The Psychological Experience of Frontline Perioperative Health Care Staff in Responding to COVID-19: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The rapid spread of the novel coronavirus (COVID-19) has presented immeasurable challenges to health care workers who remain at the frontline of the pandemic. A rapidly evolving body of literature has quantitatively demonstrated significant psychological impacts of the pandemic on health care workers. However, little is known about the lived experience of the pandemic for frontline medical staff. OBJECTIVE: This study aimed to explore the qualitative experience of perioperative staff from a large trauma hospital in Melbourne, Australia. METHODS: Inductive thematic analysis using a critical realist approach was used to analyze data from 9 semistructured interviews. RESULTS: Four key themes were identified. Hospital preparedness related to the perceived readiness of the hospital to respond to the pandemic and encompassed key subthemes around communication of policy changes, team leadership, and resource availability. Perceptions of readiness contributed to the perceived psychological impacts of the pandemic, which were highly varied and ranged from anger to anxiety. A number of coping strategies were identified in response to psychological impacts which incorporated both internal and external coping mechanisms. Finally, adaptation with time reflected change and growth over time, and encompassed all other themes. CONCLUSIONS: While frontline staff and hospitals have rapidly marshalled a response to managing the virus, relatively less consideration was seen regarding staff mental health in our study. Findings highlight the vulnerability of health care workers in response to the pandemic and reinforce the need for a coordinated approach to managing mental health.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".