DSM IV, culture and child psychiatry.
Bibliographic record
Abstract
OBJECTIVE: The expanding cultural diversity of children and families with mental health needs raises questions about the cultural appropriateness of diagnostic classifications like the DSM IV. This paper briefly surveys the literature on culture and DSM-IV in child psychiatry, presenting ADHD as an example of the relationship between diagnostic categories and cultural issues, and illustrating some of the clinical dilemmas of differential diagnosis in a migration context. METHOD: A literature review was performed and analysed, and a case vignette was constructed to illustrate key points. RESULTS: The literature does not provide a definite answer about the DSM IV cultural validity in child psychiatry. On the one hand it suggests that all diagnostic categories may be found universally. On the other, variations in prevalence rates support the hypothesis of a role for social and cultural factors in the diagnostic process. The clinical formulation may be a useful tool to address the validity issue by modulating the process of diagnosis with a cultural understanding of the symptoms, the patient-therapist alliance and the appropriateness of treatment recommendations. CONCLUSION: Although the DSM IV diagnostic categories may be found cross culturally, clinicians need to be aware of how culture may influence the diagnostic process in child psychiatry.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".