Improving the Prevention of Cardiovascular Disease in Primary Health Care: The Model for Prevention Study Protocol
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death globally, and accounted for nearly 31% of all deaths in Australia in 2011. The primary health care sector is at the frontline for addressing CVD, however, an evidence-to-practice gap exists in CVD risk assessment and management. General practice plays a key role in CVD risk assessment and management, but this sector cannot provide ongoing lifestyle change support in isolation. Community-based lifestyle modification services and programs provided outside the general practice setting have a key role in supporting and sustaining health behavior change. Fostering linkages between the health sector and community-based lifestyle services, and creating sustainable systems that support these sectors is important. OBJECTIVE: The objective of the study Model for Prevention (MoFoP) is to take a case study approach to examine a CVD risk reduction intervention in primary health care, with the aim of identifying the key elements required for an effective and sustainable approach to coordinate CVD risk reduction across the health and community sectors. These elements will be used to consider a new systems-based model for the prevention of CVD that informs future practice. METHODS: The MoFoP study will use a mixed methods approach, comprising two complementary research elements: (1) a case study, and (2) a pre/post quasi-experimental design. The case study will consider the organizations and systems involved in a CVD risk reduction intervention as a single case. The pre/post experimental design will be used for HeartLink, the intervention being tested, where a single cohort of patients between 45 and 74 years of age (or between 35 and 74 years of age if Aboriginal or Torres Strait Islander) considered to be at high risk for a CVD event will be recruited through general practice, provided with enhanced usual care and additional health behavior change support. A range of quantitative and qualitative data will be collected. This will include individual health and well being data collected at baseline and again at 12 months for HeartLink participants, and systems related data collected over the period of the intervention to inform the case study. RESULTS: The intervention is currently underway, with results expected in late 2015. CONCLUSIONS: Gaining a better understanding of CVD prevention in primary health care requires a research approach that can capture and express its complexity. The MoFoP study aims to identify the key elements for effective CVD prevention across the health and community sectors, and to develop a model to better inform policy and practice in this key health priority area for Australia.
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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 | 0.056 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.080 | 0.015 |
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".