MétaCan
Menu
Back to cohort
Record W4402116826 · doi:10.1071/ib23058

The development of a cognitive screening protocol for Aboriginal and/or Torres Strait Islander peoples: the Guddi Way screen

2024· article· en· W4402116826 on OpenAlexaff
M. H. McIntyre, Jennifer Cullen, Caoilfionn Turner, India Bohanna, Ali Lakhini, Kylie Rixon

Bibliographic record

VenueBrain Impairment · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsImpact
Fundersnot available
KeywordsPsychosocialCognitionCulturally appropriateReferralProtocol (science)IndigenousMedicineNeuropsychologyCulturally sensitiveClinical psychologyPsychologyGerontologyPsychiatryFamily medicineAlternative medicineSocial psychology

Abstract

fetched live from OpenAlex

Background Many Aboriginal and/or Torres Strait Islander peoples are exposed to risk factors for cognitive impairment. However, culturally appropriate methods for identifying potential cognitive impairment are lacking. This paper reports on the development of a screen and interview protocol designed to flag possible cognitive impairments and psychosocial disability in Aboriginal and/or Torres Strait Islander adults over the age of 16years. Methods The Guddi Way screen includes items relating to cognition and mental functions across multiple cognitive domains. The screen is straightforward, brief, and able to be administered by non-clinicians with training. Results Early results suggest the Guddi Way screen is reliable and culturally acceptable, and correctly flags cognitive dysfunction among Aboriginal and/or Torres Strait Islander adults. Conclusions The screen shows promise as a culturally appropriate and culturally developed method to identify the possibility of cognitive impairments and psychosocial disability in Aboriginal and/or Torres Strait Islander adults. A flag on the Guddi Way screen indicates the need for referral to an experienced neuropsychologist or neuropsychiatrist for further assessment and can also assist in guiding support services.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.851
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.000
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 head0.036
GPT teacher head0.402
Teacher spread0.366 · 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 designOther design
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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueBrain ImpairmentSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207