Exploring factors associated with condom use self-efficacy and condom use among Northern and Indigenous adolescent peer leaders in Northern Canada
Bibliographic record
Abstract
Social and health disparities compromise Northern and Indigenous adolescents’ wellbeing in the Northwest Territories (NWT) where food insecurity, sexually transmitted infections (STI), and depression prevalence are higher than other Canadian regions. Condoms are an accessible STI prevention strategy for adolescents, yet depression and food insecurity may constrain condom use self-efficacy. The potential role of resilience in cultivating condom use self-efficacy is understudied. This study examined factors associated with condom use self-efficacy among Northern and Indigenous adolescents. We examined: (1) resilience as a mediator in the relationship between depression and condom use self-efficacy; (2) if food insecurity influenced the indirect effect of depression on condom use self-efficacy through resilience; and (3) condom use self-efficacy as a mediator of the relationship between resilience and condom use. We conducted a cross-sectional survey in 17 NWT communities with adolescents aged 13–18 who had attended a peer leadership training held by a NWT sexual health organization. We conducted descriptive statistics, followed by ordinary least squares regression to test the mediation models, and a conditional process analysis to examine the moderating role of food insecurity in the relationship between depression, resilience, and condom use self-efficacy. Most participants (n = 86; mean age: 15.77, SD = 2.05) identified as Indigenous (n = 65; 77.4%) and women (n = 70; 82.4%) and reported depressive symptoms (n = 54; 70.1%). Results suggest that resilience mediated the relationship between depression and condom use self-efficacy, and among sexually active participants, resilience mediated the association between condom use self-efficacy and condom use. There was a significant positive interaction effect between resilience and food insecurity on condom use self-efficacy, suggesting that food insecure participants with higher resilience reported higher condom use self-efficacy. Findings can inform strengths-based, resilience focused strategies to advance sexual health among Northern adolescents. These findings underscore the need to address syndemics of poverty, mental health, and sexual health.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".