Impact of the COVID-19 pandemic on the experiences of hepatology nurses in Canada
Bibliographic record
Abstract
Background: In March 2020, COVID-19 was declared a global pandemic, directly affecting the management of liver disease. Aims: This study aimed to gain insights on the impact of COVID-19 on Canadian hepatology nursing care practices, on the personal stress levels of nurses and on strategies employed in the delivery of care. Methods: The 129 members of the Canadian Association of Hepatology Nurses (CAHN) were invited to an online survey, with a mixed-methods design consisting of 22 quantitative and seven optional qualitative questions. Findings: Of CAHN members, 41 (32%) responded to the survey; 90% reported moderate-to-severe negative impacts on practice settings, while 68% reported hepatitis C testing and treatment delays. The qualitative data identified six main themes within two broad categories: barriers in access to care and strategies employed by nurses. Conclusions: Participants identified that COVID-19 had negative impacts on themselves personally and on their delivery of healthcare to patients. Hepatology nurses led positive changes through collaboration with community partners and mobilisation of outreach work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".