Do general practitioners adhere to NICE guidelines for depression? Systematic Questionnaire Survey
Bibliographic record
Abstract
Background Guidelines may improve clinical outcomes for depression, but whether they are followed in primary care is uncertain. Aim To assess general practioners (GPs’) adherence to the National Institute for Health and Clinical Excellence (NICE) guidelines for managing depression in adults (2004). Design of study Anonymized Questionnaire Survey. Setting Thirty-eight partnerships within one primary care trust in England. Method Focused questionnaire incorporating measurable criteria, posted to GPs in May 2007. Results The response rate was 67% (143/215 GPs). GPs followed NICE guidelines when screening for depression in patients with physical illness, using selective serotonin reuptake inhibitor antidepressants appropriately and referring to counselling and secondary care. However, 48% GPs did not screen patients with a history of depression, 44% discontinued medication too soon and 38% avoided prescribing for ‘understandable’ moderate depression. GPs identified poor access to cognitive behaviour therapy (CBT) as the greatest barrier to implementing guidelines. Only 41% personally used CBT. Adherence to NICE guidelines was significantly higher for GPs trained in psychiatry and in younger GPs, but was not associated with gender, practice size, possessing the Membership of the Royal College of General Practitioners or reading guidelines. Less than half (38%) of the GPs rated NICE as having a moderate or substantial impact upon their clinical management. The Quality and Outcomes Framework (QOF) had more influence than NICE guidelines upon detection and recording of care, especially in larger practices. Conclusion Training more cognitive behaviour therapists, making psychiatry experience mandatory for future GPs and focusing QOF incentives upon treatment outcomes as well as screening may improve adherence to NICE depression guidelines.
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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 | 0.012 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".