What features of images affect parents’ appraisal of safety messages? Examining images from the <i>A Million Messages</i> programme in Canada
Bibliographic record
Abstract
BACKGROUND: Enhancing caregivers' awareness of children's injury risks and increasing knowledge about strategies for injury prevention often involve presenting parents with written materials and accompanying images. OBJECTIVES: To assess parents' appraisals of different variations of images and identify those features that enhance their attention to safety messages. METHODS: Eight images showing risk situations were taken from the A Million Messages safety education parent-directed programme in Canada and modified to create a corresponding image that clearly showed negative consequences for the child, and facial expressions of fear and/or upset. Mothers with young children were presented with the eight pairs of images (negative consequence vs risk situation) and asked to select the best accompaniment to a safety message and to provide an explanation for their choice. Each image was then also rated for fit to the safety message, communication of danger, emotional arousal and attention elicitation. RESULTS: The images depicting negative consequences were chosen for most comparisons (78%) and higher scores were assigned to these images for all four features rated by parents (danger communicated, emotions evoked, attention elicitation and fit to the safety message). Moreover, ratings of danger, emotions and attention predicted 'fit to safety message' scores. CONCLUSIONS: Depicting negative consequences and showing negative emotions is important to maximise the effectiveness of images in communicating danger and evoking attention and concern when targeting parents with child-safety messaging.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".