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Record W2059293814 · doi:10.3109/09638288.2011.624249

Validation of the Danish version of the McGill Ingestive Skills Assessment using classical test theory and the Rasch model

2011· article· en· W2059293814 on OpenAlexafffundabout
Tina Hansen, Heather C. Lambert, Jens Faber

Bibliographic record

VenueDisability and Rehabilitation · 2011
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsMcGill University
FundersHerlev HospitalHospital Research FoundationMcGill University
KeywordsRasch modelConstruct validityPsychologyReliability (semiconductor)Construct (python library)Internal consistencyDanishClassical test theoryPsychometricsClinical psychologyDevelopmental psychologyItem response theoryComputer science

Abstract

fetched live from OpenAlex

PURPOSE: The study aimed to validate the Danish version of the Canadian the "McGill Ingestive Skills Assessment" (MISA-DK) for measuring dysphagia in frail elders. METHOD: One-hundred and ten consecutive older medical patients were recruited to the study. Reliability was assessed by internal consistency (Chronbach's alpha). External construct validity (convergent and known-groups validity) was evaluated against theoretical constructs assessing the complex concept of ingestive skills. Internal construct validity was tested using Rasch analysis. RESULTS: High internal consistency reliability with Chronbach's alpha of 0.77-0.95 was evident. External construct validity was supported by expected high correlations with most of the constructs related to ingestive skills (r(s) = 0.53 to r(s) = 0.66). The MISA-DK discriminated significantly between known-groups. Fit to the Rasch model (x(2) (df) = 12 (12), p = 0.424) and unidimensionality of the MISA-DK was confirmed after resolving disordered thresholds for 11 items and adjustment of local dependency. CONCLUSION: The psychometric properties of the MISA-DK equal the original Canadian version. Assessment of internal construct validity indicated multidimensionality due to local dependency. Although achieving good fit to the Rasch model after adjustments, additional studies are needed to establish cross-cultural validity. Finally, establishment of the inter- and intra-rater reliability of the MISA-DK is also needed.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.182
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.033
GPT teacher head0.369
Teacher spread0.336 · 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

Citations19
Published2011
Admission routes3
Has abstractyes

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