Long-term Cognitive, Psychological, and Health Outcomes Associated With Child Abuse and Neglect
Bibliographic record
Abstract
Potential long-lasting adverse effects of child maltreatment have been widely reported, although little is known about the distinctive long-term impact of differing types of maltreatment. Our objective for this special article is to integrate findings from the Mater-University of Queensland Study of Pregnancy, a longitudinal prenatal cohort study spanning 2 decades. We compare and contrast the associations of specific types of maltreatment with long-term cognitive, psychological, addiction, sexual health, and physical health outcomes assessed in up to 5200 offspring at 14 and/or 21 years of age. Overall, psychological maltreatment (emotional abuse and/or neglect) was associated with the greatest number of adverse outcomes in almost all areas of assessment. Sexual abuse was associated with early sexual debut and youth pregnancy, attention problems, posttraumatic stress disorder symptoms, and depression, although associations were not specific for sexual abuse. Physical abuse was associated with externalizing behavior problems, delinquency, and drug abuse. Neglect, but not emotional abuse, was associated with having multiple sexual partners, cannabis abuse and/or dependence, and experiencing visual hallucinations. Emotional abuse, but not neglect, revealed increased odds for psychosis, injecting-drug use, experiencing harassment later in life, pregnancy miscarriage, and reporting asthma symptoms. Significant cognitive delays and educational failure were seen for both abuse and neglect during adolescence and adulthood. In conclusion, child maltreatment, particularly emotional abuse and neglect, is associated with a wide range of long-term adverse health and developmental outcomes. A renewed focus on prevention and early intervention strategies, especially related to psychological maltreatment, will be required to address these challenges in the future.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".