Health Service Utilisation, Detection Rates by Family Practitioners, and Management of Patients with Common Mental Disorders in French Family Practice
Bibliographic record
Abstract
OBJECTIVE: Provide up-to-date detection rates for common mental disorders (CMD) and examine patient service-use since the Preferred Doctor scheme was introduced to France in 2005, with patients encouraged to register with and consult a family practitioner (FP) of their choice. METHODS: Study of 1133 consecutive patients consulting 38 FPs in the Montpellier region, replicating a study performed before the scheme. Patients in the waiting room completed the self-report Patient Health Questionnaire (PHQ) and Client Service-Receipt Inventory with questions on registration with a Preferred Doctor and doctor-shopping. CMD was defined as reaching PHQ criteria for depression, somatoform, panic or anxiety disorder. For each patient, FPs completed a questionnaire capturing psychiatric caseness. RESULTS: 81.2% of patients were seeing their Preferred Doctor on the survey-day. Of those with a CMD, 52.6% were detected by the FP. This increased with CMD severity and comorbidity. Detected cases were more likely to be consulting their Preferred Doctor (84.7% versus 79.4% for non-detected cases, p = 0.05) rather than another FP. They declared more visits to psychiatrists (17.2% versus 6.7%, p = 0.002). There was no association with consultation frequency or doctor-shopping, which both declined between the two studies. CONCLUSION: The CMD detection rate is relatively high, with no increase compared to our previous study, despite a decline in doctor-shopping. An explanation is the same high proportion of patients visiting their usual FP on the survey-day at both periods, suggesting a limited impact of the scheme on care continuity. FP action taken highlights the importance of improving detection for providing care to patients with CMDs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".