Scale Development of Individual and Organisation Infrastructure for Heart Health Promotion in Regional Health Authorities
Bibliographic record
Abstract
Objective The purpose of this study was to validate measures of individual and organisational infrastructure for health promotion within Alberta's (Canada) 17 Regional Health Authorities (RHAs). Design A series of phases were conducted to develop individual and organisational scales to measure health promotion infrastructure. Instruments were designed with focus groups and then pre-tested prior to the validation study. Setting In 1993 all hospitals and Public Health Units in the province of Alberta were regionalised into 17 RHAs, with responsibility for public health, community health, and acute and long-term care. While regionalisation may offer more opportunity for community participation, reorganisation of the public health system may have fragmented and diluted resources and skills for heart health promotion in some RHAs. Infrastructure (for example, human and financial resources), amongst other items, is believed to contribute to the capacity to promote health. Method All 17 RHAs participated in the study, yielding a total of 144 individuals (that is board members, senior/middle management, and front line staff). These representative employees completed a self- administered questionnaire on individual- and organisational-level infrastructure measures. Results Psychometric analyses of survey data provided empirical evidence for the robustness of the measures. Principal component analyses verified the construct validity of the scales, with alpha coefficients ranging from 0.75 to 0.95. Conclusion The scales can be used by health professionals and researchers to assess individual- and organisational-level infrastructure, and tailor interventions to increase infrastructure for health promotion in health organisations.
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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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".