Changing Trends in the Mental Health Status of Healthcare Workers at COVID-19 Wards Three Years After the COVID-19 Pandemic Outbreak in Saudi Arabia
Bibliographic record
Abstract
Sami Hamoud Alharbi,1,* Alia Mohammed Almoajel,1,* Shabana Tharkar,1 Abdullah Hamoud Alharbi,2 Khalid Almutairi,1 Hanan Abdullah Alzaidi,1 Basmah Faisal Kattan1 1Department of Community Health Science, College of Applied Medical Science, King Saud University, Riyadh, Saudi Arabia; 2Ministry of Health, Riyadh, Saudi Arabia*These authors contributed equally to this workCorrespondence: Khalid Almutairi, Department of Community Health Science, College of Applied Medical Sciences, King Saud University, Riyadh, 12372, Saudi Arabia, Email kalmutairim@ksu.edu.saBackground: The current study aimed to investigate the severity of anxiety and depression symptoms among the healthcare workers of COVID-19 wards three years after the pandemic outbreak in Saudi Arabia.Methods: An online cross-sectional survey was conducted during the fourth quarter of 2022 and early 2023 at the COVID-19 wards of public primary healthcare hospitals of the AlQassim region of Saudi Arabia. The sample included 323 healthcare workers including physicians, nurses, laboratory, and imaging personnel. The Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) questionnaires were used to collect data using the self-administered approach. The degree of severity of anxiety and depressive symptoms were the main outcome variables. Descriptive and inferential statistics were derived using Statistical Package for Social Science (SPSS) software version 28.0.Results: Three years following the outbreak of the pandemic, a transition toward a high prevalence of mild symptoms of anxiety and depression was noted. The present study reported 85.1%, 8.4%, and 6.5% mild, moderate, or moderately severe depression and 90.7%, 6.8%, and 2.5% anxiety, respectively. Depression was more common in men (t=3.009; p=0.003). Phlebotomists, x-ray and imaging personnel, and paramedics showed a strong association with symptoms of depression (t=8.36; p< 0.001) and anxiety (t= 10.325; p< 0.001). Sleep deprivation, fatigue, loss of interest, and changes in eating behavior were depressive symptoms with a high degree of severity. Anxiety symptoms that showed a high degree of severity were having trouble relaxing and getting annoyed quickly. An overall depressive and anxiety score of 16.5 and 12.8 was obtained.Conclusion: The long-term impact of the pandemic on healthcare workers in COVID-19 wards includes the persistence of depression and anxiety symptoms. These findings highlight the need for implementing mental health wellness programs and coping strategies that reduce work stress and improve the quality of life.Keywords: healthcare workers, Saudi Arabia, depression, anxiety, COVID-19
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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 | 0.000 | 0.001 |
| 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".