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Record W2605878864 · doi:10.1177/1533317517691122

Validation of the Turkish Version of the Quick Mild Cognitive Impairment Screen

2017· article· en· W2605878864 on OpenAlexaboutno aff
Burcu Balam Doğu, Hacer Doğan Varan, Rónán Ó’Caoimh, Muhammet Cemal Kızılarslanoğlu, Mustafa Kemal Kılıç, D. William Molloy, Rana Tuna Doğrul, Erdem Karabulut, Anton Svendrovski, Aykut Sağır, Eylem Şahin Cankurtaran, Yusuf Yeşil, Mehmet Emin Kuyumcu, Meltem Halil, Mustafa Cankurtaran

Bibliographic record

VenueAmerican Journal of Alzheimer s Disease & Other Dementias® · 2017
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentDementiaCognitive impairmentTurkishMemory clinicCognitionAudiologyPsychologyMedicineGerontologyPopulationPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: The objective of this study was to validate the Turkish version of the Quick Mild Cognitive Impairment (Q mci-TR) screen. METHODS: In total, 100 patients aged ≥65 years referred to a geriatric outpatient clinic with memory loss were included. The Q mci was compared to the Turkish versions of the standardized Mini-Mental State Examination and the Montreal Cognitive Assessment (MoCA). RESULTS: The Q mci-TR had higher accuracy than the MoCA in discriminating subjective memory complaints (SMCs) from cognitive impairment (mild cognitive impairment [MCI] or dementia), of borderline significance after adjusting for age and education ( P = .06). The Q mci-TR also had higher accuracy than the MoCA in differentiating MCI from SMC, which became nonsignificant after adjustment ( P = .15). A similar pattern was shown for distinguishing MCI from dementia. Test reliability for the Q mci-TR was strong. CONCLUSION: The Q mci-TR is a reliable and useful screening tool for discriminating MCI from SMC and dementia in a Turkish population.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.321
Teacher spread0.300 · 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

Citations41
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Alzheimer s Disease & Other Dementias®Same topicDementia and Cognitive Impairment ResearchFrench-language works237,207