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The specifics of the physiological stress of the population in self-isolation due to the COVID-19 pandemic

2021· article· en· W3213020484 on OpenAlex
O.B. Polyakova, Tatyana I. Bonkalo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHealth Care of the Russian Federation · 2021
Typearticle
Languageen
FieldMedicine
TopicHuman Health and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicPopulationCoronavirus disease 2019 (COVID-19)Isolation (microbiology)PsychologyMedicineStress (linguistics)Clinical psychologyAudiologyGerontologyDemographyDiseaseInternal medicineEnvironmental healthInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.355
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it