EMOTION BELIEFS AND DAILY AFFECTIVE EXPERIENCES ACROSS THE ADULT LIFESPAN
Bibliographic record
Abstract
Abstract Emotion beliefs refer to the extent to which people believe emotions “should” and “can” be controlled. Importantly, past research has linked peoples’ emotion beliefs to the extent to which they utilize effective emotional regulation strategies, and psychological well-being. To our knowledge, research has yet to examine the association between emotional beliefs and affective experiences at the daily-level, and how developmental factors are associated with emotion control beliefs in adults. The present research sought to examine age differences in within-person associations of daily emotion beliefs and daily positive and negative affect. To do so, we used 14-day daily diary data from an adult lifespan community sample [N = 91, age range = 19-92]. Multilevel models revealed that when younger (but not older) people endorsed higher-than-normal beliefs they “should” control their emotions they reported greater negative affect, while higher-than-normal beliefs they “can” control their emotions were associated with higher positive affect. In addition, when older (but not younger) people endorsed higher-than-normal beliefs that they “can” control their emotions they experienced greater declines in negative affect. These findings add to theory and research on emotional aging by highlighting that: 1) emotion beliefs are differentially associated with affective experience on a daily-level, and 2) these associations change across the adult lifespan.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".