Dietary and lifestyle habits of patients with type 2 diabetes in Subotica
Bibliographic record
Abstract
The activities of the health care service in the control of diabetes and the improvement of glucoregulation of patients are primarily focused on lifestyle modification. The goal of this study was to review the recommendations in the field of adequate nutrition and lifestyle and to assess the health behavior of patients with type 2 diabetes in Subotica. The research was conducted in the form of a cross-sectional study in February 2017 at the Diabetes Counseling Center of the Health Center in Subotica, Serbia. The study included 114 patients with type 2 diabetes. The research instrument consisted of a customized survey questionnaire. Only a third of the patients actually consumed at least five meals a day, that was suggested as part of the treatment. Three-quarters of patients always prepared their own meals, but 41% of them never read the declarations about the ingredients of the food they consumed. Twenty percent of patients did not know how to assemble a healthy plate and what low-carbohydrate foods were. Two-thirds of patients used dietary supplements. A relatively small number, one-quarter of patients, consumed alcoholic beverages and 22 patients were active smokers. More than half of the patients exercised lightly, although 68% of them were dissatisfied with their body weight. We identified some deficiencies in the health behavior and lifestyle of people with diabetes. There is a recommendation to repeat the information on proper nutrition and the importance of physical activity in achieving ideal health and optimal glucoregulation during the educational work with patients.
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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 | 0.000 | 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 | 0.001 | 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) | 0.001 | 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".