Message Framing and Parents' Intentions to have their Children Vaccinated Against <scp>HPV</scp>
Bibliographic record
Abstract
OBJECTIVE: Framing a message in terms of the benefits of engaging in the behavior (gain frame), the costs of failing to engage in the behavior (loss frame), or both the benefits and the costs (mixed frame) can impact parents' decisions about their childrens' and adolescents' health. This study, investigated the effect of framed messages on parents' intentions to have their children vaccinated against human papillomavirus (HPV). DESIGN AND SAMPLE: The study employed a 2 (gender of the parent) × 2 (gender of the child) × 3 (message frame) between-groups, quasi-experimental design. A convenience sample of 367 parents with children in Grade 5, 6, or 7 who had at least one child who had not been vaccinated against HPV. MEASURES: Social-cognitive variables relating to intentions to vaccinate a child were assessed. INTERVENTION: Participants were randomly assigned to read one of three framed messages about the HPV vaccine (gain, loss, or mixed). RESULTS: Gain-framed messages seemed to persuade mothers of sons to speak to a doctor about the vaccine (p < .05). Framing effects were not significant for other outcomes. CONCLUSIONS: Findings provide preliminary evidence that certain vaccination messages may be more effective for different parent-child dyads.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".