Impact of Activity Preferences on Cognitive Skills and Life Satisfaction in Elderly
Bibliographic record
Abstract
Purpose: The study was designed to determine the activity preferences and performance levels of elderly and examine the impact of the activities on cognitive status and satisfaction with life. Materials and Method: 50 elderly (m=23; f=27) were included. Demographic information were recorded. Activity preferences and involvement were determined by Canadian Occupational Performance Measure (COPM), cognitive levels were determined by Lowenstein Occupational Therapy Cognitive Assessment (LOTCA-G) and life satisfaction was determined by Satisfaction with Life Scale (SWLS). Results were compared by statistical analysis. Results: There is a strong relation between activity performance and activity satisfaction level (p<0,001). As the activity performance and satisfaction level increase, satisfaction with life increases as well (p<0,01). In individuals who perform productive activities, satisfaction with life and activity performance were found to be more successful. It was determined that there is no relation among cognitive status, activity performance, activity satisfaction and satisfaction with life (p>0,05). It was determined that the cognitive status of the males who perform leisure activities is more successful than the females (p< 0,001). Conclusion: In our study, it is determined that elderly individuals should be supported in self-care and leisure activities. Client-centered occupational therapy assesments and interventions may help elderly to improve life satisfaction. Further studies must be designed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".