279 - Optimizing Engagement in Digital Depression Prevention: The Impact of Motivational Interviewing

Publication Number: 3268.279

Morgan R. Jones, Brown University, Providence, RI, United States; Morgan Jones, Brown University, Providence, RI, United States; Kathleen R. Diviak, University of Illinois At Chicago, Chicago, IL, United States; Benjamin VanVoorhees, University of Illinois, Chicago, IL, United States; Tracy Gladstone, Brown University, Providence, RI, United States

Background: Depression affects approximately 1 in 5 adolescents in the United States, underscoring the need for accessible, scalable mental health resources. Digital prevention tools offer increased access by bypassing financial and logistical barriers associated with traditional care. However, these interventions often face challenges with engagement and adherence, and disparities in engagement persist across demographic groups.

Objective: CATCH-IT is a digital depression prevention program designed for adolescents with subsyndromal depressive symptoms. To enhance engagement, the intervention includes brief Motivational Interviewing (MI) calls - guided conversations that help participants reflect on their personal motivations for behavior change. This study evaluated whether MI increases engagement in CATCH-IT, identified which aspects of MI are most effective, and examined whether engagement varied across demographic groups.

Design/Methods: The study included 399 adolescents aged 13-19 who participated in a randomized trial comparing CATCH-IT to a group therapy intervention. Engagement metrics included percent of pages visited, number of modules completed, and any CATCH-IT logins. MI quality was assessed using Motivational Interviewing Treatment Integrity (MITI) scores, and regression and moderation analyses were conducted on a subsample of 87 participants with coded MI sessions who also logged into the intervention.

Results: Results showed that, across the full sample, receiving a baseline MI significantly increased engagement across all metrics: participants with an MI were more likely to log in, complete more modules, and visit a greater percentage of pages. Within the subsample of participants whose MIs were coded, higher-quality MIs, particularly those emphasizing reflective listening statements, were associated with significantly greater engagement. Notably, engagement outcomes did not differ significantly by age, gender, race/ethnicity, or income.

Conclusion(s): These findings suggest that even brief, high-quality MI interactions can meaningfully enhance engagement in digital interventions and may do so equitably across diverse adolescent populations. This supports the broader integration of MI as a scalable, human-centered strategy for optimizing digital mental health tools.

Table 1: Relation Between Receiving MI and Engagement Across Full Sample


Table 2: Engagement Metrics Among Those Who Logged in to CATCH-IT


Table 3: Standardized Relation Between MI Quality and Engagement Outcomes Among Those Who Logged in to CATCH-IT
Adjusted for PHQ score at baseline, age, gender, race/ethnicity, and household income