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Record W2742279455 · doi:10.1044/2017_jslhr-l-17-0012

Normative Study of the Functional Assessment of Verbal Reasoning and Executive Strategies (FAVRES) Test in the French-Canadian Population

2017· article· en· W2742279455 on OpenAlexaffabout
Karine Marcotte, Marie‐Pier McSween, Monica Pouliot, Sarah Martineau, Anne‐Marie Pauzé, Catherine Wiseman‐Hakes, Sheila MacDonald

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversité de MontréalHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsNormativePsychologyTest (biology)ComprehensionPopulationCognitive psychologyDevelopmental psychologyLinguisticsMedicine

Abstract

fetched live from OpenAlex

Purpose: The Functional Assessment of Verbal Reasoning and Executive Strategies (FAVRES; MacDonald, 2005) test was designed for use by speech-language pathologists to assess verbal reasoning, complex comprehension, discourse, and executive skills during performance on a set of challenging and ecologically valid functional tasks. A recent French version of this test was translated from English; however, it had not undergone standardization. The development of normative data that are linguistically and culturally sensitive to the target population is of importance. The present study aimed to establish normative data for the French version of the FAVRES, a commonly used test with native French-speaking patients with traumatic brain injury in Québec, Canada. Method: The normative sample consisted of 181 healthy French-speaking adults from various regions across the province of Québec. Age and years of education were factored into the normative model. Results: Results indicate that age was significantly associated with performance on time, accuracy, reasoning subskills, and rationale criteria, whereas the level of education was significantly associated with accuracy and rationale. Conclusion: Overall, mean scores on each criterion were relatively lower than in the original English version, which reinforces the importance of using the present normative data when interpreting performance of French speakers who have sustained a traumatic brain injury.

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 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.062
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.116
GPT teacher head0.440
Teacher spread0.324 · 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 teacher head, 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

Citations14
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Speech Language and Hearing ResearchSame topicTraumatic Brain Injury ResearchFrench-language works237,207