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Record W4295136226 · doi:10.51793/os.2022.25.8.002

Healthy lifestyle of a scientist as a factor for professional longevity and efficiency

2022· article· ru· W4295136226 on OpenAlexaboutno aff
Е.В. Макарова, А.А. Костров

Bibliographic record

VenueЛечащий врач · 2022
Typearticle
Languageru
FieldMedicine
TopicHealthcare Systems and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)Quarter (Canadian coin)Interpersonal communicationPsychologyCognitionLongevityGerontologyMedicineClinical psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

A study of the commitment of Russian scientists to a healthy lifestyle and an assessment of behavioral and social risk factors for reducing their professional activity was fulfilled. A cross-sectional study of a single-stage section of 213 researchers from state scientific institutions in Moscow was carried out. At the age of 23 to 78 years (mean age = 45.48 ± 15.33 years), 116 women, 97 men. It was found that in the group of Russian researchers about a quarter of the respondents did not follow the principles of a healthy lifestyle well enough (25.34%). The main problem was low physical activity, identified in 79.3% of the respondents, as well as: non-compliance with the principles of rational nutrition, primarily among scientists with a teaching load; low stress management skills among doctors who combine clinical practice with science; Difficulties in interpersonal relationships in people engaged only in scientific work. In addition, a high frequency of violations and problems that can lead to a decrease in professional effectiveness has been recorded. In 9.85%, probable cognitive impairments were detected, and not associated with the age of the scientist, in 3.28% there were signs of senile asthenia, in 2.34% – senile depression. Two-thirds lived in a sub-depressive state (74.6%). Only one fifth of the respondents (19.71%, n = 42) had no cognitive impairment, no asthenic syndrome, no depression. It was concluded that risk factors for reducing professional efficiency among scientists, such as: low physical activity, poor nutrition, low stress management skills, subdepressive state, are modifiable and can be corrected, which will lead to a lesser occurrence of asthenia and cognitive impairment. It is necessary to develop and implement programs for the prevention, early diagnosis and correction of risk factors among researchers in order to maintain their effectiveness in their work and prolong their professional longevity.

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 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.392
Teacher spread0.354 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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