Implementing A Winter Wellness University Program: A Community Health Nursing Project
Bibliographic record
Abstract
To improve the health and wellness of students, faculty and staff in a university setting, the authors developed and implemented a four-week health and wellness challenge project based on the application of the Population Health Promotion Model and the Community as Partner model to each of the steps of the community health nursing process. The purpose of this paper is to describe this community health improvement project, The Winter Wellness Challenge (WWC), which involved one university faculty in Western Canada. The entire project, which occurred over a 3-month period, included the following elements: a community health assessment of the community where the university was situated, which was initiated via a windshield survey, self-evaluated health status of program participants done via Survey Monkey prior to the start of the WWC program, the four-week intervention, and a post-intervention survey. In addition, key informant interviews were conducted with 21 participants after completion of the WWC to solicit participants’ feedback about the utility of the project and to seek recommendations to improve future WWCs. The salient findings showed improvement in social support, duration of sleep, and stress level. From the participants’ perspective, the greatest improvement was in physical and nutritional wellness. The participants advocated for continuing implementation of the challenge in the future. Recommendations for improving the WWC were also provided.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".