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Record W4205164368 · doi:10.1080/23279095.2021.2021411

Exploration of the application of Picture-Based Memory Impairment Screen in stroke patients in a preliminary study

2022· article· en· W4205164368 on OpenAlexaboutno aff
Fei Xiao, Yi Zhang, Yun Cheng, Yu Zhang, Jing Guo

Bibliographic record

VenueApplied Neuropsychology Adult · 2022
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentDementiaReliability (semiconductor)Stroke (engine)KappaPhysical therapyCohen's kappaPsychologyCognitionMedicineCognitive impairmentInternal medicinePsychiatryStatisticsMathematics

Abstract

fetched live from OpenAlex

Objective The objective was to explore the validity and reliability of the Picture-Based Memory Impairment Screen (PMIS) assessment tool in stroke patients and to provide an objective basis for its application in China.Methods: A total of 30 stroke patients in the Department of Rehabilitation Medicine were assessed using the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the PMIS. The results were evaluated by content validity, simultaneous validity, consistency test of instruments of assessment, inter-scorer reliability, and retest reliability.Results: The correlation coefficient between each item score and total score of PMIS was between 0.422 and 0.778 (p < 0.05), showing good content validity. The total score of PMIS was moderately positively correlated with the MMSE short-term memory score (p < 0.001), highly positively correlated with the MMSE long-term memory score and retrospective memory score (p < 0.001), and highly positively correlated with the MoCA long-term memory score, memory index and total score (p < 0.001), indicating good criterion validity. The consistency test of the two instruments of assessment showed that a PMIS ≤ 5 was used as the demarcation score for dementia, and it was tested for consistency with the MMSE dementia score of stroke patients, and the Kappa value was 0.81 (p < 0.001). The inter-scorer reliability and retest reliability were good (inter-scorer reliability intra-group correlation coefficient (ICC) >0.95; retest reliability ICC 0.904).Conclusion: The PMIS was a reliable and valid assessment tool, which can be used as memory impairment screening tool for stroke patients in China.

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 score0.014
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.298
Teacher spread0.283 · 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
Published2022
Admission routes1
Has abstractyes

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