Using cognitive behavioural therapy in practice: qualitative study of family physicians' experiences.
Bibliographic record
Abstract
OBJECTIVE: To investigate whether family physicians thought they could use cognitive behavioural therapy (CBT) in their practices, and if so, how, and to discover what the barriers to implementation might be. DESIGN: Qualitative study using taped interviews. SETTING: British Columbia and Ontario. PARTICIPANTS: Physicians practising family medicine in a variety of settings who attended an educational session on CBT. METHOD: Six months after participating in a 5-hour seminar on CBT, consenting physicians were interviewed to determine their experiences with using CBT in their practices. The interviews used a semistructured guide and were audiotaped and transcribed verbatim. The constant comparative method of data analysis was used to identify key words and themes. MAIN FINDINGS: Most participants (34 of 42) reported using elements of CBT in their practices. Barriers mentioned by physicians to offering CBT to patients were lack of time, practice distractions and interruptions, and the perception that some patients were not good candidates for CBT. Barriers to patients' accepting or using CBT were preferences for pharmacotherapy and lack of motivation or interest. Physicians could overcome some barriers by using CBT's structure; this reduced the amount of in-office time required and helped them cope with interruptions. They selected specific CBT methods that fit their practices and patients. CONCLUSION: Most participants saw CBT as a useful part of practice and reported implementing it successfully. There were, however, barriers to implementation in primary care. These barriers need to be addressed if CBT is to be taught to primary care physicians and offered in their practices.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".