Predictive Relationship between Depression and Quality of Life among Patients with Type II Diabetes in Karachi-Pakistan
Bibliographic record
Abstract
The aim of the present study was to explore the relationship between depression and quality of life among individuals with type II diabetes. On the basis of literature review it was hypothesized that a) depression will predict quality of life among patients with diabetes b) there will be negative relationship between depression and quality of life among patients with diabetes. A purposive sample of 96 people with diabetes type II diagnosed by physicians was selected from different hospitals and different organizations of Karachi, Pakistan. Their age range was between 25 to 75 years (mean age = 41.2, SD = 12.3) and they belonged to three major socioeconomic status i.e. low, middle and high. To measure the depression Salma Siddiqui Depression Scale was used and quality of life was assessed through WHO Quality of life BREF-Urdu Version. Descriptive statistics and linear regression were applied for the analysis of data. Findings revealed that there was moderately significant negative relationship between Depression and Quality of Life (p
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".