The Detrimental Consequences of Overestimating Future Health in Late Life
Bibliographic record
Abstract
OBJECTIVES: Although forecasting a positive future can be adaptive, it may not be when expectations are unmet. Our study examined whether such inaccurate expectations about future health status (overestimation) were maladaptive for older adults who commonly experience late life declines in physical functioning. METHOD: We analyzed data from the nationally representative German Aging Survey (DEAS; 1996-2011; n = 2,539; age range 60-85 years) using multilevel growth models that assessed the influence of inaccurate health expectations on older adults' physical functioning over a 9-year period. RESULTS: Overestimating future health status predicted reduced day-to-day physical functioning when age, gender, and self-rated health were controlled. A Time × Overestimation interaction indicated that the negative effects of overestimation on physical functioning became more pronounced over the 9-year period. DISCUSSION: Results suggest that repeatedly unmet health expectations may undermine motivational resources and accelerate late life declines in physical functioning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".