Randomized trial examines smartphone CBT's impact on subthreshold depression in individuals with comorbidities, suggesting effective strategies.
BACKGROUND: This study aimed to examine the effectiveness of smartphone-delivered cognitive behavioral therapy (CBT) in participants with subthreshold depression, considering the potential influence of physical comorbidities. METHODS: In this secondary analysis of the RESiLIENT trial, participants with subthreshold depression were randomized to various CBT interventions or control groups. Physical comorbidities were self-reported at baseline and categorized as no, past, or current. Depression severity was assessed by the Patient Health Questionnaire-9 (PHQ-9) at weeks 6 and 26. Mixed-effects models for repeated measures estimated treatment effects and tested interaction terms for comorbidity category. Latent class analysis (LCA) explored multimorbidity patterns and their impact on outcomes. RESULTS: A total of 3577 participants were analyzed (no comorbidity n = 1384; past comorbidity n = 1004; current comorbidity n = 1189). All CBT interventions improved PHQ-9 scores at week 6 across comorbidity groups. Behavioral activation (BA) combined with problem solving showed the largest effects in the no comorbidity (least-squares mean difference = -1.74, 95% confidence interval: -2.44 to -1.05) and current comorbidity groups (-1.94, -2.67 to -1.20), while BA alone was most effective in the past comorbidity group (-1.91, -2.69 to -1.14). By week 26, BA combined with cognitive restructuring maintained benefits across all groups. LCA identified five multimorbidity classes. Although the effect sizes showed small variations across subgroups, no significant effect modification by comorbidity type was found. CONCLUSIONS: Smartphone-delivered CBT effectively reduces depressive symptoms in subthreshold depression, including among individuals with physical comorbidities. Although comorbidity type did not significantly modify outcomes, the observed patterns may help inform personalized iCBT strategies.
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Cui et al. (2026) studied this question.
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