Limited effects of pre‐existing maternal antisocial behaviours on infant neurodevelopment: A pilot study
Bibliographic record
Abstract
Abstract Antisocial behaviour disorders (ABDs) are among the most costly and treatment resistant of all psychiatric syndromes. Select neurodevelopmental abnormalities have been labelled a risk factor for ABDs, but it is unknown if maternal ABDs are associated with early neurodevelopmental abnormalities. This study tested whether infants of ABD mothers had more neurodevelopmental abnormalities than mothers with no psychiatric disorder (ND). Thirty‐nine pregnant women (49% with ABDs; 51% no psychiatric disorder) were recruited from the community. Infant neurodevelopment was assessed at ≤1 and 8 weeks using the Neonatal Behavioural Assessment Scale and at 16 weeks of age using the Bayley Scales of Infant and Toddler Development‐III. There was no significant group difference at ≤8 weeks. At 16 weeks, ABD mothers rated their infants higher on the Adapted Behaviours subscale, specifically on the leisure and self‐directed scales, when corrected for substance use and socio‐economic status. This pilot study found higher maternal ratings of Adapted Behaviours at 16 weeks, which may be due to unrealistic expectations about infant development. Highlights Maternal Antisocial behaviour disorders (ABDs) do not impact early infant neurodevelopment at ≤ 8 weeks old as measured by standardized assessment. Mothers with ABDs view their infants at 16 weeks as better adapted than women without any psychiatric disorder. Specifically, mothers with ABDs reported their infants as better adapted on the leisure and self‐direction subscales of the Bayley Scales of Infant and Toddler Development‐III. This finding may be due to less knowledge about normal infant adaptive behavior.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".