The development of the Compulsive Sexual Behavior Disorder Scale (CSBD-19): An ICD-11 based screening measure across three languages
Bibliographic record
Abstract
BACKGROUND: Compulsive Sexual Behavior Disorder (CSBD) is included in the eleventh edition of The International Classification of Diseases (ICD-11) as an impulse-control disorder. AIMS: The aim of the present work was to develop a scale (Compulsive Sexual Behavior Disorder Scale-CSBD-19) that can reliably and validly assess CSBD based on ICD-11 diagnostic guidelines. METHOD: Four independent samples of 9,325 individuals completed self-reported measures from three countries (the United States, Hungary, and Germany). The psychometric properties of the CSBD-19 were examined in terms of factor structure, reliability, measurement invariance, and theoretically relevant correlates. A potential threshold was determined to identify individuals with an elevated risk of CSBD. RESULTS: The five-factor model of the CSBD-19 (i.e., control, salience, relapse, dissatisfaction, and negative consequences) had an excellent fit to the data and demonstrated appropriate associations with the correlates. Measurement invariance suggested that the CSBD-19 functions similarly across languages. Men had higher means than women. A score of 50 points was found as an optimal threshold to identify individuals at high-risk of CSBD. CONCLUSIONS: The CSBD-19 is a short, valid, and reliable measure of potential CSBD based on ICD-11 diagnostic guidelines. Its use in large-scale, cross-cultural studies may promote the identification and understanding of individuals with a high risk of CSBD.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".