“You can push these conversations, but don’t push your patient away”: healthcare learner perspectives on virtual simulation games as an educational approach to address vaccine hesitancy
Bibliographic record
Abstract
Background: Vaccine hesitancy is a significant threat to public health. Healthcare providers (HCPs) can address hesitancy during routine patient conversations; however, few multidisciplinary education tools exist for HCPs to learn to engage in vaccine discussion especially considering new vaccine technologies such as mRNA vaccines. The objectives of this study were to explore HCP learners' experiences with COVID-19 vaccine communication, and qualitatively evaluate an online learning module composed of virtual simulation games (VSGs) which utilize the PrOTCT Framework for HCP vaccine communication. Methods: = 7) who participated in a larger study measuring the effectiveness of the VSGs. Using a pragmatic approach, a qualitative thematic analysis was conducted using NVivo to identify themes and subthemes. Results: A total of 22 HCP learners participated in this study and three key themes were identified. Across all three disciplines, participants expressed that (1) their prior education lacked training on how to hold vaccine conversations, resulting in uncomfortable personal experiences with patients; (2) the VSGs increased their confidence in holding vaccine conversations by providing novel tools and skills; and (3) participants also provided feedback to improve the VSGs which was implemented and supported the dissemination to all HCP professions. Conclusion: Although HCPs are a trusted source of vaccine information, participants in this study felt they received little training on how to engage in challenging conversations regarding COVID-19 vaccines. The introduction of the PrOTCT Framework and presumptive statements provided novel strategies for HCP to initiate vaccine conversations, especially considering new vaccine technologies and participants appreciated the emphasis on coping strategies and resilience. It is essential that HCP are provided both opportunities to practice managing these conversations, and tools and skills to succeed at an early point in their careers to prepare them for future roles in vaccine advocacy, delivery, and promotion.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".