The Effect of Interventions Based on the Information-Motivation-Behavioral Skills Model on the Human Papillomavirus Vaccination Rate Among 11-13-Year-Old Girls in Central and Western China: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Persistent infection of high-risk human papillomavirus (HPV) can lead to cervical intraepithelial neoplasia, cervical cancer, and even death. HPV vaccination for girls aged 9-14 years can effectively prevent the occurrence of cervical cancer. Some Chinese provinces and cities have launched free HPV vaccination programs for school-age girls; however, due to the lack of supportive government policies, the high price and supply shortage of HPV vaccines, and vaccine hesitancy, some parents refuse to vaccinate their daughters. OBJECTIVE: This protocol reports the design of a randomized controlled trial (RCT) aiming to explore the efficacy of a digital HPV vaccination education intervention based on the information-motivation-behavioral skills (IMB) model in improving the HPV vaccination rate among 11-13-year-old girls in central and western China. METHODS: A multicenter intervention study based on an online applet will be conducted in December 2024, and about 750 eligible parents of 11-13-year-old girls will be assigned in a 1:1 ratio to an intervention group receiving 7-day digital HPV vaccination education based on the IMB model or a control group using non-HPV publicity materials. Free HPV vaccination pilot projects will be carried out among this population by our research team in central and western China (some parents might refuse to vaccinate their daughters). All participants will be asked to complete online questionnaires at baseline; postintervention; and 1 week, 1 month, and 3 months after the intervention. RESULTS: The primary outcome of this study will be receipt of the first HPV vaccination within 3 months. Data will be analyzed based on an intention-to-treat approach, and Stata 16.0 will be used for statistical analysis. CONCLUSIONS: This study aims to improve the HPV vaccination rate among 11-13-year-old girls and will examine the impact of a digital HPV vaccination education intervention based on the IMB model. The findings of this study may offer promising intervention measures for HPV vaccine hesitancy in low-health-resource areas in the future. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2300067402; https://tinyurl.com/v5zt4hc9. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/58873.
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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 | 0.027 | 0.024 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.052 | 0.006 |
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".