The specifics of the physiological stress of the population in self-isolation due to the COVID-19 pandemic
Bibliographic record
Abstract
Introduction. The COVID-19 pandemic has forced national governments to take measures to prevent the spread of coronavirus. Self-isolation as one of the forms of protection against infection with viral diseases has led to an increase in physiological stress. The purpose of the study is to identify the specifics of the physiological stress of the population in self-isolation due to the COVID-19 pandemic. Material and methods. The study involved 638 students (average age - 23.38 years) undergraduate, specialist and graduate programs of full-time and part-time forms of analysis who went online during the period of self-isolation via Skype to participate in training sessions. Questionnaires were used: “What stress are you experiencing?” (P. Legeron), “Inventory of stress symptoms” (T. Ivanchenko), neuropsychic stress questionnaire (T.A. Nemchin), Toronto alexithymia scale (G.J. Taylor, D. Ryan, R.M. Bagby). Mathematical and statistical data processing - K. Pearson’s correlation criterion and Chaddock’s table. Results. Both the average level of physiological stress (6.74) and its components with a high connection were revealed: severity, increase, duration and frequency of neuropsychic stress (0.84, 0.86, 0.76, 0.86); disturbed sleep and wakefulness (0.82); negative sensations of the activity of the cardiovascular system (0.79), respiratory organs (0.80); pain and temperature sensations (0.73 and 0.75); drop in muscle tone (0.81); physical discomfort (0.84); increased susceptibility to external stimuli (0.87); decreased physical activity (0.79). Discussion. The results of studies by domestic and foreign doctors and psychologists confirm the need for diagnostics, prevention and correction of all types of stress conditions and levelling of physiological stress. Conclusion. The revealed specificity of physiological stress (pain in different parts of the body, dizziness and headaches, poor sleep, stiffness of movements, difficulty in breathing, an increase in the amount of food, coffee, cigarettes, fatigue, heart palpitations and physical stress) provides a basis for the management of primary and secondary prevention of general, physiological and emotional stress with the involvement of doctors, physiologists and psychologists.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".