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Record W3181830261 · doi:10.1177/23337214211027683

The Cultural Adaptation of the Everyday Problems Test—Greek Version: An Instrument to Examine Everyday Functioning

2021· article· en· W3181830261 on OpenAlexaff
George Pavlidis, Stephanie Hatzifilalithis, Nikolaos Marwan Zawaher, G. Athanasiosos Papaioannou, Eleni Giagkousiklidou, Ana B. Vivas

Bibliographic record

VenueGerontology and Geriatric Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychologyTest (biology)CognitionAdaptation (eye)Cognitive skillEveryday lifeCognitive impairmentTask (project management)Sample (material)Activities of daily livingDevelopmental psychologyCognitive psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Assessing cognitive decline and everyday functioning (EvF) in older age is valuable in detecting age-related neurological disorders. In Greece, there is a lack of sensitive instruments that capture fluctuations in EvF among older persons who are cognitively healthy or have subtle cognitive impairments. The EPT 28-items test, a widely used paper-and-pencil EvF measure, was translated in Greek and adapted to the Greek culture in this study. A multi-step methodology using a sample of 139 older Greek persons was employed. The results indicate that the Greek version of the EPT 28-items (i.e., the EPT-G) was well adapted, representing everyday tasks in Greece within a good range of task difficulty. The psychometric properties of the EPT-G replicate those of the original instrument, capturing EvF fluctuations among older persons with mild cognitive impairments. It was concluded that the EPT-G is a useful measure of EvF among Greek older persons.

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)0.001
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 score0.328
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.042
GPT teacher head0.303
Teacher spread0.261 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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