Speaking about flexibility: Age differences in the variability and situational sensitivity of emotion regulation strategies.
Bibliographic record
Abstract
= 3.50, 61% female) reported their use of cognitive reappraisal and situation modification strategies in relation to their most stressful situation each day. They also rated the perceived controllability of these situations. Analyses revealed multidirectional age differences in the variability of strategy use: Older adults showed greater temporal variability in situation modification but less variability in cognitive reappraisal, compared to younger adults. Additionally, there were significant age differences in how situation modification strategies were adapted to the perceived controllability of stressors. The within-person correlation between stressor controllability and situation modification use was stronger in older adults than in younger adults. In contrast, no such age differences were found for cognitive reappraisal strategies. These effects remained robust even after controlling for various person- and stressor-related characteristics. Overall, our results suggest that age differences in the ability to flexibly adjust emotion regulation strategies to specific situations might depend on the strategy used. Further research should examine additional situational characteristics and emotion regulation strategies. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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) | 0.003 | 0.001 |
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".