Factors that Facilitate and Impede the Implementation of Evidence-Informed Chronic Disease Prevention Programs and Policies in Rural Ontario Public Health Units
Bibliographic record
Abstract
Practitioners, research funders, and policymakers acknowledge the need to implement evidence-informed public health (EIPH) practice to reduce the prevalence of chronic diseases. Although it is difficult to estimate how widely EIPH practices are being applied, several surveys in public health settings demonstrate that, on average, just over half of recommended health practices are implemented. In Canada, people living in rural and remote areas are most vulnerable to chronic diseases. However, the implementation of EIPH practice in rural Ontario public health units (PHUs) is a complex, multidisciplinary process, that occurs within heterogenous and dynamic communities and encompasses different sectors of society. Therefore, this study explores and develops a realist account of the factors that facilitate and impede the implementation of evidence-informed chronic disease prevention (CDP) programs and policies in rural Ontario PHUs (i.e. Rural Public Health Systems – RulPHS). \n \nIntensive, in-depth, semi-structured qualitative interviews and focus groups were conducted in six rural Ontario public health units. Fifteen executives (i.e. CDP Manager/Directors and MOH), participated in the interviews, and 50 public health staff in the area of CDP participated in the focus groups. Interview and focus group data were supplemented by field and reflective notes, and unobtrusive documents provided by the participants. \n \nThe primary method that was used was a qualitative collective case study (multiple), and the study perspective was based on a critical realist ontology. Propositions, sensitizing concepts, and a basic realist model was developed a priori based on extensive research. The Consolidated Framework for Implementation Research (CFIR) was also used to guide the research study. Inductive, deductive, abductive, and retroductive analysis procedures were used to produce a final data structure hierarchy (i.e. categorization scheme). The categorization scheme included five categories, seventeen (17) themes, twenty-one (21) subthemes, and eighty-one (81) factors that facilitated or impeded implementation of CDP programs and policies in rural Ontario PHUs, which were verified through member checks. Solutions were also identified to address barriers to implementation. \n \nFactors that facilitated or impeded implementation were summarized under five broad categories and a further seventeen major themes within them. Major themes were as follows: evidence strength and quality, complexity, adaptability, trialability, cosmopolitanism, external policies and incentives, external leadership engagement, population external communication, reach, population needs and resources, structural characteristics, culture, implementation climate, readiness for implementation, intraorganizational networks and communications, individual identification with organization, and planning. Key lessons learned from the study were also identified. \n \nImplementation was seen to be complex, and there was a plethora of related factors that facilitated and impeded the implementation of evidence-informed CDP programs and policies in Ontario rural PHUs, that occurred over time. These factors closely aligned to many of the factors in the CFIR, which was used to guide this study. Further, critical realism offered insight into the mechanisms (M) with the program and policy, the conditions and contexts (C), under which the generative mechanisms operated, and the patterns of outcomes (O) produced (i.e. realist model). Contributions of rural public health practice, strengths and limitations, and future research were also discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".