Transdiagnostic internet cbt for mixed anxiety and depressive: Results from a feasibility study in primary care
Bibliographic record
Abstract
Introduction In response to the treatment gap for anxiety and depressive disorders, psychological treatments with innovative modalities and high implementation potential are essential. Internet CBT (iCBT) is a cost/effective approach that could improve access to a low-intensity evidence-based CBT intervention. Objectives To assess the feasibility and acceptability of the French adaptation of the physician-prescribed six-lesson This Way Up transdiagnostic iCBT program for mixed anxiety and depressive disorders developed in Australia. Methods Feasibility study with pre- post-intervention evaluations, including an embedded qualitative study in Family Medicine Groups (Quebec, Canada). Inclusion criteria comprise a family physician diagnosis of Major Depression, Panic Disorder, Agoraphobia, Social Anxiety Disorder or Generalized Anxiety Disorder. Primary self-reported outcomes: PHQ-9 (depression) and GAD-7 (anxiety); secondary measures include diagnostic-specific scales and health service utilisation. Results Family physicians (N=21) from five Family Medicine Groups prescribed iCBT to 45 patients (30 women, 15 men; mean age = 39.7), 31 initiated the program. To date, 20 patients completed 5 or 6 lessons, nine completed between 2 and 4. Intervention and post-treatment assessments are ongoing, results forthcoming. Results of semi-structured interviews with patients (N=15) and family physicians (ongoing) on iCBT acceptability indicate it is beneficial, practical and easy to use. Program adherence requires patient readiness and determination and could be fostered by motivational support from clinicians. Conclusions Results support this French iCBT program’s scaling-up potential to contribute to reducing the gap in evidence-based treatments for common mental disorders. Its implementation in primary care could improve the effectiveness, efficiency and equity to a rapidly accessible treatment.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".