Healthy lifestyle of a scientist as a factor for professional longevity and efficiency
Bibliographic record
Abstract
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.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".