Bibliographic record
Abstract
Maintaining a healthy lifestyle is one of the main conditions for health preservation. The paper examines subjective predictors of commitment to a healthy lifestyle as assessed by health workers. The article is based on a secondary analysis of data from the study «Study of the Human Resources Potential of Moscow Healthcare» conducted in 2023 by the State Budgetary Institution «Research Institute for Healthcare Organization and Medical Management of the Moscow Department of Healthcare» - NIIOZMM. 1,449 specialists - doctors and nurses of medical organizations of the capital were surveyed. Most of the study participants (67%) answered that their lifestyle is rather healthy, a quarter (26%) - unhealthy, 6% could not give an answer. Employees with secondary specialized education are less likely to note commitment to a healthy lifestyle (59%), and those who have completed residency - more often (74%). Commitment to a healthy lifestyle is more often demonstrated by employees working in medical organizations that carry out activities to form a healthy lifestyle among the population (78%). The main predictors of refusal to lead a healthy lifestyle based on logistic regression were identified as the perceptions of health workers about the conditions that hinder health behavior: lack of confidence in the benefits of a healthy lifestyle, lack of support from others, the presence of psychological problems, stress at work and at home. On the contrary, employees committed to a healthy lifestyle consider it important for the population to trust medical organizations and health workers. They are ready to bear responsibility for the healthy lifestyle of the population along with the state and the people themselves.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".