A Qualitative Approach to Understanding Canadian Healthcare Workers’ Use of Coping Strategies during the COVID-19 Pandemic
Bibliographic record
Abstract
Throughout the COVID-19 pandemic, healthcare workers (HCWs) have been exposed to highly stressful situations, including increased workloads and exposure to mortality, thus posing a risk for adverse psychological outcomes, including acute stress, moral injury, and depression or anxiety symptoms. Although several reports have sought to identify the types of coping strategies used by HCWs over the course of the pandemic (e.g., physical activity, religion/spirituality, meditation, and alcohol), it remains unclear which factors may influence HCWs' choice of these coping strategies. Accordingly, using a qualitative approach, the purpose of the present study was to gain a deeper understanding of the factors influencing HCWs' choice of coping strategies during the COVID-19 pandemic in Canada. Fifty-one HCWs participated in virtual, semi-structured interviews between February and June 2021. Interview transcripts were analysed through an inductive thematic approach, yielding two primary themes. First, HCWs described an ongoing shift in their approach to coping depending on their mental "bandwidth", ranging from "quick fix" to more "intentional effort" strategies to engage in proactive strategies to improve mental health. Second, many HCWs identified various barriers to desired coping strategies during the pandemic, including the preponderance of pandemic- and other circumstantial-related barriers. The findings from this study offer a unique understanding of the factors influencing HCWs' choice of coping strategies under novel and increased stress. This knowledge will be central to developing appropriate forms of support and resources to equip HCWs throughout and after the pandemic period, and in mitigating the potential adverse mental health impacts of this period of prolonged stress and potential trauma.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.023 | 0.014 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".