Humans not heroes: Canadian emergency physician experiences during the early COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: The pandemic has upended much clinical care, irrevocably changing our health systems and thrusting emergency physicians into a time of great uncertainty and change. This study is a follow-up to a survey that examined the early pandemic experience among Canadian emergency physicians and aimed to qualitatively describe the experiences of these physicians during the global pandemic. The study was conducted at a time when Canadian COVID-19 case numbers were low. METHODS: The investigators engaged in an interview-based study that used an interpretive description analytic technique, sensitised by the principles of phenomenology. One-to-one interviews were conducted, transcribed and then analysed to establish a codebook, which was subsequently grouped into key themes. Results underwent source triangulation (with survey data from a similar period) and investigator-driven audit trail analysis. RESULTS: A total of 16 interviews (11 female, 5 male) were conducted between May and September 2020. The isolated themes on emergency physicians' experiences during the early pandemic included: (1) disruption and loss of emergency department shift work; (2) stress of COVID-19 uncertainty and information bombardment; (3) increased team bonding; (4) greater personal life stress; (5) concern for patients' isolation, miscommunication and disconnection from care; (6) emotional distress. CONCLUSIONS: Canadian emergency physicians experienced emotional and psychological distress during the early COVID-19 pandemic, at a time when COVID-19 prevalence was low. This study's findings could guide future interventions to protect emergency physicians against pandemic-related distress.
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 | 0.002 | 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 | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.368 | 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".