Susceptibility of functional impairment ratings to noncredible reporting in postsecondary students undergoing screening for ADHD
Bibliographic record
Abstract
Objective: Clinical evaluation for attention-deficit/hyperactivity disorder (ADHD) not only requires assessment of symptoms, but also consideration of the degree to which symptoms lead to impairment within various functional domains. However, ADHD evaluations in adulthood often rely on self-reported functional impairment, which might be vulnerable to malingering/noncredible responding. The present study utilized a clinical sample/known groups design to examine the relationship of noncredible presentation to functional impairment ratings by analyzing differential associations with both symptom and performance validity tests (SVTs and PVTs). Method: Participants were 168 postsecondary students who completed psychoeducational assessments for ADHD to determine their eligibility for academic accommodations and/or medications. Impairment ratings on the Weiss Functional Impairment Rating Scale (WFIRS) of 71 students who presented in a noncredible fashion were compared to 72 students who appeared to present credibly (controls) and 25 students diagnosed with ADHD who appeared to present credibly (clinical controls). Results: Relative to both control groups, individuals who presented noncredibly reported higher levels of disability on most functional domains and a higher percentage provided responses that fell in the impaired range on all functional domains of the WFIRS. Conclusions: Findings provide additional evidence that ADHD-related functional impairment ratings are susceptible to noncredible presentation and highlight the need for assessors to include both SVTs and PVTs in ADHD evaluations.
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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 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".