Volunteering in Young Adulthood: Complex Associations With Later Health and Well-Being Outcomes
Bibliographic record
Abstract
PURPOSE: in volunteering from adolescence to young adulthood are associated with subsequent health and well-being outcomes in adulthood. DESIGN: Longitudinal cohort study. SETTING: National Longitudinal Study of Adolescent to Adult Health. SUBJECTS: U.S. adults from Wave IV (2008/2009; N = 12,234) and Wave V (2016-2018; N = 9,971). MEASURES: Any volunteering and nine types of volunteering (independent variables) and 41 health and well-being outcomes (dependent variables) using an outcome-wide approach with multiple linear-, logistic-, and generalized linear regressions. RESULTS: Volunteering in young adulthood was associated with better health behaviors (e.g., 34% decreased risk of binge drinking, 95% CI [0.54, 0.81]) and improved psychosocial and civic outcomes (e.g., lower depressive symptoms (β = -0.08, 95% CI [-0.14, -0.02]) in adulthood. Volunteering showed little evidence of associations with other health and well-being outcomes (e.g., loneliness, (β = -0.04, 95% CI [-0.09, 0.01])). Assessing volunteering by organization types showed a range of positive and negative outcomes. For example, volunteering in hospitals/nursing homes was associated with a 36% increased risk of high cholesterol (95% CI [1.06, 1.73]) and volunteering with political clubs was associated with a 52% increased risk of an anxiety diagnosis (95% CI [1.13, 2.05]). CONCLUSION: Our findings suggest more work is needed to determine the conditions under which volunteering is health promoting and to minimize potential adverse effects associated with some types of volunteering.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".