Sociodemographic and clinical predictors of digital mental health intervention engagement among treatment-seeking psychiatric outpatients

Clinical Snapshot

Key Findings

• P Value: Not explicitly reported but CI excludes 1.0

• Effect Size: Headspace users engaged 2.4 times more days than SilverCloud users

• Primary Outcome: Median engagement of 8 days across both interventions, with 88.2% using assigned app at least once

• Nnt Or Sensitivity: Predictors: female sex, white race, college education, older age up to 60 years associated with greater engagement

• Confidence Interval: IRR 2.4 (95% CI: 2.1, 2.7)

Clinical Application

High feasibility as apps are commercially available and require minimal clinical oversight Relevant to Australian digital mental health initiatives; however, demographic differences may limit direct applicability. Consider cultural adaptation for Indigenous and multicultural populations Adults seeking outpatient psychiatric care, particularly those with depression and anxiety disorders

Abstract

BACKGROUND: Digital mental health interventions (DMHIs) have shown promise improving depression, anxiety, and psychiatric distress, yet real-world engagement remains low. Increasing engagement has great potential to improve the impact of DMHIs, but little is known about the drivers of engagement in naturalistic settings. To better understand predictors of engagement, we examined sociodemographic and clinical characteristics associated with DMHI usage among a large clinical sample of adults. METHOD: 1223 adults (74% White, 68% women, Mage = 36.8 years) with scheduled intake appointments for outpatient psychiatric services were randomized to either a mindfulness-based app (Headspace) or a CBT-based app (SilverCloud). Usage data were automatically collected, and participants were neither required nor compensated to use the apps. RESULTS: Participants engaged with their assigned DMHIs a median of 8 days, with 88.2% of participants using their assigned DMHI at least once. Participants engaged with Headspace for more than twice as many days [IRR (95% CI) = 2.4 (2.1, 2.7)] as SilverCloud. Female sex, white race, a college degree, and older age up to 60 predicted greater engagement. Further, depression severity was associated with engagement in a non-linear manner for those assigned to Headspace, with less engagement at minimal/mild and severe symptoms compared to moderate and moderately-severe symptoms. CONCLUSIONS: These findings indicate meaningful differences in engagement between DMHIs based on sociodemographic and clinical characteristics. There may be opportunities to improve engagement by tailoring DMHI offerings, with a particular emphasis on meeting the needs of less-engaged populations.

References

1. 1.Horwitz, A. G., Mills, E. D., Nanwani, R., Bohnert, A. S. B., & Sen, S. (2026). Sociodemographic and clinical predictors of digital mental health intervention engagement among treatment-seeking psychiatric outpatients. Journal of Affective Disorders. https://doi.org/10.1177/20552076231152164