Child Abuse and Neglect and Cognitive Function at 14 Years of Age: Findings From a Birth Cohort
Bibliographic record
Abstract
OBJECTIVE: To examine the association between child maltreatment (abuse and neglect) and long-term cognitive outcomes within a prospective birth cohort. METHODS: A birth cohort of 7223 children was recruited. Independent reports of suspected child maltreatment were confidentially linked to the longitudinal study database. The principal predictor variable was notification to the state child-protection authority for suspected maltreatment (abuse, neglect, or both). The outcome variables were scores on the Wide Range Achievement Test (WRAT) reading test and Raven's Standard Progressive Matrices (RSPM), completed at 14 years of age. Multivariate regression analysis was used to adjust for potential confounders. RESULTS: A total of 3796 subjects completed either the WRAT or RSPM. There was a higher loss to follow-up among children who had been reported to the state as suspected victims of maltreatment. After controlling for a range of possible confounders and modifiers, notification to the state for child maltreatment (abuse, neglect, or both) was associated with a lower score on both the WRAT (mean difference: -4.4 when the SD is 15 [95% confidence interval: -6.3 to -2.5]) and RSPM (mean difference: -4.8 when the SD is 15 [95% confidence interval: -6.7 to -2.9]). Both reported abuse and neglect were independently associated with lower reading ability and perceptual reasoning. CONCLUSIONS: Both child abuse and child neglect are independently associated with impaired cognition and academic functioning in adolescence. These findings suggest that both abuse and neglect have independent and important adverse effects on a child's cognitive development.
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.
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 | 0.001 |
| 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".