Statistical Analysis
Descriptive summaries were generated for participant baseline characteristics, and user interaction and response measures for each session. The Pearson correlations between each possible pair of the 4 user interaction measures at each session for 8 sessions were obtained. The Pearson correlations between each user interaction measure for a session (eg, session 1) and a response measure completed before the immediate next session (eg, PHQ-9 or GAD-7 change at session 2 from session 1) also were obtained. Given the exploratory nature, we opted to not adjust for multiple comparisons in accordance with statistical and publication guidelines [Given the expected relationship between treatment alliance and response, we performed mixed models to evaluate whether the participants’ reported treatment alliance with Lumen predicted their treatment response across the intervention sessions. Each participant’s treatment alliance was coded as 2 variables: the person mean of total sessions and the deviation of individual sessions from the person mean. The response outcomes were PHQ-9 and GAD-7 score changes from session 1, which were analyzed in separate models. The fixed effects of each model included the 2 treatment alliance variables and the number of total sessions completed by the time of response outcome data collected, adjusting for PHQ-9 or GAD-7 score at session 1, sex, race or ethnicity, education, and digital health literacy score. The random effect accounted for repeated measures with an autoregressive covariance matrix.