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Evaluation of manual ability in stroke patients in Benin: cultural adaptation and Rasch validation of the ABILHAND-Stroke questionnaire

2019· article· en· W2917487585 on OpenAlexaff
Charles Sèbiyo Batcho, Gaëtan Stoquart, E. Alagnidé, Toussaint Kpadonou, Thierry Lejeune

Bibliographic record

VenueEuropean Journal of Physical and Rehabilitation Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversité LavalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsRasch modelDifferential item functioningPolytomous Rasch modelFunctional Independence MeasureStroke (engine)RehabilitationActivities of daily livingMedicinePhysical medicine and rehabilitationPhysical therapyConstruct validityPsychometricsObservational studyTest (biology)PsychologyClinical psychologyItem response theoryDevelopmental psychology

Abstract

fetched live from OpenAlex

BACKGROUND: ABILHAND is a self-reported questionnaire assessing manual ability. It was validated and calibrated using the Rasch analysis for European stroke patients. After a stroke, performing upper limb activities of daily living is influenced by personal and environmental contextual factors. It is thus important to conduct a contextual validation to use this questionnaire outside of Europe. AIM: The aim of this study was to perform a cross cultural validation of the ABILHAND-Stroke questionnaire for post-stroke patients living in Benin, a West-African country. DESIGN: Observational cross-sectional study. SETTING: Outpatient rehabilitation centres. POPULATION: 223 Beninese chronic stroke patients. METHODS: The experimental questionnaire was made of 59 items evaluating manual activities. Patients had to estimate their difficulty of performing each activity according to four response categories: impossible, very difficult, difficult and easy. For construct validity analysis, patients were also evaluated with other assessment tools: Box and Block Test, the motor subscale of the Functional Independence Measure, the Stroke Impairment Assessment Set, and ACTIVLIM-Stroke. Data were analysed with the Rasch partial credit model. RESULTS: The response categories very difficult and difficult were merged and the number of response categories was reduced from 4 to 3 (impossible, difficult and easy). The Rasch analyses selected 16 bimanual activities that fit the Rasch model (chi square=42.35; P=0.10). The item location ranged from -1.10 to 2.24 logits. The standard error ranged from 0.15 to 0.22 logits. There is no differential item functioning between subgroups (age, sex, dexterity, affected side, time since stroke). The person separation index is 0.82. The questionnaire can measure 3 levels of manual ability, similarly to the occidental version. CONCLUSIONS: The ABILHAND-stroke is a Rasch validated, unidimensional and invariant questionnaire to assess manual ability among Beninese patients. The ordinal score can be transformed into linear score using a conversion table. CLINICAL REHABILITATION IMPACT: This assessment tool is clinically relevant in Benin, a developing country, since it requires no specific equipment or training. It should promote and standardize assessments for stroke patients in clinical practice and research in this African country.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.292
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), 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".

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Citations4
Published2019
Admission routes1
Has abstractyes

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