Understanding Barriers for Communicating Injury Prevention Messages and Strategies Moving Forward: Perspectives from Community Stakeholders
Bibliographic record
Abstract
OBJECTIVES: The primary objective of this study was to elicit the perspectives of direct care providers on barriers and facilitators to communicating injury prevention messages to parents/caregivers of children under 4 years of age. The secondary objective was to examine characteristics of an injury prevention messaging strategy preferred by direct care providers. DESIGN AND SAMPLE: This qualitative study was conducted across four regions in Ontario Canada. Fifty-nine direct care providers were purposefully sampled and data interpreted using focus group analysis. MEASURES: Transcripts were analyzed verbatim using content and discourse analysis. RESULTS: Several barriers to communicating injury prevention messages were identified encompassing (a) role, (b) parental, (c) social determinants, and (d) evidence impediments. In an effort to offset some of these barriers, participants endorsed the development of a tailored multicomponent injury prevention strategy adopting action-based messages. CONCLUSION: The results of this study provide an in-depth exploration of direct care providers perceptions that can inform the design of materials and dissemination strategies to help increase and optimize access to injury prevention information. Injury prevention messages should be action-oriented, specifically tailored to the stage of child development, and disseminated through both face-to-face interactions and mobile technology.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".