Community pharmacists’ roles during the closure stage of the COVID-19 pandemic in Newfoundland and Labrador, Canada: a qualitative case study
Bibliographic record
Abstract
OBJECTIVES: To explore the experiences and perspectives of community pharmacists regarding their roles during the closure stage (ie, March to May 2020) of the COVID-19 pandemic in Newfoundland and Labrador (NL), Canada. DESIGN: This qualitative case study included a document analysis and semistructured interviews with community pharmacists who provided direct patient care during the COVID-19 pandemic. The document analysis was used to develop a chronology that informed the interviews. Themes from qualitative interviews were developed through iterative cycles of data review and analysis using applied thematic analysis. Findings are presented specifically for the time period between March and May 2020, defined as the 'Closure Stage'. SETTING: Community pharmacies in NL, Canada. RESULTS: 12 community pharmacists participated in the interviews. Four themes were developed including (1) pharmacists' leadership in continuity of care, (2) pharmacists as medication stewards, (3) pharmacists as a source of COVID-19 health information and (4) the impact of COVID-19 on pharmacists' mental health and well-being. The first three themes described the key roles played by community pharmacists during the early days of the COVID-19 pandemic, including coordinating care, prescribing for common ailments, delivering medications and supplies, providing information on COVID-19 symptoms and their management, renewing chronic medications and protecting the medication supply. Unclear guidance on scope of practice, limited scope of practice, inadequate staffing and limited support from government bodies were identified as barriers to these roles. Facilitators included access to a delivery service, swift regulatory changes, reimbursement and support from colleagues and other healthcare professionals. The fourth theme is presented independently, emphasising the impact of working within the primary healthcare (PHC) system during the COVID-19 pandemic on pharmacists' mental health and well-being. CONCLUSION: Pharmacists played a critical role in the delivery of PHC services during the closure stage of the COVID-19 pandemic. The findings of this research highlight the essential elements of a strong PHC pandemic preparedness plan that is inclusive of community pharmacists, including improved communication strategies, mental health support and access to resources.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".