Trends in pre-military sexually transmitted infections and associated risk behaviours in Canadian Armed Forces recruits
Bibliographic record
Abstract
BACKGROUND: Sexually transmitted infections (STIs) have historically been problematic for militaries. Recent reports indicating that rates of STIs among young male Canadian Armed Forces (CAF) members are higher than civilians prompted a need to better understand CAF members' reported rates of STIs and their behavioural risk factors for STIs. This study examined the prevalence of self-reported pre-military sexual behaviours (i.e. number of sexual partners and frequency of condom use) and history of a STI diagnosis among CAF recruits attending basic military training using data collected from the Recruit Health Questionnaire. METHODS: Data came from 50,603 recruits who participated in the survey between 2003 and 2018 (84.9% male, 78.6% Non-Commissioned Member candidates, 64.9% aged between 17 and 24 years). RESULTS: Among sexually active recruits, the proportions who had more than one sexual partner in the previous year increased from 30.5% in 2003 (95% CI, 27.8-33.4) to 35.5% in 2018 (95% CI, 34.0-37.0). Of recruits who were not in an exclusive relationship at the time, the proportions who reported always using a condom decreased from 50.8% in 2003 (95% CI, 46.4-55.1) to 40.2% in 2018 (95% CI, 38.3-42.2). Overall, 5.5% (95% CI, 5.3-5.7) reported ever having received a STI diagnosis. Demographic differences by age and sex were also found. CONCLUSION: These observations provide an indication of the baseline, pre-enlistment STI risk behaviours, and STI history among CAF recruits, and may provide insight into avenues for targeted interventions and health promotion programming, such as education and screening initiatives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".