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Record W4362458101 · doi:10.1080/10790268.2023.2183334

A multi-center international study on the spinal cord independence measure, version IV: Rasch psychometric validation

2023· article· en· W4362458101 on OpenAlexaff
Amiram Catz, Malka Itzkovich, Rotem Rozenblum, Keren Elkayam, Adi Kfir, Luigi Tesio, Harvinder Singh Chhabra, Dianne Michaeli, Gabi Zeilig, Einat Engel‐Haber, Emiliana Bizzarini, Claudio Pilati, Salvatore Stigliano, Marcella Merafina, Giulio Del Popolo, Gabriele Righi, Jacopo Bonavita, Ilaria Baroncini, Nan Liu, Hua-Yi Xing, Paulo Margalho, Inês Campos, Marcelo Riberto, Thabata Pasquini Soeira, Bobeena Rachel Chandy, George Tharion, Mrinal Joshi, Jean-François Lemay, Marie-Thérèse Laramée, Dorothyann Curran, Annelie Schedin Leiulfsrud, Linda Sørensen, Fin Biering‐Sørensen, Henrik Hagen Poder, Nur Kesiktaş, Lisa Burgess-Collins, Jayne Edwards, Aheed Osman, Vadim Bluvshtein

Bibliographic record

VenueJournal of Spinal Cord Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsOttawa HospitalInstitut de Readaptation Gingras Lindsay de Montreal
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsRasch modelMedicineFunctional Independence MeasurePsychometricsMeasure (data warehouse)Physical therapyIndependence (probability theory)Polytomous Rasch modelPhysical medicine and rehabilitationClinical psychologyRehabilitationItem response theoryPsychologyDevelopmental psychologyData miningStatistics

Abstract

fetched live from OpenAlex

CONTEXT: The Spinal Cord Independence Measure is a comprehensive functional rating scale for individuals with spinal cord lesion (SCL). OBJECTIVE: To validate the scores of the three subscales of SCIM IV, the fourth version of SCIM, using advanced statistical methods. STUDY DESIGN: Multi-center cohort study. SETTING: Nineteen SCL units in 11 countries. METHODS: SCIM developers created SCIM IV following comments by experts, included more accurate definitions of scoring criteria in the SCIM IV form, and adjusted it to assess specific conditions or situations that the third version, SCIM III, does not address. Professional staff members assessed 648 SCL inpatients, using SCIM IV and SCIM III, at admission to rehabilitation, and at discharge. The authors examined the validity and reliability of SCIM IV subscale scores using Rasch analysis. RESULTS: The study included inpatients aged 16-87 years old. SCIM IV subscale scores fit the Rasch model. All item infit and most item outfit mean-square indices were below 1.4; statistically distinct strata of abilities were 2.6-6; most categories were properly ordered; item hierarchy was stable across most clinical subgroups and countries. In a few items, however, we found misfit or category threshold disordering. We found SCIM III and SCIM IV Rasch properties to be comparable. CONCLUSIONS: Rasch analysis suggests that the scores of each SCIM IV subscale are reliable and valid. This reinforces the justification for using SCIM IV in clinical practice and research.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.794

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.224
GPT teacher head0.473
Teacher spread0.249 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

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