Literature DB >> 34550343

Assumptions Not Often Assessed or Satisfied in Published Mediation Analyses in Psychology and Psychiatry.

Elizabeth A Stuart, Ian Schmid, Trang Nguyen, Elizabeth Sarker, Adam Pittman, Kelly Benke, Kara Rudolph, Elena Badillo-Goicoechea, Jeannie-Marie Leoutsakos.   

Abstract

Mediation analysis aims to investigate the mechanisms of action behind the effects of interventions or treatments. Given the history and common use of mediation in mental health research, we conducted this review to understand how mediation analysis is implemented in psychology and psychiatry and whether analyses adhere to, address, or justify the key underlying assumptions of their approaches. All articles (n = 206) were from top academic psychiatry or psychology journals in the PsycInfo database and were published in English from 2013 to 2018. Information extracted from each article related to study design, covariates adjusted for in the analysis, temporal ordering of variables, and the specific method used to perform the mediation analysis. In most studies, underlying assumptions were not adhered to. Only approximately 20% of articles had full temporal ordering of exposure, mediator, and outcome. Confounding of the exposure-mediator and/or mediator-outcome relationships was controlled for in fewer than half of the studies. In almost none of the articles were the underlying assumptions of their approaches discussed or causal mediation methods used. These results provide insights to how methodologists should aim to communicate methods, and motivation for more outreach to the research community on best practices for mediation analysis.
© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  causal inference; mental health; statistical methods

Mesh:

Year:  2022        PMID: 34550343      PMCID: PMC8900288          DOI: 10.1093/epirev/mxab007

Source DB:  PubMed          Journal:  Epidemiol Rev        ISSN: 0193-936X            Impact factor:   4.280


  14 in total

1.  A general approach to causal mediation analysis.

Authors:  Kosuke Imai; Luke Keele; Dustin Tingley
Journal:  Psychol Methods       Date:  2010-12

2.  Quantifying and Testing Indirect Effects in Simple Mediation Models When the Constituent Paths Are Nonlinear.

Authors:  Andrew F Hayes; Kristopher J Preacher
Journal:  Multivariate Behav Res       Date:  2010-08-06       Impact factor: 5.923

3.  Bias in Cross-Sectional Analyses of Longitudinal Mediation: Partial and Complete Mediation Under an Autoregressive Model.

Authors:  Scott E Maxwell; David A Cole; Melissa A Mitchell
Journal:  Multivariate Behav Res       Date:  2011-09-30       Impact factor: 5.923

4.  Addressing Moderated Mediation Hypotheses: Theory, Methods, and Prescriptions.

Authors:  Kristopher J Preacher; Derek D Rucker; Andrew F Hayes
Journal:  Multivariate Behav Res       Date:  2007 Jan-Mar       Impact factor: 5.923

5.  Identifiability and exchangeability for direct and indirect effects.

Authors:  J M Robins; S Greenland
Journal:  Epidemiology       Date:  1992-03       Impact factor: 4.822

6.  Bias in cross-sectional analyses of longitudinal mediation.

Authors:  Scott E Maxwell; David A Cole
Journal:  Psychol Methods       Date:  2007-03

7.  A Viable Alternative When Propensity Scores Fail: Evaluation of Inverse Propensity Weighting and Sequential G-Estimation in a Two-Wave Mediation Model.

Authors:  Matthew J Valente; David P MacKinnon; Gina L Mazza
Journal:  Multivariate Behav Res       Date:  2019-06-20       Impact factor: 5.923

8.  The conduct and reporting of mediation analysis in recently published randomized controlled trials: results from a methodological systematic review.

Authors:  Tat-Thang Vo; Cecilia Superchi; Isabelle Boutron; Stijn Vansteelandt
Journal:  J Clin Epidemiol       Date:  2019-10-05       Impact factor: 6.437

9.  Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros.

Authors:  Linda Valeri; Tyler J Vanderweele
Journal:  Psychol Methods       Date:  2013-02-04

10.  Semiparametric Theory for Causal Mediation Analysis: efficiency bounds, multiple robustness, and sensitivity analysis.

Authors:  Eric J Tchetgen Tchetgen; Ilya Shpitser
Journal:  Ann Stat       Date:  2012-06       Impact factor: 4.028

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