A global perspective on risk factors for social isolation in community-dwelling older adults: A systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: Older people's physical and mental health are now significantly impacted by social isolation, a major threat to public health. Our goal was to identify the connections between risk factors and social isolation among this population across various geographic areas. METHODS: Seven databases were thoroughly searched, from their inception until April 2023. Inclusion and exclusion criteria were used to choose the studies. For the included cross-sectional studies, we used the Agency for Healthcare Research and Quality (AHRQ) to assess the probability of bias, and the Newcastle-Ottawa scale for the cohort studies. The statistical analysis was performed using STATA 15 to calculate pooled odds ratios (OR) and 95% CI. RESULTS: All 3043 papers were carefully examined, and 42 satisfied the criteria for inclusion. The results indicated that multi-domain risk factors and social isolation among older persons worldwide are significantly correlated. These multi-domain risk factors included biological factors, socioeconomic factors, and psychological and behavioral factors. It is also important to note that these factors may vary from region to region. CONCLUSION: Many domain factors were linked to social isolation in older individuals living in communities throughout the world. To develop effective strategies for controlling social isolation, it is crucial to conduct assessments of social isolation risk factors in local communities.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.019 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".