Panel Discussion 14 - Engagement in Digital Mental Health Interventions: Towards a Unified Model of Measurement, Reporting, and Interpretation

While many digital mental health interventions (DMHIs) have demonstrated efficacy, and have potential to radically increase access to evidence-based mental healthcare, engagement with these interventions has been suboptimal, especially in real-world settings, thereby limiting their impact to date (e.g., Boucher & Raiker, 2024). Further, there is no consensus definition of engagement in the field, or standard of what engagement data should be reported. Research studies often report on different metrics of engagement and provide minimal associated data (Lipschitz et al., 2023). The term “engagement” is also often used interchangeably with related terms like “adherence” and “retention” without prominent definitions of each, leading to additional confusion.

This panel will focus on best practices for defining and measuring engagement in DMHIs, including consideration of objective behavioral data (e.g., number of exercises completed in an app), individuals’ subjective report about their experience with a product (e.g., how often did you practice the skill from the app in the real world?), and affective components of engagement (e.g., how much of a bond the person feels with the app). Panelists will discuss the importance of identifying optimal or meaningful engagement for a specific product—i.e., the type of engagement that is associated with the specific desired outcome versus measuring engagement in ways that may not correspond to desired outcomes. Finally, the importance of identifying different patterns of engagement (e.g., a group who engages early and often and relationship to outcomes versus other groups) will be discussed. Panelists are experts in DMHIs, have specific expertise related to engagement in DMHIs, and work in both academic and industry settings.

By discussing and sharing best practices for measuring and reporting engagement data, this discussion will advance the field toward a unified model of measurement and interpretation of engagement data, in the service of better understanding what kinds of engagement matter and increasing access to inclusive evidence-based DMHIs that ultimately produce the desired outcomes. This panel is consistent with ABCT’s strategic goal to advance innovation in the science of behavioral health.