Contextualizing the proven effectiveness of a lifestyle intervention for type 2 diabetes in primary care: A qualitative assessment using re-aim
Bibliographic record
Abstract
Objective: The Healthy Eating and Active Living for Diabetes in Primary Care Networks (HEALD) intervention proved effective in increasing daily physical activity among people with type 2 diabetes in four community-based Primary Care Networks (PCNs) in Alberta. Here, we contextualize its effectiveness by describing implementation fidelity and PCN staff's perceptions of its success in improving diabetes management. Methods: We used the RE-AIM framework to evaluate HEALD. Qualitative methods used to collect data related to the RE-AIM dimensions of Implementation and Effectiveness included interviews with PCN staff (n=24), research team reflections (n=4) and systematic documentation. We used content analysis, and data were imported into and managed using Nvivo 10. Results: HEALD was implemented as intended with adequate fidelity across all four PCNs. Identified implementation facilitators included appropriate human resources, training provided, ongoing support, provision of space and simplicity of the intervention. However, PCN staff reported varying opinions regarding its potential for improving diabetes management among patients. Rationales for their views included: intervention "dose" inadequacy, quality of usual care for people with diabetes was already good, patients were already managing their diabetes well and potential for co-intervention. Recommended improvements to HEALD included increasing the dose of the intervention, expanding it to other modes of exercise and incorporating a medical clearance process. Conclusions: Based on the high degree of fidelity, the demonstrated effectiveness of HEALD in improving physical activity among patients was a result of sound implementation of an efficacious intervention. Increasing the dose of HEALD could result in additional improvements for patients.Acknowledgments: This work was supported in part by a contract from Alberta Health, a grant from the Lawson Foundation and a Canadian Institutes for Health Research (CIHR) Team Grant to the Alliance for Canadian Health Outcomes Research in Diabetes sponsored by the CIHR Institute of Nutrition, Metabolism and Diabetes.
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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 | 0.051 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".