Investigation of the Activities and Participation of Nursing Home Residents: A Pilot Study
Bibliographic record
Abstract
Purpose: This study was conducted to evaluate the activity levels and independence of the individuals residing at a nursing home and to determine their participation in activities. Material and Methods: Mini Mental State Examination (MMSE), Geriatric Depression Scale, Canadian Occupational Performance Measure (COPM), Functional Independence Measure (FIM) were administered to the residents. Results: The total FIM score was found 119.13±13.73. It has been found that according to COPM the mean activity performance score was 6.48±2.96; satisfaction from performance’s score was 6.08±2.92. 31 people said that the performance areas that they had the most problem were as follows: 23% walking (performance score (ps): 3.89; satisfaction score (ss): 3.80), 19% bathing (pp: 4.17; ss: 4.00), 16% performing prayer (ps: 4.1; ss: 4.6), reading book (ps:5.2; ss: 4.2), 13% reading newspaper (ps: 4.6; ss: 5.75), 9% visiting friends (ps:4; ss: 4.2), chatting (ps: 4.5; ss: 3.8), watching tv (ps: 4.7; ss: 4.7, 6% puzzle-solving (ps: 5.5; ss: 6), gardening (ps:3.5; ss: 3), travelling (ps:6; ss: 4.5, jewellery design(ps:6.5; ss: 6.5), painting (ps:5.5; ss: 7.5). conclusion: In our study, it was found that within self-care activities, bathing was the activity that bothered the nursing home residents the most. Other activities are leisure-time activities. We found the nursing home provided a good level of self-care activities, but leisure-time activities needed to be configured emphasizing an individual-centred approach
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".