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Record W2981233402 · doi:10.1016/j.jalz.2019.06.1078

P1‐473: CROSS‐CULTURAL APPLICABILITY OF THE REPEATABLE BATTERY FOR THE ASSESSMENT OF NEUROPSYCHOLOGICAL STATUS (RBANS) IN COGNITIVELY NORMAL SUBJECTS

2019· article· en· W2981233402 on OpenAlexaff
Christopher J. Weber, Christopher Randolph, Selam Negash

Bibliographic record

VenueAlzheimer s & Dementia · 2019
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHamilton Health Sciences
Fundersnot available
KeywordsRepeatable Battery for the Assessment of Neuropsychological StatusNeurocognitiveClinical trialPsychologyNeuropsychologyIndex (typography)Clinical psychologyCognitionMedicineGerontologyPsychiatry

Abstract

fetched live from OpenAlex

Globally conducted Alzheimer's disease (AD) clinical trials depend upon neurocognitive performance measures free from cultural bias. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) is an instrument that has been translated into over 40 languages, and has been used as both an inclusion measure in clinical trials of early symptomatic AD as well as an endpoint in secondary prevention trials for AD. To determine whether any systematic differences on the RBANS exists due to cultural/linguistic, the present study explored RBANS domain and total index scores in cognitively normal individuals enrolled in AD prevention trials. Aggregated screening/baseline data from four ongoing global multisite trials of individuals enrolled in AD secondary prevention trials were examined, including RBANS data from 16 countries (18 different language forms) at screening or baseline visits (N=8525). All subjects were determined to be cognitively intact at the time of RBANS testing. Index score scaling was done based upon the standard North American normative data. There were some minor geographical variations in terms of RBANS total scale score, but this did not appear to be due to any specific cultural/linguistic factors, as there were no meaningful differences in domain-based index score profiles. Index score profiles were normally distributed across countries. The minor overall performance differences across geographic area might be attributable to differences in educational systems, recruiting practices, or a combination thereof. The fact that there was no difference in the domain-based index score profile across countries suggests that there is no systematic cultural/linguistic bias in the existing translations that would require adjustments.

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)0.009
metaresearch head score (Gemma)0.012
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 score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.036
GPT teacher head0.371
Teacher spread0.334 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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