Online CBT Is Effective in Overcoming Cultural and Language Barriers in Patients With Depression
Bibliographic record
Abstract
OBJECTIVE: The goal of this study was to evaluate the efficacy of weekly email in delivering online cognitive behavioral therapy (CBT) to treat mild to moderately depressed individuals. The effectiveness of the online CBT was measured following treatment and then again at a 6-month follow-up and was compared with outcomes in a waitlist control group. METHODS: Participants were recruited through announcements on psychology Web sites, Iranian organization Web sites, and weblogs and flyers. Ninety-three individuals who met inclusion criteria, including a score >18 on the Beck Depression Inventory (BDI), participated in the study, with 47 randomly assigned to the CBT group and 46 to the control group. The CBT group received 10 to 12 sessions of online CBT conducted by a psychiatrist and a psychiatry resident. Following completion of the CBT, a second BDI was sent to participants. Another BDI was then sent to participants 6 months after the completion of treatment. RESULTS: Email-based CBT significantly reduced BDI scores compared with results in a waitlist control group following 10 to 12 weeks of treatment and at 6-month follow-up. CONCLUSIONS: Email is a viable method for delivering CBT to individuals when face-to-face interaction is not possible. Limitations and future directions are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".