Incidence of depression, anxiety and sleep disorders in healthcare personal after the onset of Covid 19 pandemic – a survey based study.
Bibliographic record
Abstract
INTRODUCTION: Coronavirus disease 2019 (COVID-19) was first reported in Wuhan, China in December 2019. It was declared a global pandemic by WHO. There are 77.8 million reported cases of and 1.7 million deaths due to COVID-19 in the world at the time of writing this article. The main symptoms of COVID‐19 are fever, cough, fatigue, dyspnea, sore throat, headache and gastrointestinal disturbances. It has caused increased psychological impact to the society, particularly in healthcare personnel (HCPs). We aimed to assess the incidence of depression, anxiety and insomnia in healthcare personnel after the onset of COVID-19 Pandemic. MATERIAL AND METHODS: This was a survey-based study. A questionnaire was shared through emails and social media. The study instruments used were PHQ9 for depression, GAD7 for anxiety and Insomnia Severity Index for Insomnia. Data was collected from April 2020 to October 2020. RESULTS: The data was analyzed using IBM SPSS software version 26.0. The sample size was 312. A total of 26 (39.25%) respondents were single, 169 (52.64%) were male, 158 (49.2%) were between 20 and 29 years of age, 151 (47.04%) of respondents were doctors and 22 (6.8%) were nurses. Psychological impact was significantly more in paramedics and nurses. Severe psychological impact was seen in 24 (7.34%) of healthcare personnel. The study showed severe depression mostly in paramedics and surgical sub specialties while mild and moderate depression was more commonly reported by anesthesiologists, dentists and pathologists. The study also showed that people who had previous histories of depression, reported an increase in the severity of their symptoms as compared to those with no previous histories. CONCLUSIONS:COVID-19 pandemic has created fear and uncertainty. The health care workers and other front line workers who are at a greater risk of exposure and contraction of COVID-19 are subject to extensive physical and psychological trauma. The purpose of this study is to highlight the intensity and incidence of depression, anxiety and insomnia in health care personnel and to emphasize the need to support the mental health of these front line workers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".