MIND OVER MATTER: THE REQUIRED PHYSICAL AND SOCIAL ACTIVITIES FOR COGNITIVE ALERTNESS AMONG PAKISTANI GERIATRIC POPULATION
Bibliographic record
Abstract
Background and Objective: Aging is influenced by culture, individual experiences, and socio-demographic characteristics along with societal expectations. Cognitive functioning and activity level in geriatric population may alter their participation in daily life activities thus this study aims to explore the required physical and social activities for cognitive alertness among Pakistani Geriatric population. Methodology: An observation based study of 169 aging individuals who performed on MoCA for cognitive functioning and interviewed on IPAQ for duration of physical activity in everyday life. Results: It is an observational study, conducted among the geriatric population of different areas of Pakistan. A total number of 169 individuals participated out of which 59 % were males and 40 % were females with a majority of the population 74% falling between 65-75 years of age. It was found that 59% of the male and only 19% of the female had 22 score on MoCA for cognitive functioning and these individuals were practicing physical activities such as brisk walk for 3 days a week for more than 40 minutes and are involve at least once a week in social activities. Conclusion: The research finding concluded that physical activities and social gathering both has impact on cognitive function of geriatric population to participate actively in daily activities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".