Chronic illness and loneliness in older adulthood: The role of self-protective control strategies.
Bibliographic record
Abstract
OBJECTIVES: This study examined whether levels of chronic illness predict enhanced feelings of loneliness in older adulthood. In addition, it investigated whether engagement in health-related self-protection (e.g., positive reappraisals), but not in health engagement control strategies (e.g., investment of time and effort), would buffer the adverse effect of chronic illness on older adults' feelings of loneliness. METHOD: Loneliness was examined repeatedly in 2-year intervals over 8 years in a longitudinal study of 121 community-dwelling older adults (Time 1 age = 64 to 83 years). In addition, levels of chronic illness, health-related control strategies, and sociodemographic variables were assessed at baseline. RESULTS: Growth-curve models showed that loneliness linearly increased over time and that this effect was observed only among participants who reported high, but not low, baseline levels of chronic illness. In addition, health-related self-protection, but not health engagement control strategies, buffered the adverse effect of chronic illness on increases in loneliness. CONCLUSIONS: Loneliness increases in older adulthood as a function of chronic illness. Older adults who engage in self-protective strategies to cope with their health threats might be protected from experiencing this adverse effect.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".