Association of Cognitive Function, Depression, and Social Engagement with Quality of Life among Community-Dwelling Elderly in West Jakarta, Indonesia
Bibliographic record
Abstract
Background: As Indonesia’s elderly population grows, quality of life (QoL) has become a critical indicator of healthy aging. Evidence regarding the influence of cognitive function, depression, and social engagement on QoL remains inconsistent and is often limited to institutionalized elderly. This study examined these associations among community-dwelling elderly in an urban setting.Methods: A cross-sectional study was conducted at PUSAKA Kebon Jeruk, West Jakarta, from March to November 2023. Ninety-eight participants aged ≥60 years were selected using simple random sampling. Cognitive function was assessed using the Montreal Cognitive Assessment–Indonesian version (MoCA-INA), depression using the Geriatric Depression Scale (GDS), social engagement using the Social Disengagement Index, and QoL using the WHO Quality of Life–Brief Version (WHOQOL-BREF). Data were analyzed using Chi-square, Fisher’s exact, and multivariate logistic regression.Results: Most respondents were female (71.4%), aged 60–74 years (74.5%). The majority demonstrated normal cognitive function (63.3%), good social engagement (90.8%), and no depression. Overall QoL satisfaction was high, particularly in the social relationship (71.4%) and environmental domains (90.8%). Bivariate analysis showed associations between education, cognitive function, social engagement, gender, depression and specific QoL domains (p<0.05). Multivariate analysis identified gender as the strongest predictor of the environmental QoL (OR=5.63, p=0.025), education for social relationship (OR=2.99, p=0.020), and depression for general health perception (OR=3.16, p=0.041).Conclusions: Cognitive function, depression, education, and social engagement are key determinants of QoL among community-dwelling elderly. Community-based interventions focusing on mental health, cognitive stimulation, and social participation may improve QoL and support healthy aging.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".