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Items for consideration in a reporting guideline for mediation analyses: a Delphi study

Cashin, Aidan G, McAuley, James H, Lamb, Sallie, Hopewell, Sally, Kamper, Steven J, Williams, Christopher M, Henschke, Nicholas, Lee, Hopin·2021·BMJ Evidence-Based Medicine

Abstract

Objectives: Mediation analysis is a widely used quantitative method for investigating how interventions and exposures in randomised controlled trials and observational studies have an effect on healthcare outcomes. This study aimed to assess the importance of items that should be considered in a consensus meeting aimed at developing a guideline for reporting mediation analyses. Design: International online Delphi study. Participants: International experts in the development and application of mediation analysis. Main outcome measures: The Delphi panel were asked to rate the importance of a list of items for inclusion in a guideline for reporting mediation analyses. Thresholds for disagreement and consensus on importance for inclusion were specified a priori. We used the Research ANd Development/University of California Los Angeles appropriateness method to quantitatively assess the importance for inclusion and panel agreement. Results: Nineteen expert panellists (10 female) from seven countries agreed to participate. All panellists contributed to all three rounds conducted between 10 June 2019 and 6 November 2019. The panel reached consensus on 34 unique reporting items for study design, analytic procedures and effect estimates, with three items rated ‘optional’. Panellists added one extra item and provided 60 qualitative comments for item refinement and prioritisation. Conclusion: This Delphi study used a rigorous consensus process to reach consensus on 34 reporting items for studies that use mediation analysis. These results will inform a consensus meeting that will consolidate a core set of recommended items for reporting mediation analyses.

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Research works printed but not linked: 26

  1. 10.1136/bmj.h1258 · DOI · Paper page
  2. Lee, 2019, Investigating causal mechanisms in randomised controlled trials, Trials, 20, 10.1186/s13063-019-3593-z · DOI
  3. Lange, 2017, Applied mediation analyses: a review and tutorial, Epidemiol Health, 39, 10.4178/epih.e2017035 · DOI
  4. Lee, 2019, Mediation analysis, JAMA, 321, 697, 10.1001/jama.2018.21973 · DOI
  5. VanderWeele T . Explanation in causal inference. Oxford University Press, 2015.
  6. Keele, 2015, Identifying mechanisms behind policy interventions via causal mediation analysis, J Policy Anal Manag, 34, 937, 10.1002/pam.21853 · DOI
  7. Lee, 2017, Advancing physical therapist interventions by investigating causal mechanisms, Phys Ther, 97, 1119, 10.1093/ptj/pzx095 · DOI
  8. Nguyen TQ , Schmid I , Stuart EA . Clarifying causal mediation analysis for the applied researcher: defining effects based on what we want to learn, 2019. Available: http://arxiv.org/abs/1904.08515 · arXiv
  9. Liu, 2016, Implementation and reporting of causal mediation analysis in 2015: a systematic review in epidemiological studies, BMC Res Notes, 9, 10.1186/s13104-016-2163-7 · DOI
  10. 10.3200/GENP.136.2.153-178 · DOI
  11. 10.1016/j.berh.2013.10.001 · DOI
  12. Hertzog, 2018, Trends in mediation analysis in nursing research: improving current practice, West J Nurs Res, 40, 907, 10.1177/0193945916687782 · DOI
  13. 10.1177/1094428106297811 · DOI
  14. 10.1186/s12874-018-0578-7 · DOI
  15. Vo, 2020, The conduct and reporting of mediation analysis in recently published randomized controlled trials: results from a methodological systematic review, J Clin Epidemiol, 117, 78, 10.1016/j.jclinepi.2019.10.001 · DOI
  16. 10.1186/1741-7015-8-18 · DOI · Paper page
  17. 10.1136/bmj.39335.541782.AD · DOI · Paper page
  18. Cashin AG , McAuley JH , Lamb SE , et al . Development of a guideline for reporting mediation analyses (AGReMA). BMC Med Res Methodol 2020;20.doi:10.1186/s12874-020-0915-5 · DOI
  19. 10.1371/journal.pmed.1000217 · DOI · Paper page
  20. 10.1136/bmj.311.7001.376 · DOI · Paper page
  21. Froud, 2020, Opportunities and challenges around adapting supported employment interventions for people with chronic low back pain: modified nominal group technique, Disabil Rehabil, 1
  22. 10.1016/j.ejpain.2011.04.015 · DOI
  23. Murphy, 1998, Consensus development methods, and their use in clinical Guideline development, Health Technol Assess, 2, 1, 10.3310/hta2030 · DOI
  24. 10.1136/bmj.j3453 · DOI · Paper page
  25. 10.1186/1741-7015-8-24 · DOI · Paper page
  26. 10.1186/s13012-015-0235-z · DOI · Paper page

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Metadata

Authors
Cashin, A. G., McAuley, J. H., Lamb, S., Hopewell, S., Kamper, S. J., Williams, C. M., Henschke, N., & Lee, H.
Venue
BMJ Evidence-Based Medicine
Publisher
BMJ
Published
2020-08-26
Volume
26
Issue
3
Pages
106-106
ISSN
  • 2515-446X
  • 2515-4478
Cited by
7
References
7
Language
en
Funders
The Berkeley Initiative for Transparency in the Social Sciences, a program of the Center for Effective Global Action (CEGA), with support from the Laura and John Arnold Foundation (SSMART Grant)

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