Helping Children to Participate in Human Papillomavirus–Related Discussions: Mixed Methods Study of Multimedia Messages
Bibliographic record
Abstract
BACKGROUND: Human papillomavirus (HPV) can cause several types of cancers and genital warts. A vaccine is available to prevent HPV infections, and several efforts have been made to increase HPV education and, eventually, vaccination. Although previous studies have focused on the development of messages to educate children about HPV and the existence of the HPV vaccine, limited research is available on how to help children better communicate with their parents and health care professionals about the HPV vaccination. In addition, limited research is available on the target audience of this study (Italian children). OBJECTIVE: This manuscript describes a study assessing the feasibility of using an evidence-based animated video and a web-based game to help children (aged 11-12 years) participate in discussions about their health-in particular when such conversations center around the HPV vaccination-and improve several HPV-related outcomes. The study also compares the effects of these 2 educational multimedia materials on children's knowledge and perceptions of HPV prevention. METHODS: A mixed methods approach consisting of focus group discussions and an experiment with children (N=35) was used to understand children's experiences with, and perceptions of, the animated video and the game and to measure possible improvements resulting from their interaction with these materials. RESULTS: Both the animated video and a web-based game increased children's knowledge and positive perceptions about HPV and HPV vaccination. Any single message was not more effective than the others. The children discussed aspects of the features and characters they liked and those that need improvements. CONCLUSIONS: This study shows that both materials were effective for improving children's education about the HPV vaccine and for helping them to feel more comfortable and willing to communicate with their parents and health care professionals about their health. Several elements emerged that will allow further improvements in the design and development of the messages used in this study as well as the creation of future campaigns.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".