Do practitioners and friends support patients with coronary heart disease in lifestyle change? a qualitative study
Bibliographic record
Abstract
BACKGROUND: Healthy lifestyles help to prevent coronary heart disease (CHD) but outcomes from secondary prevention interventions which support lifestyle change have been disappointing. This study is a novel, in-depth exploration of patient factors affecting lifestyle behaviour change within an intervention designed to improve secondary prevention for patients with CHD in primary care using personalised tailored support. We aimed to explore patients' perceptions of factors affecting lifestyle change within a trial of this intervention (the SPHERE Study), using semi-structured, one-to-one interviews, with patients in general practice. METHODS: Interviews (45) were conducted in purposively selected general practices (15) which had participated in the SPHERE Study. Individuals, with CHD, were selected to include those who succeeded in improving physical activity levels and dietary fibre intake and those who did not. We explored motivations, barriers to lifestyle change and information utilised by patients. Data collection and analysis, using a thematic framework and the constant comparative method, were iterative, continuing until data saturation was achieved. RESULTS: We identified novel barriers to lifestyle change: such disincentives included strong negative influences of social networks, linked to cultural norms which encouraged consumption of 'delicious' but unhealthy food and discouraged engagement in physical activity. Findings illustrated how personalised support within an ongoing trusted patient-professional relationship was valued. Previously known barriers and facilitators relating to support, beliefs and information were confirmed. CONCLUSIONS: Intervention development in supporting lifestyle change in secondary prevention needs to more effectively address patients' difficulties in overcoming negative social influences and maintaining interest in living healthily.
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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 | 0.001 |
| 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".