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Record W2944361211 · doi:10.5014/ajot.2019.027755

Development, Reliability, and Validity of the Multiple Errands Test Home Version (MET–Home) in Adults With Stroke

2019· article· en· W2944361211 on OpenAlexaff
Suzanne Perea Burns, Deirdre Dawson, Jaimee Perea, Asha Vas, Noralyn Davel Pickens, Marsha Neville

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2019
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsBaycrest Hospital
Fundersnot available
KeywordsInter-rater reliabilityStroke (engine)PsychologyTest (biology)Reliability (semiconductor)Internal consistencyActivities of daily livingClinical psychologyPhysical medicine and rehabilitationPsychometricsMedicinePsychiatryDevelopmental psychologyRating scale

Abstract

fetched live from OpenAlex

OBJECTIVE: Our objective was to perform initial psychometric analysis of the Multiple Errands Test Home Version (MET-Home), which was designed to assess the influence of poststroke executive dysfunction on in-home task performance. METHOD: We examined the reliability and validity of the MET-Home in adults with stroke (n = 23) and individually matched control participants (n = 23). All participants completed a series of assessments during a single in-home visit. RESULTS: Notable differences in MET-Home subscores were discovered between participants with stroke and control participants. Participants with stroke omitted more tasks, broke more rules, passed by tasks more often, and were less efficient than matched control participants. The MET-Home demonstrated evidence of adequate internal consistency, excellent interrater reliability, and significant moderate associations with several tests. CONCLUSION: This preliminary study suggests that the MET-Home differentiates between adults with stroke and matched control participants. The MET-Home provides evidence of initial reliability and validity among adults with stroke.

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)0.000
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 score0.006
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.022
GPT teacher head0.291
Teacher spread0.269 · 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

Citations18
Published2019
Admission routes1
Has abstractyes

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