Assessment of Health Level and Socio-Economic Characteristics of People Working in the Shipbuilding Industry: A Control Group Study
Bibliographic record
Abstract
INTRODUCTION: The health level of the population and the way people perceive it has been associated with their physical and mental health, as well as with their social and occupational characteristics. PURPOSE: The comparative assessment of mental and health level in shipbuilding industry workers and general population and its relationship to social and economic parameters. METHODS: A group of one hundred men working in the shipbuilding industry aged 51.8±8.2 years old and a control group of one hundred men of the general population aged 51.1±6.4 were studied. All participants completed the General Health Questionnaire - 28 and Fagerstrom test and a form with demographic, occupational and economic status characteristics. The statistical software SPSS 17.0 was used for data analysis. RESULTS: Twenty-six percent of the general population and 47% of men working in the shipbuilding industry assessed their health as moderate/poor. Higher median values of anxiety and depressive symptomatology were observed in individuals characterizing their health as moderate/poor (p<0.001), their work as physically too demanding and in individuals with high dependency on smoking (p<0.05). With regard to the parameter of physical complaints, people working in the shipbuilding industry, non-active employees and those with comorbidities were found more burdened in relation to the general population (p<0.05). Depressive disorders were more common in those stating that their economic situation had been significantly deteriorated and in individuals with chronic diseases, which also showed reduced social functioning (p<0.05). CONCLUSIONS: Health level and its individual dimensions are both associated with health self-assessment and occupational and economic status. The coexistence of chronic diseases and smoking dependence affects emotion and social functioning of individuals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.051 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".