From Risky Behavior to Health Risk: Continuity Across Two Generations
Bibliographic record
Abstract
The purpose of this study was to determine the impact of childhood aggression and social withdrawal on adolescent health risk behaviors and adult health outcomes, and to examine the transfer of health risk to preschool offspring. This was a prospective, longitudinal, and intergenerational study of 114 mothers from disadvantaged neighborhoods, who were identified in childhood as being highly aggressive and/or withdrawn or with low scores on these 2 behavioral risk dimensions, and their preschool offspring aged 1 to 6 years old. The health histories of mothers (adolescent health risk behavior, health during pregnancy, current symptoms) and target children were taken during structured interviews conducted at home. Regression analyses tested the relationship between maternal childhood risk status and subsequent health outcomes, and these were followed by structural equation modeling of a proposed intergenerational pathway. Maternal childhood aggression predicted current health risk behaviors (e.g., daily cigarette smoking), whereas maternal childhood social withdrawal was not associated with maternal health risk at the time of testing. Mothers who had high scores on both aggression and withdrawal were more likely to engage in adolescent health risk behavior, which was directly related to health problems in preschoolers (even after controlling for covariates, such as neonatal health status and sex). In summary, there are distinct health trajectories for women who are highly aggressive and socially withdrawn in childhood, with implications for women's long-term health. Specifically, aggression in girls is likely to lead to health risk behaviors that may also place the next generation at risk for pediatric illness. Results are interpreted in terms of the health-hostility link, best known in adult men and intergenerational models.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".