Family Ties and Older Adult Well-Being: Incorporating Social Networks and Proximity
Bibliographic record
Abstract
OBJECTIVES: This paper examines the family ties of older adults in the United States and how they are associated with mental health and social activity. We compare older adults with 4 types of family ties: adults "close" to family in proximity and social network, "kinless" older adults without a partner or children, "distanced" adults who live far from close kin, and "disconnected" older adults who do not report kin in their social network or do not report a location for some kin. METHODS: Using pooled data from the National Health and Aging Trends Study 2015-2019 for older adults aged 70 and older (N = 24,818 person-waves), we examine how family ties are associated with mental health and social activity, and whether lacking family is tied to poor well-being because older adults' needs are not being met. RESULTS: Kinless older adults and disconnected older adults have poorer outcomes (lower mental health scores and less social activity), compared to those close to their family. These findings suggest that both the presence and quality of the connection, as measured here via both location and social network, are critical for understanding which older adults are "at risk." Older adults who were not geographically proximate to their close kin (i.e., distanced) were not disadvantaged relative to those close to their families. Unmet needs do not help explain these patterns. DISCUSSION: Our results highlight that family ties are important for older adults well-being, not just through their existence but also their quality and strength.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".