Age-related and death-related differences in emotional complexity.
Bibliographic record
Abstract
The present study aimed to examine an aspect of emotional complexity as seen in covariation between retrospective judgments of positive and negative affects. We assume that individuals can experience positive affect independently of negative affect. Theories argue that emotional complexity increases in old age, but research shows mixed evidence. Additionally, emotional complexity has been shown to decrease in situations prevalent in old age, such as physical illness and disability. Integrating distinct effects of age and distance to death, we propose that emotional complexity may remain intact or even increase in old age, and yet it decreases in light of functional deterioration shortly before death. The current research examined whether emotional complexity decreases as a function of subjective perception of closeness to death (subjective survival probability) or actual closeness to death. We used 3 large-scale databases: 2 cross-sectional (SHARE, N = 17,437, mean age = 64; HRS, N = 6,032, mean age = 67) and 1 longitudinal (CALAS, N = 1,310, mean age at baseline = 83). Hierarchical multiple regressions and multilevel models showed that respondents who perceived themselves as closer to death or were actually closer to death showed lower emotional complexity (a stronger negative correlation between positive and negative affects). Age and emotional complexity were unrelated or positively related, depending on the sample. Findings remained the same after controlling for demographic characteristics, as well as physical and cognitive functioning. The results indicate that both subjective and objective closeness to death are associated with lower emotional complexity. This death-related decrease in emotional complexity is discussed within current theories of aging.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".