  Mediation analysis is a statistical approach that can provide insights
regarding the intermediary processes by which an intervention or exposure
affects a given outcome. Mediation analyses rose to prominence, particularly in
social science research, with the publication of the seminal paper by Baron and
Kenny and is now commonly applied in many research disciplines, including
health services research. Despite the growth in popularity, applied researchers
may still encounter challenges in terms of conducting mediation analyses in
practice. In this paper, we provide an overview of conceptual and
methodological challenges that researchers face when conducting mediation
analyses. Specifically, we discuss the following key challenges: (1)
Conceptually differentiating mediators from other third variables, (2)
Extending beyond the single mediator context, (3) Identifying appropriate
datasets in which measurement and temporal ordering supports the hypothesized
mediation model, (4) Selecting mediation effects that reflect the scientific
question of interest, (5) Assessing the validity of underlying assumptions of
no omitted confounders, (6) Addressing measurement error regarding the
mediator, and (7) Clearly reporting results from mediation analyses. We discuss
each challenge and highlight ways in which the applied researcher can approach
these challenges.
