Geographic Distance and Social Isolation Among Family Caregivers Providing Care to Older Adults
Bibliographic record
Abstract
Abstract Family caregiving is associated with social isolation, but the role of geographic distance between caregiver and receiver in caregiving experience is unclear with mixed research findings. This study examined the relationship between geographic distance and caregiver social isolation (CSI), and explored the interaction between geographic distance and caregiving intensity in association with CSI. Based on the Ecological Model of Caregiver Isolation, hierarchical linear regression and ANCOVA analyses were applied to conduct data analysis with the 2012 Canadian General Social Survey (N=2,881). Caregivers living a short distance from receivers reported the lowest CSI than coresident, moderate and long distance caregivers. Being involved in higher intensity caregiving as the primary caregiver, undertaking more caregiving tasks, and providing care more frequently resulted in higher CSI scores. Additionally, long and moderate distance caregivers reported greater CSI than coresident and short distance caregivers only when providing higher intensity caregiving. Geographic distance is a salient contextual factor affecting CSI, and longer distance creates environmental barriers for caregiving provision. Employing a granulated measure of geographic distance positioned within an ecological framework facilitates an understanding of the nuanced association between geographic proximity and CSI. Furthermore, the identified interactive effects between geographic distance and caregiving intensity on CSI further reveal the complexity of caregiving experience. The findings are relevant for programs supporting caregivers in different contexts, especially physical distance.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".