Prevalence of Social Isolation in Community-Dwelling Elderly by Differences in Household Composition and Related Factors
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to measure the prevalence of social isolation in community-dwelling elderly and related factors based on household composition differences. METHOD: We used the six-item Lubben Social Network Scale to measure social isolation in 2,000 individuals. Multiple logistic regression analysis was performed to examine factors related to social isolation with household composition after adjusting for gender and age. RESULTS: The prevalence of social isolation was 31.0% for elderly living alone and 24.1% for those living with family. For both, poor mental health and lack of social support from nonfamily members were associated with social isolation risk. For elderly living with family, low intellectual activities and poor health practice were associated with social isolation risk. DISCUSSION: This study showed high prevalence of social isolation. For prevention, promoting mental health and encouraging them to make friends may be important. For elderly living with family, promoting intellectual activities and good health practice is recommended.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it