Disability is associated with sexually transmitted infection: Severity and female sex are important risk factors
Bibliographic record
Abstract
It has been suggested that disabled people may experience higher rates of sexually transmitted infections (STI) due to health inequities and sexual education gaps. Using a pan-Canadian health survey, we sought to explore the association with disability and STI. Using the public use microdata file for the 2013–2014 cycles of the Canadian Community Health Survey (Statistics Canada), the association between disability and STI was explored. Modelling included adjustment for age, ethnicity, geography, living arrangement, educational status, and marital status. Results were stratified for females and males, disability severity, and type. Both females (odds ratio [OR] 1.54, 95% confidence intervals [CI] 1.27–1.86) and males (OR 1.29, 95% CI 1.03–1.62) with any impairments were more likely to report a diagnosis of STI. A graduated effect was seen, with the odds increasing as the severity of disability increased. Females with severe visual impairment (OR 6.88, 95% CI 2.13–22.17) had the highest association with STI. Associations were most consistently seen in females, suggesting sex differences in risk for disabled people. Given that Canadians living with disabilities are more likely to report having been diagnosed with a STI, future work is needed to further understand the causes. In the meantime, these findings signal a need for clinicians to ensure this group is engaged with STI screening, as well as the greater need for improved strategies to address the sexual health needs of those living with a disability of all severities and types.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".