Building the backbone for organisational research in public health systems: development of measures of organisational capacity for chronic disease prevention
Bibliographic record
Abstract
BACKGROUND: : Research to investigate levels of organisational capacity in public health systems to reduce the burden of chronic disease is challenged by the need for an integrative conceptual model and valid quantitative organisational level measures. OBJECTIVE: To develop measures of organisational capacity for chronic disease prevention/healthy lifestyle promotion (CDP/HLP), its determinants, and its outcomes, based on a new integrative conceptual model. METHODS: Items measuring each component of the model were developed or adapted from existing instruments, tested for content validity, and pilot tested. Cross sectional data were collected in a national telephone survey of all 216 national, provincial, and regional organisations that implement CDP/HLP programmes in Canada. Psychometric properties of the measures were tested using principal components analysis (PCA) and by examining inter-rater reliability. RESULTS: PCA based scales showed generally excellent internal consistency (Cronbach's alpha = 0.70 to 0.88). Reliability coefficients for selected measures were variable (weighted kappa(kappa(w)) = 0.11 to 0.77). Indicators of organisational determinants were generally positively correlated with organisational capacity (r(s) = 0.14-0.45, p<0.05). CONCLUSIONS: This study developed psychometrically sound measures of organisational capacity for CDP/HLP, its determinants, and its outcomes based on an integrative conceptual model. Such measures are needed to support evidence based decision making and investment in preventive health care systems.
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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 | 0.317 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".