Childhood maltreatment and prospectively observed quality of early care as predictors of antisocial personality disorder features
Bibliographic record
Abstract
Abstract Few studies have evaluated the separate contributions of maltreatment and ongoing quality of parent–child interaction to the etiology of antisocial personality features using a prospective longitudinal design. One hundred twenty low‐income young adults (aged 18–23) were assessed for extent of antisocial personality disorder (ASPD) features on the Structured Clinical Interview for Diagnosis (M.B. First, R.L. Spitzer, M. Gibbon, & J.B.W. Williams, 1997) for the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (American Psychiatric Association, 1994) Axis II, for presence of maltreatment on the Conflict Tactics Scale (M.A. Straus, S.L. Hamby, D. Finkelhor, D.W. Moore, & D. Runyan, 1998), Traumatic Experiences Scale (L. Dutra, J.F. Bureau, B. Holmes, A. Lyubchik, & K. Lyons‐Ruth, 2009), and Adult Attachment Interview (C. George, N. Kaplan, & M. Main, 1984), and for referral in infancy to parent–infant clinical services. Fifty‐six of these families had been studied longitudinally since the first year of life. In infancy, attachment disorganization and disrupted mother–infant interaction were assessed; in middle childhood, disorganized‐controlling attachment behaviors were reliably rated. In kindergarten and second grade, behavior problems were assessed by teacher report. In cross‐sectional analyses, maltreatment was significantly associated with ASPD features, but did not account for the independent effect of early referral to parent–infant services on ASPD features. In longitudinal analyses, maternal withdrawal in infancy predicted the extent of ASPD features 20 years later, independently of childhood abuse. In middle childhood, disorganized attachment behavior and maladaptive behavior at school added to prediction of later ASPD features. Antisocial features in young adulthood have precursors in the minute‐to‐minute process of parent–child interaction beginning in infancy.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".