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Record W2981852969 · doi:10.1177/1352458519879094

Computerized neuropsychological assessment devices in multiple sclerosis: A systematic review

2019· review· en· W2981852969 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMultiple Sclerosis Journal · 2019
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNeuropsychologyNeuropsychological assessmentCognitionCognitive testReliability (semiconductor)Test (biology)PsychologyNeuropsychological testMedicinePsychometricsModalitiesClinical psychologyMultiple sclerosisPhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The proliferation of computerized neuropsychological assessment devices (CNADs) for screening and monitoring cognitive impairment is increasing exponentially. Previous reviews of computerized tests for multiple sclerosis (MS) were primarily qualitative and did not rigorously compare CNADs on psychometric properties. OBJECTIVE: We aimed to systematically review the literature on the use of CNADs in MS and identify test batteries and single tests with good evidence for reliability and validity. METHOD: A search of four major online databases was conducted for publications related to computerized testing and MS. Test-retest reliability and validity coefficients and effect sizes were recorded for each CNAD test, along with administration characteristics. RESULTS: We identified 11 batteries and 33 individual tests from 120 peer-reviewed articles meeting the inclusion criteria. CNADs with the strongest psychometric support include the CogState Brief Battery, Cognitive Drug Research Battery, NeuroTrax, CNS-Vital Signs, and computer-based administrations of the Symbol Digit Modalities Test. CONCLUSION: We identified several CNADs that are valid to screen for MS-related cognitive impairment, or to supplement full, conventional neuropsychological assessment. The necessity of testing with a technician, and in a controlled clinic/laboratory environment, remains uncertain.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.004
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0000.001

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 head0.367
GPT teacher head0.418
Teacher spread0.051 · 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