Validation and refinement of the Stakeholder-driven Community Diffusion Survey for childhood obesity prevention
Bibliographic record
Abstract
BACKGROUND: Whole-of-community interventions hold promise in addressing childhood obesity. The COMPACT Stakeholder-driven Community Diffusion theory posits that stakeholders' knowledge of childhood obesity prevention efforts and engagement with the issue contribute to successful intervention implementation. Building on completed formative research and pilot testing, we describe the validation and refinement of knowledge and engagement measures. METHODS: We assessed content validity using a modified Delphi process with science (n=18) and practice-based (n=16) experts. Next, we refined the survey based on input from science- and practice-based experts, cognitive response testing, and item analysis of extant survey data. Field testing of the refined survey involved community stakeholders in Greenville County, South Carolina (n=50), East Boston, Massachusetts (n=30), and Tucson, Arizona (n=84) between 2019 and 2020. Construct validity was assessed with confirmatory factor analysis (CFA). Two-week test-retest reliability was assessed among a subsample of 14 paired respondents in South Carolina. RESULTS: Experts rated existing knowledge domains (intervention factors, roles, sustainability, problem, resources) and engagement domains (dialogue/mutual learning, flexibility, influence/power, leadership/stewardship, trust) highly for their importance in addressing childhood obesity. Expert input resulted in 11 new knowledge items and 7 new engagement items that mapped onto existing domains. Correspondingly, two domain names were modified: implementation/sustainability and trust/trustworthiness. We also eliminated 8 extant items (4 knowledge and 4 engagement) and adapted item language for comprehension and consistency. Further modifications based on CFA results and item analyses resulted in 23 knowledge items across four domains (roles and resources merged) and 23 engagement items across five domains. Modified knowledge and engagement scales had adequate fit and strong item factor loadings (most >0.7 and all >0.5). Knowledge (α=0.86-0.87) and engagement (α=0.75-0.90) subscales had high internal scale consistency. Knowledge intraclass correlation coefficients (ICCs) for test-retest agreement of subscale scores ranged from 0.50 for intervention factors to 0.86 for roles/resources. For engagement subscale scores, ICCs ranged from 0.70 for trust/trustworthiness to 0.96 for leadership/stewardship. CONCLUSIONS: Findings from this multi-method survey development process increase our confidence of the knowledge and engagement measures' content validity, construct validity, and reliability.
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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 | 0.069 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".