A Qualitative Analysis of the Functions of Primary Care Nurses in <scp>COVID</scp> ‐19 Vaccination
Bibliographic record
Abstract
AIM: To describe vaccination roles of primary care nurses during the COVID-19 pandemic in Canada. DESIGN: This analysis was part of a larger mixed-methods case study. METHODS: We conducted semi-structured qualitative interviews from May 2022 to January 2023 with primary care nurses across four provinces: British Columbia, Ontario, Newfoundland and Labrador, and Nova Scotia. We asked participants to describe their roles during various stages of the pandemic, facilitators and challenges encountered and possible roles that nurses could have played. We used thematic analysis and analysed codes relevant to vaccination. RESULTS: We interviewed a total of 76 nurses and identified four key functions of primary care nurses' roles in COVID-19 vaccination: (1) education, (2) vaccine administration, (3) outreach and (4) advocacy. Themes outlined nurses' roles with respect to patient education, addressing vaccine hesitancy, partaking in vaccination roles outside of regular primary care practice and supporting accessibility in COVID-19 vaccination. Specific tasks varied by nursing professions. CONCLUSION: Primary care nurses fostered trust through existing patient-provider relationships to enhance roles and activities related to education, outreach and advocacy in COVID-19 vaccination. Some COVID-19 vaccine-related roles were more easily integrated into primary care, whereas others competed with routine primary care roles. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Findings highlight the vital contributions of primary care nurses towards COVID-19 vaccination efforts in Canada. Leveraging nursing expertise can enhance future pandemic response efforts and improve patient care by addressing barriers to vaccination and promoting equitable access to vaccination services. IMPACT: This study addresses a knowledge gap by describing the vaccination-related roles of primary care nurses during the pandemic. Findings illustrate that nurses demonstrated adaptability through their engagement in vaccine education, administration, outreach and advocacy. This research informs resource allocation, policy development and workforce planning for future vaccination efforts during a pandemic response. REPORTING METHOD: The authors have adhered to the Standards for Reporting Qualitative Research (SRQR) guidelines included in the Empirical Research Qualitative reporting method. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. WHAT DOES THIS PAPER CONTRIBUTE TO THE WIDER GLOBAL CLINICAL COMMUNITY?: Provides insight into the pivotal roles of primary care nurses during the COVID-19 vaccination efforts in Canada, highlighting their diverse contributions towards education, vaccine administration, outreach and advocacy. Offers implications for future pandemic planning by informing resource allocation, policy development and workforce planning for vaccination efforts.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".