A survey of neuropsychologists’ use of validity tests with children and adolescents
Bibliographic record
Abstract
A web-based survey of validity test use by North American neuropsychologists was conducted, with 282 participants meeting inclusion criteria. Respondents indicated that they use a median of one stand-alone performance validity test (PVT), one embedded PVT, and one symptom validity test (SVT) per pediatric assessment. The vast majority of respondents indicated they give at least one PVT (92%) and at least one SVT (88%) during each pediatric assessment. A meaningful difference in validity use (i.e., at least a medium effect size) was only found for those who engage in forensic work, with those clinicians giving more stand-alone PVTs than those who do not conduct forensic work. The most frequently used validity measures in pediatric assessments are presented, as are reasons participants reported for both using and not using validity tests. Limitations and qualitative comparisons to other surveys on validity test use with adults are discussed.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".