Let us suppose that we have an intervention, for example technology integration in the science classroom. Can we study what mediators could affect the results of the intervention, for example learning motivation? Can we study what moderators could affect the results of the intervention? And why.
For example, can we study how gender mediates the influence of the intervention on the learning otivation? or it would be better if we consider the interaction of gender and the intervention?
Wajeeh Daher You might want to take a close look at the literature concerning the mediator versus moderator distinction (e.g., Baron & Kenny, 1986; Hayes, 2022). A mediator is a variable that results in an indirect effect of one variable on another. In the simplest case, X (the intervention) causes M (the mediator) which then causes Y (the outcome). For example, an intervention (X) might cause greater motivation (M) which might then cause greater learning success (Y). The indirect (mediated) effect here is from X via M to Y and can be analyzed via path analysis (the product of path coefficients allows us to quantify the indirect effect). In path analysis, different regression equations for different outcomes (here: M and Y) are estimated simultaneously. See, MacKinnon (2008) or Hayes (2022) for good introductions to statistical mediation analysis.
Gender could not be a mediator in the relationship between the intervention and learning motivation, because a technology integration intervention cannot cause gender (to my knowledge). However, gender could be a moderator. That is, the intervention may have a differential effect on motivation for males versus females.
A moderator is a variable for which the effect of one variable (say X, intervention) on another (say M, motivation, and/or Y, learning) varies across the levels of the moderator Z (e.g., across gender groups). This is also called an interaction effect. For example, an intervention may cause increases in motivation (which may then cause improved learning), but only for females, not for males. Moderation analysis involves creating product terms (e.g., Z*X or Z*M) and adding them to a regression or path model as additional "predictors."
In summary, you could study both mediators and moderators of an intervention effect (also both these effects simultaneously in a path model, often termed a "moderated mediation analysis"), however gender would not be a plausible candidate for a mediator, but perhaps for a moderator variable.
References
Article The moderator-mediator variable distinction in social psycho...
Hayes (2022): https://www.guilford.com/books/Introduction-to-Mediation-Moderation-and-Conditional-Process-Analysis/Andrew-Hayes/9781462549030
MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. Taylor & Francis Group/Lawrence Erlbaum Associates.
You may want to look at this question: https://www.researchgate.net/post/How-can-we-distinguish-between-mediator-and-moderator-variable-theoretically
and this paper on intervention (in early years)
Article Mediators and moderators in early intervention research
Dear Christian Geiser and Kelvyn Jones,
Thank you for you detailed answers and wonderful references. They helped a lot.
Mediation analysis is used in social sciences, biology, epidemiology, and other fields in order to evaluate the mechanism through which an independent variable (X) affects a dependent variable (Y).
You can probably mix up between moderator and mediator. You may google these terms. Interaction terms are for moderators and path analysis is for mediation.
To answer your question on whether mediation or moderator can be tested for intervention studies, yes you can. However, it should be theoretically sound and the type of analysis is mentioned above.
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