EARLY-LIFE ADVERSITY, LATER-LIFE MENTAL HEALTH, AND RESILIENCE RESOURCES: A LONGITUDINAL BIRTH COHORT ANALYSIS
Bibliographic record
Abstract
Robust and persistent links between early-life adversities and later-life mental distress have previously been observed. Individual and social resources are associated with greater mental health and resilience. This study aimed to test these resources as moderators and mediators of the association between childhood psychosocial adversity and later-life mental distress. Participant data came from the Medical Research Council National Survey of Health and Development, a nationally-representative birth cohort study. The General Health Questionnaire-28(GHQ-28) captured mental distress at ages 53,60-64, and 68–69. An eight-item cumulative psychosocial adversity score was created(0,1,2,≥3 adversities). Individual(i.e. childhood cognition, childhood self-organisation, education, occupational status, physical activity), social(i.e. social support, neighbourhood cohesion) resources were examined as mediators and moderators of CPA and GHQ-28 in longitudinal multilevel models.Greater adversity was associated with an average GHQ-28 score increase of 0.017, per unit adversity(β=0·017, p<0·001, 95% CI 0·011, 0·022). Lower mental distress was associated with higher levels of physical activity, occupational status, education, childhood cognition, self-organisation, social support, and neighbourhood cohesion. There was no evidence that resources moderated the relationship between GHQ-28 and adversity. All resources, save for physical activity and occupational status, partly mediated this relationship. Individual and social resources were associated with lower mental distress. They did not modify, but partly mediated the association between childhood adversity and adult mental distress. Social support was the most important mediator, suggesting that interventions to promote greater social support may offset psychosocial adversities experienced in childhood to foster better mental health in older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".