Self-Reported Mental Health Problems Among Adults Born Preterm: A Meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CONTEXT: Preterm birth increases the risk for mental disorders in adulthood, yet findings on self-reported or subclinical mental health problems are mixed. OBJECTIVE: To study self-reported mental health problems among adults born preterm at very low birth weight (VLBW; ≤1500 g) compared with term controls in an individual participant data meta-analysis. DATA SOURCES: Adults Born Preterm International Collaboration. STUDY SELECTION: = 1512). DATA EXTRACTION: We obtained individual participant data from 6 study cohorts and compared preterm and control groups by mixed random coefficient linear and Tobit regression. RESULTS: Adults born preterm reported more internalizing (pooled β = .06; 95% confidence interval .01 to .11) and avoidant personality problems (.11; .05 to .17), and less externalizing (-.10; -.15 to -.06), rule breaking (-.10; -.15 to -.05), intrusive behavior (-.14; -.19 to -.09), and antisocial personality problems (-.09; -.14 to -.04) than controls. Group differences did not systematically vary by sex, intrauterine growth pattern, neurosensory impairments, or study cohort. LIMITATIONS: Exclusively self-reported data are not confirmed by alternative data sources. CONCLUSIONS: Self-reports of adults born preterm at VLBW reveal a heightened risk for internalizing problems and socially avoidant personality traits together with a lowered risk for externalizing problem types. Our findings support the view that preterm birth constitutes an early vulnerability factor with long-term consequences on the individual into adulthood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it