Increasing Vaccination Awareness for Italian Primary Care Pediatricians: Game Design and Usability Study
Bibliographic record
Abstract
Background: Invasive meningococcal disease has a high fatality rate and can lead to severe long-term health issues. In Europe, serogroup B meningococcal disease (MenB) accounts for over half of invasive meningococcal disease cases. In Italy, MenB vaccination is recommended for all newborns, but the uptake is below the Ministry of Health Vaccination Plan target (uptake: 80.91%; target: 90%). Objective: A vaccine-based digital educational tool, Meningioca, was designed to increase primary care pediatricians' (PCPs') knowledge on the value and proper timing of MenB vaccination and to support communication of this value to parents. Methods: Meningioca was developed using Articulate, an authoring software, and released via the TalentLMS online platform. Players engaged in a sequence of activities and mini-games, taking on the role of a PCP and progressing through 7 modules. Each module corresponds to a different age group and follows a fixed sequence of topics, simulating typical discussions that might occur during health checks for each specific age group. At the launch, members of the Italian Federation of PCPs were invited to play the game via an email link and rated the game based on aspects such as overall enjoyment, the difficulty of modules, and usefulness of the game as a teaching tool. Results: Between March 2023 and May 2024, 471 PCPs accessed Meningioca, completing 1206 modules and 482 hours of learning. Meningioca received a mean rating of 4.4/5 (5 being the highest score), with many participants noting that they would recommend Meningioca to a colleague. "Communicating with the parent" and "health checks" were voted as participants' favorite module topics; "general culture" and "child growth and development" were voted as the most difficult. At the end of Module 3, 75% (n/N=50/67) of players agreed that Meningioca was a teaching tool to refresh and strengthen knowledge to a high or very high extent. Conclusions: User feedback from Meningioca's first year suggests that the game is enjoyable and a potentially valuable learning tool for increasing PCPs' knowledge on vaccination.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".