Effect of Maternal Adverse Childhood Experiences on the Stress Level of Mothers of Children Diagnosed with Attention-Deficit/Hyperactivity Disorder: A Case-Control Study
Bibliographic record
Abstract
Attention deficit-hyperactivity disorder (ADHD) is a psychiatric disorder that affects children’s ability to function and could be carried into adolescence and adulthood with a prevalence of approximately 66-85%. However, few studies have assessed the association between prenatal maternal stress and ADHD in children in Jeddah, Saudi Arabia. This study aimed to assess the impact of adverse childhood experiences on parents of children with ADHD. This was a case-control study with a sample size of 180 mothers of children with ADHD diagnosed in a child psychiatric clinic at King Abdulaziz University Hospital from 2015 to 2020. We recruited 94 mothers of non-ADHD children for the control group. We investigated stress with a validated questionnaire using the Perceived Stress Scale and Adverse Childhood Experience questionnaire and considered ADHD symptoms as determined using the Conners’ Parent Rating Scale–revised (CPRS-R). The one-way ANOVA revealed a significant association (p=0.002) between multiple early-life traumas and elevated adult stress. Mothers with ADHD children affected severely by past traumas displayed significantly higher stress (p<0.05), unlike the control group, which showed no notable link between PSS levels, ACE questionnaire scores, or the effect of past experiences on maternal health (p>0.05). Of note, mothers of children with ADHD had higher levels of stress than control participants. Boys had a higher prevalence (67.8%) of ADHD than girls.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".