Subclinical ADHD-Symptoms Are Associated with Executive-Functioning and Externalizing Problems in College Students without ADHD-Diagnoses
Bibliographic record
Abstract
This study investigated whether problem behaviors, typically associated with a clinical diagnosis of ADHD, would also be associated with subclinical ADHD symptoms within a non-clinical college sample. These are symptoms characteristic of ADHD, which are insufficient to warrant a DSM-IV diagnosis of ADHD. Self-ratings of behaviors known to be comorbid with ADHD (Oppositional-Defiant Disorder (ODD) behaviors, risk-taking, and Executive-Functioning (EF) problems) were examined as predictors of self-ratings of ADHD symptoms. Measures of ODD symptoms, risk-taking, and EF behavioral problems (related to poor management of time) significantly predicted ADHD symptoms, as measured by Barkley’s ADHD Combined Subscale. These predictors accounted for 26% of the variance. The same measures predicted symptoms of ADHD, Inattentive type, as measured by Barkley’s Inattentiveness (IA) Subscale, and accounted for 30% of the variance. For the Hyperactivity-Impulsivity Subscale (HI), the ODD measure significantly entered the equation, while the other two measures were borderline significant, accounting altogether for 10% of the variance. As hypothesized, the EF measure was the strongest predictor for IA, and the ODD measure was the strongest predictor for HI. In conclusion, problem behaviors comorbid with a formal clinical ADHD diagnosis were found to be significantly associated with subclinical ADHD symptoms within a non-clinical sample of college students, as indicated by the substantial proportion of the variance they accounted for in predicting the Barkley’s’ Combined and Inattentiveness Subscales, and to a lessor extent for the Hyperactivity/Impulsivity Subscale. This indicates that college students with ADHD symptoms may have substantial problems not only with their ADHD symptoms, but also with executive functioning and externalizing behaviors associated with these symptoms.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".