Bibliographic record
Abstract
During the pandemic caused by the SARS-CoV-2 virus, healthcare workers are at the forefront of the battle undergoing not only significant physical but also emotional stress. At the same time medical workers are considered to be at high risk for the incidence of COVID-19. Staying in a state of constant emotional stress over time leads to the emergence of both mental and somatic disorders. The purpose of this article is to conduct a literature review on the principles of consistency regarding the mental health of staff members of medical institutions providing care to patients with COVID-19. A systematic literature search has been carried out, as a result of which 32 articles with reports of mental and behavioral disorders during the pandemic have been selected for analysis. The main group of disorders are disorders of the anxious-depressive spectrum. According to various sources, from a quarter to a third of medical workers have clinically significant anxiety, about a third – depression. Significant prevalence of sleep disorders in individuals providing medical care to patients with COVID-19 has also been indicated. In the long term, the expectation of an increase in the level of post-traumatic stress disorder has been indicated. The article also provides modern views on the socio-psychological effects of epidemics and pandemics. Excessive attention, especially on social media devoted to the problem of COVID-19 significantly complicates the fight against the real problem of overcoming the pandemic. It has been proven that overconcentration on problems associated with COVID-19 is a factor of the increased risk of developing generalized anxiety disorder in the end. Thus, the protection of mental health and the socio-psychological support of medical workers are some of the important directions in the fight against the coronavirus pandemic. The management of psychological crises during pandemics should be based on psycho-hygienic and psycho-preventive measures both at the level of the individual and society as a whole.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".