Improving internet-delivered cognitive behaviour therapy for alcohol misuse: Patient perspectives following program completion
Bibliographic record
Abstract
Although Internet-delivered cognitive behaviour therapy (ICBT) for alcohol misuse is efficacious in research trials, it is not routinely available in practice. Moreover, there is considerable variability in engagement and outcomes of ICBT for alcohol misuse across studies. The Alcohol Change Course (ACC) is an ICBT program that is offered free of charge by an online clinic in Saskatchewan, Canada, which seeks to fill this service gap, while also conducting research to direct future improvements of ICBT. As there is limited qualitative patient-oriented research designed to improve ICBT for alcohol misuse, in this study, we describe patient perceptions of the ACC post-treatment. Specifically, post-treatment feedback was obtained from 191 of 312 patients who enrolled in the ACC. Qualitative thematic analysis was used to examine post-treatment written comments related to what patients liked and disliked about the course, which skills were most helpful for them, and their suggestions for future patients. The majority of patients endorsed being very satisfied or satisfied with the course (n = 133, 69.6%) and 94.2% (n = 180) perceived the course as being worth their time. Worksheets (n = 61, 31.9%) and reflections of others (n = 40, 20.9%) received the most praise. Coping with cravings (n = 63, 33.0%), and identifying and managing risky situations (n = 46, 24.1%) were reported as the most helpful skills. Several suggestions for refining the course were provided with the most frequent recommendation being a desire for increased personal interaction (n = 24, 12.6%) followed by a desire for wanting more information (n = 22, 11.5%). Many patients offered advice for future ACC patients, including suggestions to make a commitment (n = 47, 24.6%), do all of the work (n = 29, 15.2%), and keep a consistent approach to the course (n = 24, 12.6%). The results provide valuable patient-oriented directions for improving ICBT for alcohol misuse.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".