Examining the COVID-19 pandemic and its impact on social work in health care
Bibliographic record
Abstract
Summary This qualitative study examined the COVID-19 pandemic as experienced by healthcare-based social workers in relation to practice, and personal and professional impacts of providing care in this context, with recommendations for pandemic preparedness and response. A total of 12 focus groups were convened between June 2020 and March 2021, comprising 67 hospital social workers across multiple hospitals and other care facilities in western Canada. Findings Based on an Interpretive Description approach, themes emerged reflecting practice shifts; increased work and changing roles; imposed restrictions; problems in communication and decision-making; distress, fear, and demoralization; and co-existing silver linings amid challenges. Applications The COVID-19 pandemic has substantially impacted social workers and their delivery of service. Addressing concerns through proactive responsiveness, both during and beyond the pandemic, are important in nurturing patient-centered care and a supported workforce. Along with that of interdisciplinary colleagues in health care, social workers’ practice has been profoundly impacted by the COVID-19 pandemic. This article explores the experiences of social workers in healthcare settings during the COVID-19 pandemic.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.018 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".