Thou shalt versus thou shalt not: a meta-synthesis of GPs' attitudes to clinical practice guidelines
Bibliographic record
Abstract
BACKGROUND: GPs' adherence to clinical practice guidelines is variable. Barriers to guideline implementation have been identified but qualitative studies have not been synthesised to explore what underpins these attitudes. AIM: To explore and synthesise qualitative research on GPs' attitudes to and experiences with clinical practice guidelines. DESIGN OF STUDY: Systematic review and meta-synthesis of qualitative studies. METHOD: PubMed, CINAHL, EMBASE, Social Science Citation Index, and Science Citation Index were used as data sources, and independent data extraction was carried out. Discrepancies were resolved by consensus. Initial thematic analysis was conducted, followed by interpretative synthesis. RESULTS: Seventeen studies met the inclusion criteria. Five were excluded following quality appraisal. Twelve papers were synthesised which reported research in the UK, US, Canada, and the Netherlands, and covered different clinical guideline topics. Six themes were identified: questioning the guidelines, GPs' experience, preserving the doctor-patient relationship, professional responsibility, practical issues, and guideline format. Comparative analysis and synthesis revealed that GPs' reasons for not following guidelines differed according to whether the guideline in question was prescriptive, in that it encouraged a certain type of behaviour or treatment, or proscriptive, in that it discouraged certain treatments or behaviours. CONCLUSION: Previous analyses of guidelines have focused on professional attitudes and organisational barriers to adherence. This synthesis suggests that the purpose of the guideline, whether its aims are prescriptive or proscriptive, may influence if and how guidelines are received and implemented.
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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 | 0.092 | 0.236 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.017 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".