The Adult ADHD Self-Report Scale: utility and reliability in college students with attention deficit hyperactivity disorder
Bibliographic record
Abstract
Background. Attention Deficit Hyperactivity Disorder is a debilitating condition that often persists into adulthood. The past number of decades an increased number of adults with ADHD have gained entrance into the post-secondary education section and register with college or university Disability Service Offices. There is a need to explore utility of affordable materials to gain confidence in validating the original diagnoses and potentially detect feigning. Methods. 135 college students (mean age = 24, 42% males) with ADHD were recruited from post-secondary institutions. The freely available Adult ADHD Self-Report Scale (ASRS) self-report was utilized to assess current ADHD symptomatology. The ASRS was compared to an interview (over the phone) and other-report version (filled out by a significant other) that were directly derived from the original Self-report. Results. Results showed moderate levels of congruency between ASRS-Self and Other Report (correlation = .47). Furthermore, a robust relationship was shown between the ASRS-Self and the interview version (correlation = .66). Discussion. Current findings suggest the telephone-interview version of the ASRS may be an easy-to-use, reliable, and cost-effective supplement in gaining more confidence in determining ADHD in post-secondary education students. More research is required specifically testing its merits to detect feigning or support in diagnosis.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".