Diabetes Self-Care Activities (Diet & Exercise) and Adherence to Treatment: A Hospital –Based Study among Diabetic Male Patients in Taif, Saudi Arabia
Bibliographic record
Abstract
Diabetes mellitus is a complex disorder that requires constant adherence to certain lifestyle measures and medication to achieve good glycaemic control. The main aim of this study was to measure adherence to self- care practices (diet, exercise and medication) among diabetic patients and to identify predicators of adherence. A hospital-based study was conducted in King Abdul Aziz Specialized Hospital, Taif, KSA during June – October 2013. Convenient method of sampling was adopted, whereby all adult (> 18 years) male diabetic patients were recruited. Data was collected through face-to-face interview method using structured questionnaire. Data was processed using the software Statistical Package for Social Science (SPSS) (Version 21). Overall 378 patients were eligible; 191 (50.5%) > 50 years old and nearly two third had secondary or university education. Overweight and obese patients constituted more than two third of the respondents. Generally adherence to diet, exercise was found to be low. Multivariate analysis showed that only presence of other diseases {adjusted OR 2.8 (1.3-6.0), P = 0.011} and marital status {adjusted OR 3.4 (1.0-11.7), P = 0.049} were found to be significantly associated with adherence to diet.Patients’ age was the only predicator for patients’ commitment to practicing exercise {adjusted OR 4.7(1.3-17.8), P = 0.020)}. Non adherence to medication was found to 80.6 % (n=305). In conclusion non-adherence to the studied self-care practices was suboptimal. Proper and continuous health education accompanied with patients’ motivation may improve patients’ adherence.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".