Canadian adolescent perceptions and knowledge about the social determinants of health: an observational study of Kingston, Ontario youth
Bibliographic record
Abstract
BACKGROUND: Upstream social determinants of health (SDH) have become widely acknowledged as lying at the root of poor health outcomes in Canada and globally. The Commission on the Social Determinants of Health maintains that educating the public about the SDH is a key step towards population health equity. Little is known about adolescent perceptions of the determinants of health. Curriculum in Ontario is lacking in SDH content, placing a much greater emphasis on individual, lifestyle behaviors, such as diet, physical activity, and safe sex practices. Identifying a gap in SDH knowledge within the adolescent population is required to advocate for health curriculum revision to include SDH material. METHODS: Student sociodemographic information was obtained through a self-administered questionnaire. Concept mapping exercises were used to determine students' knowledge of the determinants of health and the SDH. Knowledge was approximated by the relative number of SDH concepts present in student maps. Poisson regression analysis was used to determine correlations between sociodemographic characteristics and SDH knowledge. RESULTS: Concept maps indicated that students attributed their health primarily to physical determinants versus social determinants; 44% of maps contained no SDH content. Statistical analyses indicated that students' SDH knowledge varied by their relative socioeconomic status (SES). CONCLUSIONS: Findings suggest that 1) there is an SDH knowledge gap in the adolescent population, and 2) an inequity in adolescent SDH knowledge exists across socio-economic factors. Current Ontario health curriculum requires revision to include SDH material, which will require greater communication and collaboration from both educational institutions and health agencies in Canada.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".