Predictors of adolescent engagement and outcomes – A cross-sectional study using the togetherall (formerly Big White Wall) digital mental health platform

Background
Online mental health platforms can improve access to, and use of, mental health support for young people who may find it difficult to engage with face-to-face delivery.
Objective
We modelled predictors of engagement and symptom change in adolescent users of the Togetherall (formerly “Big White Wall”) anonymous digital mental health peer-support platform.
Methods
We report a retrospective analysis of longitudinal user data from UK 16–18 year Togetherall users, referred from mental health services (N = 606). Baseline demographics were reported for participants who logged anxiety and depression measures. Number of log-ins, mean session duration, total usage time, number of guided support courses and self-help materials accessed were our usage metrics. Participant characteristics and symptoms were used to predict engagement. For n = 245 users with symptom measures at >1 timepoint we modelled the effect of predictors on symptom scores.

Results
Mean logins was 5.11 and mean usage time was 64.22 mins. Participants with one log-in represented 33.5% of the sample. Total time accessing Togetherall predicated greater usage of self-help materials and courses. Females made greater use of materials and courses than males. In a subsample, higher baseline depression and anxiety, longer total usage time and mean session duration predicted final depression scores, whereas higher baseline depression and anxiety and greater accessed self-help materials predicted lower final anxiety scores.
LimitationsA naturalistic design was used and symptom modelling should be interpreted with caution.
Conclusions
Findings suggest adolescents can engage with the Togetherall platform. Baseline symptoms and characteristics can inform user engagement with digital platforms.