Exploring the Interdisciplinary Roles of Dermatologists and Psychiatrists in the Management of Excoriation (Skin-picking) Disorder
Bibliographic record
Abstract
ABSTRACT:Excoriation disorder is a mental health disorder characterized by excessive picking of one’s skin resulting in clinically significant functional impairment. Diagnosing this condition has been historically challenging due to the varied associated behaviours and lack of inclusion in the Diagnostic and Statistical Manual of Mental Disorders (DSM). As dermatologists and psychiatrists are the specialists most likely to encounter these individuals, this article discusses the new DSM-5 criteria and outlines the approaches and treatment options for these specialists to optimally manage patients with excoriation disorder.RÉSUMÉ:L’acné excoriée est un trouble de santé mentale caractérisé par le grattage et l’arrachage excessif de la peau qui mènent à une dysfonction clinique significative. Le diagnostic précis de cette condition demeure un défi lorsqu’on tient compte de la variété des comportements qui y sont associés et le manque d’inclusion des caractéristiques de ce problème de santé dans le DSM(Manuel diagnostique et statistique des troubles mentaux). Étant donné que les dermatologues et les psychiatres sont les spécialistes les plus susceptibles de traiter ces problèmes de santé mentale, cet article présente les nouveaux critères du DSM-5 et décrit les grandes lignes cliniques, les approches nécessaires et les options de traitement afin que ces spécialistes puissent intervenir auprès des patients avec l’acné excoriée de façon optimale.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".