Enhancing Public Health Communication Regarding Vaccine Trials: Design and Development of the Pan-European VACCELERATE Toolkit
Bibliographic record
Abstract
BACKGROUND: The pan-European VACCELERATE network aims to implement the first transnational harmonized and sustainable vaccine trial Volunteer Registry, being a single entry point for potential volunteers of large-scale vaccine trials across Europe. This work exhibits a set of harmonized vaccine trial-related educational and promotional tools for the general public, designed and disseminated by the pan-European VACCELERATE network. OBJECTIVE: This study primarily aimed to design and develop a standard toolkit to increase positive attitudes and access to trustworthy information for better access and increased recruitment to vaccine trials for the public. More specifically, the produced tools are focused on inclusiveness and equity, and are targeting different population groups, including underserved ones, as potential volunteers for the VACCELERATE Volunteer Registry (older individuals, migrants, children, and adolescents). The promotional and educational material is aligned with the main objectives of the Volunteer Registry to increase public literacy and awareness regarding vaccine-related clinical research or trials and trial participation, including informed consent and legal issues, side effects, and frequently asked questions regarding vaccine trial design. METHODS: Tools were developed per the aims and principles of the VACCELERATE project, focusing on trial inclusiveness and equity, and are adjusted to local country-wise requirements to improve public health communication. The produced tools are selected based on the cognitive theory, inclusiveness, and equity of differently aged and underrepresented groups, and standardized material from several official trustworthy sources (eg, COVID-19 Vaccines Global Access; the European Centre for Disease Prevention and Control; the European Patients' Academy on Therapeutic Innovation; Gavi, the Vaccine Alliance; and the World Health Organization). A team of multidisciplinary specialists (infectious diseases, vaccine research, medicine, and education) edited and reviewed the subtitles and scripts of the educational videos, extended brochures, interactive cards, and puzzles. Graphic designers selected the color palette, audio settings, and dubbing for the video story-tales and implemented QR codes. RESULTS: This study presents the first set of harmonized promotional and educational materials and tools (ie, educational cards, educational and promotional videos, extended brochures, flyers, posters, and puzzles) for vaccine clinical research (eg, COVID-19 vaccines). These tools inform the public about possible benefits and disadvantages of trial participation and build confidence among participants about the safety and efficacy of COVID-19 vaccines and the health care system. This material has been translated into several languages and is intended to be freely and easily accessible to facilitate dissemination among VACCELERATE network participant countries and the European and global scientific, industrial, and public community. CONCLUSIONS: The produced material could help fill knowledge gaps of health care personnel, providing the appropriate future patient education for vaccine trials, and tackling vaccine hesitancy and parents' concerns for potential participation of children in vaccine trials.
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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 | 0.152 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".