Sexual dysfunction prevalence, risk factors, and help-seeking behavior in opioid agonist treatment and general psychiatry: a cross-sectional study
Bibliographic record
Abstract
Background Mental disorders pose a high risk for the occurrence of sexual dysfunctions (SD). This study aimed to investigate prevalence of risk factors and help-seeking behavior for sexual dysfunctions in patients with opioid use disorder compared to patients seeking psychotherapeutic help. Methods Ninety-seven patients at two opioid agonist treatment (OAT) centers and 65 psychotherapeutic patients from a psychiatric practice (PP) in Switzerland were included in the study. Self-report assessments comprised sexual functioning (IIEF: International Index of Erectile Function; FSFI: Female Sexual Function Index), depressive state, psychological distress, alcohol consumption, nicotine use, and a self-designed questionnaire on help-seeking behavior. We used chi-squared and Mann–Whitney U tests for group comparisons and binary logistic regression models to identify variables predicting the occurrence of sexual dysfunctions. Results There was no statistically significant difference (p = 0.140) in the prevalence of SD between OAT (n = 64, 66.0%) and PP sample (n = 35, 53.8%). OAT patients scored significantly higher in scales assessing nicotine use (p < 0.001) and depressive state (p = 0.005). Male OAT patients scored significantly worse on the Erectile Function scale (p = 0.005) and female PP patients scored significantly worse on the FSFI Pain domain (p = 0.022). Opioid use disorder, higher age, and being female predicted the occurrence of SD in the total sample. In the OAT sample, only higher age remained predictive for the occurrence of SD. A lack of help-seeking behavior was observed in both groups, with only 31% of OAT patients and 35% of PP patients ever having talked about their sexual health with their treating physician. Conclusion SD are common among psychiatric patients receiving OAT and general psychiatric patients seeking psychotherapy. Professionals providing mental healthcare to patients must emphasize prevention and routine assessments of sexual functioning needs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".