Prevalence of sexually transmitted infections among military personnel: a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Military personnel are a unique population with heightened vulnerability to sexually transmitted infections (STIs), often exhibiting higher prevalence rates than civilians due to demographic, environmental and occupational factors. These vulnerabilities underscore the need for global prevalence estimates to guide effective, evidence-based interventions. This study aims to quantify the global burden of STIs among military personnel, providing a comprehensive and up-to-date assessment. METHODS AND ANALYSIS: This systematic review will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis Guidelines (2020). Using the CoCoPop (Condition, Context, and Population) framework, a comprehensive search strategy will be conducted in MEDLINE, Embase, Global Health and Scopus to retrieve peer-reviewed records published between January 2010 and June 2025. Eligible studies will report numerical STI prevalence data among military personnel. Studies with insufficient information to calculate prevalence or those relying on self-reported STI data will be excluded. Data extraction will include study details, military descriptors, STI prevalence and diagnostic methods. Risk of bias will be assessed using the Joanna Briggs Institute critical assessment tool for prevalence and incidence studies. Prevalence estimates with 95% CIs will be reported for each STI and, where appropriate, pooled for curable STIs. Subgroup analyses will stratify prevalence by geographic region, service status, deployment status and socioeconomic factors. Heterogeneity will be evaluated within predefined subgroups using the I² statistic. Data will be presented in comprehensive tables and visualised with graphical tools, including forest plots for subgroup analyses and pooled estimates. ETHICS AND DISSEMINATION: Ethical approval is not required for this review. The results will be disseminated through a peer-reviewed publication and conference presentations. PROSPERO REGISTRATION NUMBER: CRD42023472113.
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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 | 0.065 | 0.060 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.022 | 0.015 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.069 | 0.009 |
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".