R.; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J.; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N.; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J.; Greene, Mark H.; Couch, Fergus J.; Offit, Kenneth; Pharoah, Paul D. P.; Chenevix-Trench, Georgia; Antoniou, Antonis C.

2016-01-01

Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10−16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10−6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population. PMID:27463617

Fine-Scale Mapping at 9p22.2 Identifies Candidate Causal Variants That Modify Ovarian Cancer Risk in BRCA1 and BRCA2 Mutation Carriers.

PubMed

Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A; Andrulis, Irene L; Arun, Banu K; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A; Campbell, Ian; Chan, Salina B; Claes, Kathleen B M; Cohn, David E; Cook, Jackie; Daly, Mary B; Damiola, Francesca; Davidson, Rosemarie; Pauw, Antoine de; Delnatte, Capucine; Diez, Orland; Domchek, Susan M; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K; Goldgar, David E; Hake, Christopher R; Hansen, Thomas V O; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B L; Houdayer, Claude; Hulick, Peter J; Imyanitov, Evgeny N; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M; Vijai, Joseph; Karlan, Beth Y; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R; Montagna, Marco; Nathanson, Katherine L; Neuhausen, Susan L; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I; Ong, Kai-Ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C; Rookus, Matti A; Ross, Eric A; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F; Slavin, Thomas P; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I; Tea, Muy-Kheng; Teixeira, Manuel R; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J; Greene, Mark H; Couch, Fergus J; Offit, Kenneth; Pharoah, Paul D P; Chenevix-Trench, Georgia; Antoniou, Antonis C

2016-01-01

Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10-16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10-6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population.

Helicobacter pylori infection as a cause of gastritis, duodenal ulcer, gastric cancer and nonulcer dyspepsia: a systematic overview.

PubMed

Veldhuyzen van Zanten, S J; Sherman, P M

1994-01-15

To evaluate current evidence for a causal relation between Helicobacter pylori infection and gastritis, duodenal ulcer, gastric cancer and nonulcer dyspepsia. A MEDLINE search for articles published in English between January 1983 and December 1992 with the use of MeSH terms Helicobacter pylori, gastritis, duodenal ulcer, gastric cancer, dyspepsia and clinical trial; abstracts were excluded. Six journals and Current Contents were searched manually for pertinent articles published in that time frame. Original studies with at least 25 patients, case reports and reviews that examined the relation between H. pylori and the four gastrointestinal disorders; 350 articles were on gastritis, 122 on duodenal ulcer, 44 on gastric cancer and 96 on nonulcer dyspepsia. The quality of the studies was rated independently on a four-point scale. The strength of the evidence was assessed using a six-point scale for each of the eight established guidelines for determining a causal relation. There was conclusive evidence of a causal relation between H. pylori infection and histologic gastritis. Koch's postulates for the identification of a microorganism as the causative agent of a disease were fulfilled for H. pylori as a causative agent of gastritis. There was strong evidence that H. pylori is the main cause of duodenal ulcers not induced by nonsteroidal anti-inflammatory drugs, but all of Koch's postulates were not fulfilled. There was moderate epidemiologic evidence of an association between chronic H. pylori infection and gastric cancer. There was a lack of convincing evidence of a causal association between H. pylori and nonulcer dyspepsia. The evidence supports a strong causal relation between H. pylori infection and gastritis and duodenal ulcer and a moderate relation between such infection and gastric cancer. Further studies are needed to clarify the role of H. pylori in these disorders. Thus far, there is no evidence of a causal relation between H. pylori and nonulcer dyspepsia.

Understanding bias in relationships between the food environment and diet quality: the Coronary Artery Risk Development in Young Adults (CARDIA) study.

PubMed

Rummo, Pasquale E; Guilkey, David K; Ng, Shu Wen; Meyer, Katie A; Popkin, Barry M; Reis, Jared P; Shikany, James M; Gordon-Larsen, Penny

2017-12-01

The relationship between food environment exposures and diet behaviours is unclear, possibly because the majority of studies ignore potential residual confounding. We used 20 years (1985-1986, 1992-1993 2005-2006) of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study across four US cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California) and instrumental variables (IV) regression to obtain causal estimates of longitudinal associations between the percentage of neighbourhood food outlets (per total food outlets within 1 km network distance of respondent residence) and an a priori diet quality score, with higher scores indicating higher diet quality. To assess the presence and magnitude of bias related to residual confounding, we compared results from causal models (IV regression) to non-causal models, including ordinary least squares regression, which does not account for residual confounding at all and fixed-effects regression, which only controls for time-invariant unmeasured characteristics. The mean diet quality score across follow-up was 63.4 (SD=12.7). A 10% increase in fast food restaurants (relative to full-service restaurants) was associated with a lower diet quality score over time using IV regression (β=-1.01, 95% CI -1.99 to -0.04); estimates were attenuated using non-causal models. The percentage of neighbourhood convenience and grocery stores (relative to supermarkets) was not associated with diet quality in any model, but estimates from non-causal models were similarly attenuated compared with causal models. Ignoring residual confounding may generate biased estimated effects of neighbourhood food outlets on diet outcomes and may have contributed to weak findings in the food environment literature. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Causal interpretation of correlational studies – Analysis of medical news on the website of the official journal for German physicians

PubMed Central

Rahn, Anne Christin; Bock, Merle; Mühlhauser, Ingrid

2018-01-01

Background Media frequently draws inappropriate causal statements from observational studies. We analyzed the reporting of study results in the Medical News section of the German medical journal Deutsches Ärzteblatt (DÄ). Methods Study design: Retrospective quantitative content analysis of randomly selected news reports and related original journal articles and press releases. A medical news report was selected if headlines comprised at least two linked variables. Two raters independently categorized the headline and text of each news report, conclusions of the abstract and full text of the related journal article, and the press release. The assessment instrument comprised five categories from ‘neutral’ to ‘unconditionally causal’. Outcome measures: degree of matching between 1) news headlines and conclusions of the journal article, 2) headlines and text of news reports, 3) text and conclusions, and 4) headlines and press releases. We analyzed whether news headlines rated as unconditionally causal based on randomized controlled trials (RCTs). Results One-thousand eighty-seven medical news reports were published between April 2015 and May 2016. The final random sample comprised 176 news reports and 100 related press releases. Degree of matching: 1) 45% (79/176) for news headlines and journal article conclusions, 2) 55% (97/176) for headlines and text, 3) 53% (93/176) for text and conclusions, and 4) 41% (41/100) for headlines and press releases. Exaggerations were found in 45% (80/176) of the headlines compared to the conclusions of the related journal article. Sixty-five of 137 unconditionally causal statements of the news headlines were phrased more weakly in the subsequent news text body. Only 52 of 137 headlines (38%) categorized as unconditionally causal reported RCTs. Conclusion Reporting of medical news in the DÄ medical journal is misleading. Most headlines that imply causal associations were not based on RCTs. Medical journalists should follow standards of reporting scientific study results. PMID:29723258

Helicobacter pylori infection as a cause of gastritis, duodenal ulcer, gastric cancer and nonulcer dyspepsia: a systematic overview.

PubMed Central

Veldhuyzen van Zanten, S J; Sherman, P M

1994-01-01

OBJECTIVE: To evaluate current evidence for a causal relation between Helicobacter pylori infection and gastritis, duodenal ulcer, gastric cancer and nonulcer dyspepsia. DATA SOURCES: A MEDLINE search for articles published in English between January 1983 and December 1992 with the use of MeSH terms Helicobacter pylori, gastritis, duodenal ulcer, gastric cancer, dyspepsia and clinical trial; abstracts were excluded. Six journals and Current Contents were searched manually for pertinent articles published in that time frame. STUDY SELECTION: Original studies with at least 25 patients, case reports and reviews that examined the relation between H. pylori and the four gastrointestinal disorders; 350 articles were on gastritis, 122 on duodenal ulcer, 44 on gastric cancer and 96 on nonulcer dyspepsia. DATA EXTRACTION: The quality of the studies was rated independently on a four-point scale. The strength of the evidence was assessed using a six-point scale for each of the eight established guidelines for determining a causal relation. DATA SYNTHESIS: There was conclusive evidence of a causal relation between H. pylori infection and histologic gastritis. Koch's postulates for the identification of a microorganism as the causative agent of a disease were fulfilled for H. pylori as a causative agent of gastritis. There was strong evidence that H. pylori is the main cause of duodenal ulcers not induced by nonsteroidal anti-inflammatory drugs, but all of Koch's postulates were not fulfilled. There was moderate epidemiologic evidence of an association between chronic H. pylori infection and gastric cancer. There was a lack of convincing evidence of a causal association between H. pylori and nonulcer dyspepsia. CONCLUSIONS: The evidence supports a strong causal relation between H. pylori infection and gastritis and duodenal ulcer and a moderate relation between such infection and gastric cancer. Further studies are needed to clarify the role of H. pylori in these disorders. Thus far, there is no evidence of a causal relation between H. pylori and nonulcer dyspepsia. PMID:8287340

A quantum causal discovery algorithm

NASA Astrophysics Data System (ADS)

Giarmatzi, Christina; Costa, Fabio

2018-03-01

Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.

Structure and Strength in Causal Induction

ERIC Educational Resources Information Center

Griffiths, Thomas L.; Tenenbaum, Joshua B.

2005-01-01

We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…

Causal simulation and sensor planning in predictive monitoring

NASA Technical Reports Server (NTRS)

Doyle, Richard J.

1989-01-01

Two issues are addressed which arise in the task of detecting anomalous behavior in complex systems with numerous sensor channels: how to adjust alarm thresholds dynamically, within the changing operating context of the system, and how to utilize sensors selectively, so that nominal operation can be verified reliably without processing a prohibitive amount of sensor data. The approach involves simulation of a causal model of the system, which provides information on expected sensor values, and on dependencies between predicted events, useful in assessing the relative importance of events so that sensor resources can be allocated effectively. The potential applicability of this work to the execution monitoring of robot task plans is briefly discussed.

Assessing the Impact of Drug Use and Drug Selling on Violent Offending in a Panel of Delinquent Youth

PubMed Central

Phillips, Matthew D.

2016-01-01

Despite a vast number of empirical studies arguing for or against a causal relationship between illegal drug use and selling and violent behavior, the debate continues. In part this is due to methodological weaknesses of previous research. Using data from the Rochester Youth Development Study, the current study seeks to improve on prior research designs to allow for a more precise examination of the mechanisms that lead from an individual’s drug use (chiefly, marijuana use in the current sample) and drug selling to violent action. Results will allow for greater confidence in making causal inference regarding a long-standing concern in the discipline. PMID:26889079

Exploratory Causal Analysis in Bivariate Time Series Data

NASA Astrophysics Data System (ADS)

McCracken, James M.

Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data sets, but little research exists of how these tools compare to each other in practice. This work introduces and defines exploratory causal analysis (ECA) to address this issue along with the concept of data causality in the taxonomy of causal studies introduced in this work. The motivation is to provide a framework for exploring potential causal structures in time series data sets. ECA is used on several synthetic and empirical data sets, and it is found that all of the tested time series causality tools agree with each other (and intuitive notions of causality) for many simple systems but can provide conflicting causal inferences for more complicated systems. It is proposed that such disagreements between different time series causality tools during ECA might provide deeper insight into the data than could be found otherwise.

A Decision Support Framework For Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

EPA Science Inventory

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environ...

Stressor Identification (Si) at Contaminated Sites: Upper Arkansas River, Colorado (Final)

EPA Science Inventory

EPA announced the availability of the final report, Stressor Identification (SI) at Contaminated Sites: Upper Arkansas River, Colorado. This report describes a causal assessment for impairments of plant growth and plant species richness at a terrestrial contaminated site ...

Assessment of Sensorimotor Abilities of Severely Retarded Children and Adolescents.

ERIC Educational Resources Information Center

Hupp, Susan C.; And Others

1984-01-01

An investigation of the order of acquisition of domains by severely retarded children and adolescents indicated that object permanence performance always equaled or exceeded means-ends, which in turn always equaled or exceeded causality for 23 of 25 subjects. (Author/CL)

A Critique of the Diagnostic Construct Schizophrenia

ERIC Educational Resources Information Center

Wong, Stephen E.

2014-01-01

This article examines problems in the clinical utility of the diagnosis of schizophrenia including reliance on questionable data, arbitrary criteria and categorization, inadequate precision for assessment and treatment evaluation, and omission of information on causal current and historical environmental factors. Some alternatives to the…

Causality links among renewable energy consumption, CO2 emissions, and economic growth in Africa: evidence from a panel ARDL-PMG approach.

PubMed

Attiaoui, Imed; Toumi, Hassen; Ammouri, Bilel; Gargouri, Ilhem

2017-05-01

This research examines the causality (For the remainder of the paper, the notion of causality refers to Granger causality.) links among renewable energy consumption (REC), CO 2 emissions (CE), non-renewable energy consumption (NREC), and economic growth (GDP) using an autoregressive distributed lag model based on the pooled mean group estimation (ARDL-PMG) and applying Granger causality tests for a panel consisting of 22 African countries for the period between 1990 and 2011. There is unidirectional and irreversible short-run causality from CE to GDP. The causal direction between CE and REC is unobservable over the short-term. Moreover, we find unidirectional, short-run causality from REC to GDP. When testing per pair of variables, there are short-run bidirectional causalities among REC, CE, and GDP. However, if we add CE to the variables REC and NREC, the causality to GDP is observable, and causality from the pair REC and NREC to economic growth is neutral. Likewise, if we add NREC to the variables GDP and REC, there is causality. There are bidirectional long-run causalities among REC, CE, and GDP, which supports the feedback assumption. Causality from GDP to REC is not strong for the panel. If we test per pair of variables, the strong causality from GDP and CE to REC is neutral. The long-run PMG estimates show that NREC and gross domestic product increase CE, whereas REC decreases CE.

Causal learning and inference as a rational process: the new synthesis.

PubMed

Holyoak, Keith J; Cheng, Patricia W

2011-01-01

Over the past decade, an active line of research within the field of human causal learning and inference has converged on a general representational framework: causal models integrated with bayesian probabilistic inference. We describe this new synthesis, which views causal learning and inference as a fundamentally rational process, and review a sample of the empirical findings that support the causal framework over associative alternatives. Causal events, like all events in the distal world as opposed to our proximal perceptual input, are inherently unobservable. A central assumption of the causal approach is that humans (and potentially nonhuman animals) have been designed in such a way as to infer the most invariant causal relations for achieving their goals based on observed events. In contrast, the associative approach assumes that learners only acquire associations among important observed events, omitting the representation of the distal relations. By incorporating bayesian inference over distributions of causal strength and causal structures, along with noisy-logical (i.e., causal) functions for integrating the influences of multiple causes on a single effect, human judgments about causal strength and structure can be predicted accurately for relatively simple causal structures. Dynamic models of learning based on the causal framework can explain patterns of acquisition observed with serial presentation of contingency data and are consistent with available neuroimaging data. The approach has been extended to a diverse range of inductive tasks, including category-based and analogical inferences.

Effects of risk factors for and components of metabolic syndrome on the quality of life of patients with systemic lupus erythematosus: a structural equation modeling approach.

PubMed

Lee, Jeong-Won; Kang, Ji-Hyoun; Lee, Kyung-Eun; Park, Dong-Jin; Kang, Seong Wook; Kwok, Seung-Ki; Kim, Seong-Kyu; Choe, Jung-Yoon; Kim, Hyoun-Ah; Sung, Yoon-Kyoung; Shin, Kichul; Lee, Sang-Il; Lee, Chang Hoon; Choi, Sung Jae; Lee, Shin-Seok

2018-01-01

This study assessed the relationships among the risk factors for and components of metabolic syndrome (MetS) and health-related quality of life (HRQOL) in a hypothesized causal model using structural equation modeling (SEM) in patients with systemic lupus erythematosus (SLE). Of the 505 SLE patients enrolled in the Korean Lupus Network (KORNET registry), 244 had sufficient data to assess the components of MetS at enrollment. Education level, monthly income, corticosteroid dose, Systemic Lupus Erythematosus Disease Activity Index, Physicians' Global Assessment, Beck Depression Inventory, MetS components, and the Short Form-36 at the time of cohort entry were determined. SEM was used to test the causal relationship based on the Analysis of Moment Structure. The average age of the 244 patients was 40.7 ± 11.8 years. The SEM results supported the good fit of the model (χ 2  = 71.629, p = 0.078, RMSEA 0.034, CFI 0.972). The final model showed a direct negative effect of higher socioeconomic status and a positive indirect effect of higher disease activity on MetS, the latter through corticosteroid dose. MetS did not directly impact HRQOL but had an indirect negative impact on it, through depression. In our causal model, MetS risk factors were related to MetS components. The latter had a negative indirect impact on HRQOL, through depression. Clinicians should consider socioeconomic status and medication and seek to modify disease activity, MetS, and depression to improve the HRQOL of SLE patients.

Adverse effects of plant food supplements and botanical preparations: a systematic review with critical evaluation of causality

PubMed Central

Di Lorenzo, Chiara; Ceschi, Alessandro; Kupferschmidt, Hugo; Lüde, Saskia; De Souza Nascimento, Elizabeth; Dos Santos, Ariana; Colombo, Francesca; Frigerio, Gianfranco; Nørby, Karin; Plumb, Jenny; Finglas, Paul; Restani, Patrizia

2015-01-01

AIMS The objective of this review was to collect available data on the following: (i) adverse effects observed in humans from the intake of plant food supplements or botanical preparations; (ii) the misidentification of poisonous plants; and (iii) interactions between plant food supplements/botanicals and conventional drugs or nutrients. METHODS PubMed/MEDLINE and Embase were searched from database inception to June 2014, using the terms ‘adverse effect/s’, ‘poisoning/s’, ‘plant food supplement/s’, ‘misidentification/s’ and ‘interaction/s’ in combination with the relevant plant name. All papers were critically evaluated according to the World Health Organization Guidelines for causality assessment. RESULTS Data were obtained for 66 plants that are common ingredients of plant food supplements; of the 492 papers selected, 402 (81.7%) dealt with adverse effects directly associated with the botanical and 89 (18.1%) concerned interactions with conventional drugs. Only one case was associated with misidentification. Adverse effects were reported for 39 of the 66 botanical substances searched. Of the total references, 86.6% were associated with 14 plants, including Glycine max/soybean (19.3%), Glycyrrhiza glabra/liquorice (12.2%), Camellia sinensis/green tea ( 8.7%) and Ginkgo biloba/gingko (8.5%). CONCLUSIONS Considering the length of time examined and the number of plants included in the review, it is remarkable that: (i) the adverse effects due to botanical ingredients were relatively infrequent, if assessed for causality; and (ii) the number of severe clinical reactions was very limited, but some fatal cases have been described. Data presented in this review were assessed for quality in order to make the results maximally useful for clinicians in identifying or excluding deleterious effects of botanicals. PMID:25251944

Stable Causal Relationships Are Better Causal Relationships.

PubMed

Vasilyeva, Nadya; Blanchard, Thomas; Lombrozo, Tania

2018-05-01

We report three experiments investigating whether people's judgments about causal relationships are sensitive to the robustness or stability of such relationships across a range of background circumstances. In Experiment 1, we demonstrate that people are more willing to endorse causal and explanatory claims based on stable (as opposed to unstable) relationships, even when the overall causal strength of the relationship is held constant. In Experiment 2, we show that this effect is not driven by a causal generalization's actual scope of application. In Experiment 3, we offer evidence that stable causal relationships may be seen as better guides to action. Collectively, these experiments document a previously underappreciated factor that shapes people's causal reasoning: the stability of the causal relationship. Copyright © 2018 Cognitive Science Society, Inc.

Behavioral and Neural Correlates of Executive Function: Interplay between Inhibition and Updating Processes.

PubMed

Kim, Na Young; Wittenberg, Ellen; Nam, Chang S

2017-01-01

This study investigated the interaction between two executive function processes, inhibition and updating, through analyses of behavioral, neurophysiological, and effective connectivity metrics. Although, many studies have focused on behavioral effects of executive function processes individually, few studies have examined the dynamic causal interactions between these two functions. A total of twenty participants from a local university performed a dual task combing flanker and n-back experimental paradigms, and completed the Operation Span Task designed to measure working memory capacity. We found that both behavioral (accuracy and reaction time) and neurophysiological (P300 amplitude and alpha band power) metrics on the inhibition task (i.e., flanker task) were influenced by the updating load (n-back level) and modulated by working memory capacity. Using independent component analysis, source localization (DIPFIT), and Granger Causality analysis of the EEG time-series data, the present study demonstrated that manipulation of cognitive demand in a dual executive function task influenced the causal neural network. We compared connectivity across three updating loads (n-back levels) and found that experimental manipulation of working memory load enhanced causal connectivity of a large-scale neurocognitive network. This network contains the prefrontal and parietal cortices, which are associated with inhibition and updating executive function processes. This study has potential applications in human performance modeling and assessment of mental workload, such as the design of training materials and interfaces for those performing complex multitasking under stress.

Assessment of Surface Water Storage trends for increasing groundwater areas in India

NASA Astrophysics Data System (ADS)

Banerjee, Chandan; Kumar, D. Nagesh

2018-07-01

Recent studies based on Gravity Recovery and Climate Experiment (GRACE) satellite mission suggested that groundwater has increased in central and southern parts of India. However, surface water, which is an equally important source of water in these semi-arid areas has not been studied yet. In the present study, the study areas were outlined based on trends in GRACE data followed by trend identification in surface water storages and checking the hypothesis of causality. Surface Water Extent (SWE) and Surface Soil Moisture (SSM) derived from Moderate-resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) respectively, are selected as proxies of surface water storage (SWS). Besides SWE and SSM, trend test was performed for GRACE derived terrestrial water storage (TWS) for the study areas named as R1, R2, GOR1 and KOR1. Granger-causality test is used to test the hypothesis that rainfall is a causal factor of the inter-annual variability of SWE, SSM and TWS. Positive trends were observed in TWS for R1, R2 and GOR1 whereas SWE and SSM show increasing trends for all the study regions. Results suggest that rainfall is the granger-causal of all the storage variables for R1 and R2, the regions exhibiting the most significant positive trends in TWS.

Genetics of Triglycerides and the Risk of Atherosclerosis.

PubMed

Dron, Jacqueline S; Hegele, Robert A

2017-07-01

Plasma triglycerides are routinely measured with a lipid profile, and elevated plasma triglycerides are commonly encountered in the clinic. The confounded nature of this trait, which is correlated with numerous other metabolic perturbations, including depressed high-density lipoprotein cholesterol (HDL-C), has thwarted efforts to directly implicate triglycerides as causal in atherogenesis. Human genetic approaches involving large-scale populations and high-throughput genomic assessment under a Mendelian randomization framework have undertaken to sort out questions of causality. We review recent large-scale meta-analyses of cohorts and population-based sequencing studies designed to address whether common and rare variants in genes whose products are determinants of plasma triglycerides are also associated with clinical cardiovascular endpoints. The studied loci include genes encoding lipoprotein lipase and proteins that interact with it, such as apolipoprotein (apo) A-V, apo C-III and angiopoietin-like proteins 3 and 4, and common polymorphisms identified in genome-wide association studies. Triglyceride-raising variant alleles of these genes showed generally strong associations with clinical cardiovascular endpoints. However, in most cases, a second lipid disturbance-usually depressed HDL-C-was concurrently associated. While the findings collectively shift our understanding towards a potential causal role for triglycerides, we still cannot rule out the possibilities that triglycerides are a component of a joint phenotype with low HDL-C or that they are but markers of deeper causal metabolic disturbances that are not routinely measured in epidemiological-scale genetic studies.

Attention to irrelevant cues is related to positive symptoms in schizophrenia.

PubMed

Morris, Richard; Griffiths, Oren; Le Pelley, Michael E; Weickert, Thomas W

2013-05-01

Many modern learning theories assume that the amount of attention to a cue depends on how well that cue predicted important events in the past. Schizophrenia is associated with deficits in attention and recent theories of psychosis have argued that positive symptoms such as delusions and hallucinations are related to a failure of selective attention. However, evidence demonstrating that attention to irrelevant cues is related to positive symptoms in schizophrenia is lacking. We used a novel method of measuring attention to nonpredictive (and thus irrelevant) cues in a causal learning test (Le Pelley ME, McLaren IP. Learned associability and associative change in human causal learning. Q J Exp Psychol B. 2003;56:68-79) to assess whether healthy adults and people with schizophrenia discriminate previously predictive and nonpredictive cues. In a series of experiments with independent samples, we demonstrated: (1) when people with schizophrenia who had severe positive symptoms successfully distinguished between predictive and nonpredictive cues during training, they failed to discriminate between predictive and nonpredictive cues relative to healthy adults during subsequent testing and (2) learning about nonpredictive cues was correlated with more severe positive symptoms scores in schizophrenia. These results suggest that positive symptoms of schizophrenia are related to increased attention to nonpredictive cues during causal learning. This deficit in selective attention results in learning irrelevant causal associations and may be the basis of positive symptoms in schizophrenia.

Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals

PubMed Central

Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F.; Ramchand, Rajeev; Yuen, Robert A.; Murphy, Susan A.

2014-01-01

This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. PMID:23873437

Quantitative EEG analysis using error reduction ratio-causality test; validation on simulated and real EEG data.

PubMed

Sarrigiannis, Ptolemaios G; Zhao, Yifan; Wei, Hua-Liang; Billings, Stephen A; Fotheringham, Jayne; Hadjivassiliou, Marios

2014-01-01

To introduce a new method of quantitative EEG analysis in the time domain, the error reduction ratio (ERR)-causality test. To compare performance against cross-correlation and coherence with phase measures. A simulation example was used as a gold standard to assess the performance of ERR-causality, against cross-correlation and coherence. The methods were then applied to real EEG data. Analysis of both simulated and real EEG data demonstrates that ERR-causality successfully detects dynamically evolving changes between two signals, with very high time resolution, dependent on the sampling rate of the data. Our method can properly detect both linear and non-linear effects, encountered during analysis of focal and generalised seizures. We introduce a new quantitative EEG method of analysis. It detects real time levels of synchronisation in the linear and non-linear domains. It computes directionality of information flow with corresponding time lags. This novel dynamic real time EEG signal analysis unveils hidden neural network interactions with a very high time resolution. These interactions cannot be adequately resolved by the traditional methods of coherence and cross-correlation, which provide limited results in the presence of non-linear effects and lack fidelity for changes appearing over small periods of time. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Causality Analysis of Neural Connectivity: Critical Examination of Existing Methods and Advances of New Methods

PubMed Central

Hu, Sanqing; Dai, Guojun; Worrell, Gregory A.; Dai, Qionghai; Liang, Hualou

2012-01-01

Granger causality (GC) is one of the most popular measures to reveal causality influence of time series and has been widely applied in economics and neuroscience. Especially, its counterpart in frequency domain, spectral GC, as well as other Granger-like causality measures have recently been applied to study causal interactions between brain areas in different frequency ranges during cognitive and perceptual tasks. In this paper, we show that: 1) GC in time domain cannot correctly determine how strongly one time series influences the other when there is directional causality between two time series, and 2) spectral GC and other Granger-like causality measures have inherent shortcomings and/or limitations because of the use of the transfer function (or its inverse matrix) and partial information of the linear regression model. On the other hand, we propose two novel causality measures (in time and frequency domains) for the linear regression model, called new causality and new spectral causality, respectively, which are more reasonable and understandable than GC or Granger-like measures. Especially, from one simple example, we point out that, in time domain, both new causality and GC adopt the concept of proportion, but they are defined on two different equations where one equation (for GC) is only part of the other (for new causality), thus the new causality is a natural extension of GC and has a sound conceptual/theoretical basis, and GC is not the desired causal influence at all. By several examples, we confirm that new causality measures have distinct advantages over GC or Granger-like measures. Finally, we conduct event-related potential causality analysis for a subject with intracranial depth electrodes undergoing evaluation for epilepsy surgery, and show that, in the frequency domain, all measures reveal significant directional event-related causality, but the result from new spectral causality is consistent with event-related time–frequency power spectrum activity. The spectral GC as well as other Granger-like measures are shown to generate misleading results. The proposed new causality measures may have wide potential applications in economics and neuroscience. PMID:21511564

What Do Patients Think about the Cause of Their Mental Disorder? A Qualitative and Quantitative Analysis of Causal Beliefs of Mental Disorder in Inpatients in Psychosomatic Rehabilitation.

PubMed

Magaard, Julia Luise; Schulz, Holger; Brütt, Anna Levke

2017-01-01

Patients' causal beliefs about their mental disorders are important for treatment because they affect illness-related behaviours. However, there are few studies exploring patients' causal beliefs about their mental disorder. (a) To qualitatively explore patients' causal beliefs of their mental disorder, (b) to explore frequencies of patients stating causal beliefs, and (c) to investigate differences of causal beliefs according to patients' primary diagnoses. Inpatients in psychosomatic rehabilitation were asked an open-ended question about their three most important causal beliefs about their mental illness. Answers were obtained from 678 patients, with primary diagnoses of depression (N = 341), adjustment disorder (N = 75), reaction to severe stress (N = 57) and anxiety disorders (N = 40). Two researchers developed a category system inductively and categorised the reported causal beliefs. Qualitative analysis has been supplemented by logistic regression analyses. The causal beliefs were organized into twelve content-related categories. Causal beliefs referring to "problems at work" (47%) and "problems in social environment" (46%) were most frequently mentioned by patients with mental disorders. 35% of patients indicate causal beliefs related to "self/internal states". Patients with depression and patients with anxiety disorders stated similar causal beliefs, whereas patients with reactions to severe stress and adjustment disorders stated different causal beliefs in comparison to patients with depression. There was no opportunity for further exploration, because we analysed written documents. These results add a detailed insight to mentally ill patients' causal beliefs to illness perception literature. Additionally, evidence about differences in frequencies of causal beliefs between different illness groups complement previous findings. For future research it is important to clarify the relation between patients' causal beliefs and the chosen treatment.

What Do Patients Think about the Cause of Their Mental Disorder? A Qualitative and Quantitative Analysis of Causal Beliefs of Mental Disorder in Inpatients in Psychosomatic Rehabilitation

PubMed Central

Magaard, Julia Luise; Schulz, Holger; Brütt, Anna Levke

2017-01-01

Background Patients’ causal beliefs about their mental disorders are important for treatment because they affect illness-related behaviours. However, there are few studies exploring patients’ causal beliefs about their mental disorder. Objectives (a) To qualitatively explore patients’ causal beliefs of their mental disorder, (b) to explore frequencies of patients stating causal beliefs, and (c) to investigate differences of causal beliefs according to patients’ primary diagnoses. Method Inpatients in psychosomatic rehabilitation were asked an open-ended question about their three most important causal beliefs about their mental illness. Answers were obtained from 678 patients, with primary diagnoses of depression (N = 341), adjustment disorder (N = 75), reaction to severe stress (N = 57) and anxiety disorders (N = 40). Two researchers developed a category system inductively and categorised the reported causal beliefs. Qualitative analysis has been supplemented by logistic regression analyses. Results The causal beliefs were organized into twelve content-related categories. Causal beliefs referring to “problems at work” (47%) and “problems in social environment” (46%) were most frequently mentioned by patients with mental disorders. 35% of patients indicate causal beliefs related to “self/internal states”. Patients with depression and patients with anxiety disorders stated similar causal beliefs, whereas patients with reactions to severe stress and adjustment disorders stated different causal beliefs in comparison to patients with depression. Limitations There was no opportunity for further exploration, because we analysed written documents. Conclusions These results add a detailed insight to mentally ill patients’ causal beliefs to illness perception literature. Additionally, evidence about differences in frequencies of causal beliefs between different illness groups complement previous findings. For future research it is important to clarify the relation between patients’ causal beliefs and the chosen treatment. PMID:28056066

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

PubMed

Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L

2016-03-01

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015 Cognitive Science Society, Inc.

The causal role of smoking on the risk of hip or knee replacement due to primary osteoarthritis: a Mendelian randomisation analysis of the HUNT study.

PubMed

Johnsen, M B; Vie, G Å; Winsvold, B S; Bjørngaard, J H; Åsvold, B O; Gabrielsen, M E; Pedersen, L M; Hellevik, A I; Langhammer, A; Furnes, O; Flugsrud, G B; Skorpen, F; Romundstad, P R; Storheim, K; Nordsletten, L; Zwart, J A

2017-06-01

Smoking has been associated with a reduced risk of hip and knee osteoarthritis (OA) and subsequent joint replacement. The aim of the present study was to assess whether the observed association is likely to be causal. 55,745 participants of a population-based cohort were genotyped for the rs1051730 C > T single-nucleotide polymorphism (SNP), a proxy for smoking quantity among smokers. A Mendelian randomization analysis was performed using rs1051730 as an instrument to evaluate the causal role of smoking on the risk of hip or knee replacement (combined as total joint replacement (TJR)). Association between rs1051730 T alleles and TJR was estimated by hazard ratios (HRs) and 95% confidence intervals (CIs). All analyses were adjusted for age and sex. Smoking quantity (no. of cigarettes) was inversely associated with TJR (HR 0.97, 95% CI 0.97-0.98). In the Mendelian randomization analysis, rs1051730 T alleles were associated with reduced risk of TJR among current smokers (HR 0.84, 95% CI 0.76-0.98, per T allele), however we found no evidence of association among former (HR 0.97, 95% CI 0.88-1.07) and never smokers (HR 0.97, 95% CI 0.89-1.06). Neither adjusting for body mass index (BMI), cardiovascular disease (CVD) nor accounting for the competing risk of mortality substantially changed the results. This study suggests that smoking may be causally associated with the reduced risk of TJR. Our findings add support to the inverse association found in previous observational studies. More research is needed to further elucidate the underlying mechanisms of this causal association. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Weight-of-evidence evaluation of short-term ozone exposure and cardiovascular effects.

PubMed

Goodman, Julie E; Prueitt, Robyn L; Sax, Sonja N; Lynch, Heather N; Zu, Ke; Lemay, Julie C; King, Joseph M; Venditti, Ferdinand J

2014-10-01

There is a relatively large body of research on the potential cardiovascular (CV) effects associated with short-term ozone exposure (defined by EPA as less than 30 days in duration). We conducted a weight-of-evidence (WoE) analysis to assess whether it supports a causal relationship using a novel WoE framework adapted from the US EPA's National Ambient Air Quality Standards causality framework. Specifically, we synthesized and critically evaluated the relevant epidemiology, controlled human exposure, and experimental animal data and made a causal determination using the same categories proposed by the Institute of Medicine report Improving the Presumptive Disability Decision-making Process for Veterans ( IOM 2008). We found that the totality of the data indicates that the results for CV effects are largely null across human and experimental animal studies. The few statistically significant associations reported in epidemiology studies of CV morbidity and mortality are very small in magnitude and likely attributable to confounding, bias, or chance. In experimental animal studies, the reported statistically significant effects at high exposures are not observed at lower exposures and thus not likely relevant to current ambient ozone exposures in humans. The available data also do not support a biologically plausible mechanism for CV effects of ozone. Overall, the current WoE provides no convincing case for a causal relationship between short-term exposure to ambient ozone and adverse effects on the CV system in humans, but the limitations of the available studies preclude definitive conclusions regarding a lack of causation. Thus, we categorize the strength of evidence for a causal relationship between short-term exposure to ozone and CV effects as "below equipoise."

Statistical Evidence Suggests that Inattention Drives Hyperactivity/Impulsivity in Attention Deficit-Hyperactivity Disorder

PubMed Central

Sokolova, Elena; Groot, Perry; Claassen, Tom; van Hulzen, Kimm J.; Glennon, Jeffrey C.; Franke, Barbara

2016-01-01

Background Numerous factor analytic studies consistently support a distinction between two symptom domains of attention-deficit/hyperactivity disorder (ADHD), inattention and hyperactivity/impulsivity. Both dimensions show high internal consistency and moderate to strong correlations with each other. However, it is not clear what drives this strong correlation. The aim of this paper is to address this issue. Method We applied a sophisticated approach for causal discovery on three independent data sets of scores of the two ADHD dimensions in NeuroIMAGE (total N = 675), ADHD-200 (N = 245), and IMpACT (N = 164), assessed by different raters and instruments, and further used information on gender or a genetic risk haplotype. Results In all data sets we found strong statistical evidence for the same pattern: the clear dependence between hyperactivity/impulsivity symptom level and an established genetic factor (either gender or risk haplotype) vanishes when one conditions upon inattention symptom level. Under reasonable assumptions, e.g., that phenotypes do not cause genotypes, a causal model that is consistent with this pattern contains a causal path from inattention to hyperactivity/impulsivity. Conclusions The robust dependency cancellation observed in three different data sets suggests that inattention is a driving factor for hyperactivity/impulsivity. This causal hypothesis can be further validated in intervention studies. Our model suggests that interventions that affect inattention will also have an effect on the level of hyperactivity/impulsivity. On the other hand, interventions that affect hyperactivity/impulsivity would not change the level of inattention. This causal model may explain earlier findings on heritable factors causing ADHD reported in the study of twins with learning difficulties. PMID:27768717

Development of Effective Connectivity during Own- and Other-Race Face Processing: A Granger Causality Analysis

PubMed Central

Zhou, Guifei; Liu, Jiangang; Ding, Xiao Pan; Fu, Genyue; Lee, Kang

2016-01-01

Numerous developmental studies have suggested that other-race effect (ORE) in face recognition emerges as early as in infancy and develops steadily throughout childhood. However, there is very limited research on the neural mechanisms underlying this developmental ORE. The present study used Granger causality analysis (GCA) to examine the development of children's cortical networks in processing own- and other-race faces. Children were between 3 and 13 years. An old-new paradigm was used to assess their own- and other-race face recognition with ETG-4000 (Hitachi Medical Co., Japan) acquiring functional near infrared spectroscopy (fNIRS) data. After preprocessing, for each participant and under each face condition, we obtained the causal map by calculating the weights of causal relations between the time courses of [oxy-Hb] of each pair of channels using GCA. To investigate further the differential causal connectivity for own-race faces and other-race faces at the group level, a repeated measure analysis of variance (ANOVA) was performed on the GCA weights for each pair of channels with the face race task (own-race face vs. other-race face) as the within-subject variable and the age as a between-subject factor (continuous variable). We found an age-related increase in functional connectivity, paralleling a similar age-related improvement in behavioral face processing ability. More importantly, we found that the significant differences in neural functional connectivity between the recognition of own-race faces and that of other-race faces were modulated by age. Thus, like the behavioral ORE, the neural ORE emerges early and undergoes a protracted developmental course. PMID:27713696

Hip fracture in the elderly: a re-analysis of the EPIDOS study with causal Bayesian networks.

PubMed

Caillet, Pascal; Klemm, Sarah; Ducher, Michel; Aussem, Alexandre; Schott, Anne-Marie

2015-01-01

Hip fractures commonly result in permanent disability, institutionalization or death in elderly. Existing hip-fracture predicting tools are underused in clinical practice, partly due to their lack of intuitive interpretation. By use of a graphical layer, Bayesian network models could increase the attractiveness of fracture prediction tools. Our aim was to study the potential contribution of a causal Bayesian network in this clinical setting. A logistic regression was performed as a standard control approach to check the robustness of the causal Bayesian network approach. EPIDOS is a multicenter study, conducted in an ambulatory care setting in five French cities between 1992 and 1996 and updated in 2010. The study included 7598 women aged 75 years or older, in which fractures were assessed quarterly during 4 years. A causal Bayesian network and a logistic regression were performed on EPIDOS data to describe major variables involved in hip fractures occurrences. Both models had similar association estimations and predictive performances. They detected gait speed and mineral bone density as variables the most involved in the fracture process. The causal Bayesian network showed that gait speed and bone mineral density were directly connected to fracture and seem to mediate the influence of all the other variables included in our model. The logistic regression approach detected multiple interactions involving psychotropic drug use, age and bone mineral density. Both approaches retrieved similar variables as predictors of hip fractures. However, Bayesian network highlighted the whole web of relation between the variables involved in the analysis, suggesting a possible mechanism leading to hip fracture. According to the latter results, intervention focusing concomitantly on gait speed and bone mineral density may be necessary for an optimal prevention of hip fracture occurrence in elderly people.

Public beliefs about and attitudes towards bipolar disorder: testing theory based models of stigma.

PubMed

Ellison, Nell; Mason, Oliver; Scior, Katrina

2015-04-01

Given the vast literature into public beliefs and attitudes towards schizophrenia and depression, there is paucity of research on attitudes towards bipolar disorder despite its similar prevalence to schizophrenia. This study explored public beliefs and attitudes towards bipolar disorder and examined the relationship between these different components of stigma. Using an online questionnaire distributed via email, social networking sites and public institutions, 753 members of the UK population were presented with a vignette depicting someone who met DSM-IV criteria for bipolar disorder. Causal beliefs, beliefs about prognosis, emotional reactions, stereotypes, and social distance were assessed in response to the vignette. Preacher and Hayes procedure for estimating direct and indirect effects of multiple mediators was used to examine the relationship between these components of stigma. Bipolar disorder was primarily associated with positive beliefs and attitudes and elicited a relatively low desire for social distance. Fear partially mediated the relationship between stereotypes and social distance. Biomedical causal beliefs reduced desire for social distance by increasing compassion, whereas fate causal beliefs increased it through eliciting fear. Psychosocial causal beliefs had mixed effects. The measurement of stigma using vignettes and self-report questionnaires has implications for ecological validity and participants may have been reluctant to reveal the true extent of their negative attitudes. Dissemination of these findings to people with bipolar disorder has implications for the reduction of internalised stigma in this population. Anti-stigma campaigns should attend to causal beliefs, stereotypes and emotional reactions as these all play a vital role in discriminatory behaviour towards people with bipolar disorder. Copyright © 2015 Elsevier B.V. All rights reserved.

Causal discovery and inference: concepts and recent methodological advances.

PubMed

Spirtes, Peter; Zhang, Kun

This paper aims to give a broad coverage of central concepts and principles involved in automated causal inference and emerging approaches to causal discovery from i.i.d data and from time series. After reviewing concepts including manipulations, causal models, sample predictive modeling, causal predictive modeling, and structural equation models, we present the constraint-based approach to causal discovery, which relies on the conditional independence relationships in the data, and discuss the assumptions underlying its validity. We then focus on causal discovery based on structural equations models, in which a key issue is the identifiability of the causal structure implied by appropriately defined structural equation models: in the two-variable case, under what conditions (and why) is the causal direction between the two variables identifiable? We show that the independence between the error term and causes, together with appropriate structural constraints on the structural equation, makes it possible. Next, we report some recent advances in causal discovery from time series. Assuming that the causal relations are linear with nonGaussian noise, we mention two problems which are traditionally difficult to solve, namely causal discovery from subsampled data and that in the presence of confounding time series. Finally, we list a number of open questions in the field of causal discovery and inference.

Causal and causally separable processes

NASA Astrophysics Data System (ADS)

Oreshkov, Ognyan; Giarmatzi, Christina

2016-09-01

The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B, either A is in the causal past of B, B is in the causal past of A, or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B, an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and outcomes for each party, these correlations form a polytope whose facets define causal inequalities. The case of quantum correlations in this paradigm is captured by the process matrix formalism. We investigate the link between causality and the closely related notion of causal separability of quantum processes, which we here define rigorously in analogy with the link between Bell locality and separability of quantum states. We show that causality and causal separability are not equivalent in general by giving an example of a physically admissible tripartite quantum process that is causal but not causally separable. We also show that there are causally separable quantum processes that become non-causal if extended by supplying the parties with entangled ancillas. This motivates the concepts of extensibly causal and extensibly causally separable (ECS) processes, for which the respective property remains invariant under extension. We characterize the class of ECS quantum processes in the tripartite case via simple conditions on the form of the process matrix. We show that the processes realizable by classically controlled quantum circuits are ECS and conjecture that the reverse also holds.

Processing of Positive-Causal and Negative-Causal Coherence Relations in Primary School Children and Adults: A Test of the Cumulative Cognitive Complexity Approach in German

ERIC Educational Resources Information Center

Knoepke, Julia; Richter, Tobias; Isberner, Maj-Britt; Naumann, Johannes; Neeb, Yvonne; Weinert, Sabine

2017-01-01

Establishing local coherence relations is central to text comprehension. Positive-causal coherence relations link a cause and its consequence, whereas negative-causal coherence relations add a contrastive meaning (negation) to the causal link. According to the cumulative cognitive complexity approach, negative-causal coherence relations are…

Does Causal Action Facilitate Causal Perception in Infants Younger than 6 Months of Age?

ERIC Educational Resources Information Center

Rakison, David H.; Krogh, Lauren

2012-01-01

Previous research has established that infants are unable to perceive causality until 6 1/4 months of age. The current experiments examined whether infants' ability to engage in causal action could facilitate causal perception prior to this age. In Experiment 1, 4 1/2-month-olds were randomly assigned to engage in causal action experience via…

Factors affecting the causality assessment of adverse events following immunisation in paediatric clinical trials: An online survey.

PubMed

Voysey, Merryn; Tavana, Rahele; Farooq, Yama; Heath, Paul T; Bonhoeffer, Jan; Snape, Matthew D

2015-12-16

Serious adverse events (SAEs) in clinical trials require reporting within 24h, including a judgment of whether the SAE was related to the investigational product(s). Such assessments are an important component of pharmacovigilance, however classification systems for assigning relatedness vary across study protocols. This on-line survey evaluated the consistency of SAE causality assessment among professionals with vaccine clinical trial experience. Members of the clinical advisory forum of experts (CAFÉ), a Brighton Collaboration online-forum, were emailed a survey containing SAEs from hypothetical vaccine trials which they were asked to classify. Participants were randomised to either two classification options (related/not related to study immunisation) or three options (possibly/probably/unrelated). The clinical scenarios, were (i) leukaemia diagnosed 5 months post-immunisation with a live RSV vaccine, (ii) juvenile idiopathic arthritis (JIA) 3 months post-immunisation with a group A streptococcal vaccine, (iii) developmental delay diagnosed at age 10 months after infant capsular group B meningococcal vaccine, (iv) developmental delay diagnosed at age 10 months after maternal immunisation with a group B streptococcal vaccine. There were 140 respondents (72 two options, 68 three options). Across all respondents, SAEs were considered related to study immunisation by 28% (leukaemia), 74% (JIA), 29% (developmental delay after infant immunisation) and 42% (developmental delay after maternal immunisation). Having only two options made respondents significantly less likely to classify the SAE as immunisation-related for two scenarios (JIA p=0.0075; and maternal immunisation p=0.045). Amongst study investigators (n=43) this phenomenon was observed for three of the four scenarios: (JIA p=0.0236; developmental delay following infant immunisation p=0.0266; and developmental delay after maternal immunisation p=0.0495). SAE causality assessment is inconsistent amongst study investigators and can be influenced by the classification systems available to them. There is a pressing need for SAE classification systems to be standardised across study protocols. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evidence for the effectiveness of minimum pricing of alcohol: a systematic review and assessment using the Bradford Hill criteria for causality

PubMed Central

Scannell, Jack W; Marlow, Sally

2017-01-01

Objectives To assess the evidence for price-based alcohol policy interventions to determine whether minimum unit pricing (MUP) is likely to be effective. Design Systematic review and assessment of studies according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, against the Bradford Hill criteria for causality. Three electronic databases were searched from inception to February 2017. Additional articles were found through hand searching and grey literature searches. Criteria for selecting studies We included any study design that reported on the effect of price-based interventions on alcohol consumption or alcohol-related morbidity, mortality and wider harms. Studies reporting on the effects of taxation or affordability and studies that only investigated price elasticity of demand were beyond the scope of this review. Studies with any conflict of interest were excluded. All studies were appraised for methodological quality. Results Of 517 studies assessed, 33 studies were included: 26 peer-reviewed research studies and seven from the grey literature. All nine of the Bradford Hill criteria were met, although different types of study satisfied different criteria. For example, modelling studies complied with the consistency and specificity criteria, time series analyses demonstrated the temporality and experiment criteria, and the analogy criterion was fulfilled by comparing the findings with the wider literature on taxation and affordability. Conclusions Overall, the Bradford Hill criteria for causality were satisfied. There was very little evidence that minimum alcohol prices are not associated with consumption or subsequent harms. However the overall quality of the evidence was variable, a large proportion of the evidence base has been produced by a small number of research teams, and the quantitative uncertainty in many estimates or forecasts is often poorly communicated outside the academic literature. Nonetheless, price-based alcohol policy interventions such as MUP are likely to reduce alcohol consumption, alcohol-related morbidity and mortality. PMID:28588106

Psychosocial Environment and Affective Outcomes in Technology-Rich Classrooms: Testing a Causal Model

ERIC Educational Resources Information Center

Dorman, Jeffrey P.; Fraser, Barry J.

2009-01-01

Research investigated classroom environment antecedent variables and student affective outcomes in Australian high schools. The Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI) was used to assess 10 classroom environment dimensions: student cohesiveness, teacher support, involvement, investigation, task orientation,…

Assessment of Two Desk-Top Computer Simulations Used to Train Tactical Decision Making (TDM) of Small Unit Infantry Leaders

DTIC Science & Technology

2007-04-01

judgmental self-doubt, depression, and causal uncertainty, tend to take fewer risks, and have lower self-esteem. Results from two studies (Nygren, 2000...U.S. Army Research Institute for the Behavioral and Social Sciences Research Report 1869 Assessment of Two Desk-Top Computer Simulations Used to...SUBTITLE 5a. CONTRACT OR GRANT NUMBER Assessment of Two Desk-Top Computer Simulations Used to Train Tactical Decision Making (TDM) of Small Unit

Testosterone administration does not affect men's rejections of low ultimatum game offers or aggressive mood.

PubMed

Cueva, Carlos; Roberts, R Edward; Spencer, Tom J; Rani, Nisha; Tempest, Michelle; Tobler, Philippe N; Herbert, Joe; Rustichini, Aldo

2017-01-01

Correlative evidence suggests that testosterone promotes dominance and aggression. However, causal evidence is scarce and offers mixed results. To investigate this relationship, we administered testosterone for 48h to 41 healthy young adult men in a within-subjects, double-blind placebo-controlled balanced crossover design. Subjects played the role of responders in an ultimatum game, where rejecting a low offer is costly, but serves to destroy the proposer's profit. Such action can hence be interpreted as non-physical aggression in response to social provocation. In addition, subjects completed a self-assessed mood questionnaire. As expected, self-reported aggressiveness was a key predictor of ultimatum game rejections. However, while testosterone affected subjective ratings of feeling energetic and interested, our evidence strongly suggests that testosterone had no effect on ultimatum game rejections or on aggressive mood. Our findings illustrate the importance of using causal interventions to assess correlative evidence. Copyright © 2016. Published by Elsevier Inc.

Faulty judgment, expert opinion, and decision-making capacity.

PubMed

Silberfeld, M; Checkland, D

1999-08-01

An assessment of decision-making capacity is the accepted procedure for determining when a person is not competent. An inferential gap exists between the criteria for capacity specific abilities and the legal requirements to understand relevant information and appreciate the consequences of a decision. This gap extends to causal influences on a person's capacity to decide. Using a published case of depression, we illustrate that assessors' uses of diagnostic information is frequently not up to the task of bridging this inferential gap in a justifiable way. We then describe cases of faulty judgement which challenge the understanding of diagnostic causal influences. These cases help to clarify the nature of the expertise required for capacity assessments. In practice, the requirements of decision-making capacity are often abandoned to other considerations due to a lack of requisite expertise. The legal policy supporting decision-making capacity as a means to protective intervention is justified only if the requisite expertise is developed. We propose the requisite expertise to be developed in the long term as a distinct multidisciplinary endeavour.

Clinical judgement and the medical profession

PubMed Central

Kienle, Gunver S; Kiene, Helmut

2011-01-01

Objectives Clinical judgment is a central element of the medical profession, essential for the performance of the doctor, and potentially generating information also for other clinicians and for scientists and health care managers. The recently renewed interest in clinical judgement is primarily engaged with its role in communication, diagnosis and decision making. Beyond this issue, the present article highlights the interrelations between clinical judgement, therapy assessment and medical professionalism. Methods Literature review and theory development. Results The article presents different methodological approaches to causality assessment in clinical studies and in clinical judgement, and offers criteria for clinical single case causality. The article outlines models of medical professionalism such as technical rationality and practice epistemology, and characterizes features of professional expertise such as tacit knowledge, reflection in action, and gestalt cognition. Conclusions Consequences of a methodological and logistical advancement of clinical judgment are discussed, both in regard to medical progress and to the renewel of the cognitive basis of the medical profession. PMID:20973873

Does the evidence for an inverse relationship between serum vitamin D status and breast cancer risk satisfy the Hill criteria?

PubMed

Mohr, Sharif B; Gorham, Edward D; Alcaraz, John E; Kane, Christopher I; Macera, Caroline A; Parsons, J Kellogg; Wingard, Deborah L; Garland, Cedric F

2012-04-01

A wide range of epidemiologic and laboratory studies combined provide compelling evidence of a protective role of vitamin D on risk of breast cancer. This review evaluates the scientific evidence for such a role in the context of the A.B. Hill criteria for causality, in order to assess the presence of a causal, inverse relationship, between vitamin D status and breast cancer risk. After evaluation of this evidence in the context of Hill's criteria, it was found that the criteria for a causal relationship were largely satisfied. Studies in human populations and the laboratory have consistently demonstrated that vitamin D plays an important role in the prevention of breast cancer. Vitamin D supplementation is an urgently needed, low cost, effective, and safe intervention strategy for breast cancer prevention that should be implemented without delay. In the meantime, randomized controlled trials of high doses of vitamin D(3) for prevention of breast cancer should be undertaken to provide the necessary evidence to guide national health policy.

Lateral habenula perturbation reduces default-mode network connectivity in a rat model of depression.

PubMed

Clemm von Hohenberg, Christian; Weber-Fahr, Wolfgang; Lebhardt, Philipp; Ravi, Namasivayam; Braun, Urs; Gass, Natalia; Becker, Robert; Sack, Markus; Cosa Linan, Alejandro; Gerchen, Martin Fungisai; Reinwald, Jonathan Rochus; Oettl, Lars-Lennart; Meyer-Lindenberg, Andreas; Vollmayr, Barbara; Kelsch, Wolfgang; Sartorius, Alexander

2018-03-27

Hyperconnectivity of the default-mode network (DMN) is one of the most widely replicated neuroimaging findings in major depressive disorder (MDD). Further, there is growing evidence for a central role of the lateral habenula (LHb) in the pathophysiology of MDD. There is preliminary neuroimaging evidence linking LHb and the DMN, but no causal relationship has been shown to date. We combined optogenetics and functional magnetic resonance imaging (fMRI), to establish a causal relationship, using an animal model of treatment-resistant depression, namely Negative Cognitive State rats. First, an inhibitory light-sensitive ion channel was introduced into the LHb by viral transduction. Subsequently, laser stimulation was performed during fMRI acquisition on a 9.4 Tesla animal scanner. Neural activity and connectivity were assessed, before, during and after laser stimulation. We observed a connectivity decrease in the DMN following laser-induced LHb perturbation. Our data indicate a causal link between LHb downregulation and reduction in DMN connectivity. These findings may advance our mechanistic understanding of LHb inhibition, which had previously been identified as a promising therapeutic principle, especially for treatment-resistant depression.

Selection and explosive growth alter genetic architecture and hamper the detection of causal rare variants.

PubMed

Uricchio, Lawrence H; Zaitlen, Noah A; Ye, Chun Jimmie; Witte, John S; Hernandez, Ryan D

2016-07-01

The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature. © 2016 Uricchio et al.; Published by Cold Spring Harbor Laboratory Press.

The effects of stress-tension on depression and anxiety symptoms: evidence from a novel twin modelling analysis.

PubMed

Davey, C G; López-Solà, C; Bui, M; Hopper, J L; Pantelis, C; Fontenelle, L F; Harrison, B J

2016-11-01

Negative mood states are composed of symptoms of depression and anxiety, and by a third factor related to stress, tension and irritability. We sought to clarify the nature of the relationships between the factors by studying twin pairs. A total of 503 monozygotic twin pairs completed the Depression Anxiety Stress Scales (DASS), an instrument that assesses symptoms of depression, anxiety and stress-tension. We applied a recently developed twin regression methodology - Inference about Causation from Examination of FAmiliaL CONfounding (ICE FALCON) - to test for evidence consistent with the existence of 'causal' influences between the DASS factors. There was evidence consistent with the stress-tension factor having a causal influence on both the depression (p < 0.0001) and anxiety factors (p = 0.001), and for the depression factor having a causal influence on the anxiety factor (p < 0.001). Our findings suggest a critical role for stress-tension in the structure of negative mood states, and that interventions that target it may be particularly effective in reducing depression and anxiety symptoms.

SHAME AND GUILT-PRONENESS AS MEDIATORS OF ASSOCIATIONS BETWEEN GENERAL CAUSALITY ORIENTATIONS AND DEPRESSIVE SYMPTOMS

PubMed Central

YOUNG, CHELSIE M.; NEIGHBORS, CLAYTON; DIBELLO, ANGELO M.; TRAYLOR, ZACHARY K.; TOMKINS, MARY

2017-01-01

The present study examined the roles of shame- and guilt-proneness as mediators of associations between general causality orientations and depressive symptoms. We expected autonomy would be associated with less depressive symptoms based on higher guilt-proneness and lower shame-proneness, whereas control would be associated with more depressive symptoms based on lower guilt-proneness and higher shame-proneness. Undergraduates (N = 354) completed assessments of general causality orientations, shame- and guilt-proneness, and depressive symptoms in exchange for extra credit. Results of mediation analyses were generally supportive of the framework indicating that shame- and guilt-proneness mediate associations between self-determination and depressive symptoms. Autonomy was indirectly associated with less depressive symptoms through positive associations with guilt-proneness, in spite of unexpected positive associations with shame-proneness. Control and impersonal orientation were indirectly associated with more depressive symptoms through positive associations with shame-proneness. Results extend previous research relating self-determination to mental health in providing preliminary support suggesting that individual differences in self-determination facilitate differential tendencies in experiencing guilt and shame. PMID:28344381

Measuring causal perception: connections to representational momentum?

PubMed

Choi, Hoon; Scholl, Brian J

2006-01-01

In a collision between two objects, we can perceive not only low-level properties, such as color and motion, but also the seemingly high-level property of causality. It has proven difficult, however, to measure causal perception in a quantitatively rigorous way which goes beyond perceptual reports. Here we focus on the possibility of measuring perceived causality using the phenomenon of representational momentum (RM). Recent studies suggest a relationship between causal perception and RM, based on the fact that RM appears to be attenuated for causally 'launched' objects. This is explained by appeal to the visual expectation that a 'launched' object is inert and thus should eventually cease its movement after a collision, without a source of self-propulsion. We first replicated these demonstrations, and then evaluated this alleged connection by exploring RM for different types of displays, including the contrast between causal launching and non-causal 'passing'. These experiments suggest that the RM-attenuation effect is not a pure measure of causal perception, but rather may reflect lower-level spatiotemporal correlates of only some causal displays. We conclude by discussing the strengths and pitfalls of various methods of measuring causal perception.

Assessing Causality in the Association between Child Adiposity and Physical Activity Levels: A Mendelian Randomization Analysis

PubMed Central

Richmond, Rebecca C.; Davey Smith, George; Ness, Andy R.; den Hoed, Marcel; McMahon, George; Timpson, Nicholas J.

2014-01-01

Background Cross-sectional studies have shown that objectively measured physical activity is associated with childhood adiposity, and a strong inverse dose–response association with body mass index (BMI) has been found. However, few studies have explored the extent to which this association reflects reverse causation. We aimed to determine whether childhood adiposity causally influences levels of physical activity using genetic variants reliably associated with adiposity to estimate causal effects. Methods and Findings The Avon Longitudinal Study of Parents and Children collected data on objectively assessed activity levels of 4,296 children at age 11 y with recorded BMI and genotypic data. We used 32 established genetic correlates of BMI combined in a weighted allelic score as an instrumental variable for adiposity to estimate the causal effect of adiposity on activity. In observational analysis, a 3.3 kg/m2 (one standard deviation) higher BMI was associated with 22.3 (95% CI, 17.0, 27.6) movement counts/min less total physical activity (p = 1.6×10−16), 2.6 (2.1, 3.1) min/d less moderate-to-vigorous-intensity activity (p = 3.7×10−29), and 3.5 (1.5, 5.5) min/d more sedentary time (p = 5.0×10−4). In Mendelian randomization analyses, the same difference in BMI was associated with 32.4 (0.9, 63.9) movement counts/min less total physical activity (p = 0.04) (∼5.3% of the mean counts/minute), 2.8 (0.1, 5.5) min/d less moderate-to-vigorous-intensity activity (p = 0.04), and 13.2 (1.3, 25.2) min/d more sedentary time (p = 0.03). There was no strong evidence for a difference between variable estimates from observational estimates. Similar results were obtained using fat mass index. Low power and poor instrumentation of activity limited causal analysis of the influence of physical activity on BMI. Conclusions Our results suggest that increased adiposity causes a reduction in physical activity in children and support research into the targeting of BMI in efforts to increase childhood activity levels. Importantly, this does not exclude lower physical activity also leading to increased adiposity, i.e., bidirectional causation. Please see later in the article for the Editors' Summary PMID:24642734

Empirical evaluation of the conceptual model underpinning a regional aquatic long-term monitoring program using causal modelling

USGS Publications Warehouse

Irvine, Kathryn M.; Miller, Scott; Al-Chokhachy, Robert K.; Archer, Erik; Roper, Brett B.; Kershner, Jeffrey L.

2015-01-01

Conceptual models are an integral facet of long-term monitoring programs. Proposed linkages between drivers, stressors, and ecological indicators are identified within the conceptual model of most mandated programs. We empirically evaluate a conceptual model developed for a regional aquatic and riparian monitoring program using causal models (i.e., Bayesian path analysis). We assess whether data gathered for regional status and trend estimation can also provide insights on why a stream may deviate from reference conditions. We target the hypothesized causal pathways for how anthropogenic drivers of road density, percent grazing, and percent forest within a catchment affect instream biological condition. We found instream temperature and fine sediments in arid sites and only fine sediments in mesic sites accounted for a significant portion of the maximum possible variation explainable in biological condition among managed sites. However, the biological significance of the direct effects of anthropogenic drivers on instream temperature and fine sediments were minimal or not detected. Consequently, there was weak to no biological support for causal pathways related to anthropogenic drivers’ impact on biological condition. With weak biological and statistical effect sizes, ignoring environmental contextual variables and covariates that explain natural heterogeneity would have resulted in no evidence of human impacts on biological integrity in some instances. For programs targeting the effects of anthropogenic activities, it is imperative to identify both land use practices and mechanisms that have led to degraded conditions (i.e., moving beyond simple status and trend estimation). Our empirical evaluation of the conceptual model underpinning the long-term monitoring program provided an opportunity for learning and, consequently, we discuss survey design elements that require modification to achieve question driven monitoring, a necessary step in the practice of adaptive monitoring. We suspect our situation is not unique and many programs may suffer from the same inferential disconnect. Commonly, the survey design is optimized for robust estimates of regional status and trend detection and not necessarily to provide statistical inferences on the causal mechanisms outlined in the conceptual model, even though these relationships are typically used to justify and promote the long-term monitoring of a chosen ecological indicator. Our application demonstrates a process for empirical evaluation of conceptual models and exemplifies the need for such interim assessments in order for programs to evolve and persist.

The Effects of the Collaborative Leadership Style Provided by Professional Learning Communities on the Tennessee Comprehensive Assessment Program Mean Value-Added Scores in Selected Middle Schools in East Tennessee

ERIC Educational Resources Information Center

Jones, Jone S.

2011-01-01

This causal-comparative study examined the effects of the collaborative leadership style provided by professional learning communities (PLCs) on the students' Tennessee Comprehensive Assessment Program (TCAP) mean Value-Added achievement scores in language arts and mathematics. The study used twenty-nine selected middle schools in eight different…

Maintenance of peripheral venous access and its impact on the development of phlebitis: a survey of 186 catheters in a general surgery department in Portugal.

PubMed

do Rego Furtado, Luís Carlos

2011-01-01

This article reports the results of a clinical audit conducted to assess the minimum requirements for safe maintenance of peripheral intravenous catheters. The audit also determined the incidence of phlebitis and attempted to establish a causal relationship between some of the variables used to assess a catheter's maintenance status and the development of phlebitis.

OVERWEIGHT/OBESITY AND HUMAN CAPITAL FORMATION FROM INFANCY TO ADOLESCENCE: EVIDENCE FROM TWO LARGE US COHORTS.

PubMed

Murasko, Jason E

2015-03-01

Body mass index (BMI) levels in US children and adolescents have increased over the past several decades. The negative health effects of this trend are well-documented. Recent work has evaluated the potential effects on skills formation. Studies are mixed on whether there is an association between high BMI and skills outcomes, and those that estimate causal effects find none. This paper offers estimates on the causal effect of BMI-defined overweight and obesity on skills formation using two large cohorts of contemporary US children followed from infancy to 5 years and from kindergarten (6 years) to the eighth grade (14 years). Significant negative associations were observed in the random effects models for males in early life with respect to a mental skills assessment, for females during the pre-school years for reading and maths assessments, for both males and females during the schooling years for reading assessments and for females during the schooling years for maths assessments. Fixed effects models yielded a significant negative association only with respect to the latter. The implication of these findings is that any improvement in skills outcomes that may accompany reductions in obesity prevalence may depend on whether interventions are general to overall health productivity or whether they are specific to dietary and exercise behaviours.

Metabolic signatures of adiposity in young adults: Mendelian randomization analysis and effects of weight change.

PubMed

Würtz, Peter; Wang, Qin; Kangas, Antti J; Richmond, Rebecca C; Skarp, Joni; Tiainen, Mika; Tynkkynen, Tuulia; Soininen, Pasi; Havulinna, Aki S; Kaakinen, Marika; Viikari, Jorma S; Savolainen, Markku J; Kähönen, Mika; Lehtimäki, Terho; Männistö, Satu; Blankenberg, Stefan; Zeller, Tanja; Laitinen, Jaana; Pouta, Anneli; Mäntyselkä, Pekka; Vanhala, Mauno; Elliott, Paul; Pietiläinen, Kirsi H; Ripatti, Samuli; Salomaa, Veikko; Raitakari, Olli T; Järvelin, Marjo-Riitta; Smith, George Davey; Ala-Korpela, Mika

2014-12-01

Increased adiposity is linked with higher risk for cardiometabolic diseases. We aimed to determine to what extent elevated body mass index (BMI) within the normal weight range has causal effects on the detailed systemic metabolite profile in early adulthood. We used Mendelian randomization to estimate causal effects of BMI on 82 metabolic measures in 12,664 adolescents and young adults from four population-based cohorts in Finland (mean age 26 y, range 16-39 y; 51% women; mean ± standard deviation BMI 24 ± 4 kg/m(2)). Circulating metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays. In cross-sectional analyses, elevated BMI was adversely associated with cardiometabolic risk markers throughout the systemic metabolite profile, including lipoprotein subclasses, fatty acid composition, amino acids, inflammatory markers, and various hormones (p<0.0005 for 68 measures). Metabolite associations with BMI were generally stronger for men than for women (median 136%, interquartile range 125%-183%). A gene score for predisposition to elevated BMI, composed of 32 established genetic correlates, was used as the instrument to assess causality. Causal effects of elevated BMI closely matched observational estimates (correspondence 87% ± 3%; R(2)= 0.89), suggesting causative influences of adiposity on the levels of numerous metabolites (p<0.0005 for 24 measures), including lipoprotein lipid subclasses and particle size, branched-chain and aromatic amino acids, and inflammation-related glycoprotein acetyls. Causal analyses of certain metabolites and potential sex differences warrant stronger statistical power. Metabolite changes associated with change in BMI during 6 y of follow-up were examined for 1,488 individuals. Change in BMI was accompanied by widespread metabolite changes, which had an association pattern similar to that of the cross-sectional observations, yet with greater metabolic effects (correspondence 160% ± 2%; R(2) = 0.92). Mendelian randomization indicates causal adverse effects of increased adiposity with multiple cardiometabolic risk markers across the metabolite profile in adolescents and young adults within the non-obese weight range. Consistent with the causal influences of adiposity, weight changes were paralleled by extensive metabolic changes, suggesting a broadly modifiable systemic metabolite profile in early adulthood. Please see later in the article for the Editors' Summary.

Social capital, mental health and biomarkers in Chile: Assessing the effects of social capital in a middle-income country

PubMed Central

Riumallo-Herl, Carlos Javier; Kawachi, Ichiro; Avendano, Mauricio

2014-01-01

In high-income countries, higher social capital is associated with better health. However, there is little evidence of this association in low- and middle-income countries. We examine the association between social capital (social support and trust) and both self-rated and biologically assessed health outcomes in Chile, a middle-income country that experienced a major political transformation and welfare state expansion in the last two decades. Based on data from the Chilean National Health Survey (2009–10), we modeled self-rated health, depression, measured diabetes and hypertension as a function of social capital indicators, controlling for socio-economic status and health behavior. We used an instrumental variable approach to examine whether social capital was causally associated with health. We find that correlations between social capital and health observed in high-income countries are also observed in Chile. All social capital indicators are significantly associated with depression at all ages, and at least one social capital indicator is associated with self-rated health, hypertension and diabetes at ages 45 and above. Instrumental variable models suggest that associations for depression may reflect a causal effect from social capital indicators on mental well-being. Using aggregate social capital as instrument, we also find evidence that social capital may be causally associated with hypertension and diabetes, early markers of cardiovascular risk. Our findings highlight the potential role of social capital in the prevention of depression and early cardiovascular disease in middle-income countries. PMID:24495808

Are bruxism and the bite causally related?

PubMed

Lobbezoo, F; Ahlberg, J; Manfredini, D; Winocur, E

2012-07-01

In the dental profession, the belief that bruxism and dental (mal-)occlusion ('the bite') are causally related is widespread. The aim of this review was to critically assess the available literature on this topic. A PubMed search of the English-language literature, using the query 'Bruxism [Majr] AND (Dental Occlusion [Majr] OR Malocclusion [Majr])', yielded 93 articles, of which 46 papers were finally included in the present review*. Part of the included publications dealt with the possible associations between bruxism and aspects of occlusion, from which it was concluded that neither for occlusal interferences nor for factors related to the anatomy of the oro-facial skeleton, there is any evidence available that they are involved in the aetiology of bruxism. Instead, there is a growing awareness of other factors (viz. psychosocial and behavioural ones) being important in the aetiology of bruxism. Another part of the included papers assessed the possible mediating role of occlusion between bruxism and its purported consequences (e.g. tooth wear, loss of periodontal tissues, and temporomandibular pain and dysfunction). Even though most dentists agree that bruxism may have several adverse effects on the masticatory system, for none of these purported adverse effects, evidence for a mediating role of occlusion and articulation has been found to date. Hence, based on this review, it should be concluded that to date, there is no evidence whatsoever for a causal relationship between bruxism and the bite. © 2012 Blackwell Publishing Ltd.

The safety of acupuncture during pregnancy: a systematic review

PubMed Central

Park, Jimin; Sohn, Youngjoo; White, Adrian R; Lee, Hyangsook

2014-01-01

Objective Although there is a growing interest in the use of acupuncture during pregnancy, the safety of acupuncture is yet to be rigorously investigated. The objective of this review is to identify adverse events (AEs) associated with acupuncture treatment during pregnancy. Methods We searched Medline, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Allied and Complementary Medicine Database (AMED) and five Korean databases up to February 2013. Reference lists of relevant articles were screened for additional reports. Studies were included regardless of their design if they reported original data and involved acupuncture needling and/or moxibustion treatment for any conditions in pregnant women. Studies of acupuncture for delivery, abortion, assisted reproduction or postpartum conditions were excluded. AE data were extracted and assessed in terms of severity and causality, and incidence was determined. Results Of 105 included studies, detailed AEs were reported only in 25 studies represented by 27 articles (25.7%). AEs evaluated as certain, probable or possible in the causality assessment were all mild/moderate in severity, with needling pain being the most frequent. Severe AEs or deaths were few and all considered unlikely to have been caused by acupuncture. Total AE incidence was 1.9%, and the incidence of AEs evaluated as certainly, probably or possibly causally related to acupuncture was 1.3%. Conclusions Acupuncture during pregnancy appears to be associated with few AEs when correctly applied. PMID:24554789

Cleaning and asthma: A systematic review and approach for effective safety assessment.

PubMed

Vincent, Melissa J; Parker, Ann; Maier, Andrew

2017-11-01

Research indicates a correlative relationship between asthma and use of consumer cleaning products. We conduct a systematic review of epidemiological literature on persons who use or are exposed to cleaning products, both in occupational and domestic settings, and risk of asthma or asthma-like symptoms to improve understanding of the causal relationship between exposure and asthma. A scoring method for assessing study reliability is presented. Although research indicates an association between asthma and the use of cleaning products, no study robustly investigates exposure to cleaning products or ingredients along with asthma risk. This limits determination of causal relationships between asthma and specific products or ingredients in chemical safety assessment. These limitations, and a lack of robust animal models for toxicological assessment of asthma, create the need for a weight-of-evidence (WoE) approach to examine an ingredient or product's asthmatic potential. This proposed WoE method organizes diverse lines of data (i.e., asthma, sensitization, and irritation information) through a systematic, hierarchical framework that provides qualitatively categorized conclusions using hazard bands to predict a specific product or ingredient's potential for asthma induction. This work provides a method for prioritizing chemicals as a first step for quantitative and scenario-specific safety assessments based on their potential for inducing asthmatic effects. Acetic acid is used as a case study to test this framework. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Processing of positive-causal and negative-causal coherence relations in primary school children and adults: a test of the cumulative cognitive complexity approach in German.

PubMed

Knoepke, Julia; Richter, Tobias; Isberner, Maj-Britt; Naumann, Johannes; Neeb, Yvonne; Weinert, Sabine

2017-03-01

Establishing local coherence relations is central to text comprehension. Positive-causal coherence relations link a cause and its consequence, whereas negative-causal coherence relations add a contrastive meaning (negation) to the causal link. According to the cumulative cognitive complexity approach, negative-causal coherence relations are cognitively more complex than positive-causal ones. Therefore, they require greater cognitive effort during text comprehension and are acquired later in language development. The present cross-sectional study tested these predictions for German primary school children from Grades 1 to 4 and adults in reading and listening comprehension. Accuracy data in a semantic verification task support the predictions of the cumulative cognitive complexity approach. Negative-causal coherence relations are cognitively more demanding than positive-causal ones. Moreover, our findings indicate that children's comprehension of negative-causal coherence relations continues to develop throughout the course of primary school. Findings are discussed with respect to the generalizability of the cumulative cognitive complexity approach to German.

Disease causality extraction based on lexical semantics and document-clause frequency from biomedical literature.

PubMed

Lee, Dong-Gi; Shin, Hyunjung

2017-05-18

Recently, research on human disease network has succeeded and has become an aid in figuring out the relationship between various diseases. In most disease networks, however, the relationship between diseases has been simply represented as an association. This representation results in the difficulty of identifying prior diseases and their influence on posterior diseases. In this paper, we propose a causal disease network that implements disease causality through text mining on biomedical literature. To identify the causality between diseases, the proposed method includes two schemes: the first is the lexicon-based causality term strength, which provides the causal strength on a variety of causality terms based on lexicon analysis. The second is the frequency-based causality strength, which determines the direction and strength of causality based on document and clause frequencies in the literature. We applied the proposed method to 6,617,833 PubMed literature, and chose 195 diseases to construct a causal disease network. From all possible pairs of disease nodes in the network, 1011 causal pairs of 149 diseases were extracted. The resulting network was compared with that of a previous study. In terms of both coverage and quality, the proposed method showed outperforming results; it determined 2.7 times more causalities and showed higher correlation with associated diseases than the existing method. This research has novelty in which the proposed method circumvents the limitations of time and cost in applying all possible causalities in biological experiments and it is a more advanced text mining technique by defining the concepts of causality term strength.

Tri-level study of the causes of traffic accidents. Volume 1, Causal factor tabulations and assessments

DOT National Transportation Integrated Search

1977-03-31

This is the Final Report of the "Tri-Level Study of the Causes of Traffic Accidents," performed by the Indiana University Institute for Research in Public Safety (IRPS), under contract to the National Highway Traffic Safety Administration (Contract N...

Semantics, Cross-Cultural Style

ERIC Educational Resources Information Center

Machery, Edouard; Mallon, Ron; Nichols, Shaun; Stich, Stephen P.

2004-01-01

Theories of reference have been central to analytic philosophy, and two views, "the descriptivist view of reference" and "the causal-historical view of reference," have dominated the field. In this research tradition, theories of reference are assessed by consulting one's intuitions about the reference of terms in hypothetical situations. However,…

Professional Development Urban Schools: What Do Teachers Say?

ERIC Educational Resources Information Center

Green, Tanya R.; Allen, Mishaleen

2015-01-01

This quantitative causal-comparative study compared perceptions of professional development opportunities between high-achieving and low-achieving elementary-middle school teachers in an urban school district using the Standards Assessment Inventory (SAI). A total of 271 teachers participated including 134 (n = 134) teachers from high-achieving…

Automated Writing Evaluation Program's Effect on Student Writing Achievement

ERIC Educational Resources Information Center

Holman, Lester Donnie

2011-01-01

In an ex post facto causal-comparative research design, this study investigated the effectiveness of Automated Writing Evaluation (AWE) programs on raising the student writing achievement. Tennessee Comprehensive Assessment Program (TCAP) writing achievement scores from the 2010 administration were utilized for this study. The independent variable…

Direct Broadcasting Satellite in the United States.

ERIC Educational Resources Information Center

Kim, Haeryon

The introduction of Direct Broadcasting Satellites (DBS) in the United States sparked both government's regulatory development of domestic DBS services and the communication industry's efforts to implement a commercial DBS system. J. D. Slack's symptomatic causality and technological assessment models help to explain how these practices were…

Assessing the association between homocysteine and cognition: reflections on Bradford Hill, meta-analyses, and causality.

PubMed

McCaddon, Andrew; Miller, Joshua W

2015-10-01

Hyperhomocysteinemia is a recognized risk factor for cognitive decline and incident dementia in older adults. Two recent reports addressed the cumulative epidemiological evidence for this association but expressed conflicting opinions. Here, the evidence is reviewed in relation to Sir Austin Bradford Hill's criteria for assessing "causality," and the latest meta-analysis of the effects of homocysteine-lowering on cognitive function is critically examined. The meta-analysis included 11 trials, collectively assessing 22,000 individuals, that examined the effects of B vitamin supplements (folic acid, vitamin B12, vitamin B6) on global or domain-specific cognitive decline. It concluded that homocysteine-lowering with B vitamin supplements has no significant effect on cognitive function. However, careful examination of the trials in the meta-analysis indicates that no conclusion can be made regarding the effects of homocysteine-lowering on cognitive decline, since the trials typically did not include individuals who were experiencing such decline. Further definitive trials in older adults experiencing cognitive decline are still urgently needed. © The Author(s) 2015. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Strategic planning for MyRA performance: A causal loop diagram approach

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Zaibidi, Nerda Zura; Karim, Khairah Nazurah

2017-10-01

The nexus of research and innovation in higher education are continually receiving worldwide priority attention. Hence, Malaysia has taken its move to enhance public universities as a center of excellence by introducing the status of Research University (RU). To inspire all universities towards becoming a research university, The Ministry of Higher Education (MoHE) had revised an assessment called Malaysian Research Assessment Instrument (MyRA) to evaluate the performance of existence RUs, and other potential higher education institutions. The available spreadsheet tool to access MyRA performance is inadequate to support strategic planning. Since, higher education management is a complex system, in which components and their interactions are ever changing over time, there is a need to for an efficient approach to investigate system behavior and devise research management policies for the benefit of the institution itself and the higher education system. In this paper, we proposed a system dynamics simulation model to evaluate the impact of policies for obtaining the highest performance in MyRA assessment. Causal loop diagram is developed to investigate the relationship of various elements in research management, their inter-relationship that link together and their evolution of behavior over time.

Classification and Verification of Handwritten Signatures with Time Causal Information Theory Quantifiers.

PubMed

Rosso, Osvaldo A; Ospina, Raydonal; Frery, Alejandro C

2016-01-01

We present a new approach for handwritten signature classification and verification based on descriptors stemming from time causal information theory. The proposal uses the Shannon entropy, the statistical complexity, and the Fisher information evaluated over the Bandt and Pompe symbolization of the horizontal and vertical coordinates of signatures. These six features are easy and fast to compute, and they are the input to an One-Class Support Vector Machine classifier. The results are better than state-of-the-art online techniques that employ higher-dimensional feature spaces which often require specialized software and hardware. We assess the consistency of our proposal with respect to the size of the training sample, and we also use it to classify the signatures into meaningful groups.

Category transfer in sequential causal learning: the unbroken mechanism hypothesis.

PubMed

Hagmayer, York; Meder, Björn; von Sydow, Momme; Waldmann, Michael R

2011-07-01

The goal of the present set of studies is to explore the boundary conditions of category transfer in causal learning. Previous research has shown that people are capable of inducing categories based on causal learning input, and they often transfer these categories to new causal learning tasks. However, occasionally learners abandon the learned categories and induce new ones. Whereas previously it has been argued that transfer is only observed with essentialist categories in which the hidden properties are causally relevant for the target effect in the transfer relation, we here propose an alternative explanation, the unbroken mechanism hypothesis. This hypothesis claims that categories are transferred from a previously learned causal relation to a new causal relation when learners assume a causal mechanism linking the two relations that is continuous and unbroken. The findings of two causal learning experiments support the unbroken mechanism hypothesis. Copyright © 2011 Cognitive Science Society, Inc.

Study on localization of epileptic focus based on causality analysis

NASA Astrophysics Data System (ADS)

Shan, Shaojie; Li, Hanjun; Tang, Xiaoying

2018-05-01

In this paper, we considered that the ECoG signal contain abundant pathological information, which can be used for the localization of epileptic focus before epileptic seizures in 1-2 mins. In order to validate this hypothesis, cutting the ECoG into three stages: before seizure, seizure and after seizure, then through using Granger causality algorithm, PSI causality algorithm, Transfer Entropy causality algorithm at different stages of epilepsy ECoG, we were able to do the causality analysis of ECoG data. The results have shown that there is significant difference with the causality value of the epileptic focus area in before seizure, seizure and after seizure. An increase is in the causality value of each channel during epileptic seizure. After epileptic seizure, the causality between the channels showed a downward trend, but the difference was not obvious. The difference of the causality provides a reliable technical method to assist the clinical diagnosis of epileptic focus.

Children's Counterfactual Reasoning About Causally Overdetermined Events.

PubMed

Nyhout, Angela; Henke, Lena; Ganea, Patricia A

2017-08-07

In two experiments, one hundred and sixty-two 6- to 8-year-olds were asked to reason counterfactually about events with different causal structures. All events involved overdetermined outcomes in which two different causal events led to the same outcome. In Experiment 1, children heard stories with either an ambiguous causal relation between events or causally unrelated events. Children in the causally unrelated version performed better than chance and better than those in the ambiguous condition. In Experiment 2, children heard stories in which antecedent events were causally connected or causally disconnected. Eight-year-olds performed above chance in both conditions, whereas 6-year-olds performed above chance only in the connected condition. This work provides the first evidence that children can reason counterfactually in causally overdetermined contexts by age 8. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Failures of explaining away and screening off in described versus experienced causal learning scenarios.

PubMed

Rehder, Bob; Waldmann, Michael R

2017-02-01

Causal Bayes nets capture many aspects of causal thinking that set them apart from purely associative reasoning. However, some central properties of this normative theory routinely violated. In tasks requiring an understanding of explaining away and screening off, subjects often deviate from these principles and manifest the operation of an associative bias that we refer to as the rich-get-richer principle. This research focuses on these two failures comparing tasks in which causal scenarios are merely described (via verbal statements of the causal relations) versus experienced (via samples of data that manifest the intervariable correlations implied by the causal relations). Our key finding is that we obtained stronger deviations from normative predictions in the described conditions that highlight the instructed causal model compared to those that presented data. This counterintuitive finding indicate that a theory of causal reasoning and learning needs to integrate normative principles with biases people hold about causal relations.

Exploring individual differences in preschoolers' causal stance.

PubMed

Alvarez, Aubry; Booth, Amy E

2016-03-01

Preschoolers, as a group, are highly attuned to causality, and this attunement is known to facilitate memory, learning, and problem solving. However, recent work reveals substantial individual variability in the strength of children's "causal stance," as demonstrated by their curiosity about and preference for new causal information. In this study, we explored the coherence and short-term stability of individual differences in children's causal stance. We also began to investigate the origins of this variability, focusing particularly on the potential role of mothers' explanatory talk in shaping the causal stance of their children. Two measures of causal stance correlated with each other, as well as themselves across time. Both also revealed internal consistency of response. The strength of children's causal stance also correlated with mother's responses on the same tasks and the frequency with which mothers emphasized causality during naturalistic joint activities with their children. Implications for theory and practice are discussed. (c) 2016 APA, all rights reserved).

Detectability of Granger causality for subsampled continuous-time neurophysiological processes.

PubMed

Barnett, Lionel; Seth, Anil K

2017-01-01

Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity from neurophysiological recordings. Copyright © 2016 Elsevier B.V. All rights reserved.

Interactions of information transfer along separable causal paths

NASA Astrophysics Data System (ADS)

Jiang, Peishi; Kumar, Praveen

2018-04-01

Complex systems arise as a result of interdependences between multiple variables, whose causal interactions can be visualized in a time-series graph. Transfer entropy and information partitioning approaches have been used to characterize such dependences. However, these approaches capture net information transfer occurring through a multitude of pathways involved in the interaction and as a result mask our ability to discern the causal interaction within a subgraph of interest through specific pathways. We build on recent developments of momentary information transfer along causal paths proposed by Runge [Phys. Rev. E 92, 062829 (2015), 10.1103/PhysRevE.92.062829] to develop a framework for quantifying information partitioning along separable causal paths. Momentary information transfer along causal paths captures the amount of information transfer between any two variables lagged at two specific points in time. Our approach expands this concept to characterize the causal interaction in terms of synergistic, unique, and redundant information transfer through separable causal paths. Through a graphical model, we analyze the impact of the separable and nonseparable causal paths and the causality structure embedded in the graph as well as the noise effect on information partitioning by using synthetic data generated from two coupled logistic equation models. Our approach can provide a valuable reference for an autonomous information partitioning along separable causal paths which form a causal subgraph influencing a target.

Sufficiency and Necessity Assumptions in Causal Structure Induction

ERIC Educational Resources Information Center

Mayrhofer, Ralf; Waldmann, Michael R.

2016-01-01

Research on human causal induction has shown that people have general prior assumptions about causal strength and about how causes interact with the background. We propose that these prior assumptions about the parameters of causal systems do not only manifest themselves in estimations of causal strength or the selection of causes but also when…

Different Kinds of Causality in Event Cognition

ERIC Educational Resources Information Center

Radvansky, Gabriel A.; Tamplin, Andrea K.; Armendarez, Joseph; Thompson, Alexis N.

2014-01-01

Narrative memory is better for information that is more causally connected and occurs at event boundaries, such as a causal break. However, it is unclear whether there are common or distinct influences of causality. For the event boundaries that arise as a result of causal breaks, the events that follow may subsequently become more causally…

A Theory of Causal Learning in Children: Causal Maps and Bayes Nets

ERIC Educational Resources Information Center

Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously…

Foundational perspectives on causality in large-scale brain networks

NASA Astrophysics Data System (ADS)

Mannino, Michael; Bressler, Steven L.

2015-12-01

A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical likelihood that a change in the activity of one neuronal population affects the activity in another. We argue that these measures access the inherently probabilistic nature of causal influences in the brain, and are thus better suited for large-scale brain network analysis than are DC-based measures. Our work is consistent with recent advances in the philosophical study of probabilistic causality, which originated from inherent conceptual problems with deterministic regularity theories. It also resonates with concepts of stochasticity that were involved in establishing modern physics. In summary, we argue that probabilistic causality is a conceptually appropriate foundation for describing neural causality in the brain.

Foundational perspectives on causality in large-scale brain networks.

PubMed

Mannino, Michael; Bressler, Steven L

2015-12-01

A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical likelihood that a change in the activity of one neuronal population affects the activity in another. We argue that these measures access the inherently probabilistic nature of causal influences in the brain, and are thus better suited for large-scale brain network analysis than are DC-based measures. Our work is consistent with recent advances in the philosophical study of probabilistic causality, which originated from inherent conceptual problems with deterministic regularity theories. It also resonates with concepts of stochasticity that were involved in establishing modern physics. In summary, we argue that probabilistic causality is a conceptually appropriate foundation for describing neural causality in the brain. Copyright © 2015 Elsevier B.V. All rights reserved.

Pharmacy study of natural health product adverse reactions (SONAR): a cross-sectional study using active surveillance in community pharmacies to detect adverse events associated with natural health products and assess causality.

PubMed

Necyk, Candace; Tsuyuki, Ross T; Boon, Heather; Foster, Brian C; Legatt, Don; Cembrowski, George; Murty, Mano; Barnes, Joanne; Charrois, Theresa L; Arnason, John T; Ware, Mark A; Rosychuk, Rhonda J; Vohra, Sunita

2014-03-28

To investigate the rates and causality of adverse event(s) (AE) associated with natural health product (NHP) use, prescription drug use and concurrent NHP-drug use through active surveillance in community pharmacies. Cross-sectional study of screened patients. 10 community pharmacies across Alberta and British Columbia, Canada from 14 January to 30 July 2011. The participating pharmacy staff screened consecutive patients, or agents of patients, who were dropping or picking up prescription medications. Patients were screened to determine the proportions of them using prescription drugs and/or NHPs, as well as their respective AE rates. All AEs reported by the screened patients who took a NHP, consented to, and were available for, a detailed telephone interview (14%) were adjudicated fully to assess for causality. Over a total of 105 pharmacy weeks and 1118 patients screened, 410 patients reported taking prescription drugs only (36.7%; 95% CI 33.9% to 39.5%), 37 reported taking NHPs only (3.3%; 95% CI 2.4% to 4.5%) and 657 reported taking prescription drugs and NHPs concurrently (58.8%; 95% CI 55.9% to 61.6%). In total, 54 patients reported an AE, representing 1.2% (95% CI 0.51% to 2.9%), 2.7% (95% CI 0.4% to 16.9%) and 7.3% (95% CI 5.6% to 9.6%) of each population, respectively. Compared with patients who reported using prescription drugs, the patients who reported using prescription drugs and NHPs concurrently were 6.4 times more likely to experience an AE (OR; 95% CI 2.52 to 16.17; p<0.001). Combined with data from Ontario, Canada, a national proportion was calculated, which found that 45.4% (95% CI 43.8% to 47.0%) of Canadians who visit community pharmacies take NHPs and prescription drugs concurrently, and of those, 7.4% (95% CI 6.3% to 8.8%) report an AE. A substantial proportion of community pharmacy patients use prescription drugs and NHPs concurrently; these patients are at a greater risk of experiencing an AE. Active surveillance provides a means of detecting such AEs and collecting high-quality data on which causality assessment can be based.

Tracking time-varying causality and directionality of information flow using an error reduction ratio test with applications to electroencephalography data.

PubMed

Zhao, Yifan; Billings, Steve A; Wei, Hualiang; Sarrigiannis, Ptolemaios G

2012-11-01

This paper introduces an error reduction ratio-causality (ERR-causality) test that can be used to detect and track causal relationships between two signals. In comparison to the traditional Granger method, one significant advantage of the new ERR-causality test is that it can effectively detect the time-varying direction of linear or nonlinear causality between two signals without fitting a complete model. Another important advantage is that the ERR-causality test can detect both the direction of interactions and estimate the relative time shift between the two signals. Numerical examples are provided to illustrate the effectiveness of the new method together with the determination of the causality between electroencephalograph signals from different cortical sites for patients during an epileptic seizure.

Inferring Causes of Biological Impairment in the Clear Fork Watershed, West Virginia (Final)

EPA Science Inventory

EPA announced the availability of the final report, Inferring Causes of Biological Impairment in the Clear Fork Watershed, West Virginia. This study illustrates a causal assessment in a watershed using the US EPA stressor identification process described on the www.epa....

Interpersonal Valence Dimensions as Discriminators of Communication Contexts: An Empirical Assessment of Dyadic Linkages.

ERIC Educational Resources Information Center

Garrison, John P.; And Others

The capability of 14 interpersonal dimensions to predict dyadic communication contexts was investigated in this study. Friend, acquaintance, co-worker, and family contexts were examined. The interpersonal valence construct, based on a coactive or mutual-causal paradigm, encompasses traditional source-valence components (credibility, power,…

Estimating Causal Effects in Mediation Analysis Using Propensity Scores

ERIC Educational Resources Information Center

Coffman, Donna L.

2011-01-01

Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…

Category Coherence and Category-Based Property Induction

ERIC Educational Resources Information Center

Rehder, Bob; Hastie, Reid

2004-01-01

One important property of human object categories is that they define the sets of exemplars to which newly observed properties are generalized. We manipulated the causal knowledge associated with novel categories and assessed the resulting strength of property inductions. We found that the theoretical coherence afforded to a category by…

Assessing Methods for Generalizing Experimental Impact Estimates to Target Populations

ERIC Educational Resources Information Center

Kern, Holger L.; Stuart, Elizabeth A.; Hill, Jennifer; Green, Donald P.

2016-01-01

Randomized experiments are considered the gold standard for causal inference because they can provide unbiased estimates of treatment effects for the experimental participants. However, researchers and policymakers are often interested in using a specific experiment to inform decisions about other target populations. In education research,…

Partial Identification of Treatment Effects: Applications to Generalizability

ERIC Educational Resources Information Center

Chan, Wendy

2016-01-01

Results from large-scale evaluation studies form the foundation of evidence-based policy. The randomized experiment is often considered the gold standard among study designs because the causal impact of a treatment or intervention can be assessed without threats of confounding from external variables. Policy-makers have become increasingly…

Heart Rate Variability – a Tool to Differentiate Positive and Negative Affective States in Pigs?

USDA-ARS?s Scientific Manuscript database

The causal neurophysiological processes, such as autonomic nervous system activity, that mediate behavioral and physiological reactivity to an environment have largely been ignored. Heart rate variability (HRV) analysis is a clinical diagnostic tool used to assess affective states (stressful and ple...

Communication and Sensorimotor Functioning in Children with Autism.

ERIC Educational Resources Information Center

Abrahamsen, Eileen P.; Mitchell, Jennifer R.

1990-01-01

Sensorimotor functioning in 10 autistic children, age 3-7, was assessed on object permanence, means-end, causality, vocal and gestural imitation, the construction of objects in space, and schemes for relating objects. The number and diversity of pragmatic functions in the children's communication were also analyzed and related to sensorimotor…

Measurement and Model Linkages in Assessing School Environments.

ERIC Educational Resources Information Center

Schmitt, Neal

Detailed methodology used to evaluate a causal model of school environment is presented in this report. The model depicts societal features that influence school district values and organizational characteristics, which in turn influence school operations and personnel attitudes and values. These school variables affect school community members'…

Improvements to Elementary Children's Epistemic Understanding from Sustained Argumentation

ERIC Educational Resources Information Center

Ryu, Suna; Sandoval, William A.

2012-01-01

The aim of this study was to assess whether and how a sustained instructional focus on argumentation might improve children's understanding and application of key epistemic criteria for scientific arguments. These criteria include the articulation of clear, coherent causal claims, and the explicit justification of such claims with appropriate…

Multimodal cues drive host-plant assessment in Asian citrus psyllid (Diaphorina citri)

USDA-ARS?s Scientific Manuscript database

Asian citrus psyllid (Diaphorina citri) transmits the causal agent of Huanglongbing, a devastating disease of citrus trees. In this study, we measured behavioral responses of D. citri to combinations of visual, olfactory, and gustatory stimuli in test arenas. Stimuli were presented to the psyllids ...

Quasi-Experimental Analysis: A Mixture of Methods and Judgment.

ERIC Educational Resources Information Center

Cordray, David S.

1986-01-01

The role of human judgment in the development and synthesis of evidence has not been adequately developed or acknowledged within quasi-experimental analysis. Corrective solutions need to confront the fact that causal analysis within complex environments will require a more active assessment that entails reasoning and statistical modeling.…

Identification of Most Probable Stressors to Aquatic Life in the Touchet River, Washington (Final)

EPA Science Inventory

EPA announced the availability of the final report, Identification of Most Probable Stressors to Aquatic Life in the Touchet River, Washington. This study includes the screening causal assessment of the Touchet River, a sub-watershed of the Walla Walla River in eastern ...

A Life-Course Perspective on the "Gateway Hypothesis"

ERIC Educational Resources Information Center

Van Gundy, Karen; Rebellon, Cesar J.

2010-01-01

Drawing on stress and life-course perspectives and using panel data from 1,286 south Florida young adults, we assess three critical questions regarding the role of marijuana in the "gateway hypothesis." First, does teen marijuana use independently (causally) affect subsequent use of more dangerous substances? Second, if so, does that…

Learning about causes from people and about people as causes: probabilistic models and social causal reasoning.

PubMed

Buchsbaum, Daphna; Seiver, Elizabeth; Bridgers, Sophie; Gopnik, Alison

2012-01-01

A major challenge children face is uncovering the causal structure of the world around them. Previous research on children's causal inference has demonstrated their ability to learn about causal relationships in the physical environment using probabilistic evidence. However, children must also learn about causal relationships in the social environment, including discovering the causes of other people's behavior, and understanding the causal relationships between others' goal-directed actions and the outcomes of those actions. In this chapter, we argue that social reasoning and causal reasoning are deeply linked, both in the real world and in children's minds. Children use both types of information together and in fact reason about both physical and social causation in fundamentally similar ways. We suggest that children jointly construct and update causal theories about their social and physical environment and that this process is best captured by probabilistic models of cognition. We first present studies showing that adults are able to jointly infer causal structure and human action structure from videos of unsegmented human motion. Next, we describe how children use social information to make inferences about physical causes. We show that the pedagogical nature of a demonstrator influences children's choices of which actions to imitate from within a causal sequence and that this social information interacts with statistical causal evidence. We then discuss how children combine evidence from an informant's testimony and expressed confidence with evidence from their own causal observations to infer the efficacy of different potential causes. We also discuss how children use these same causal observations to make inferences about the knowledge state of the social informant. Finally, we suggest that psychological causation and attribution are part of the same causal system as physical causation. We present evidence that just as children use covariation between physical causes and their effects to learn physical causal relationships, they also use covaration between people's actions and the environment to make inferences about the causes of human behavior.

Self-regulated learning processes of medical students during an academic learning task.

PubMed

Gandomkar, Roghayeh; Mirzazadeh, Azim; Jalili, Mohammad; Yazdani, Kamran; Fata, Ladan; Sandars, John

2016-10-01

This study was designed to identify the self-regulated learning (SRL) processes of medical students during a biomedical science learning task and to examine the associations of the SRL processes with previous performance in biomedical science examinations and subsequent performance on a learning task. A sample of 76 Year 1 medical students were recruited based on their performance in biomedical science examinations and stratified into previous high and low performers. Participants were asked to complete a biomedical science learning task. Participants' SRL processes were assessed before (self-efficacy, goal setting and strategic planning), during (metacognitive monitoring) and after (causal attributions and adaptive inferences) their completion of the task using an SRL microanalytic interview. Descriptive statistics were used to analyse the means and frequencies of SRL processes. Univariate and multiple logistic regression analyses were conducted to examine the associations of SRL processes with previous examination performance and the learning task performance. Most participants (from 88.2% to 43.4%) reported task-specific processes for SRL measures. Students who exhibited higher self-efficacy (odds ratio [OR] 1.44, 95% confidence interval [CI] 1.09-1.90) and reported task-specific processes for metacognitive monitoring (OR 6.61, 95% CI 1.68-25.93) and causal attributions (OR 6.75, 95% CI 2.05-22.25) measures were more likely to be high previous performers. Multiple analysis revealed that similar SRL measures were associated with previous performance. The use of task-specific processes for causal attributions (OR 23.00, 95% CI 4.57-115.76) and adaptive inferences (OR 27.00, 95% CI 3.39-214.95) measures were associated with being a high learning task performer. In multiple analysis, only the causal attributions measure was associated with high learning task performance. Self-efficacy, metacognitive monitoring and causal attributions measures were associated positively with previous performance. Causal attributions and adaptive inferences measures were associated positively with learning task performance. These findings may inform remediation interventions in the early years of medical school training. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Alpha Oscillations Are Causally Linked to Inhibitory Abilities in Ageing.

PubMed

Borghini, Giulia; Candini, Michela; Filannino, Cristina; Hussain, Masud; Walsh, Vincent; Romei, Vincenzo; Zokaei, Nahid; Cappelletti, Marinella

2018-05-02

Aging adults typically show reduced ability to ignore task-irrelevant information, an essential skill for optimal performance in many cognitive operations, including those requiring working memory (WM) resources. In a first experiment, young and elderly human participants of both genders performed an established WM paradigm probing inhibitory abilities by means of valid, invalid, and neutral retro-cues. Elderly participants showed an overall cost, especially in performing invalid trials, whereas younger participants' general performance was comparatively higher, as expected.Inhibitory abilities have been linked to alpha brain oscillations but it is yet unknown whether in aging these oscillations (also typically impoverished) and inhibitory abilities are causally linked. To probe this possible causal link in aging, we compared in a second experiment parietal alpha-transcranial alternating current stimulation (tACS) with either no stimulation (Sham) or with two control stimulation frequencies (theta- and gamma-tACS) in the elderly group while performing the same WM paradigm. Alpha- (but not theta- or gamma-) tACS selectively and significantly improved performance (now comparable to younger adults' performance in the first experiment), particularly for invalid cues where initially elderly showed the highest costs. Alpha oscillations are therefore causally linked to inhibitory abilities and frequency-tuned alpha-tACS interventions can selectively change these abilities in the elderly. SIGNIFICANCE STATEMENT Ignoring task-irrelevant information, an ability associated to rhythmic brain activity in the alpha frequency band, is fundamental for optimal performance. Indeed, impoverished inhibitory abilities contribute to age-related decline in cognitive functions like working memory (WM), the capacity to briefly hold information in mind. Whether in aging adults alpha oscillations and inhibitory abilities are causally linked is yet unknown. We experimentally manipulated frequency-tuned brain activity using transcranial alternating current stimulation (tACS), combined with a retro-cue paradigm assessing WM and inhibition. We found that alpha-tACS induced a significant improvement in target responses and misbinding errors, two indexes of inhibition. We concluded that in aging alpha oscillations are causally linked to inhibitory abilities, and that despite being impoverished, these abilities are still malleable. Copyright © 2018 the authors 0270-6474/18/384419-12$15.00/0.

Estimating Causal Effects of Local Air Pollution on Daily Deaths: Effect of Low Levels.

PubMed

Schwartz, Joel; Bind, Marie-Abele; Koutrakis, Petros

2017-01-01

Although many time-series studies have established associations of daily pollution variations with daily deaths, there are fewer at low concentrations, or focused on locally generated pollution, which is becoming more important as regulations reduce regional transport. Causal modeling approaches are also lacking. We used causal modeling to estimate the impact of local air pollution on mortality at low concentrations. Using an instrumental variable approach, we developed an instrument for variations in local pollution concentrations that is unlikely to be correlated with other causes of death, and examined its association with daily deaths in the Boston, Massachusetts, area. We combined height of the planetary boundary layer and wind speed, which affect concentrations of local emissions, to develop the instrument for particulate matter ≤ 2.5 μm (PM2.5), black carbon (BC), or nitrogen dioxide (NO2) variations that were independent of year, month, and temperature. We also used Granger causality to assess whether omitted variable confounding existed. We estimated that an interquartile range increase in the instrument for local PM2.5 was associated with a 0.90% increase in daily deaths (95% CI: 0.25, 1.56). A similar result was found for BC, and a weaker association with NO2. The Granger test found no evidence of omitted variable confounding for the instrument. A separate test confirmed the instrument was not associated with mortality independent of pollution. Furthermore, the association remained when all days with PM2.5 concentrations > 30 μg/m3 were excluded from the analysis (0.84% increase in daily deaths; 95% CI: 0.19, 1.50). We conclude that there is a causal association of local air pollution with daily deaths at concentrations below U.S. EPA standards. The estimated attributable risk in Boston exceeded 1,800 deaths during the study period, indicating that important public health benefits can follow from further control efforts. Citation: Schwartz J, Bind MA, Koutrakis P. 2017. Estimating causal effects of local air pollution on daily deaths: effect of low levels. Environ Health Perspect 125:23-29; http://dx.doi.org/10.1289/EHP232.

Identification of neural connectivity signatures of autism using machine learning

PubMed Central

Deshpande, Gopikrishna; Libero, Lauren E.; Sreenivasan, Karthik R.; Deshpande, Hrishikesh D.; Kana, Rajesh K.

2013-01-01

Alterations in interregional neural connectivity have been suggested as a signature of the pathobiology of autism. There have been many reports of functional and anatomical connectivity being altered while individuals with autism are engaged in complex cognitive and social tasks. Although disrupted instantaneous correlation between cortical regions observed from functional MRI is considered to be an explanatory model for autism, the causal influence of a brain area on another (effective connectivity) is a vital link missing in these studies. The current study focuses on addressing this in an fMRI study of Theory-of-Mind (ToM) in 15 high-functioning adolescents and adults with autism and 15 typically developing control participants. Participants viewed a series of comic strip vignettes in the MRI scanner and were asked to choose the most logical end to the story from three alternatives, separately for trials involving physical and intentional causality. The mean time series, extracted from 18 activated regions of interest, were processed using a multivariate autoregressive model (MVAR) to obtain the causality matrices for each of the 30 participants. These causal connectivity weights, along with assessment scores, functional connectivity values, and fractional anisotropy obtained from DTI data for each participant, were submitted to a recursive cluster elimination based support vector machine classifier to determine the accuracy with which the classifier can predict a novel participant's group membership (autism or control). We found a maximum classification accuracy of 95.9% with 19 features which had the highest discriminative ability between the groups. All of the 19 features were effective connectivity paths, indicating that causal information may be critical in discriminating between autism and control groups. These effective connectivity paths were also found to be significantly greater in controls as compared to ASD participants and consisted predominantly of outputs from the fusiform face area and middle temporal gyrus indicating impaired connectivity in ASD participants, particularly in the social brain areas. These findings collectively point toward the fact that alterations in causal connectivity in the brain in ASD could serve as a potential non-invasive neuroimaging signature for autism. PMID:24151458

The development of causal reasoning.

PubMed

Kuhn, Deanna

2012-05-01

How do inference rules for causal learning themselves change developmentally? A model of the development of causal reasoning must address this question, as well as specify the inference rules. Here, the evidence for developmental changes in processes of causal reasoning is reviewed, with the distinction made between diagnostic causal inference and causal prediction. Also addressed is the paradox of a causal reasoning literature that highlights the competencies of young children and the proneness to error among adults. WIREs Cogn Sci 2012, 3:327-335. doi: 10.1002/wcs.1160 For further resources related to this article, please visit the WIREs website. Copyright © 2012 John Wiley & Sons, Ltd.

A dynamic analysis of S&P 500, FTSE 100 and EURO STOXX 50 indices under different exchange rates.

PubMed

Chen, Yanhua; Mantegna, Rosario N; Pantelous, Athanasios A; Zuev, Konstantin M

2018-01-01

In this study, we assess the dynamic evolution of short-term correlation, long-term cointegration and Error Correction Model (hereafter referred to as ECM)-based long-term Granger causality between each pair of US, UK, and Eurozone stock markets from 1980 to 2015 using the rolling-window technique. A comparative analysis of pairwise dynamic integration and causality of stock markets, measured in common and domestic currency terms, is conducted to evaluate comprehensively how exchange rate fluctuations affect the time-varying integration among the S&P 500, FTSE 100 and EURO STOXX 50 indices. The results obtained show that the dynamic correlation, cointegration and ECM-based long-run Granger causality vary significantly over the whole sample period. The degree of dynamic correlation and cointegration between pairs of stock markets rises in periods of high volatility and uncertainty, especially under the influence of economic, financial and political shocks. Meanwhile, we observe the weaker and decreasing correlation and cointegration among the three developed stock markets during the recovery periods. Interestingly, the most persistent and significant cointegration among the three developed stock markets exists during the 2007-09 global financial crisis. Finally, the exchange rate fluctuations, also influence the dynamic integration and causality between all pairs of stock indices, with that influence increasing under the local currency terms. Our results suggest that the potential for diversifying risk by investing in the US, UK and Eurozone stock markets is limited during the periods of economic, financial and political shocks.

STAMP-Based HRA Considering Causality Within a Sociotechnical System: A Case of Minuteman III Missile Accident.

PubMed

Rong, Hao; Tian, Jin

2015-05-01

The study contributes to human reliability analysis (HRA) by proposing a method that focuses more on human error causality within a sociotechnical system, illustrating its rationality and feasibility by using a case of the Minuteman (MM) III missile accident. Due to the complexity and dynamics within a sociotechnical system, previous analyses of accidents involving human and organizational factors clearly demonstrated that the methods using a sequential accident model are inadequate to analyze human error within a sociotechnical system. System-theoretic accident model and processes (STAMP) was used to develop a universal framework of human error causal analysis. To elaborate the causal relationships and demonstrate the dynamics of human error, system dynamics (SD) modeling was conducted based on the framework. A total of 41 contributing factors, categorized into four types of human error, were identified through the STAMP-based analysis. All factors are related to a broad view of sociotechnical systems, and more comprehensive than the causation presented in the accident investigation report issued officially. Recommendations regarding both technical and managerial improvement for a lower risk of the accident are proposed. The interests of an interdisciplinary approach provide complementary support between system safety and human factors. The integrated method based on STAMP and SD model contributes to HRA effectively. The proposed method will be beneficial to HRA, risk assessment, and control of the MM III operating process, as well as other sociotechnical systems. © 2014, Human Factors and Ergonomics Society.

The influence of linguistic and cognitive factors on the time course of verb-based implicit causality.

PubMed

Koornneef, Arnout; Dotlačil, Jakub; van den Broek, Paul; Sanders, Ted

2016-01-01

In three eye-tracking experiments the influence of the Dutch causal connective "want" (because) and the working memory capacity of readers on the usage of verb-based implicit causality was examined. Experiments 1 and 2 showed that although a causal connective is not required to activate implicit causality information during reading, effects of implicit causality surfaced more rapidly and were more pronounced when a connective was present in the discourse than when it was absent. In addition, Experiment 3 revealed that-in contrast to previous claims-the activation of implicit causality is not a resource-consuming mental operation. Moreover, readers with higher and lower working memory capacities behaved differently in a dual-task situation. Higher span readers were more likely to use implicit causality when they had all their working memory resources at their disposal. Lower span readers showed the opposite pattern as they were more likely to use the implicit causality cue in the case of an additional working memory load. The results emphasize that both linguistic and cognitive factors mediate the impact of implicit causality on text comprehension. The implications of these results are discussed in terms of the ongoing controversies in the literature-that is, the focusing-integration debate and the debates on the source of implicit causality.

Learning a theory of causality.

PubMed

Goodman, Noah D; Ullman, Tomer D; Tenenbaum, Joshua B

2011-01-01

The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be learned from co-occurrence of events. We begin by phrasing the causal Bayes nets theory of causality and a range of alternatives in a logical language for relational theories. This allows us to explore simultaneous inductive learning of an abstract theory of causality and a causal model for each of several causal systems. We find that the correct theory of causality can be learned relatively quickly, often becoming available before specific causal theories have been learned--an effect we term the blessing of abstraction. We then explore the effect of providing a variety of auxiliary evidence and find that a collection of simple perceptual input analyzers can help to bootstrap abstract knowledge. Together, these results suggest that the most efficient route to causal knowledge may be to build in not an abstract notion of causality but a powerful inductive learning mechanism and a variety of perceptual supports. While these results are purely computational, they have implications for cognitive development, which we explore in the conclusion.

Knowing Who Dunnit: Infants Identify the Causal Agent in an Unseen Causal Interaction

ERIC Educational Resources Information Center

Saxe, Rebecca; Tzelnic, Tania; Carey, Susan

2007-01-01

Preverbal infants can represent the causal structure of events, including distinguishing the agentive and receptive roles and categorizing entities according to stable causal dispositions. This study investigated how infants combine these 2 kinds of causal inference. In Experiments 1 and 2, 9.5-month-olds used the position of a human hand or a…

Causal Systems Categories: Differences in Novice and Expert Categorization of Causal Phenomena

ERIC Educational Resources Information Center

Rottman, Benjamin M.; Gentner, Dedre; Goldwater, Micah B.

2012-01-01

We investigated the understanding of causal systems categories--categories defined by common causal structure rather than by common domain content--among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative…

They Work Together to Roar: Kindergartners' Understanding of an Interactive Causal Task

ERIC Educational Resources Information Center

Solis, S. Lynneth; Grotzer, Tina A.

2016-01-01

The aim of this study was to investigate kindergartners' exploration of interactive causality during their play with a pair of toy sound blocks. Interactive causality refers to a type of causal pattern in which two entities interact to produce a causal force, as in particle attraction and symbiotic relationships. Despite being prevalent in nature,…

[Benefit assessment of medical services in German health service - legal framework, historical and international perspective].

PubMed

Windeler, Jürgen; Lange, Stefan

2015-03-01

The term benefit describes the (positive) causal, patient-relevant consequences of medical interventions, whether diagnostic or therapeutic. Benefit assessments form the basis of rational decision-making within a health care system. They are based on clinical trials that are able to provide valid answers to the question regarding the relevant benefit or harm that can be caused by an intervention. In Germany, evidence-based benefit assessments are fixed by law, i.e., the Social Code Book V. The application and the practical impact of these assessments could be improved.

Learning About Causes From People: Observational Causal Learning in 24-Month-Old Infants

PubMed Central

Meltzoff, Andrew N.; Waismeyer, Anna; Gopnik, Alison

2013-01-01

How do infants and young children learn about the causal structure of the world around them? In 4 experiments we investigate whether young children initially give special weight to the outcomes of goal-directed interventions they see others perform and use this to distinguish correlations from genuine causal relations—observational causal learning. In a new 2-choice procedure, 2- to 4-year-old children saw 2 identical objects (potential causes). Activation of 1 but not the other triggered a spatially remote effect. Children systematically intervened on the causal object and predictively looked to the effect. Results fell to chance when the cause and effect were temporally reversed, so that the events were merely associated but not causally related. The youngest children (24- to 36-month-olds) were more likely to make causal inferences when covariations were the outcome of human interventions than when they were not. Observational causal learning may be a fundamental learning mechanism that enables infants to abstract the causal structure of the world. PMID:22369335

Context and Time in Causal Learning: Contingency and Mood Dependent Effects

PubMed Central

Msetfi, Rachel M.; Wade, Caroline; Murphy, Robin A.

2013-01-01

Defining cues for instrumental causality are the temporal, spatial and contingency relationships between actions and their effects. In this study, we carried out a series of causal learning experiments that systematically manipulated time and context in positive and negative contingency conditions. In addition, we tested participants categorized as non-dysphoric and mildly dysphoric because depressed mood has been shown to affect the processing of all these causal cues. Findings showed that causal judgements made by non-dysphoric participants were contextualized at baseline and were affected by the temporal spacing of actions and effects only with generative, but not preventative, contingency relationships. Participants categorized as dysphoric made less contextualized causal ratings at baseline but were more sensitive than others to temporal manipulations across the contingencies. These effects were consistent with depression affecting causal learning through the effects of slowed time experience on accrued exposure to the context in which causal events took place. Taken together, these findings are consistent with associative approaches to causal judgement. PMID:23691147

How multiple causes combine: independence constraints on causal inference.

PubMed

Liljeholm, Mimi

2015-01-01

According to the causal power view, two core constraints-that causes occur independently (i.e., no confounding) and influence their effects independently-serve as boundary conditions for causal induction. This study investigated how violations of these constraints modulate uncertainty about the existence and strength of a causal relationship. Participants were presented with pairs of candidate causes that were either confounded or not, and that either interacted or exerted their influences independently. Consistent with the causal power view, uncertainty about the existence and strength of causal relationships was greater when causes were confounded or interacted than when unconfounded and acting independently. An elemental Bayesian causal model captured differences in uncertainty due to confounding but not those due to an interaction. Implications of distinct sources of uncertainty for the selection of contingency information and causal generalization are discussed.

Identifying Causal Variants at Loci with Multiple Signals of Association

PubMed Central

Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar

2014-01-01

Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20–50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. PMID:25104515

Identifying causal variants at loci with multiple signals of association.

PubMed

Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar

2014-10-01

Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20-50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. Copyright © 2014 by the Genetics Society of America.

Opening the Black Box and Searching for Smoking Guns: Process Causality in Qualitative Research

ERIC Educational Resources Information Center

Bennett, Elisabeth E.; McWhorter, Rochell R.

2016-01-01

Purpose: The purpose of this paper is to explore the role of qualitative research in causality, with particular emphasis on process causality. In one paper, it is not possible to discuss all the issues of causality, but the aim is to provide useful ways of thinking about causality and qualitative research. Specifically, a brief overview of the…

Developing Causal Understanding with Causal Maps: The Impact of Total Links, Temporal Flow, and Lateral Position of Outcome Nodes

ERIC Educational Resources Information Center

Jeong, Allan; Lee, Woon Jee

2012-01-01

This study examined some of the methodological approaches used by students to construct causal maps in order to determine which approaches help students understand the underlying causes and causal mechanisms in a complex system. This study tested the relationship between causal understanding (ratio of root causes correctly/incorrectly identified,…

Granger causality revisited

PubMed Central

Friston, Karl J.; Bastos, André M.; Oswal, Ashwini; van Wijk, Bernadette; Richter, Craig; Litvak, Vladimir

2014-01-01

This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality — providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes — as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling. PMID:25003817

Establishing causal coherence across sentences: an ERP study

PubMed Central

Kuperberg, Gina R.; Paczynski, Martin; Ditman, Tali

2011-01-01

This study examined neural activity associated with establishing causal relationships across sentences during online comprehension. ERPs were measured while participants read and judged the relatedness of three-sentence scenarios in which the final sentence was highly causally related, intermediately related and causally unrelated to its context. Lexico-semantic co-occurrence was matched across the three conditions using a Latent Semantic Analysis. Critical words in causally unrelated scenarios evoked a larger N400 than words in both highly causally related and intermediately related scenarios, regardless of whether they appeared before or at the sentence-final position. At midline sites, the N400 to intermediately related sentence-final words was attenuated to the same degree as to highly causally related words, but otherwise the N400 to intermediately related words fell in between that evoked by highly causally related and intermediately related words. No modulation of the Late Positivity/P600 component was observed across conditions. These results indicate that both simple and complex causal inferences can influence the earliest stages of semantically processing an incoming word. Further, they suggest that causal coherence, at the situation level, can influence incremental word-by-word discourse comprehension, even when semantic relationships between individual words are matched. PMID:20175676

Amodal causal capture in the tunnel effect.

PubMed

Bae, Gi Yeul; Flombaum, Jonathan I

2011-01-01

In addition to identifying individual objects in the world, the visual system must also characterize the relationships between objects, for instance when objects occlude one another or cause one another to move. Here we explored the relationship between perceived causality and occlusion. Can one perceive causality in an occluded location? In several experiments, observers judged whether a centrally presented event involved a single object passing behind an occluder, or one object causally launching another (out of view and behind the occluder). With no additional context, the centrally presented event was typically judged as a non-causal pass, even when the occluding and disoccluding objects were different colors--an illusion known as the 'tunnel effect' that results from spatiotemporal continuity. However, when a synchronized context event involved an unambiguous causal launch, participants perceived a causal launch behind the occluder. This percept of an occluded causal interaction could also be driven by grouping and synchrony cues in the absence of any explicitly causal interaction. These results reinforce the hypothesis that causality is an aspect of perception. It is among the interpretations of the world that are independently available to vision when resolving ambiguity, and that the visual system can 'fill in' amodally.

Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.

PubMed

Meng, Xiang-He; Shen, Hui; Chen, Xiang-Ding; Xiao, Hong-Mei; Deng, Hong-Wen

2018-03-01

Genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with diverse complex phenotypes and diseases, and provided tremendous opportunities for further analyses using summary association statistics. Recently, Pickrell et al. developed a robust method for causal inference using independent putative causal SNPs. However, this method may fail to infer the causal relationship between two phenotypes when only a limited number of independent putative causal SNPs identified. Here, we extended Pickrell's method to make it more applicable for the general situations. We extended the causal inference method by replacing the putative causal SNPs with the lead SNPs (the set of the most significant SNPs in each independent locus) and tested the performance of our extended method using both simulation and empirical data. Simulations suggested that when the same number of genetic variants is used, our extended method had similar distribution of test statistic under the null model as well as comparable power under the causal model compared with the original method by Pickrell et al. But in practice, our extended method would generally be more powerful because the number of independent lead SNPs was often larger than the number of independent putative causal SNPs. And including more SNPs, on the other hand, would not cause more false positives. By applying our extended method to summary statistics from GWAS for blood metabolites and femoral neck bone mineral density (FN-BMD), we successfully identified ten blood metabolites that may causally influence FN-BMD. We extended a causal inference method for inferring putative causal relationship between two phenotypes using summary statistics from GWAS, and identified a number of potential causal metabolites for FN-BMD, which may provide novel insights into the pathophysiological mechanisms underlying osteoporosis.

The role of causal criteria in causal inferences: Bradford Hill's "aspects of association".

PubMed

Ward, Andrew C

2009-06-17

As noted by Wesley Salmon and many others, causal concepts are ubiquitous in every branch of theoretical science, in the practical disciplines and in everyday life. In the theoretical and practical sciences especially, people often base claims about causal relations on applications of statistical methods to data. However, the source and type of data place important constraints on the choice of statistical methods as well as on the warrant attributed to the causal claims based on the use of such methods. For example, much of the data used by people interested in making causal claims come from non-experimental, observational studies in which random allocations to treatment and control groups are not present. Thus, one of the most important problems in the social and health sciences concerns making justified causal inferences using non-experimental, observational data. In this paper, I examine one method of justifying such inferences that is especially widespread in epidemiology and the health sciences generally - the use of causal criteria. I argue that while the use of causal criteria is not appropriate for either deductive or inductive inferences, they do have an important role to play in inferences to the best explanation. As such, causal criteria, exemplified by what Bradford Hill referred to as "aspects of [statistical] associations", have an indispensible part to play in the goal of making justified causal claims.