Staff Experiences With Remote Work in a Comprehensive Cancer Center During the COVID-19 Pandemic and Recommendations for Long-Term Adoption
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic led to the rapid implementation of remote work, but few studies have examined the impact. We evaluated clinical staff experience with working remotely at a large, urban comprehensive cancer center in Toronto, Canada. METHODS: An electronic survey was disseminated between June 2021, and August 2021, via e-mail to staff who had completed at least some remote work during the COVID-19 pandemic. Factors associated with a negative experience were examined with binary logistic regression. Barriers were derived from a thematic analysis of open-text fields. RESULTS: Most respondents (N = 333; response rate, 33.2%) were age 40-69 years (46.2%), female (61.3%), and physicians (24.6%). Although the majority of respondents wished to continue remote work (85.6%), relative to administrative staff (admin), physicians (odds ratio [OR], 16.6; 95% CI, 1.45 to 190.14) and pharmacists (OR, 12.6; 95% CI, 1.0 to 158.9) were more likely to want to return on-site. Physicians were approximately eight times more likely to report dissatisfaction with remote work (OR, 8.4; 95% CI, 1.4 to 51.6) and 24 times more likely to report that remote work negatively affected efficiency (OR, 24.0; 95% CI, 2.7 to 213.0); nurses were approximately seven times more likely to report the need for additional resources (OR, 6.5; 95% CI, 1.71 to 24.48) and/or training (OR, 7.02; 95% CI, 1.78 to 27.62). The most common barriers were the absence of fair processes for allocation of remote work, poor integration of digital applications and connectivity, and poor role clarity. CONCLUSION: Although overall satisfaction with working remotely was high, work is needed to overcome barriers to implementation of remote and hybrid work models in the health care setting.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".