Community Readiness Assessment of the “Take TIME for Your Child’s Health” Intervention
Bibliographic record
Abstract
Take TIME (Tobacco-free, Injury-free, Moving daily, Eating healthy) was an early intervention strategy targeting community readiness to support healthy lifestyles for young children in Uxbridge, Canada. This study aimed to assess the effectiveness of Take TIME using the Community Readiness Model adapted for childhood obesity prevention. Six interviews were completed in Uxbridge, before and after the intervention, with purposively selected community leaders in education, political, business, religious, not-for-profit, and healthcare fields. Each interview was rated independently by two scorers. Interview content was scored (scale from 1 to 9, with 1 being no awareness and 9 being a high level of community ownership) according to the Community Readiness Model criteria on six dimensions, with overall readiness calculated as the mean score of all dimensions. T-tests compared readiness by time-point and between communities. Overall community readiness significantly improved (p = 0.03) in Uxbridge from pre-intervention (3.63 ± 1.14 vague awareness) to post-intervention (5.21 ± 0.97 preparation). Seven interviews were also completed with leaders in the matched town of Rockwood, Canada which served as the control community. Rockwood readiness was close to the Uxbridge post-intervention score (5.35 ± 1.11). Results indicated increased awareness and leadership support post-intervention in Uxbridge, but further improvements in community knowledge, formalized efforts, and additional leadership support are desired. Take TIME increased community readiness to support healthy lifestyles for young children and may be useful to other communities at similar stages, given its theoretical alignment with the community readiness model. Future research should investigate the impact of Take TIME in demographically diverse communities and appropriate interventions to move communities from the preparation to the action stage.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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; 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".