Health care provider trust in vaccination: a systematic review and qualitative meta-synthesis
Bibliographic record
Abstract
BACKGROUND: Vaccine hesitancy is a growing issue globally amongst various populations, including health care providers. This study explores the factors that influence vaccine hesitancy amongst nurses and physicians. METHODS: We performed a qualitative meta-synthesis of 22 qualitative and mixed-method studies exploring the factors that may contribute to vaccine hesitancy amongst nurses and physicians. We included all articles that mentioned any aspect of trust concerning vaccination, including how trust may influence or contribute to vaccine hesitancy in nurses and physicians. RESULTS: Our findings revealed that vaccine hesitancy amongst nurses stemmed predominantly from two factors: distrust in health authorities and their employers, and distrust in vaccine efficacy and safety. Both nurses and physicians had a precarious relationship with health authorities. Nurses felt that their employers and health authorities did not prioritize their health over patients' health, provided inaccurate and inconsistent vaccine information, and were mistrustful of pharmaceutical company motives. Like nurses, physicians were also skeptical of pharmaceutical company motives when it came to vaccination. Additionally, physicians also held doubts regarding vaccine efficacy and safety. CONCLUSIONS: The relationship health care providers or their patients have with health authorities and other providers regarding vaccination serves as unsystematic clinical experiences that may bolster vaccine hesitancy. Providing accurate and tangible information to emphasize the safety and efficacy of vaccines to health care providers may help address their specific concerns that may ultimately increase vaccine uptake.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.062 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".