Wellness 101: health education for the university student
Bibliographic record
Abstract
Purpose This paper aims to describe two phases of a mixed‐method study: in phase I, the wellness practices of students at a Canadian university are reported. These data informed the re‐development of a first‐year health education course. Subsequent to its revision, phase II of the study assessed the impact of the course on students' wellness practices and learnings. Design/methodology/approach In phase I, 855 students completed a survey rating ten wellness practices relating to themselves. Survey results were explored further in focus groups with 60 students. In phase II, a pre‐ and post‐design assessed the impact of the health education curriculum. Wellness practices were surveyed, at the beginning and end of term, and content analysis was conducted on students' assignments. Findings In phase I, the mean overall wellness score was 779.7 out of 1,000 or “good”. Students scored highest in sexuality and safety, and lowest in physical activity and nutrition. Qualitative analyses revealed four primary themes important to students' wellness: being or holistic health; belonging or feeling connected to others and the campus; becoming or studying to achieve a professional or scholarly degree; and balance – or the search for stability. In phase II, significant changes were found for seven wellness scores when comparing the beginning and end of semester. Analysis of course assignments found that students left the course with enhanced affect and knowledge levels. Originality/value The results support the argument that a health education curriculum, responsive to students' identified needs, and in conjunction with a healthy campus environment, promises to enhance student wellness.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".