A comparison of two online cognitive‐behavioural interventions for symptoms of depression in a student population: The role of therapist responsiveness
Bibliographic record
Abstract
Abstract Objectives: The study aimed to compare the efficacy of eight weekly sessions of a self‐administered online CBT treatment (cCBT; n=51) to a therapist‐assisted email CBT treatment (eCBT; n=50) in University students. Design: The design was a randomised parallel group trial. The study randomised participants with symptoms of depression to one of two available treatments. Method: Participants were offered eight weekly sessions of either cCBT or eCBT. Participants completed the Beck Depression Inventory‐II (BDI‐II) and the Clinical Outcomes in Routine Evaluation – Outcome Measure (CORE‐OM) at pre‐and post‐treatment, at weeks 16 and 32 follow‐up. The Working Alliance Inventory‐Short Form (WAI‐SR) was completed at weeks 2, 4, and 6. Results: For both groups, pre‐post within group effect sizes reported were large for the BDI‐II and the CORE‐OM and these were maintained at follow‐up. Perceptions of working alliance were similar in each group, but Bond was significantly stronger for the eCBT condition. WAI scores correlated more positively with the outcome on BDI‐II for those in the eCBT condition than the cCBT condition, but not significantly. Conclusion: There were no significant differences between the two online treatments, both reduced depressive symptoms and improved general functioning. Similarly, at post‐treatment and follow‐up, clinical improvement and recovery was demonstrated for both groups equally. The study demonstrates the possibility for cCBT in a university setting that may contribute to addressing the shortcomings in meeting increasing demands that mental health services presently face.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".