Organizational capacity and dissemination practices for chronic disease prevention in the Canadian public health system
Bibliographic record
Abstract
Introduction: The public health system is of central importance in efforts to reduce the burden of chronic disease, yet there are no national data on organizational capacity (OC) or dissemination practices pertaining to chronic disease prevention (CDP) programming in the public health system. The aim of this thesis is to investigate OC and dissemination practices within the Canadian public health system. Two new conceptual models pertaining to these constructs were developed, and a survey of all public health organizations across Canada engaged in CDP was conducted in 2004-5. Method: Data were collected in telephone interviews with persons most knowledgeable about CDP programming in 77 "resource" organizations that develop and transfer CDP innovations to other organizations, and 216 "user" organizations that adopt and deliver CDP programs in specific populations. Reliable measures of the constructs of interest were developed using principal components analyses. Levels of OC, its potential determinants, and involvement in CDP programming were compared across three types of organizations and across Canada. In addition, levels of 13 dissemination-related practices were compared across organizations and independent correlates of dissemination were identified in multiple linear regression. Results: Levels of skill and involvement were highest for tobacco control and healthy eating programming; lowest for stress management, social determinants of health, and program evaluation. Any notable differences in skill levels favoured central Canada. Resource adequacy was low overall; lowest in eastern Canada and within formal public health organizations. Supports for OC were highest in central Canada and in grouped organizations. Dissemination practices most heavily engaged in included: Identification of barriers to adoption/implementation of the innovation, tailoring dissemination strategies and design of dissemination plan. There was little coherence across organizations in the number or types of dissemination practices engaged in. Skill at planning/implementing dissemination, external sources of funding, type of resource organization, attitude toward the process of collaboration, and user-centeredness were all positively associated with dissemination (R2=0,42; F value 8.20, p<0.0001). Conclusions: These results provide a backbone for organizational research in public health systems. Strengths and gaps identified in OC and dissemination practices will guide strategic investment in the public health system.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".