The effect of spiritual care on spiritual well-beingand quality of life in diabetic patients: a clinical trial
Bibliographic record
Abstract
Background.Diabetes negatively affects patients' quality of life and increases the use of spirituality as a coping mechanism.spiritual well-being is regarded as one of the basic concepts for coping with problems caused by this disease.Objectives.This study was conducted to determine the effect of spiritual care on spiritual well-being and quality of life in patients with type-2 diabetes.Material and methods.This randomized clinical trial was conducted on 90 eligible patients with type-2 diabetes visiting a diabetes clinic in Shiraz in southern Iran.Patients were selected by systematic random sampling and divided into the intervention and control groups by block randomization.The intervention group received six sessions of spiritual interventions, and the control group received routine care.Data was collected using the spiritual well-being (SWB) and diabetes quality of life (DQoL) questionnaires, which were completed before and one month after the intervention.The data was analyzed in SPSS-22, using descriptive and inferential statistics, and p < 0.05 was considered significant.Results.In the intervention group, the mean score of the DQoL (54.04 ± 2.3 vs 39.38 ± 4.8; p < 0.001) and SWB (107 ± 10.3 vs 91.7 ± 9.2; p < 0.001) was significantly higher than the control group after the intervention.In dimensions of DQoL and SWB, significant differences were also seen between the two groups (p < 0.001). Conclusions.The development and implementation of holistic care programs in conjunction with spiritual care programs can be beneficial for diabetic patients and help improve their spiritual well-being and quality of life.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".