Perceived Social Integration Predicts Engagement and Responsiveness to Positive Events: Test of Age Moderation
Bibliographic record
Abstract
Abstract Social Integration has important implications for health and well-being during adulthood. Being socially integrated might be an important resource that helps people to regularly engage in daily positive events. With older age, this resource might become increasingly important. However, being well socially integrated might also mean that people are certain that they experience more positive events in the future and thus, respond with less positive affect to any given positive event. We examined perceived social integration as a predictor of engagement and responsiveness to positive events using data from the National Study of Daily Experiences 2. 1904 adults (Mean age = 56.25, min = 33, max = 84) reported their daily positive affect and daily positive events during 8 consecutive days of telephone interviews. Perceived social integration was assessed at baseline. Adults higher in social integration experienced daily positive events more frequently (b = 0.01, SE = 0.003, p < .001), but showed less of an increase in positive affect on days with more-than-usual positive events (b = -0.003, SE = 0.001, p = .030). These models controlled for the Big Five personality traits, purpose in life, demographic variables and same-day occurrence of stressors. Age did not moderate the present associations. The present findings imply that social integration might be an important contributor to experiencing more positive events across adulthood. Being better socially integrated might also lead to responding with less positive emotions to any given positive event.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".