Secondary Analysis to Inform the Development of Adaptive Preventive Interventions

For the past 30 years, scholars across the fields of epidemiology, education, psychology, and numerous other fields have worked to develop interventions designed to reduce risk and enhance protection to prevent mental, emotional, and behavioral problems across the lifespan. This article presents a series of next steps that leverage this foundational science to inform the development of adaptive preventive interventions. Adaptive preventive interventions (APIs) tailor the intervention to fit the diverse, sometimes changing, needs of participants with the goal of better prevention outcomes for more individuals. Secondary analyses of data from preventive intervention trials to identify moderators, mediators, and antecedents of attrition and intervention failure can be useful for designing effective APIs. Moderators that identify intervention effect heterogeneity can be used within an API to tailor the intervention to meet the unique needs of important participant subgroups. Mediators and predictors of disengagement and attrition can be helpful tailoring variables in an API to trigger change to the intervention. Preventive intervention trials that incorporate frequent assessment of potential mediators, moderators, and antecedents of attrition during the intervention period are needed. Secondary analyses of data from preventive intervention trials provide an important foundation for next-generation APIs.