Management of Current Psychiatric Disorders
Bibliographic record
Abstract
Objective: Describe and analyse the experience of family physicians in managing current psychiatric disorders to obtain a better understanding of the underlying reasons of under-detection and inadequate prescribing identified in studies. Methods: A qualitative study using in-depth interviews. Sample of 15 practicing family physicians, recruited by telephone from a precedent cohort (Sesame1) with a maximum variation: sex, age, single or group practice, urban or rural. Qualitative method is inspired by the completed grounded theory of a verbatim semiopragmatic analysis from 2 experts in this approach. Results: Family physicians found that current psychiatric disorders were related to psychological symptoms in reaction to life events. Their role was to make patients aware of a psychiatric symptom rather than establish a diagnosis. Their management responsibility was considered in contrasting ways: it was claimed or endured. They defined their position as facilitating compliance to psychiatrist consultations, while assuring a complementary psychotherapeutic approach. Prescribing medication was not a priority for them. Conclusions: The identified under-detection is essentially due to inherent frontline conditions and complexity of clinical forms. The family physician role, facilitating compliance to psychiatrist consultations while assuring a support psychotherapy is the main result of this study. More studies should be conducted to define more accurately the clinical reality, management and course of current psychiatric disorders in primary care.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".