Hopelessness in New York State Physicians During the First Wave of the COVID-19 Outbreak
Bibliographic record
Abstract
BACKGROUND: In the United States, New York State's health care system experienced unprecedented stress as an early epicenter of the coronavirus disease 2019 (COVID-19) pandemic. This study aims to assess the level of hopelessness in New York State physicians working on the frontlines during the first wave of the COVID-19 outbreak. METHODS: A confidential online survey sent to New York State health care workers by the state health commissioner's office was used to gather demographic and hopelessness data as captured by a brief Hopelessness Scale. Adjusted linear regression models were used to assess the associations of physician age, sex, and number of triage decisions made, with level of hopelessness. RESULTS: In total, 1330 physicians were included, of whom 684 were male (51.4%). Their average age was 52.4 years (SD=12.7), with the majority of respondents aged 50 years and older (55.2%). Almost half of the physician respondents (46.3%) worked directly with COVID-19 patients, and 163 (12.3%) were involved in COVID-19-related triage decisions. On adjusted analysis, physicians aged 40 to 49 years had significantly higher levels of hopelessness compared with those aged 50 years or more (μ=0.441, SD=0.152, P=0.004). Those involved in 1 to 5 COVID-19-related triage decisions had a significantly lower mean hopelessness score (μ=-0.572, SD=0.208, P=0.006) compared with physicians involved in none of these decisions. CONCLUSION: Self-reported hopelessness was significantly higher among physicians aged 40 to 49 years and those who had not yet been involved in a life or death triage decision. Further work is needed to identify strategies to support physicians at high risk for adverse mental health outcomes during public health emergencies such as the COVID-19 pandemic.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".