Obstacles et perspectives pratiques de la consultation en médecine générale du migrant porteur de troubles psychologiques. Étude qualitative auprès de médecins généralistes français
Bibliographic record
Abstract
OBJECTIVE: The aim of this study is to understand the problems of managing psychological disorders in migrant populations, based on the experience of general practitioners. METHOD: A qualitative study was carried out with general practitioners interviewed in a semi-directive mode. We chose the continuous comparison method and Peirce's pragmatic phenomenological approach to explore the lived experience. RESULTS: Thirteen interviews revealed four phenomenological categories: (1) Immigration was an experience of mental suffering from beginning to end at the source of psychological disorder migrant population (PDMPs) with the need for specialized follow-up. (2) Inadequate support on arrival, with complicated administrative procedures and insecure societal and environmental conditions, exacerbated the precariousness of migrants, making follow-up difficult. (3) Immigration was a transcultural journey in which the language, attitudes and perceptions of each individual blurred understanding of symptoms and care, and thus professional communication. (4) Unprepared general practitioners found counselling migrants to be difficult, time-consuming and complex. They pointed to the need for a coordinated system with comprehensive multidisciplinary care.Data saturation was reached. Three researchers were brought together. CONCLUSION: This study highlights the difficulties encountered by general practitioner (GPs) dealing with migrant patients in France. They feel helpless in the face of the nature of the disorders encountered and experience a disparity between the connections that are difficult to establish and those in their usual practice, even when professional experience with this population is acquired. They point to the need for coordinated models of care, financed by public policy.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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".