Development of the Cardiovascular Assessment Screening Program (CASP) to improve the uptake of clinical practice guidelines by health care providers in Canada: Results of the integration of qualitative study findings for intervention development in a mixed methods study.
Bibliographic record
Abstract
Abstract Background There is inconsistent utilisation of clinical practice guidelines (CPGs) for cardiovascular disease (CVD) screening and management by healthcare professionals to identify CVD risk factors early and to intervene using current recommendations. This manuscript reports on the results of the integration of the qualitative study findings of a mixed methods study that led to the development of the Cardiovascular Assessment Screening Program (CASP). Methods Focus groups (5) and interviews (10) were conducted in rural and urban settings in one Canadian province with target health professionals, managers in health care organizations, and the public to obtain different perspectives to inform the CASP intervention. Three focus groups were held with nurse practitioners and two with members of the public; individual interviews were conducted with target groups as well. Application of the Theoretical Domains Framework (TDF) provided a comprehensive approach to determine the main factors influencing clinician behaviour, to assess the implementation process, and to support intervention design. Behaviour change techniques, modes of delivery, and intervention components were selected for the development of the CASP. Results Themes identified such lack of knowledge about comprehensive screening, ambiguity around responsibility for screening, lack of time and commitment to screening were addressed in the components of the CASP intervention that were developed, including a website, education module, decision tools, and a toolkit. Conclusion CASP is a theory-informed intervention developed through the integration of the findings from the focus groups and interviews with selected TDF domains, behaviour change techniques, and modes of delivery available in the local context that may be a useful approach for knowledge translation of evidence into practice.
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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 | 0.054 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".