Examining the Role of Social Isolation on Hospitalizations, Nursing Home Entry, and Mortality among Older Adults
Bibliographic record
Abstract
Social isolation affects a quarter of older adults in the United States, complicating efforts for Americans who wish to age at home or in the community. Social isolation is a key risk factor for adverse health outcomes and high health care costs, and is expected to have increased during COVID-19 due to social distancing efforts. However, little research has examined the impact of social isolation on health care utilization. Literature in this area tends to be conducted internationally, uses short follow-up times, measures social isolation through single-item variables, and usually does not control for both social isolation and loneliness in the same sample. No prior studies have examined the association between social isolation and nursing home entry in a United States-based sample. This dissertation includes three studies that expand knowledge on the associations between social isolation and hospitalization, nursing home entry, and mortality in a nationally-representative sample of community-dwelling Americans ages 65 and older. Data from the Health and Retirement Study were used to construct a multi-domain measure of social isolation while controlling for loneliness. The first study uses a panel data analysis to examine whether social isolation was associated with overnight hospital stays, nursing home entry, and mortality among older adults tracked between 2006 and 2018. The second study uses a time-to-event analysis to examine whether social isolation is associated with earlier time to long-term nursing home placement (residency of 100+ days) and mortality over ten years. The third study provides an exploratory, cross-sectional analysis to examine whether use of senior services moderates the association between social isolation and nursing home entry among respondents interviewed between 2010 and 2012. Results demonstrate that social isolation is significantly associated with increased nursing home entry and early mortality. Research examining the association between social isolation and health care utilization has important implications for the expansion of home and community-based services under Medicaid and billing codes to cover screening, referral, and treatment under Medicare. Future research should evaluate whether initiatives that enhance social connections in home or community-based settings are effective in offsetting nursing home entry, reducing premature mortality, and curbing health care costs for patients and payers.
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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 | 0.002 | 0.008 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".