Performance on the Test of Memory Malingering in children with neurological conditions
Bibliographic record
Abstract
Despite increasing interest in the use of performance validity tests with youth, relatively little is known about how children and adolescents with neurological diagnoses perform on these measures. The purpose of this study was to examine performance on the Test of Memory Malingering (TOMM) in a general pediatric neurologic sample. Data were obtained from 266 consecutive patients (mean age = 13.0, SD = 3.7, range = 5-18) referred for a neuropsychological assessment in a tertiary care pediatric hospital. As part of a broader neuropsychological battery, patients were administered the TOMM. In this sample, 94% of children passed the TOMM. Pass rate was 87% for 5-7 year-olds but was ≥ 90% for all other ages. Children with a history of stroke had the lowest pass rate (86%), with other diagnostic groups scoring ≥ 90%, including epilepsy, traumatic brain injury, and hydrocephalus. Lower TOMM performance was related to slower processing speed and weaker memory performance. The results support using the TOMM with children and adolescents who have neurological diagnoses. Caution may still be warranted when interpreting scores in those who are younger and/or who have more significant cognitive difficulty.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".