Sex and genes, part 2: A biopsychosocial approach to assess and treat challenging sexual behavior in persons with intellectual disabilities including fragile X syndrome and 22q11.2 deletion syndrome
Bibliographic record
Abstract
Individuals with intellectual disabilities (IDs) - and specifically those with genetic disorders - are more prone to medical and psychological challenges that affect their sexual development, experiences, and fertility. In this review paper we first provide an overview of the biopsychosocial (BPS) model and then explain how the model can guide and improve the assessment and treatment of challenging sexual behaviors by persons with IDs. We discuss two genetic conditions - fragile X syndrome and 22q11.2 deletion syndrome - in case studies, showing how the BPS model can be used to assess and treat the sexual problems of individuals with various types of ID. We conclude with BPS-formulated treatment considerations in three key domains: biomedical treatment (e.g., medication side effects; stopping or changing medications), psychological treatment (e.g., providing psychological therapies), and socio-environmental interventions (e.g., providing socio-sexual education and staff training). Together, these treatment interventions can aid clinicians to prevent and/or treat problematic sexual behaviors of people with IDs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".