Improving awareness, accountability, and access through health coaching: qualitative study of patients' perspectives.
Bibliographic record
Abstract
OBJECTIVE: To assess patients' experiences with and perceptions of health coaching as part of their ongoing care. DESIGN: A qualitative research design using semistructured interviews that were recorded and transcribed verbatim.Setting Ottawa, Ont. PARTICIPANTS: Eleven patients (> 18 years of age) enrolled in a health coaching pilot program who were at risk of or diagnosed with type 2 diabetes. METHODS: Patients' perspectives were assessed with semistructured interviews. Interviews were conducted with 11 patients at the end of the pilot program, using a stratified sampling approach to ensure maximum variation. MAIN FINDINGS: All patients found the overall experience with the health coaching program to be positive. Patients believed the health coaching program was effective in increasing awareness of how diabetes affected their bodies and health, in building accountability for their health-related actions, and in improving access to care and other health resources. CONCLUSION: Patients perceive one-on-one health coaching as an acceptable intervention in their ongoing care. Patients enrolled in the health coaching pilot program believed that there was an improvement in access to care, health literacy, and accountability,all factors considered to be precursors to behavioural change.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".