191 Prevalence and Factors of Sexual Dysfunctions Among Military Men: A Systematic Review
Bibliographic record
Abstract
ABSTRACT Background Military men are at a higher risk of developing sexual dysfunction (SD) as compared to the general population because military deployment exposes soldiers to stressful situations (e.g., death of comrades, combat stress, war inflicted injuries, severe environment, lack of sleep, mental distress, isolation, post-traumatic stress disorder (PTSD), polluted environment and substance abuse, etc.) that may alter their psychological and underlying biological processes. Understanding mechanisms and estimating the burden of SD in military men would also be helpful for the implication in the general population of men exposed to such harsh conditions. Objective To systematically review published reports on SD in military men. Methods Medline was searched for original articles published between 2008 and 2020 by using the search terms “sexual dysfunction in military personnel,” and “sexual dysfunction in veterans”. Quality evaluation and data extraction were done by two authors. Studies that reported the sexual dysfunction in newly inducted or interviewed men in recruitment centres or specific disease cohorts, and that reported the effect of different drugs on sexual health under controlled conditions were excluded. Information related to the sampling duration, sampling method, sample size, methods of diagnosis, cut off values, the prevalence of different sexual dysfunctions and associated factors were extracted. All discrepancies were resolved by discussion. Results A total of 8211 studies were identified initially. After the removal of duplicates, 5186 studies were screened based on titles and abstracts. The full articles were downloaded for 54 studies, of which 27 studies were finally included in the qualitative study. Among the included studies 16 were conducted in North America (US=15 and Canada=01), 4 in Europe (Netherlands=1, France=1 and Croatia=2) and 7 in Asia (Israel=3, Iran=1, South Korea=1 and Taiwan=2). All the studies included in the present review had variable sample sizes (n=53 - 456,340). Sampling methods included mailed questionnaires, in-person interviews, medical chart reviews and secondary data taken from large surveys and patients from outpatient clinics. The studies reported a wide range of prevalence of overall SD (5.6% - 88.7%), erectile dysfunction (ED) (2% - 83.4%), ejaculatory dysfunction (0.1% - 25.5.0%), orgasmic dysfunction (0.2% - 15.4%) sexual desire disorders (0.3% - 74.0%) and sexual dissatisfaction (11.8% - 73.5%). The prevalence of mild ED (16.7% - 30.3%) was highest followed by mild to moderate ED (3.4% - 20.5%), moderate ED (1.1% - 9.3%) and severe ED (0.3% - 10%). Prevalence of premature and delayed ejaculation was 0.1% - 25.5% and 18.0%, respectively. Prevalence of quick orgasms and difficulty in orgasm was reported in 15.4% and 13.8%, respectively. Orgasmic anhedonia was also reported in 11 % of men. The prevalence of SD was positively associated with PTSD, depression and anxiety, using nicotine and antidepressants, physical health (infections, cardiovascular diseases), and being non-white race. However, age, alcohol, body weight and education had no association with SD in military men. Conclusion A considerably variable number of military men had SD due to different factors. Studies in Asian and European countries were limited in number and magnitude. Disclosure Work supported by industry: no.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".