Online health promotion program and individualized health coaching for veteran wellbeing
Bibliographic record
Abstract
The pandemic has highlighted the need for accessible and effective health promotion as Canadians are isolated from their communities during social distancing measures. A web-based health promotion program in which participants also received individualized email-based health coaching from medical students has been available during the pandemic to empower veterans and their family members to engage in healthy lifestyle change. Health coaches’ email interactions with participants used techniques of motivational interviewing, including an empathetic style, statements of affirmation, and reflections. Open-ended questions were useful in gaining insight into the participant’s current lifestyle, including habits, challenges, and coping strategies. As services have transitioned online and individuals have become more isolated, the connection formed between online health coaches and individuals participating in the health promotion program became crucial in countering the mental and physical health repercussions of the pandemic. In a preliminary analysis, we show that web-based health promotion with health coaching, for Canadian Veterans and their families, leads to significant weight loss, increased activity and improvement in wellbeing metrics such as sleep and stress. The medical students acting as health coaches were able to gain a deeper understanding of the challenges involved in behaviour change, something that is seldom covered in detail in the medical school curricula. Medical students were also able to practice their motivational counseling skills surrounding lifestyle changes. Given the lack of available evidence for web-based health promotion that targets veterans and their families, these preliminary results appear promising, with longer-term follow-up planned for the next two years.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".