Understanding the Needs of Geriatric Rehabilitation Care
Bibliographic record
Abstract
Background: With the increasing age, the body undergoes several physical and psychiatric changes; it is important to address the healthcare management apprehensions among the elderly and promote geriatric rehabilitation care both socially and economically. Objective: To evaluate the need for rehabilitation amongthe geriatric population living in Pakistan. Design: Cross-sectional study Place and Duration of Study: Department of Medicine, Liaquat National Hospital, Karachi from 1st January 2020 to 30th June 2020 Methodology: One hundred and three geriatric subjects aged between 65 to 90 years were enrolled. The data were collected using a structured questionnaire designed to obtain information regarding home care and geriatric rehabilitation care. Results: Sixty (58.2%) were females and 43 (41.7%) were males. The majority were <80 years of age, 82 (79.6%). Around 52 (50.5%) subjects knew about rehabilitation care and most believed that geriatric rehabilitation care is beneficial. Sixty four (62.1%) subjects were involved in socialization once a week, 29 (28.2%) once in a month, 6 (5.8%) biannually and 4 (3.9%) marked not at all. Among all, 41% reported being isolated, and 86% were getting enough psychiatric/physical care at home. Conclusion: Although 52 (50.5%) of the study subjects reported knowing geriatric rehabilitation care, due to limited resources and economic constraints in Pakistan, we have been unable to set up centers to rehabilitate the elderly. There is a need to design and conduct rehabilitation programs to control morbidity and improve the quality of the geriatric population. Keywords: Geriatric rehabilitation care (GRC), Home care, Geriatric population
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".