An international survey of allied health & nursing professionals during the COVID‐19 pandemic: Perspectives on facilitators of & barriers to care
Bibliographic record
Abstract
BACKGROUND: Allied health and nursing professionals (AHNP) are integral members of transplant teams. During the COVID-19 pandemic, they were required to adapt to changes in their clinical practices. The goal of the present study was to describe AHNP perceptions concerning the impact of the pandemic on their roles, practice, and resource allocation. METHODS: An online survey was distributed globally via email by the International Pediatric Transplant Association to AHNP at transplant centers from September to December 2020. Responses to open-ended questions were collected using an electronic database. Using a thematic analysis approach, coding was conducted by three independent coders who identified patterns in responses, and discrepancies were resolved through discussion. RESULTS: The majority of respondents (n = 119) were from North America (78%), with many other countries represented (e.g., the United Kingdom, Europe, Australia, New Zealand, South Africa, and Central and South America). Four main categories of impacts were identified: (1) workflow changes, (2) the quality of the work environment, (3) patient care, and (4) resources. CONCLUSIONS: Participants indicated that the pandemic heightened existing barriers and resource challenges frequently experienced by AHNP; however, the value of team connections and opportunities afforded by technology were also highlighted. Virtual care was seen as increasing healthcare access but concerns about the quality and consistency of care were also expressed. A notable gap in participant responses was identified; the vast majority did not identify any personal challenges connected with the pandemic (e.g., caring for children while working remotely, personal stress) which likely further impacted their experiences.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".