Exploring the Implementation of Shared Decision-Making Involving Health Coaches for Diabetes and Hypertension Self-Management: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: An emerging focus on person-centered care has prompted the need to understand how shared decision-making (SDM) and health coaching could support self-management of diabetes and hypertension. OBJECTIVE: This study aims to explore preferences for the scope of involvement of health coaches and health care professionals (HCPs) in SDM and the factors that may influence optimal implementation of SDM from the perspectives of patients and HCPs. METHODS: We conducted focus group discussions with 39 patients with diabetes and hypertension and 45 HCPs involved in their care. The main topics discussed included the roles of health coaches and HCPs in self-management, views toward health coaching and SDM, and factors that should be considered for optimal implementation of SDM that involves health coaches. All focus group discussions were audio recorded, transcribed verbatim, and analyzed using thematic analysis. RESULTS: Participants agreed that the main responsibility of HCPs should be identifying the patient's stage of change and medication education, while health coaches should focus on lifestyle education, monitoring, and motivational conversation. The health coach was seen to be more effective in engaging patients in lifestyle education and designing goal management plans as health coaches have more time available to spend with patients. The importance of a health coach's personal attributes (eg, sufficient knowledge of both medical and psychosocial management of disease conditions) and credentials (eg, openness, patience, and empathy) was commonly emphasized. Participants viewed that addressing the following five elements would be necessary for the optimal implementation of SDM: (1) target population (newly diagnosed and less stable patients), (2) commitment of all stakeholders (discrepancy on targeted times and modality), (3) continuity of care (familiar faces), (4) philosophy of care (person-centered communication), and (5) faces of legitimacy (physician as the ultimate authority). CONCLUSIONS: The findings shed light on the appropriate roles of health coaches vis-à-vis HCPs in SDM as perceived by patients and HCPs. Findings from this study also contribute to the understanding of SDM on self-management strategies for patients with diabetes and hypertension and highlight potential opportunities for integrating health coaches into the routine care process.
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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 | 0.025 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".