Facilitating access to iCBT: a randomized controlled trial assessing a translated version of an empirically validated program using a minimally monitored delivery model
Bibliographic record
Abstract
BACKGROUND: Despite its established efficacy, access to internet-delivered CBT (iCBT) remains limited in a number of countries. Translating existing programs and using a minimally monitored model of delivery may facilitate its dissemination across countries. AIMS: This randomized control trial aims to evaluate the efficacy of an iCBT transdiagnostic program translated from English to French and offered in Canada using a minimally monitored delivery model for the treatment of anxiety and depression. METHOD: Sixty-three French speakers recruited in Canada were randomized to iCBT or a waiting-list. A French translation of an established program, the Wellbeing Course, was offered over 8 weeks using a minimally monitored delivery model. Primary outcome measures were the Generalized Anxiety Disorder-7 (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9), which were obtained pre-treatment, post-treatment and at 3-month follow-up. RESULTS: Mixed-effects models revealed that participants in the treatment group had significantly lower PHQ-9 and GAD-7 scores post-treatment than controls with small between-groups effect sizes (d = 0.34 and 0.37, respectively). Within-group effect sizes on primary outcome measures were larger in the treatment than control group. Clinical recovery rates on the PHQ-9 and GAD-7 were significantly higher among the treatment group (40 and 56%, respectively) than the controls (13 and 16%, respectively). CONCLUSIONS: The provision of a translated iCBT program using a minimally monitored delivery model may improve patients' access to treatment of anxiety and depression across countries. This may be an optimal first step in improving access to iCBT before sufficient resources can be secured to implement a wider range of iCBT services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".