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Record W2892577452 · doi:10.12669/pjms.345.15083

Development and Validation of Neuro-Cognitive Assessment Battery for Stroke Patients (NCABS) in Pakistan

2018· article· en· W2892577452 on OpenAlexaboutno aff
Syeda Namrah Mahmood, Umaiza Bashir

Bibliographic record

VenuePakistan Journal of Medical Sciences · 2018
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCognitionReliability (semiconductor)Construct validityDiscriminant validityClinical psychologyConcurrent validityStroke (engine)Cognitive testTest (biology)ValidityInternal consistencyAudiologyPsychometricsPsychiatry

Abstract

fetched live from OpenAlex

Background & Objective: Post Stroke Cognitive Impairments (PSCI) occur frequently in stroke survivors resulting in devastating consequences affecting daily living of survivors. Currently, there exists scarcity of sound assessment tools for the evaluation of PSCI as most of the commonly used scales offer a number of clinical (requires motor and linguistic skills) and cultural limitations (requires academic exposure). Therefore, current study was aimed at evaluating the efficacy of Neuro-Cognitive Assessment Battery for Stroke patients (N-CABS) in Pakistan.Methods: The participants were randomized in two groups including clinical and non-clinical group. N-CABS was administered on 61 clinical and 60 non-clinical participants (mean age=45 years; SD=5.55). Both groups were matched on all demographic variables including; age, gender, education and occupation. The psychometric properties of N-CABS were established through a number of robust measures of validity (construct, concurrent and discriminant validity) and reliability (internal consistency and test retest reliability).Results: The factor analysis suggested a two-factor solution (labeled as Verbal Cognitive Abilities and Visual Cognitive Abilities) for N-CABS explaining 67% of total variance. A significant test-retest reliability was found (? = 0.92, ***p<0.001). The findings of concurrent validity recommended a significant correlation between N-CABS and Montreal Cognitive Assessment (MoCA) (? = 0.82, ***p<0.001). Similarly, discriminant validity also revealed significant group differences to exist on N-CABS (***p<0.001) suggesting N-CABS be able to discriminate between patients and healthy controls.Conclusion: The results of the current study favor N-CABS as a psychometrically strong screening instrument to screen PSCI in our culture.doi: https://doi.org/10.12669/pjms.345.15083How to cite this:Mahmood SN, Bashir U. Development and Validation of Neuro-Cognitive Assessment Battery for Stroke Patients (NCABS) in Pakistan. Pak J Med Sci. 2018;34(5):1164-1171.

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)0.001
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 score0.117
Threshold uncertainty score0.206

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.037
GPT teacher head0.400
Teacher spread0.364 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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