According to Fairchild & MacKinnon (2008), there is often a more complex association between variables than the relations between criterion and predictors. However, the associations can be modified or informed by adding third variables such as mediators and moderators in a research design. Analyzing mediators and moderators separately for the same data type has been instrumental in research design. However, simultaneous examination of these two effects variables allows the investigation of more complex and varied research hypotheses. Moderators are variables that affect the direction and strength of the relationship between two variables. In this case, a moderator may either strengthen or weaken the relationship or change the direction of the relationship. On the other hand, mediator variables account and specify why or how a relationship occurs. A mediator often describes the psychological process that occurs when creating a relationship, and thus they are often dynamic properties of individuals such as behaviors and emotions.
The research article utilizes both mediator and moderator variables. Mediator variables used in this study include income, school enrollment, and mother’s post-secondary degree attainment. Additionally, the article utilized moderating variables, including heterogeneity, smoking, gender, global mental health, self-rated overall health and parenting stress. The author extensively analyzes the mediator, income, to check whether or why there is a relationship between income level and mothers returning to schools. The author examines income level to test for any indirect effects of income that is the main driver for the mothers’ decision to go to school. Research findings indicate that though income levels were primarily related to the associated health outcomes, they did not mediate the link between associate and vocational degree attainment and maternal health. However, income level indirectly associated the links between wave five bachelor completion and maternal health at a minor effect.
As discussed earlier, moderating variables affect the direction, strength and relationship between two variables and in this study, I identified heavy drinking, heterogeneity, measures of depression in the study. Notably, the author examines how heterogenicity affects the mothers’ primary levels of education through enhancing an association between education and time-variant measures in the field effects of the model. However, the study did not reveal a significant relationship between heterogenicity and baseline education. In addition, smoking is another moderating variable discussed used in this study. However, the study found no significant association between reduced smoking and bachelor level completion among mothers with high school degrees.
From this study, I learnt that mediating and moderating variables are significant. They assist a researcher in studying beyond the primary relationship between two variables, thus enhancing deeper understanding and getting the whole picture in the relationship between any variables. The article deploys various moderate and mediating variables, including parent stress, income, and age, to expound on maternal health and maternal education. Furthermore, employing mediation analysis within a study enhances the researcher to investigate whether the interventions in the study produced a change in the mediating variables that it was designated to change. For instance, in this study, if a bachelor’s degree was supposed to increase awareness of the mother’s maternal health, the study effects on norms should be observed. On the other hand, moderation analysis enhances the specificity of a study’s results. This enhances the researcher to identify which intervention in research has a significant effect and which does not. Notably, such information helps target groups and improves intervention.
References
Augustine, J. M. (2021). Mothers’ Out-of-Sequence Postsecondary Education and Their Health and Health Behaviors. Journal of Health and Social Behavior, 62(1), 2–18. https://doi.org/10.1177/0022146520979664
Fairchild, A. J., & MacKinnon, D. P. (2008). A General Model for Testing Mediation and Moderation Effects. Prevention Science, 10(2), 87–99. https://doi.org/10.1007/s11121-008-0109-6
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