Cognitive function and dementia risk factors among older people in nursing homes: An observational cohort study in Medan, Indonesia
Bibliographic record
Abstract
Background: Indonesia’s rapidly aging demographic presents significant challenges, particularly in dementia among older people in resource‐limited settings, such as nursing homes. However, there are limited reports on the deterioration of cognitive function and risk factors of dementia among older people in nursing homes. Early identification of dementia is essential for timely intervention and management. Objective: This study aimed to investigate and follow up on the cognitive function and risk factors of dementia among older people living in nursing homes. Methods: An observational cohort study was conducted over 6 months (April to October 2024) involving 162 participants from government (n = 83) and private nursing homes (n = 79). Implementation of early dementia screening was carried out using the Montreal Cognitive Assessment in the Indonesian version (MoCA INA) instrument to indicate cognitive function impairment. In addition, the Self-reporting of Physical Activity Questionnaire Indonesia (SPAQ-I) was used to identify physical activity. Descriptive statistics, McNemar, Chi-square, Fisher’s Exact, Independent t-test, and multivariate regression were then used to analyze data. Results: Older individuals did not differ in terms of gender, age, education, or length of stay. However, residents of the private nursing home had significantly higher physical activity levels (t = -2.04, p = 0.040), and a greater proportion engaged in adequate activity (65.8% vs. 50.6%, χ² = 4.23, p = 0.040). Over a six-month period, cognitive function significantly declined among residents in the government nursing home (normal: p = 0.021; mild: p = 0.012; moderate: p = 0.003), whereas no significant change was observed among residents in the private nursing home. At the endpoint, mean cognitive function scores were slightly higher in the private nursing home (20.23 ± 3.45) than in the government nursing home (19.70 ± 4.39), with a very small effect size (Cohen’s d = 0.13). Multiple regression analysis revealed that older age (β = -0.396, p <0.001) and lower levels of physical activity (β = 0.163, p = 0.030) were significantly associated with lower cognitive scores. Conclusion: Dementia screening can enhance care planning for age-related cognitive impairment by enabling early identification and management. Early detection allows nurses to implement more effective care strategies. Additionally, higher physical activity levels were associated with better cognitive function, highlighting a modifiable factor that may help maintain cognitive health among older adults in nursing homes.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".