MétaCan
Menu
Back to cohort
Record W2124332616 · doi:10.1093/arclin/acv012

The Medical Symptom Validity Test Measures Effort Not Ability in Children: A Comparison Between Mild TBI and Fetal Alcohol Spectrum Disorder Samples

2015· article· en· W2124332616 on OpenAlexaff
Jennifer C. Gidley Larson, Lloyd Flaro, R. L. Peterson, Amy K. Connery, David A. Baker, Michael W. Kirkwood

Bibliographic record

VenueArchives of Clinical Neuropsychology · 2015
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsAlberta Hospital Edmonton
Fundersnot available
KeywordsFetal Alcohol Spectrum DisorderNeuropsychologyPsychologyClinical psychologyTest (biology)MalingeringCognitionTraumatic brain injuryFetal alcoholFetal alcohol syndromeNeuropsychological assessmentPsychiatryAlcohol

Abstract

fetched live from OpenAlex

Inadequate effort during neuropsychological examination results in inaccurate representations of an individual's true abilities and difficulties. As such, performance validity tests (PVTs) are strongly recommended as standard practice during adult-based evaluations. One concern with using PVTs with children is that failure reflects immature cognitive ability rather than non-credible effort. The current study examined performance on the Medical Symptom Validity Test (MSVT) in two large pediatric clinical samples with strikingly different neuropsychological profiles: (1) mild traumatic brain injury (mTBI; n = 510) and (2) fetal alcohol spectrum disorder (FASD; n = 120). Despite higher IQ scores and reading ability, the mTBI group performed significantly worse than the FASD group on all effort indices. Sixteen percent of the mTBI group failed the MSVT, whereas only 5% of the FASD group did. Our findings support the idea that the MSVT measures effort, not ability, in most cases and help to justify incorporating PVTs into pediatric neuropsychological batteries.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.273
GPT teacher head0.476
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueArchives of Clinical NeuropsychologySame topicTraumatic Brain Injury ResearchFrench-language works237,207