Impact of the Novel CoronaviruS (COVID-19) on Frontline PharmacIsts Roles and ServicEs: INSPIRE Worldwide Survey
Bibliographic record
Abstract
BACKGROUND: Pharmacy has been recognized as a vital healthcare profession during the COVID-19 pandemic. The primary objective of the INSPIRE Worldwide survey was to determine the impact of COVID-19 on pharmacy practice and pharmacists' roles around the world. METHODS: A cross-sectional online questionnaire with pharmacists who provided direct patient care during the pandemic. Participants were recruited through social media, with assistance from national and international pharmacy organizations between March 2021-May 2022. The questionnaire was divided into (1) demographics, (2) pharmacists' roles, (3) communication strategies, and (4) practice challenges. The data were analyzed using SPSS 28, and descriptive statistics were used to report frequencies and percentages. RESULTS: A total of 505 pharmacists practicing in 25 countries participated. The most common role that pharmacists undertook was responding to drug information requests (90%), followed by allaying patients' fears and anxieties about COVID-19 (82.6%), and addressing misinformation about COVID-19 treatments and vaccinations (80.4%). The most common challenges were increased stress levels (84.7%), followed by medication shortages (73.8%), general supply shortages (71.8%), and inadequate staffing (69.2%). CONCLUSIONS: Pharmacists within this study were significantly impacted by the COVID-19 pandemic and took on new or adapted roles (e.g., providing COVID-specific information, managing patients' emotions, and educating on public health measures) to meet the needs of their communities. Despite, the significant challenges (e.g., increased stress, supply chain challenges, addressing misinformation, and staffing shortages) faced by pharmacists, they continued to put their patients' needs first and to provide pharmacy services.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".