The Development and Validation of Sexual Health Indicators of Canadians Aged 16–24 Years
Bibliographic record
Abstract
OBJECTIVES: We developed and validated a set of self-administered, multi-dimensional indicators of sexual health among Canadians aged 16-24 years. METHODS: This study used a mixed-method qualitative and quantitative approach to develop and validate indicators of sexual health. We used the four-stage Dillman method to identify, focus-test, pilot-test, and validate key metrics to measure sexual health. We collected quantitative data to validate the measures through a computer-assisted self-interviewing program among a purposive sample of 1,158 people aged 16-24 years recruited from four Canadian provinces. RESULTS: The survey contained 75 items measuring five dimensions of sexual health: (1) physical, mental, emotional, and social well-being in relation to sexuality; (2) approach to sexuality; (3) sexual relationships; (4) sexual experiences; and (5) discrimination, coercion, and violence. Principal components analysis for composite measures found seven components with eigenvalues ≥1. The factor structure was stable across gender, age, size of area of residence, and language in which the survey was completed. Cronbach's alpha coefficients ranged from 0.79 to 0.90. Indicators of condom use at last vaginal sex, protection self-efficacy, sexually transmitted infection/HIV testing self-efficacy, and sexual orientation also showed good construct validity. CONCLUSIONS: The indicators constituted a conceptually grounded survey that is easy for young adults to complete and contains valid, reliable, and psychometrically robust measures. The survey instrument provides a tool for future research to collect population-level data to measure and monitor trends in the sexual health of young people in Canada.
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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".