Impact of a cognitive behavioural therapy training program on family physician practices
Bibliographic record
Abstract
Objective To investigate changes in FPs’ self-reported clinical practices after participation in a comprehensive 1-year cognitive behavioural therapy (CBT) training course. Design Cross-sectional study. Setting Norway. Participants Family physicians. Main outcome measures Impact of the CBT training course on FPs’ delivery of CBT to patients and their use of referral to specialized mental health care providers. Results Of the 217 FPs who had participated in the training course between 2009 and 2016, 124 completed the survey (response rate=57.1%); 99.2% of participating FPs reported using CBT tools daily in patient consultations, more than three-quarters reported changing the way they organized their workdays to accommodate CBT, and 75.0% reported using structured CBT consultations at least monthly after completing the course. The most common patient groups receiving structured CBT were those experiencing mild or moderate depression (22.8%), anxiety disorders (30.4%), or a combination of an anxiety disorder and depression (43.5%). The odds of making fewer referrals to specialized mental health care providers were 5.4 times higher among FPs who used Socratic questioning (P=.02), 4.7 times higher among those who provided consultation summaries (P=.01), and 3.3 times higher among those who had participated in a refresher course (P=.05). Conclusion Comprehensive training in CBT promotes the use of CBT tools and strategies in family practice. Further longitudinal research (ideally randomized controlled studies) on patient outcomes related to CBT provided in family practices is required.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".