Older Adults’ Satisfaction with Hospital Medical Care as a Senior-Trusted Healthcare from Iran
Bibliographic record
Abstract
Objectives: Assessing the satisfaction of older adults with hospital services is essential for improving healthcare facilities. In addition, the quality of healthcare services for older adults enhances their satisfaction and trust at medical centers. Therefore, this study aimed to investigate the satisfaction of older adults with hospital care at Tabriz university of medical sciences. Design: A cross-sectional study. Setting(s): Imam Reza, Sina, Shohada, and Nikookari hospitals. Participants: Older adult patients. Outcome Measures: Satisfaction of older adults with hospital services. Results: The median age of the samples was 72 (67–81) years, and 211 (54.6%) out of 387 individuals were men. The overall satisfaction of older adults with the services in all hospitals was 91.4%. The highest patient satisfaction was the hospital staff’s behavior (95.2%), particularly their respectful behavior (94.2%). The multivariable analysis demonstrated that referral type and potential caregiver among older people plays a significant role in their satisfaction. Conclusions: Our findings confirmed the high satisfaction of older people with the services received in medical science hospitals in Tabriz. To further enhance their experience, it is recommended that patient waiting times, an essential factor affecting satisfaction, be reduced while improving comfort and communication facilities for older people. These changes could remarkably increase the overall satisfaction of this group with hospital services, guiding future improvements in healthcare.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".