O13.1 Factors associated with safer sex efficacy among northern and indigenous youth in the northwest territories, canada
Bibliographic record
Abstract
Background Identifying social and structural factors associated with sexually transmitted infections (STI) vulnerability is urgent in the Northwest Territories (NWT), where STI prevalence is 7-fold the Canadian average. The NWT also experiences higher food insecurity and intimate partner violence (IPV) than the national average. Safer sex efficacy (SSE) comprises knowledge, intention, and relationship dynamics for safer sex negotiation. We examined social and structural factors associated with SSE among Northern and Indigenous adolescents in the NWT. Methods With an Indigenous sexual health agency, we conducted a cross-sectional survey with adolescents aged 13–17 in 17 NWT communities. Summary statistics and statistical comparisons were conducted, followed by crude and multivariable regression models, with a canonical link function, to compare factors associated with SSE and within gender stratifications. We conducted post-hoc sensitivity analyses among Indigenous youth. Results There were 610 participants (mean age: 14.2 years [SD: 1.5]; 49.5% cisgender women, 48.9% cisgender men, 1.6% transgender persons); three-quarters (n=447; 73.3%) were Indigenous. One-quarter (n=144; 23,6%) reported food insecurity and nearly one-fifth (n=111; 18.2%) IPV. Among young women, food insecurity (β: -1.89[CI: -2.98, -0.80], p=0.001) and IPV (β: -1.31[CI: -2.53, -0.09], p=0.036) were associated with lower SSE in adjusted analyses, and currently dating was associated with increased SSSE (β: 1.17[CI: 0.15, 2.19], p=0.024). Among young men, food insecurity (β: -2.27[CI: -3.39, -1.15), p=0.014) was associated with reduced SSE. Among sexually active participants (n=115), increased SSE was associated with increased condom use among young women (β: 1.40[0.19, 2.61], p=0.024) and men (β: 2.14[0.14, 4.14], p=0.036). No differences emerged by Indigenous identity across analyses. Conclusion Food insecurity and IPV emerged as syndemic factors associated with lower SSE—a protective factor associated with condom use among Northern and Indigenous adolescents in the NWT. Poverty and violence compromise Indigenous and Northern youth’s sexual agency and in turn contribute to STI vulnerabilities, requiring urgent attention. Disclosure No significant relationships.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".