Outcome Analysis
All analyses were carried out using Stata (version 17.0; StataCorp). Baseline and postrandomization app use variables were described by intervention arm and overall, with categorical variables described using frequencies and proportions and continuous variables described using mean and SD or median and IQR as appropriate. App usage between T1 to T2 and T1 to T3 was reported, instead of T1 to T2 and T2 to T3 as specified in the SAP. Differences between arms were assessed using mixed-effects linear models (LMMs) analysis of covariance models, with T2 and T3 measures as dependent variables and a random intercept at the participant level. All models included age, gender (both prespecified), T1 outcomes, intervention arm, time, intervention arm by time interaction, and any additional baseline variables found to be predictive of missingness as fixed effects. Marginal mean Missing outcome data were summarized; those with at least 1 postrandomization value were included in the LMM models under the intention-to-treat principle. Baseline variables that predicted (at Medical (physical and psychological) and nonmedical familial AEs (eg, reduction in school attendance) and serious AEs were summarized.