Understanding Engagement with Digital Measurement-Based Care in Mental Health Services: Systemic, Individual, and Clinical Factors (Preprint)
Authors: Borgnolo Luke J , McKenna Sarah , Hickie Ian B , Varidel Mathew , Turner Ashlee , Gorban Carla , LaMonica Haley M , Chong Min K , Capon William , Dimitropoulos Gina , Battisti Robert , Whitwell Bradley , Hamilton Blake , Scott Elizabeth M , Iorfino Frank 
Published: October 2024

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 2,682 help-seeking clients from 12 Australian mental health services (11 headspace centers and one 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 here was defined as their ensuing completion of the summary questionnaire, designed for routine outcome monitoring. Participants were classified as ‘Initial Assessment Only’, 'Single Use' (one completion of the summary questionnaire), or '2+ Uses' (two or more completions). We analyzed engagement differences across services and associations between engagement and initial assessment scores.

RESULTS

Of the sample, 75.4% completed the initial assessment only, 11.5% had one completion of the summary questionnaire, and 13.0% had two or more completions. The service center was the strongest predictor of engagement, with Mind Plasticity participants showing over eight 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 = .013), and physical activity (P < .001) were associated with increased engagement. Conversely, higher levels of anxiety symptoms (P = .011), substance misuse (P < .001), self-reported mental illness severity (P = .024), 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 like 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 multi-level approach – encompassing individual, service, and system-wide considerations – is essential for realizing DMHTs' full potential in delivering effective measurement-based care.