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Table 2 Rationale and measures of effect estimated and reported for Causal Mediation Analysis

From: Implementation and reporting of causal mediation analysis in 2015: a systematic review in epidemiological studies

References Reasona Measures discussed or reported Motivation for applicationb
Randomized controlled trials
 D’Amelio et al. [27] Mediation Natural direct and natural indirect effects
Emphasized direct effect
Improve understanding to show that above and beyond how the treatment works through the mediator, there is an independent effect
 Freeman et al. [28] Mediation Direct and indirect effectsc
Proportion mediated by various factors
Improve understanding of mechanisms
Cohort studies
 Banack et al. [26] Mediation Similar to controlled direct effect (with caveat that no manipulation of obesity could actually occur) Refute/confirm that selection bias drives the obesity paradox in cardiovascular disease
 Jackson et al. [29] Mediation Natural direct and indirect effects
Proportion mediated by each medical event
Improve understanding of mechanisms
 Kositsawat et al. [30] Mediation Not identified Not clear
 Louwies et al. [31] Mediation Direct and indirect effectc Improve understanding of mechanisms
 Lu et al. [32] Mediation Natural direct and natural indirect effect
Percent excess risk mediated
Natural indirect effect emphasized
Improve understanding of mechanisms
 Mendola et al. [33] Mediation Controlled direct effect Improve understanding
 Messerlian et al. [34] Mediation Controlled direct effect Improve understanding
 Raghavan et al. [35] Mediation Direct and indirect effects but only indirect effects reportedc
Proportion of risk mediated through genetic and metabolic factors
Improve understanding of what mediators might be ripe for intervention
Case control studies
 Rao et al. [36] Mediation Controlled direct effect Improve understanding
 Song et al. [37] Mediation Effect not mediated
mediated effectc
Proportion mediated through various biomarkers
Improve understanding of mechanisms
 Xie et al. [38] Mediation Direct and indirect effectc
Proportion of effect mediated through testosterone
Improve understanding
  1. aReason for applying causal mediation analysis: Mediation, Interaction, or Interference
  2. bMotivation for each application of causal mediation analysis. For mediation (1) improve understanding; (2) confirm/refute theory; (3) intervention refinement. For interaction (1) help allocate resources better; (2) identifying groups in which treatments may be harmful or beneficial (qualitative or cross-over interactions); (3) understand mechanisms; (4) increase statistical power of main effect analysis, and (5) understand which mediator to intervene upon to eliminate most of the effect of primary exposure. For interference (1) quantify spillover effects for cost-effectiveness studies; (2) understand what proportion must be treated to attain population outcomes desired; (3) create knowledge for intervention development and refinement
  3. c“Natural” was not specifically used in the article but appeared to have counterfactual framework and appropriate references