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Executive functions assessment in patients with language impairment A systematic review

2018· review· en· W2895772560 on OpenAlexaff
Ana Paula Bresolin Gonçalves, Clarissa Mello, Andressa Hermes Pereira, Perrine Ferré, Róchele Paz Fonseca, Yves Joanette

Bibliographic record

VenueDementia & Neuropsychologia · 2018
Typereview
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsExecutive functionsPsychologyVerbal fluency testCognitionWorking memoryStroop effectComprehensionFluencyCognitive psychologyNeuropsychologyNeuropsychological assessmentDevelopmental psychologyLinguisticsPsychiatry

Abstract

fetched live from OpenAlex

Acquired language impairments may accompany different conditions. Most recent studies have shown that there is an important relationship between language and cognitive functions, such as executive functions (EF). Therefore, we aimed to investigate which main EF components appear to have the greatest impact in the most prevalent acquired communication disorders in adults, and which neuropsychological tests are being used to evaluate them. In addition, we sought to characterize the relationship between the executive functions and language in these conditions. Working memory (WM) was the most frequently chosen cognitive measure, being evaluated by different span tasks. A relationship between WM and narrative and conversational discourse, writing abilities and grammatical comprehension was found. Other currently used cognitive tests included the Trail Making, Wisconsin, Stroop and Verbal Fluency tests. Language and EF have a complex relationship; hence, a complete assessment should reflect the dynamic processing of cognitive brain functions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.348
Teacher spread0.320 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations23
Published2018
Admission routes1
Has abstractyes

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