Cognitive function and its determinants in elderly Indonesians residing in long-term care: Insights from a cross-sectional study
Bibliographic record
Abstract
Background Multiple medical conditions arising from reduced physical and physiological functioning, including cognitive decline, manifest in older persons. This study aims to examine the relationship between cognitive function and associated risk factors in older persons living in long-term care facilities in Indonesia. Methods This study involved 350 elderly individuals residing in long-term care institutions. A cross-sectional design utilizing an analytical survey methodology was implemented. Data were gathered via interviews employing a demographic questionnaire and the Montreal Cognitive Assessment (MoCA). Statistical analysis was conducted using SPSS (version 23). Results Univariate analysis demonstrated significant correlations between cognitive performance and gender, ethnicity, level of education, medical history, subjective memory issues, smoking habits, alcohol consumption, dietary intake of fruits and vegetables, and employment history (p < 0.05). Higher education (OR = 0.69, 95% CI: 0.56–0.84) and reduced subjective memory complaints (OR = 0.29, 95% CI: 0.20–0.44) correlated positively with enhanced cognitive function, but alcohol intake (OR = 6.79, 95% CI: 2.42–19.1) correlated with impaired cognitive function. Conclusions the level of education, subjective memory complaints, and alcohol intake are substantially correlated with cognitive performance in older persons residing in long-term care facilities. Evaluating demographic characteristics in elderly individuals can assist healthcare professionals in the early detection of cognitive impairment, facilitating prompt interventions in long-term care environments.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".