Impact of cognitive impairment on activities of daily living among older adults of North India
Bibliographic record
Abstract
Background: Older persons are at risk of developing cognitive impairment, often considered a precursor to more severe conditions, such as dementia or Alzheimer's disease. Cognitive impairment among older adults is one of the most rapidly growing burdens, especially in developing countries. Aim: To assess the impact of cognitive impairment on activities of daily living (ADL) among older adults. Materials and Methods: A cross-sectional descriptive study was conducted among 135 older adults visiting a selected tertiary care centre in Uttarakhand (India) during December 2020, recruited using total enumerative sampling. Data were collected using standardized and validated tools that consisted of socio-demographic information, Hindi Mental Status Examination, and Everyday Abilities Scale for India. Data were analyzed using SPSS version 23, including descriptive (frequency, percentage, mean, and median) and inferential statistics (Chi-square test, binary logistic regression). Results: The results with pooled analysis have shown that 30% of the older adults had mild cognitive impairment, 9% had moderate cognitive impairment, and 61% had normal cognition. About 16% of the older adults' ADL were affected. The statistically significant predictors for cognitive impairment were age group 80 years [odds ratio (OR) = 36.21; 95% confidence interval (CI) = 6.23-210.59], Muslim religion (OR = 6.26; 95% CI = 1.12-34.93), and middle-class families (OR = 11.95; 95% CI = 1.84-77.78). Conclusion: A considerably large proportion of the older adults had cognitive impairment, which further impacted activities of daily living. There is an urgent need to develop geriatric mental health services across all hospitals in the region.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".