Associations Among Individuals’ Perceptions of Future Time, Individual Resources, and Subjective Well-Being in Old Age
Bibliographic record
Abstract
OBJECTIVES: Perceptions of future time are of key interest to aging research because of their implications for subjective well-being. Interestingly, perceptions about future time are only moderately associated with age when looking at the second half of life, pointing to a vast heterogeneity in future time perceptions among older adults. We examine associations between future time perceptions, age, and subjective well-being across two studies, including moderations by individual resources. METHOD: Using data from the Berlin Aging Study (N = 516; Mage = 85 years), we link one operationalization (subjective nearness to death) and age to subjective well-being. Using Health and Retirement Study data (N = 2,596; Mage = 77 years), we examine associations of another future time perception indicator (subjective future life expectancy) and age with subjective well-being. RESULTS: Consistent across studies, perceptions of limited time left were associated with poorer subjective well-being (lower life satisfaction and positive affect; more negative affect and depressive symptoms). Importantly, individual resources moderated future time perception-subjective well-being associations with those of better health exhibiting reduced future time perception-subjective well-being associations. DISCUSSION: We discuss our findings in the context of the Model of Strength and Vulnerability Integration.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".