Understanding Engagement With Digital Mental Health Technology in Mental Health Services: Multicenter Observational Study.

Background: Digital technologies can substantially improve mental health care by facilitating measurement-based care through routine outcome monitoring. However, their effectiveness is constrained by the extent to which these technologies are used by services, clinicians, and clients.

Objective: This study aims to investigate engagement with the Innowell platform, a measurement-based digital mental health technology (DMHT), to gain insights into the individual- and service-level factors influencing engagement.

Methods: Participants were 2682 help-seeking clients from 12 Australian mental health services (11 headspace centers and 1 private practice, Mind Plasticity), wherein the Innowell platform was implemented. Although the initial implementation was standardized, services varied in their practical and continued use of the platform, as well as in the resources allocated to foster engagement. All participants completed an initial assessment during onboarding. Engagement was defined as their ensuing completion of the summary questionnaire, designed for routine outcome monitoring. Participants were classified as "initial assessment only," "single use" (1 completion of the summary questionnaire), or "≥2 uses" (≥2 completions). We analyzed engagement differences across services and associations between engagement and initial assessment scores.

Results: Of the 2682 help-seeking clients, 75.43% (n=2023) completed the initial assessment only, 11.56% (n=310) had 1 completion of the summary questionnaire, and 13.01% (n=349) had 2 or more completions. The service center was the strongest predictor of engagement, with Mind Plasticity participants showing >8 times higher engagement than other centers. At the individual level, higher scores in depression (P=.002), mania-like experiences (P=.047), suicide ideation (P=.004), hospitalization history for mental illness (P=.01), and physical activity (P<.001) were associated with increased engagement. In contrast, higher levels of anxiety symptoms (P=.01), alcohol use (P<.001), self-reported mental illness severity (P=.02), and social support (P=.047) predicted lower engagement. Age and several other clinical variables were not significant predictors when controlling for service-level factors.

Conclusions: This study reveals that both individual- and service-level factors significantly influence DMHT engagement, with the service center being the strongest predictor. This highlights the importance of service-level technology integration and support roles, such as digital navigators, in fostering engagement. Significant variation in engagement among user groups indicates the need for a nuanced approach to measurement-based care. While mental illness generally did not impede engagement, self-perceived severity and anxiety symptoms were barriers. These findings underscore the critical importance of systemic factors and service-level integration strategies in driving DMHT engagement. User-centered designs remain important, but effective integration of DMHTs into existing mental health services is paramount for improving engagement across diverse user groups and clinical presentations. This multilevel approach, encompassing individual, service, and system-wide considerations, is essential for realizing DMHTs' full potential in delivering effective measurement-based care.