Sexual Function, Sexual Dysfunctions, and ADHD: A Systematic Literature Review
Bibliographic record
Abstract
BACKGROUND: The scientific literature on sexuality among mentally ill patients clearly shows a higher prevalence of sexual disorders for many mental disorders, but little is known about sexuality in individuals suffering from ADHD. Clinicians will often assume that specific difficulties of ADHD are bound to affect sexual functioning. AIM: The aim of this study was to provide a review of the literature to gain better knowledge about sexuality in subjects with ADHD and to discuss screening and management of their potential sexual problems. METHODS: A systematic review of the literature was performed in Pubmed, PsychInfo, and Embase databases. MAIN OUTCOME MEASURES: The main outcome measures were sexual function and sexual dysfunctions. RESULTS: The studies indicated that subjects with ADHD report more sexual desire, more masturbation frequency, less sexual satisfaction, and more sexual dysfunctions than the general population. CLINICAL IMPLICATIONS: Clinicians working with subjects with ADHD should explore the quality of their sexual life. STRENGTHS & LIMITATIONS: This is the first systematic review of the sexuality of individuals with ADHD. However, the results are limited by the small number of studies, by the small sample size of many studies, and the potential for bias. CONCLUSIONS: ADHD is a mental disorder affecting sexual health. Further studies are warranted to learn more about sexuality in subjects with ADHD. Soldati L, Bianchi-Demicheli F, Schockaert P, et al. Sexual Function, Sexual Dysfunctions, and ADHD: A Systematic Literature Review. J Sex Med 2020;17:1653-1664.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".