EMOTIONS AND WELL-BEING IN LATER LIFE CHILDHOOD HAPPINESS, SELF-MASTERY, AND LATER-LIFE HEALTH
Bibliographic record
Abstract
Abstract Considerable work has documented that positive childhood memories, especially childhood happiness, predict better health among young adults. However, it is not known whether growing up happy has enduring health consequences across the life course. Using two waves of the National Social Life, Health and Aging Project (2010-2011 and 2015-2016; N = 1,937), we investigate the relationship between childhood happiness and changes in physical, mental, and biological functioning in later life. Childhood happiness was retrospectively assessed using a question: “When I was growing up, my family life was always happy.” Self-rated health, depressive symptoms, and frailty over a five-year period were examined to reflect changes in functional status. Childhood SES and living arrangement were examined to assess childhood sociodemographic background. Educational attainment, family support and strain, and self-mastery were considered as potential mediators. We find that, among other childhood factors, childhood happiness significantly predicts older adult health. Specifically, childhood happiness was associated with better self-rated health and lower depressive symptoms at follow-up, net of baseline health conditions. We did not find a relationship between frailty and childhood happiness. Unlike prior work, we found no significant effect of childhood SES on the measured outcomes. Associations between childhood happiness and self-rated health and depression were mediated by psychosocial resources including self-mastery and perceived social support from family members. This implies that growing up in nurturing, cherished family environment has the potential to cultivate social relationships and build resilience which could provide an important pathway to successful aging.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".