Development of a symptom validity index to assist in identifying ADHD symptom exaggeration or feigning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Concerns have been identified regarding the ease with which students and young adults can feign or exaggerate symptoms of ADHD, and no formal measures exist to identify such behavior when it occurs. This article describes the development and initial validation of a new symptom validity measure designed to detect feigned or exaggerated ADHD symptom reporting. METHOD: Employing items from a commonly used self-report measure of ADHD (Conners' Adult ADHD Rating Scale [CAARS]) and select items from a scale measuring symptoms of dissociation, we assessed students diagnosed with ADHD, students with other diagnoses, and student volunteers with no psychopathology. RESULTS: This new measure (Exaggeration Index or EI) demonstrated excellent specificity (.97) and adequate sensitivity (.24) in discriminating between those who are suspected of or instructed to feign or exaggerate symptoms of ADHD and all other clinical groups. CONCLUSION: The results strongly suggest that the EI may be a useful adjunct to existing validity measures when identifying exaggerated or implausible symptoms of ADHD.
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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 | 0.002 | 0.004 |
| 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