Exploring health coaching and mindfulness as levers for transformation in health: stakeholder perspectives
Bibliographic record
Abstract
BACKGROUND: Health coaching (HC) and mindfulness (MFN) are proven interventions for mobilizing patients' inner resources and are slowly being integrated into public primary care. Since 2015 the medical community in Gibsons BC has integrated physician-led HC and MFN-based programs into team-based care. This exploratory study aimed to understand the mechanisms by which these rural programs helped both patients and clinicians, and to elicit priorities for future study in these fields. METHODS: Using a qualitative participant-engaged constructivist approach in focus groups and large-group graphic facilitation, we elicited perspectives from patients and their physicians during a 1-day event held in September 2018. Thematic analysis of transcripts using Nvivo identified emergent themes that were regularly reviewed with coresearchers, and member checked with participants via online videoconferences held at 6 weeks and 4 months postevent. RESULTS: We identified six main themes relating to the successful implementation of these programs: (i) accessibility and affordability, (ii) offering a toolbox of practical skills, (iii) providing attuned and openhearted care, (iv) generating hope and self-efficacy, (v) experiencing a shared humanity and connection, and (vi) addressing the health of the whole person. CONCLUSION: These themes highlight critical qualities of HC and MFN programs when implemented in a Medicare system. Key features include reducing stigma around mental health through making programs physician-led and a natural part of primary care, enriching accessibility through public funding, and enhancing patient agency through cultivating embodied awareness, self-compassion, and interpersonal skills. These themes inform the next steps to support upscaling these programs to other communities.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".