Frailty is Linked to a Lower Subjective Life Expectancy Among Korean Middle-Aged and Older Adults
Bibliographic record
Abstract
Abstract Frailty in later life can lead to an identity crisis, potentially limiting individuals’ perception of their future and opportunities. This study examines differences in subjective life expectancy (SLE) between frail and non-frail Korean middle-aged and older adults. The sample was drawn from the Wave 1 of the Korean Longitudinal Study of Aging (N = 10,254). SLE was assessed based on respondents’ perceived likelihood of surviving for another 10 to 15 years, given their current age. Frailty was measured using 33 items, including self-rated health and chronic disease diagnoses. Participants with a score of 2 or higher were classified as frail (n = 682), and those with a score below 2 as non-frail (n = 8,735). To ensure homogeneous characteristics between the two groups, we performed propensity score matching with 1:1 nearest neighbor matching. A final matched sample of 1,364 participants (M age = 73.5 years, SD = 10.0, range = 45-98; 62% female), with 682 in each group was included in the final analysis, showing no significant demographic differences. Results from a multiple linear regression analysis showed that frailty was significantly associated with lower SLE scores (B = -17.66, p < .001). Additionally, an interaction analysis indicated that the effect of age on SLE varied by frailty status (B = 0.56, p < .001). Findings suggest that frail Korean middle-aged and older adults perceive their life expectancy as lower than their non-frail counterparts. This highlights the importance of addressing frailty in older adults to support positive future outlooks.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".