“I think of it as planting seeds”: challenging patient-provider discussions about COVID-19 vaccination: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Vaccination has been essential in mitigating the worst effects of the COVID-19 pandemic in Canada. Healthcare providers can play a crucial role in promoting COVID-19 vaccination by discussing immunization, addressing patients' questions, and providing them with relevant information. However, some segments of the public remained hesitant towards COVID-19 vaccination during the pandemic, reflecting an information environment crowded with misinformation and political polarization. This study examines challenging clinical discussions that healthcare providers had with patients hesitant about COVID-19 vaccines. It focuses on obstacles to fruitful conversations and strategies to overcome them, which can extend into ongoing vaccine-related conversations outside a pandemic context. METHODS: Researchers conducted individual interviews with ten healthcare providers during the pandemic (January-May 2022) in the province of Manitoba, Canada. Participants were recruited using invitations distributed via professional organizations and networks. The recruited sample included primary care physicians, nurse practitioners, and a specialist provider who had recently discussed the COVID-19 vaccine with patients. Study participants were asked about their challenging conversations regarding the COVID-19 vaccine with patients and how they navigated these experiences. The resulting data were analyzed using NVivo12 to capture and organize salient themes. RESULTS: Healthcare providers reported that COVID-19 vaccines have prompted new forms of vaccine hesitancy and resistance compared to existing vaccines, particularly due to concerns about the integrity of the vaccine (e.g., vaccine novelty, ingredients) or related public policy (i.e., vaccine mandates). Providers reported a significant rise in hostility from patients who were staunchly hesitant and experienced moral injury, burnout, and an emotional toll from witnessing disregard for public health. Participants indicated that they attempted to employ motivational interviewing strategies and shared decision-making and voiced desires for further training in such approaches. Some participants found mixed success with using decision aids or used improvised strategies to facilitate discussions. CONCLUSION: Motivational interviewing and shared decision-making strategies proved valuable to healthcare providers in navigating challenging discussions, addressing/acknowledging patient concerns, and preserving relationships. Healthcare providers need to be better supported with training in these strategies and in navigating the moral/emotional/physical consequences of experiencing a global health crisis in clinical settings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".