Can Clinicians Use Dimensional Information to Make a Categorical Diagnosis of Paraphilic Disorders? An ICD-11 Field Study
Bibliographic record
Abstract
BACKGROUND: The diagnosis of paraphilic disorder is a complicated clinical judgment based on the integration of information from multiple dimensions to arrive at a categorical (present/absent) conclusion. The recent update of the guidelines for paraphilic disorders in ICD-11 presents an opportunity to investigate how mental health professionals use the diagnostic guidelines to arrive at a diagnosis which thereby can optimize the guidelines for clinical use. AIM: This study examined clinicians' ability to use the ICD-11 diagnostic guidelines for paraphilic disorders which contain multiple dimensions that must be simultaneously assessed to arrive at a diagnosis. METHODS: The study investigated the ability of 1,263 international clinicians to identify the dimensions of paraphilic disorder in the context of written case vignettes that varied on a single dimension only. OUTCOMES: Participants provided diagnoses for the case vignettes along with dimensional ratings of the degree of presence of five dimensions of paraphilic disorder (arousal, consent, action, distress, and risk). RESULTS: Across a series of analyses, clinicians demonstrated a clear ability to recognize and appropriately integrate the dimensions of paraphilic disorders; however, there was some evidence that clinicians may over-diagnose non-pathological cases. CLINICAL TRANSLATION: Clinicians would likely benefit from targeted training on the ICD-11 definition of paraphilic disorder and should be cautious of over-diagnosing. STRENGTHS AND LIMITATIONS: This study represents a large international sample of health professionals and is the first to examine clinicians' ability to apply the ICD-11 diagnostic guidelines for paraphilic disorders. Important limitations include not generalizing to all clinicians and acknowledging that results may be different in direct clinical interactions vs written case vignettes. CONCLUSION: These results indicate that clinicians appear capable of interpreting and implementing the diagnostic guidelines for paraphilic disorders in ICD-11. Keeley JW, Briken P, Evans SC, et al. Can Clinicians Use Dimensional Information to Make a Categorical Diagnosis of Paraphilic Disorders? An ICD-11 Field Study. J Sex Med 2021;18:1592-1606.
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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 | 0.084 | 0.264 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".