Prevalence of psychological distress in nurses, physicians and leaders working in intensive care units during the COVID-19 pandemic: a national one-year follow-up study
Bibliographic record
Abstract
OBJECTIVE: To report and compare psychological distress as symptoms of anxiety, depression and post-traumatic stress among intensive care units' (ICU) nurses, physicians and leaders at 12 months after the baseline survey (spring 2020), during the COVID-19 pandemic in Norway. Furthermore, to analyse which baseline demographic and COVID ICU-related factors have a significant impact on psychological distress at 12 months. DESIGN: Prospective, longitudinal, observational cohort study. SETTING: Nationwide, 27 of 28 hospitals with COVID ICUs in Norway. PARTICIPANTS: Nurses, physicians and their leaders. At 12 month follow-up 287 (59.3%) of 484 baseline participants responded. PRIMARY AND SECONDARY OUTCOME MEASURES: Symptoms of anxiety and depression using the Hopkins Symptoms Checklist-10 (HSCL-10). Symptoms of post-traumatic stress using the post-traumatic stress disease checklist for the Diagnostic and Statistical Manual of Mental Disorders 5 (PCL-5).Demographics (included previous symptoms of anxiety and depression) and COVID ICU-related factors (professional preparations, emotional experience and support) impacting distress at 12 months. RESULTS: Psychological distress, defined as caseness on either or both HSCL-10 and PCL-5, did not change significantly and was present for 13.6% of the participants at baseline and 13.2% at 12 month follow-up. Nurses reported significantly higher levels of psychological distress than physicians and leaders. Adjusted for demographics and the COVID ICU-related factors at baseline, previous symptoms of depression and fear of infection were significantly associated with higher levels of anxiety and depression at 12 months. Previous symptoms of depression, fear of infection and feeling of loneliness was significantly associated with more symptoms of post-traumatic stress. CONCLUSION: One year into the COVID-19 pandemic 13.2% of the ICUs professionals reported psychological distress, more frequently among the nurses. Fear of infection, loneliness and previous symptoms of depression reported at baseline were associated with higher levels of distress. Protective equipment and peer support are recommended to mitigate distress. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov. Identifier: NCT04372056.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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; 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".