Identifying students faking ADHD: Preliminary findings and strategies for detection
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
When conducting psychological evaluations, clinicians typically assume that the subject being evaluated is putting forth maximal effort and is not exaggerating or magnifying symptom complaints. While the field of neuropsychology has identified that factors, such as effort and motivation, can significantly interfere with correct interpretation of self-reported symptoms and test scores, evaluation methods for other psychological conditions, such as attention deficit hyperactivity disorder (ADHD) have not addressed effort and motivation as potential factors influencing accurate diagnosis. In analyzing the performance of students simulating ADHD, and comparing it to performance of both non-ADHD and genuine ADHD students, this study clearly demonstrated that the symptoms of ADHD are easily fabricated, and that simulators would be indistinguishable from those with true ADHD. In addition, students motivated to feign ADHD could easily perform poorly on tests of reading and processing speed, thus allowing them access to academic accommodations. Implications of these findings are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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