“ <i>I don’t think there’s a point for me to discuss it with my patients”</i> : exploring health care providers’ views and behaviours regarding COVID-19 vaccination
Bibliographic record
Abstract
BACKGROUND: Health care providers' knowledge and attitudes about vaccines are important determinants of their own vaccine uptake, their intention to recommend vaccines, and their patients' vaccine uptake. This qualitative study' objective was to better understand health care providers' vaccination decisions, their views on barriers to COVID-19 vaccine acceptance and proposed solutions, their opinions on vaccine policies, and their perceived role in discussing COVID-19 vaccination with patients. METHODS: Semi-structured interviews on perceptions of COVID-19 vaccines were conducted with Canadian health care providers (N = 14) in spring 2021. A qualitative thematic analysis using NVivo was conducted. RESULTS: Participants had positive attitudes toward vaccination and were vaccinated against COVID-19 or intended to do so once eligible (two delayed their first dose). Only two were actively promoting COVID-19 vaccination to their patients; others either avoided discussing the topic or only provided answers when asked questions. Participants' proposed solutions to enhance COVID-19 vaccine uptake in the public were in relation to access to vaccination services, information in multiple languages, and community outreach. Most participants were in favor of mandatory vaccination policies and had mixed views on the potential impact of the Canadian vaccine-injury support program. CONCLUSIONS: While health care providers are recognized as a key source of information regarding vaccines, participants in our study did not consider it their role to provide advice on COVID-19 vaccination. This is a missed opportunity that could be avoided by ensuring health care providers have the tools and training to feel confident in engaging in vaccine discussions with their patients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".