Occupational Effects on the Family Well-being of Dentists in Lithuania: A Survey of Dentists
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Work-related commitments unavoidably interfere with the dentist's everyday life. Therefore, the objective of our study was to assess the impact that a dentist's occupation might have on the family well-being. MATERIAL AND METHODS: The questionnaire was sent to all (N=2449) licensed dentists registered in the Lithuanian Dental Association (response rate, 68.2%). The data were analyzed by means of multiple logistic regression analysis. RESULTS: Most dentists reported difficulties in reconciliation of their professional activities and family life, i.e., insufficient time to spend with a family, necessity to reduce family leisure activities, neglected duties to the family, limited time for hobbies, and work-related anxiety and nervousness at home. These hazardous occupational effects were mainly related to long working hours, which negatively affected all areas of family life. CONCLUSIONS: Occupational hazards, particularly long working hours of dental practitioners, had negative effects on all areas of the dentist's family life. Although dentists frequently faced difficulties in reconciliation of their professional activities and their family interests, in general, they had quite a harmonious family life. The findings suggest that the focus should be on finding the ways to reduce working hours in order to facilitate the reconciliation of a successful dental practice and family life. Additionally, there might be other effective means, e.g., to cope with stress or to develop better working and leisure time management skills.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".