Mental Health Concerns of Frontline Workers During the COVID-19 Pandemic: A Scoping Review
Bibliographic record
Abstract
OBJECTIVES: The current COVID-19 pandemic continues to have a significant impact on the mental health of frontline workers worldwide. Currently there are limited published studies addressing mental health issues in frontline workers. The objective of this scoping review is to examine the range of existing global literature on mental health issues reported in frontline workers during the COVID-19 pandemic and to understand what mitigating factors exist. METHODS: The scoping review was guided by the Levac Colquhoun and O’Brien’s adapted version of Arkey and O’Malley’s framework. We performed a comprehensive search of three databases, Pubmed, APA PsychINFO, and CINAHL, identifying 684 studies. In total, 16 original studies and 4 letters to editors were included in this review. RESULTS: Of the original studies, 13 were published in China, and the remaining 3 in Italy, Turkey, and Iraq; all letters to editors were published in China. Sources of stress reported in frontline workers across studies included direct contact with COVID-19 patients, isolation, putting loved ones at risk, facing life and death decision making with COVID-19 patients, uncertainty with COVID-19 disease control, limited personal protective equipment, time spent thinking about COVID-19, limited staff/resources/pay, burnout, and stigma. Mental health symptoms and outcomes reported in frontline workers were fear, stress, anxiety, depression, insomnia, burnout, and psychological distress. CONCLUSION: Findings demonstrate the immediate need to increase mental health awareness and resources at an individual and system wide level. Mental health programs need to be catered towards each unique workplace to provide the necessary resources for frontline workers.
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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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".