Network relationship between cognitive function and quality of life in community-dwelling older adults: an observational study from Beijing
Bibliographic record
Abstract
Objective: This observational study aims to comprehensively explore the network relationship and mechanism of action between cognitive function and quality of life among community-dwelling older adults aged 60 and above in Beijing. Methods: The research encompassed a cohort of 323 older adults individuals residing in the community in Beijing. Data were collected from January to July 2024 using convenience sampling. Cognitive function was evaluated using the Chinese adaptation of the Montreal Cognitive Assessment (MoCA), while quality of life was assessed through the Medical Outcomes Study 36-Item Short-Form Health Survey version 2 (SF-36v2). Cognitive assessment involved seven dimensions, namely visuospatial/executive function, naming, attention, language, abstraction, delayed recall, and orientation. Concurrently, quality of life was assessed across eight dimensions: physical functioning, role physical, bodily pain, general health, vitality, social functioning, role emotional, and mental health. Network analysis graphs were developed to investigate the interrelationships among variables, identify central nodes, and evaluate stability. Results: In the network, the dimensions of social functioning, role-physical, physical functioning, general health, vitality, orientation, and language showed high centrality strength. The dimensions of physical functioning, role-physical, language, and orientation exhibited strong closeness and betweenness. There were strong associations between role-physical and social functioning, physical functioning and role-physical, and vitality and mental health. The centrality stability coefficients for strength, closeness, and betweenness were 0.672, 0.672, and 0.285, respectively. Conclusion: The network structure was stable, indicating that dimensions such as social functioning, role-physical, and physical functioning play pivotal roles influencing cognitive function in community-dwelling older adults. Orientation and language were the most representative dimensions of cognitive function and may serve as important targets for interventions aimed at improving cognitive function and subsequently enhancing QoL. These findings provide practical guidance for community health interventions. Future research should explore causal relationships and develop scalable strategies to support aging populations.
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 | 0.009 | 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 | 0.001 |
| 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".