The HANS KAI Project: a community-based approach to improving health and well-being through peer support
Bibliographic record
Abstract
INTRODUCTION: HANS KAI is a unique health promotion intervention to improve participants' health by focussing on interrelated chronic disease prevention behaviours through peer support and strengthening of social support networks. The study objective was to determine the effectiveness of HANS KAI in an urban Canadian setting. METHODS: We used a mixed methods intervention research design that involved multiple sites from November 2010 to April 2015. Data was obtained from participant surveys as well as in-person interviews at zero, 6, 12 and 24 months. Participants met in groups at least once a month during the research period, to self-monitor health indicators, prepare and share a healthy snack, participate in a physical activity, set a healthy lifestyle goal (optional) and socialize. RESULTS: There were statistically significant mental health improvements from pre- to post-program, and 66% of the participants described specific behaviour changes as a result of HANS KAI participation. Additional positive health impacts included peer support; acquiring specific health knowledge; inspiration, motivation or accountability; the empowering effect of monitoring one's own health indicators; overcoming social isolation and knowing how to better access services. CONCLUSION: The need to identify innovative ways to address chronic disease prevention and management has been the driver for implementing and evaluating HANS KAI. While further research will be required to validate the present findings, it appears that HANS KAI may be an effective approach to create environments that empower community members to support each other while promoting healthy lifestyle choices and detecting early changes in health status.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".