Predictors of Physical and Mental Health-Related Quality of Life in Tunisian Workers With Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to identify demographic, medical, and occupational determinants of health-related physical and mental quality of life (QoL) of workers with type 2 diabetes (T2D) in Tunisia. METHODS: A cross-sectional study was performed among a sample of workers with T2D. QoL and functioning at work were assessed through the World Health Organisation Quality of Life-Bref (WHOQOL-BREF) and the work-role functioning questionnaires, respectively. RESULTS: Predictors of impaired physical health were high body mass index ( P = 0.001; β = -4; 95% CI = [-12; -2.3]), high number of weekly worked hours ( P = 0.001; β = -3.2; 95% CI = [-4.5; 0.8]), and macroangiopathic complications ( P = 0.001; β = -4.4; 95% CI = [-13; -2.1]). Psychological domain decreased with high body mass index ( P = 0.001; β = -3.6; 95% CI = [-4.1; -0.03]) and low socioeconomic status ( P = 0.001; β = -3.9; 95% CI = [-7.6; -0.27]). High functioning at work increased both physical ( P = 0.001; β = 5.3; 95% CI = [3.1; 5.8]) and mental well-being ( P = 0.001; β = 4.7; 95% CI = [1.2; 4.9]). CONCLUSIONS: Improving the QoL of workers with T2D through intervention programs that involve reducing overweight/obesity, chronic diabetic complications, and hazardous work environments is warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".