Effect of Life-space on Quality of life of Older Adult in Chinese Communities: the Chain Mediating Role of Social Support and Subjective Well-being
Bibliographic record
Abstract
Abstract OBJECTIVE To explore the factors influencing the quality of life of older adult by assessing their current life-space, and to examine the mechanisms mediating the effects of social support and Subjective Well-being on the quality of life in older adults’ life-space.METHODS This study surveyed 311 older adults with the Chinese version of the Life Space Assessment, Generic Quality of Life Inventory-74, Memorial University of Newfoundland Scale of Happiness, and Social Support Scale.RESULTS The results of Pearson correlation analysis showed a two-way correlation between life-space, quality of life, social support, and Subjective Well-being in older adults (r = 1.141, 0.164, 0.294, 0.304,0.447, 0.597, P < 0.001), life-space significantly positively predicted the quality of life of older adults (β = 0.294, t = 5.399, P < 0.001); the analysis of mediating effects showed that social support and Subjective Well-being mediated the chain effect between life-space and quality of life in older adults.CONCLUSION In addition to having a direct impact on older individuals' quality of life, their life-space can also have an indirect impact through social support and Subjective Well-being.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".