Using Bifactor Twin Modeling to Assess the Genetic and Environmental Dimensionality of Adult ADHD Symptoms
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Bibliographic record
Abstract
Attention Deficit Hyperactivity Disorder (ADHD) is a common and heritable neurodevelopmental condition that has been the subject of a wealth of genetics research. Because ADHD has an early age of onset, most of this work has focused on children, meaning that less is known about the genetics of ADHD in adults. Additionally, while much research has assessed the heritability of ADHD as a general dimension, less has assessed the heritability of individual subtypes (inattention, hyperactivity) or symptoms of ADHD. It therefore remains unclear whether the genetic factors underlying ADHD symptoms conform to a unidimensional or multidimensional structure. The aim of this study was to assess the genetic and environmental dimensionality of adult ADHD symptoms. We analyzed data from 10,454 twins of the Twins Early Development Study, who provided self-reports of ADHD symptoms using the Conners scale at age 21 years. The data conformed well to a psychometric bifactor model, providing support for a general dimension of ADHD in addition to secondary dimensions for inattention and hyperactivity. However, a bifactor independent pathway twin model provided support for a general dimension only at the level of non-shared environmental effects and not additive genetic or shared environmental effects. This suggests that symptoms of ADHD cluster together under a general dimension of non-shared environmental effects, although the two subtypes of ADHD (inattention and hyperactivity) are meaningfully genetically distinct. We found the overall heritability of ADHD to be 40%, comparable with previous estimates for adult ADHD symptoms. Our results provide useful insights into the genetic and environmental architecture of specific ADHD symptoms.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it