scholarly journals Heterogeneous Mediation Analysis for Causal Inference

2020 ◽  
Author(s):  
Fei Xue ◽  
Xiwei Tang ◽  
Grace Kim ◽  
Allison Aiello ◽  
Karestan Koenen ◽  
...  
Keyword(s):  
Causal Inference ◽  
Mediation Analysis ◽  
Homogeneous Model ◽  
Heterogeneous Data ◽  
Health Study ◽  
Traumatic Experiences ◽  
Post Traumatic Stress ◽  
Model Framework ◽  
Mediation Effects ◽  
Mediating Mechanisms

AbstractMediation analysis is widely used to understand mediating mechanisms of variables in causal inference. However, existing approaches do not consider heterogeneity in mediation effects. Mediators in different sub-populations could have opposite effects on the outcome, and could be difficult to identify under the homogeneous model framework. In this paper, we propose a new mediator selection method, which can identify sub-populations and select mediators in each sub-population for heterogeneous data simultaneously. We perform a multi-directional clustering analysis to determine sub-group mediators and the corresponding subjects. Specifically, to select mediators, we propose a new joint penalty which penalizes the effect of independent variable on a mediator and the effect of a mediator on the response jointly. The proposed algorithm is implemented through the convex-smooth gradient descent. Our numerical studies show that the proposed method outperforms the existing methods for heterogeneous data. We also apply the proposed mediation method to estimate mediation effects of DNA methylation variations in glucocorticoid receptor regulatory network genes for post-traumatic stress disorder (PTSD) among African-Americans. Based on data from the Detroit Neighborhood Health Study, we have found heterogeneous mediators, which are indeed associated with PTSD or traumatic experiences according to literature but were not selected by existing homogeneous mediation selection methods.

scholarly journals Bayesian causal mediation analysis with multiple ordered mediators

2018 ◽  
Vol 19 (6) ◽  
pp. 634-652
Author(s):  
Tianming Gao ◽  
Jeffrey M Albert
Keyword(s):  
Mediation Analysis ◽  
Mixed Model ◽  
Dental Health ◽  
Health Study ◽  
Mediation Effects ◽  
Causal Mediation ◽  
Causal Pathways ◽  
Sensitivity Parameter ◽  
Causal Pathway ◽  
Causal Mediation Analysis

Causal mediation analysis provides investigators insight into how a treatment or exposure can affect an outcome of interest through one or more mediators on causal pathway. When multiple mediators on the pathway are causally ordered, identification of mediation effects on certain causal pathways requires a sensitivity parameter to be specified. A mixed model-based approach was proposed in the Bayesian framework to connect potential outcomes at different treatment levels, and identify mediation effects independent of a sensitivity parameter, for the natural direct and indirect effects on all causal pathways. The proposed method is illustrated in a linear setting for mediators and outcome, with mediator-treatment interactions. Sensitivity analysis was performed for the prior choices in the Bayesian models. The proposed Bayesian method was applied to an adolescent dental health study, to see how social economic status can affect dental caries through a sequence of causally ordered mediators in dental visit and oral hygiene index.

scholarly journals Latent cause inference during extinction learning in trauma-exposed individuals with and without PTSD

2021 ◽  
pp. 1-12
Author(s):  
Agnes Norbury ◽  
Hannah Brinkman ◽  
Mary Kowalchyk ◽  
Elisa Monti ◽  
Robert H. Pietrzak ◽  
...  
Keyword(s):  
Individual Differences ◽  
Causal Inference ◽  
Traumatic Stress ◽  
Causal Structure ◽  
Traumatic Experiences ◽  
Model Parameters ◽  
Depression Symptom ◽  
Post Traumatic Stress ◽  
Extinction Learning ◽  
Post Traumatic

Abstract Background Problems in learning that sights, sounds, or situations that were once associated with danger have become safe (extinction learning) may explain why some individuals suffer prolonged psychological distress following traumatic experiences. Although simple learning models have been unable to provide a convincing account of why this learning fails, it has recently been proposed that this may be explained by individual differences in beliefs about the causal structure of the environment. Methods Here, we tested two competing hypotheses as to how differences in causal inference might be related to trauma-related psychopathology, using extinction learning data collected from clinically well-characterised individuals with varying degrees of post-traumatic stress (N = 56). Model parameters describing individual differences in causal inference were related to multiple post-traumatic stress disorder (PTSD) and depression symptom dimensions via network analysis. Results Individuals with more severe PTSD were more likely to assign observations from conditioning and extinction stages to a single underlying cause. Specifically, greater re-experiencing symptom severity was associated with a lower likelihood of inferring that multiple causes were active in the environment. Conclusions We interpret these results as providing evidence of a primary deficit in discriminative learning in participants with more severe PTSD. Specifically, a tendency to attribute a greater diversity of stimulus configurations to the same underlying cause resulted in greater uncertainty about stimulus-outcome associations, impeding learning both that certain stimuli were safe, and that certain stimuli were no longer dangerous. In the future, better understanding of the role of causal inference in trauma-related psychopathology may help refine cognitive therapies for these disorders.

scholarly journals Latent cause inference during extinction learning in trauma-exposed individuals with and without PTSD

2020 ◽  
Author(s):  
Agnes Norbury ◽  
Hannah Brinkman ◽  
Mary Kowalchyk ◽  
Elisa Monti ◽  
Robert H Pietrzak ◽  
...  
Keyword(s):  
Causal Inference ◽  
Causal Structure ◽  
Negative Relationship ◽  
Traumatic Experiences ◽  
Depression Symptom ◽  
Post Traumatic Stress ◽  
Extinction Learning ◽  
Symptom Dimensions ◽  
Primary Deficit ◽  
Cognitive Therapies

Problems in learning that sights, sounds, or situations that were once associated with danger have become safe (extinction learning) may explain why some individuals suffer prolonged psychological distress following traumatic experiences. Although simple associative learning models have been unable to provide a convincing account of how and why this learning fails, it has recently been proposed that this may be explained by individual differences in beliefs about the causal structure of the environment. Here, we tested two competing hypotheses as to how differences in causal inference might be related to trauma-related psychopathology, using extinction learning data collected from clinically well-characterized individuals with varying degrees of post-traumatic stress (N=56). Latent cause modelling revealed that individuals with more severe PTSD were more likely to assign observations from conditioning and extinction stages to a single underlying cause. Specifically, multivariate analysis incorporating multiple PTSD and depression symptom dimensions revealed a negative relationship between tendency to infer multiple causes were active in the environment and re-experiencing symptom severity. We interpret these results as providing evidence of a primary deficit in discriminative learning in participants with more severe PTSD re-experiencing symptoms. Specifically, in these individuals, a greater tendency to attribute all stimulus configurations to the same underlying cause resulted in greater uncertainty about stimulus-outcome associations, and impeded learning both that certain stimuli were safe, and that certain stimuli were no longer dangerous. Better understanding of the role of causal inference in trauma-related psychopathology may have relevance for the refinement of cognitive therapies for these disorders.

scholarly journals Mendelian randomisation for mediation analysis: current methods and challenges for implementation

2021 ◽  
Author(s):  
Alice R. Carter ◽  
Eleanor Sanderson ◽  
Gemma Hammerton ◽  
Rebecca C. Richmond ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Measurement Error ◽  
Causal Inference ◽  
Mediation Analysis ◽  
Instrumental Variable ◽  
Real Data ◽  
Mendelian Randomisation ◽  
Differential Measurement ◽  
Individual Level ◽  
Differential Measurement Error ◽  
Summary Data

AbstractMediation analysis seeks to explain the pathway(s) through which an exposure affects an outcome. Traditional, non-instrumental variable methods for mediation analysis experience a number of methodological difficulties, including bias due to confounding between an exposure, mediator and outcome and measurement error. Mendelian randomisation (MR) can be used to improve causal inference for mediation analysis. We describe two approaches that can be used for estimating mediation analysis with MR: multivariable MR (MVMR) and two-step MR. We outline the approaches and provide code to demonstrate how they can be used in mediation analysis. We review issues that can affect analyses, including confounding, measurement error, weak instrument bias, interactions between exposures and mediators and analysis of multiple mediators. Description of the methods is supplemented by simulated and real data examples. Although MR relies on large sample sizes and strong assumptions, such as having strong instruments and no horizontally pleiotropic pathways, our simulations demonstrate that these methods are unaffected by confounders of the exposure or mediator and the outcome and non-differential measurement error of the exposure or mediator. Both MVMR and two-step MR can be implemented in both individual-level MR and summary data MR. MR mediation methods require different assumptions to be made, compared with non-instrumental variable mediation methods. Where these assumptions are more plausible, MR can be used to improve causal inference in mediation analysis.

scholarly journals Work Shift, Lifestyle Factors, and Subclinical Atherosclerosis in Spanish Male Workers: A Mediation Analysis

Nutrients ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 1077
Author(s):  
José L. Peñalvo ◽  
Elly Mertens ◽  
Ainara Muñoz-Cabrejas ◽  
Montserrat León-Latre ◽  
Estíbaliz Jarauta ◽  
...  
Keyword(s):  
Mediation Analysis ◽  
Subclinical Atherosclerosis ◽  
Night Shift ◽  
Logistic Models ◽  
Health Study ◽  
Lifestyle Habits ◽  
Potential Association ◽  
Workplace Wellness Programs ◽  
Working Shift ◽  
Work Shifts

(1) Background: Working night shifts has been associated with altered circadian rhythms, lifestyle habits, and cardiometabolic risks. No information on the potential association of working shift and the presence of atherosclerosis is available. The aim of this study was to quantify the association between different work shifts and the presence of subclinical atherosclerosis objectively measured by imaging. (2) Methods: Analyses were conducted on the baseline data of the Aragon Workers Health Study (AWHS) cohort, including information on 2459 middle-aged men. Categories of shift work included central day shift, rotating morning-evening or morning-evening-night shift, and night shift. The presence of atherosclerotic plaques was assessed by 2D ultrasound in the carotid and femoral vascular territories. Multivariable logistic models and mediation analysis were conducted to characterize and quantify the association between study variables. (3) Results: Participants working night or rotating shifts presented an overall worse cardiometabolic risk profile, as well as more detrimental lifestyle habits. Workers in the most intense (morning-evening-night) rotating shift presented higher odds of subclinical atherosclerosis (odds ratio: 1.6; 95% confidence interval: 1.12 to 2.27) compared to workers in the central shift, independently of the presence of lifestyle and metabolic risk factors. A considerable (21%) proportion of this association was found to be mediated by smoking, indicating that altered sleep-wake cycles have a direct relationship with the early presence of atherosclerotic lesions. (4) Conclusions: Work shifts should be factored in during workers health examinations, and when developing effective workplace wellness programs.

Which cognitions and behaviours mediate the positive effect of cognitive behavioural therapy on fatigue in patients with multiple sclerosis?

2011 ◽  
Vol 42 (1) ◽  
pp. 205-213 ◽  
Author(s):  
H. Knoop ◽  
K. van Kessel ◽  
R. Moss-Morris
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Behavioural Therapy ◽  
Mediation Analysis ◽  
Relaxation Training ◽  
Illness Perception ◽  
Depression Scale ◽  
Behavioural Therapy ◽  
Common Symptom ◽  
Mediation Effects ◽  
Cognitive Behavioural

BackgroundChronic fatigue is a common symptom of multiple sclerosis (MS). A randomized controlled trial (RCT) showed that cognitive behavioural therapy (CBT) was more effective in reducing MS fatigue than relaxation training (RT). The aim of the current study was to analyse additional data from this trial to determine whether (1) CBT compared to RT leads to significantly greater changes in cognitions and behaviours hypothesized to perpetuate MS fatigue; (2) changes in these variables mediate the effect of CBT on MS fatigue; and (3) these mediation effects are independent of changes in mood.MethodSeventy patients (CBT, n=35; RT, n=35) completed the Cognitive and Behavioural Responses to Symptoms Questionnaire (CBSQ), the Brief Illness Perception Questionnaire (B-IPQ) modified to measure negative representations of fatigue, the Hospital Anxiety and Depression Scale (HADS), and the Chalder Fatigue Questionnaire (CFQ), pre- and post-therapy. Multiple mediation analysis was used to determine which variables mediated the change in fatigue.ResultsAvoidance behaviour and three cognitive variables (symptom focusing, believing symptoms are a sign of damage and a negative representation of fatigue) improved significantly more in the CBT than the RT group. Mediation analysis showed that changing negative representations of fatigue mediated the decrease in severity of fatigue. Change in anxiety covaried with reduction in fatigue but the mediation effect for negative representations of fatigue remained when controlling for improvements in mood.ConclusionsChange in beliefs about fatigue play a crucial role in CBT for MS fatigue. These beliefs and the role of anxiety deserve more attention in the further development of this intervention.

Causal mediation in developmental science: A primer

2021 ◽  
pp. 016502542098164
Author(s):  
Jorge Cuartas ◽  
Dana Charles McCoy
Keyword(s):  
Best Practices ◽  
Mediation Analysis ◽  
Critical Role ◽  
Experimental Studies ◽  
Developmental Theory ◽  
Potential Outcomes ◽  
Mediation Effects ◽  
Causal Mediation ◽  
Developmental Science ◽  
Potential Outcomes Framework

Mediation has played a critical role in developmental theory and research. Yet, developmentalists rarely discuss the methodological challenges of establishing causality in mediation analysis or potential strategies to improve the identification of causal mediation effects. In this article, we discuss the potential outcomes framework from statistics as a means for highlighting several fundamental challenges of establishing causality in mediation analysis, including the difficulty of meeting the key assumption of sequential ignorability, even in experimental studies. We argue that this framework—which, although commonplace in other fields, has not yet been taken up in developmental science—can inform solutions to these challenges. Based on the framework, we offer a series of recommendations for improving causal inference in mediation analysis, including an overview of best practices in both study design and analysis, as well as resources for conducting analysis. In doing so, our overall objective in this article is to support the use of rigorous methods for understanding questions of mechanism in developmental science.

Trauma Focused Psychodynamic Psychotherapy

2021 ◽  
Author(s):  
Frederic Busch ◽  
Barbara Milrod ◽  
Cory Chen ◽  
Meriamne Singer
Keyword(s):  
Traumatic Stress ◽  
Psychodynamic Psychotherapy ◽  
Symptomatic Relief ◽  
Traumatic Experiences ◽  
Veterans Administration ◽  
Post Traumatic Stress ◽  
Interpersonal Engagement ◽  
Post Traumatic ◽  
The Impact ◽  
Insight Into

This book, which operationalizes and articulates in detail a unique, brief, tested psychodynamic psychotherapy for Post-Traumatic Stress Disorder, Trauma Focused Psychodynamic Psychotherapy [TFPP], describes how to perform this helpful treatment. The book provides tailored psychodynamic background that underpins these approaches, and explains the different phases of treatment. Additionally, it articulates common underlying dynamics of PTSD that the treatment commonly addresses in patients to bring about symptomatic relief. TFPP is being tested in two diverse populations: military Veterans with PTSD who are receiving care at three Veterans Administration Hospitals, and also among LGBTQ patients with PTSD. The book is focused on the authors’ experiences treating Veterans and many clinical examples are provided demonstrating how to work with these principles and approaches. In general, patients and therapists have found the treatment to be an extremely useful tool. Veterans have gained insight into the impact of traumatic experiences on various aspects of their lives and had improvements in dissociation, interpersonal engagement, anxiety, and anger/hostility. TFPP appears to be particularly effective for patients with prominent avoidance symptoms and those who are unwilling or unable to recount the details of their trauma directly. Patients have been found to be more affectively engaged and better connected to others (including the therapist) following treatment.

scholarly journals Prying Open the Black Box of Causality - A Causal Mediation Analysis Test of Procedural Justice Policing

2017 ◽  
Author(s):  
Krisztián Pósch
Keyword(s):  
Procedural Justice ◽  
Treatment Effect ◽  
Mediation Analysis ◽  
Black Box ◽  
Mediation Effects ◽  
Causal Mediation ◽  
Treatment Implementation ◽  
Causal Mediation Analysis ◽  
The Impact ◽  
Sense Of Power

Objectives: Review causal mediation analysis as a method for estimating and assessing direct and indirect effects in experimental criminology. Test procedural justice theory by examining the extent to which procedural justice mediates the impact of contact with the police on various outcomes. Apply causal mediation analysis to better interpret data from a field experiment that had suffered from a particular type of implementation failure.Methods: Data from a block-randomised controlled trial of procedural justice policing (the Scottish Community Engagement Trial) were analysed. All constructs were measured using surveys distributed during roadside police checks. The treatment implementation was assessed by analysing the treatment effect consistency and heterogeneity. Causal mediation analysis and sensitivity analysis were used to assess the mediating role of procedural justice.Results: First, the treatment effect was consistent and fairly homogeneous, indicating that the systematic variation in the study is attributable to the design. Second, procedural justice acts as a mediator channelling the treatment’s effect towards normative alignment (NIE=-0.207), duty to obey (NIE=-0.153), sense of power (NIE=-0.078), and social identity (NIE=-0.052), all of which are moderately robust to unmeasured confounding. The NIEs for risk of sanction and personal morality were highly sensitive, while for coerced obligation and sense of power they were non-significant. Conclusions: Causal mediation analysis is a versatile tool that can salvage experiments with systematic yet ambiguous treatment effects by allowing researchers to “pry open” the black box of causality. Most of the theoretical propositions of procedural justice policing were supported. Future studies are needed with more discernible causal mediation effects.

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