Symptoms of attention‐deficit/hyperactivity disorder in first‐time expectant women: Relations with parenting cognitions and behaviors
Bibliographic record
Abstract
The relationship between maternal symptoms of attention-deficit/hyperactivity disorder (ADHD) and parenting cognitions and behaviors was studied in 86 first-time expectant women. Women high on ADHD symptoms were less likely to be married, less likely to have obtained at least some university education, and less likely to report that they wanted to get pregnant at the time they became pregnant. As predicted, ADHD symptoms were positively correlated with symptoms of anxiety and depression, and predicted less positive prenatal expectations regarding the infant and the future maternal role and lower maternal self-efficacy. Contrary to predictions, ADHD did not predict any incremental variance in maternal stressful life events or social support. Symptoms of ADHD were negatively correlated with attendance at recommended prenatal checkups, but were unrelated to other behaviors during pregnancy. Findings suggest that even prior to any contact with their infant, women with ADHD symptoms have maladaptive cognitions regarding their expectations of motherhood and parenting abilities. As a result, they may benefit from early interventions that focus on attenuating the potential negative effects that these maladaptive cognitions might have on the mother-infant relationship and later developmental outcomes for their children.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".