Through the eyes of hospital-based healthcare professionals: exploring their lived experience during the COVID-19 pandemic
Bibliographic record
Abstract
OBJECTIVE: The spread of the COVID-19 virus has caused an unforeseen strain on the healthcare system and particularly on healthcare workers (HCW). In this study, 1 year after the COVID-19 pandemic began, we used photovoice, a visual photographic approach, to understand HCW needs, concerns and resilience and to determine improvement strategies aligned with the HCW-described challenges. METHODS: Using a qualitative design, HCW were recruited from a single Western Canadian hospital, voluntarily submitting a photographic image and narrative that depicts their experiences. An artist artistically enhanced the photovoice submissions, which were then displayed at the hospital-based art gallery for public display. A survey was used to collect feedback from gallery viewers. Inductive thematic analysis was completed identifying themes from the photovoice narratives and survey comments, aiding the identification of recommendations. RESULTS: There were 25 submissions, and 1281 individuals viewed the art exhibit. Six themes emerged: (1) hopeful and resilient, (2) pandemic fatigue-negative mental and physical states, (3) personal protective equipment is our armour but masks who we are, (4) human connection, (5) responsibility, preparation and obligation and (6) technology surge. According to survey results from the art exhibit, the use of photovoice was a creative method that personalised the HCW experience and validated viewers' perceptions of the difficulties faced by HCW. Ten improvement strategies that were aligned with the described challenges were identified. CONCLUSION: The ongoing COVID-19 pandemic continues to strain HCW. Photovoice has great potential in the professional clinical setting to provide unique insights that narrative language alone cannot capture. Future research exploring the longitudinal impact of COVID-19, reviewing photographs at different timepoints could be beneficial. Using this method as a creative outlet intervention and evaluating participation artistic experience may offer additional insights to further support both HCW and patients.
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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 | 0.031 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".