User Character Strengths and Engagement Prediction on a Digital Mental Health Platform for Young People: Longitudinal Observational Study

Abstract

Background: Mental ill health is a leading cause of disability worldwide, but access to evidence-based support remains limited. Digital mental health interventions offer a timely and low-cost solution. However, improvements in clinical outcomes are reliant on user engagement, which can be low for digital interventions. User characteristics, including demographics and personality traits, could be used to personalize platforms to promote longer-term engagement and improved outcomes. Objective: This study aims to investigate how character strengths, a set of positive personality traits, influence engagement patterns with moderated online social therapy, a national digital mental health platform offering individualized, evidence-based digital mental health treatment for young people aged 12‐25 years. Methods: Data from 6967 young people who enrolled with moderated online social therapy between August 2021 and July 2023 were analyzed. Longitudinal analyses were used to investigate whether scores on 3-character strength dimensions (“social harmony,” “positive determination,” and “courage and creativity”) were associated with (1) an accelerated or decelerated rate of dropout from the platform and (2) patterns of engagement over the first 12 weeks following onboarding. Engagement metrics were time spent on the platform, number of sessions on the platform, use of the embedded social network, and messages with the clinical team. Results: On average, young people used the platform for 72.64 (SD 106.64) days. The 3-character strengths were associated with distinct engagement patterns during this time. Individuals scoring higher on “social harmony” demonstrated an accelerated dropout rate (coefficient=−0.15, 95% CI −0.26 to −0.04; P=.008). Interestingly, higher scores on this character strength were associated with high rates of initial engagement but a more precipitous decline in platform use over the first 12 weeks, in terms of time spent on the platform (β=−.01; SE 0.00; t2748=−5.05; P