Effectiveness of app-based cognitive behavioral therapy for insomnia on preventing major depressive disorder in youth with insomnia and subclinical depression: A randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Increasing evidence suggests that insomnia plays an important role in the development of depression, supporting insomnia intervention as a promising approach to prevent depression in youth. This randomized controlled trial evaluated the effectiveness of app-based cognitive behavioral therapy for insomnia (CBT-I) in preventing future onset of major depressive disorder (MDD) in youth. METHODS AND FINDINGS: This was a randomized, assessor-blind, parallel group-controlled trial in Chinese youth (aged 15-25 years) with insomnia disorder and subclinical depressive symptoms. Participants were randomly assigned (1:1) to 6-week app-based CBT-I or 6-week app-based health education (HE) delivered through smartphones. Online assessments and telephone clinical interviews were conducted at baseline, post-intervention, 6- and 12-month follow-ups. The primary outcome was time to onset of MDD. The secondary outcomes included depressive symptoms and insomnia at both symptom and disorder levels. Between September 9, 2019, and November 25, 2022, 708 participants (407 females [57%]; mean age, 22.1 years [SD = 1.9]) were randomly allocated to app-based CBT-I group (n = 354) or app-based HE group (n = 354). Thirty-seven participants (10%) in the intervention group and 62 participants (18%) in the control group developed new-onset MDD throughout the 12-month follow-up, with a hazard ratio of 0.58 (95% confidence interval 0.38-0.87; p = 0.008). The number needed to treat to prevent MDD at 1 year was 10.9 (6.8-26.6). The app-based CBT-I group has higher remission rates of insomnia disorder than the controls at post-intervention (52% versus 28%; relative risk 1.83 [1.49-2.24]; p < 0.001) and throughout 12-month follow-up. In addition, the CBT-I group reported a greater decrease in depressive (adjusted difference -1.0 [-1.6 to -0.5]; Cohen's d = 0.53; p < 0.001) and insomnia symptoms (-2.0 [-2.7 to -1.3], d = 0.78; p < 0.001) than the controls at post-intervention and throughout 6-month follow-up. Insomnia was a mediator of intervention effects on depression. No adverse events related to the interventions were reported. CONCLUSIONS: App-based CBT-I is effective in preventing future onset of major depression and improving insomnia outcomes among youth with insomnia and subclinical depression. These findings highlight the importance of targeting insomnia to prevent the onset of MDD and emphasize the need for wider dissemination of digital CBT-I to promote sleep and mental health in the youth population. TRIAL REGISTRATION: ClinicalTrials.Gov (NCT04069247).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".