Needs for mental health treatment among general practice attenders
Bibliographic record
Abstract
BACKGROUND: No study has directly assessed the need for mental health care among those consulting in general practice. AIMS: To make a direct assessment of the needs for mental health care in people with non-psychotic disorders consulting their general practitioner. METHOD: In a two-phase study design, consecutive general practice attenders aged 17-65 years were interviewed using the Structured Clinical Interview for DSM-IV Axis I Disorders. Needs for care were assessed using the community version of the Medical Research Council Needs for Care Assessment Schedule. RESULTS: Three hundred and thirty-six people were interviewed. The overall prevalence of need was 27.3%. More than half of the consulters (59.6%) had unmet needs and a further 6.2% had partially met needs. Needs were met in 28.1% and unmeetable in 6.2%. The prevalence of unmet need in those with anxiety disorders was 13.9% and depressive disorders 9.5%. CONCLUSIONS: The unmet need for mental health treatment in primary care attenders is high.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".