The Relationship between Demographic Variables and Diabetes Self-Management in Diabetic Patients in Amman City/Jordan
Bibliographic record
Abstract
BACKGROUND: Diabetes is a chronic disease that requires routine and complicated self care. Although self care can be managed by most diabetes patients, there are many variables that may make diabetes self-management difficult. AIM: The study examined the relationship between clients' demographic variables and diabetes self-management in diabetic clients in Amman city/Jordan. METHOD: The data were collected through a self-completed questionnaire developed by the researchers and combined with the perceived diabetes self-management scale (PDSMS). The sampling of the investigation comprised 178 diabetes clients from Amman city/Jordan. FINDINGS: There was proportional little relationship between income level and diabetes self management, and reversely proportional low relationship between duration of diabetes and diabetes self management. Other variables had no relationship with diabetes self management. CONCLUSION: The demographic variables related to diabetes self-management in this study are income level and duration of diabetes. As income level increases, diabetes self-management become better, and the longer the duration of diabetes, the worse is diabetes self-management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".