SP6-51 Effects of maternal history of abuse on child development at age 3
Bibliographic record
Abstract
Introduction A community sample of pregnant women participated in a randomised controlled trial of prenatal care in Calgary, Alberta between 2001 and 2004. These women were followed-up when the child was 3 years old. Longitudinal data from these studies revealed that of children who were at high risk of developmental problems, 47% had mothers with a history of abuse. The primary objective was to test the hypothesis that maternal history of abuse was associated with child development at age three. Secondary objectives were (a) to examine this association according to type (physical, emotional, sexual, and financial abuse and neglect) and (b) to examine the prevalence of types of abuse. Methods Questionnaire data from the initial study and the 3-year follow-up were used to determine the prevalence of the different types of abuse. Child development was measured using the Parents' Evaluation of Developmental Status instrument. χ2 analyses were performed to examine the relationship between these types of abuse and child development at age three. Results Of the women who answered the questions regarding abuse, 34% reported a history of abuse. Of these women, 75% experienced emotional abuse, 49% experienced physical abuse, 42% experienced sexual abuse, 16% experienced neglect, and 14% experienced financial abuse. A statistically significant relationship was observed between physical abuse (p=0.04), emotional abuse (p=0.004) and risk of child development problems at age three. Conclusion Maternal history of emotional and/or physical abuse potentially has a negative impact on child development at age three.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".