Ethnic Variation in the Impact of Negative Affect and Emotion Inhibition on the Health of Older Adults
Bibliographic record
Abstract
The relations between patterns of emotional experience, emotion inhibition, and physical health have been little studied in older adults or ethnically diverse samples. Testing hypotheses derived from work on younger adults, the authors examined the relations between negative affect and emotion inhibition and that of illness (hypertension, respiratory disease, arthritis, and sleep disorder) in a sample (N = 1,118) of community-dwelling older adults from four ethnic groups: U.S.-born African Americans, African Caribbeans, U.S.-born European Americans, and Eastern European immigrants. Participants completed measures of stress, lifestyle risk factors, health, social support, trait negative emotion, and emotion inhibition. As expected, the interaction of ethnicity with emotion inhibition, and, to a lesser extent, negative affect, was significantly related to illness, even when other known risk factors were controlled for. However, the relations among these variables were complex, and the patterns did not hold for all types of illness or operate in the same direction across ethnic groups. Implications for emotion-health relationships in ethnically diverse samples are discussed.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".