Space Meets Time: Integrating Temporal and Contextual Influences on Mental Health in Early Adulthood
Bibliographic record
Abstract
The integration of temporal life course perspectives and current social context perspectives is considered as a framework for the understanding of mental health differences in early adulthood, a formative stage in the development of long-term mental health differences. Using data from the National Survey of Children and a cross-nested random effects model to simultaneously assess the effects of current and past neighborhood, the authors find a lagged effect of childhood neighborhood socioeconomic disadvantage on early adult mental health, while accounting for initial mental health status. This lagged effect also explains the apparent (bivariate) effect of current neighborhood. Four hypotheses are assessed to explain the lagged effect of neighborhood: contextual continuity, mental health continuity, life course stress accumulation, and ambient chronic stress in the neighborhood. Support is found for a cumulative mediating effect of both life course stress and ambient neighborhood stress as children grow up; together, these variables entirely explain the lagged effect of early neighborhood. Findings suggest the need for a more temporal life course approach to the specification of social context effects in general, focusing on the history of social contexts that individuals live in and move through. Temporal-contextual perspectives also encourage a focus on theoretical models that can differentially locate formative contextual influences at different stages in the life course.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".