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Cross-Cultural Adaptation and Psychometric Properties of an Arabic Version of the Western Ontario Shoulder Instability Index (WOSI)

2020· article· en· W3111914570 on OpenAlexaboutno aff
Aliaa Khaja, Dr Ahmed Bouhamra, Dr Sager Hanna, Dr Ali Maqdis

Bibliographic record

VenueInternational Journal of Innovative Research in Medical Science · 2020
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsDashCronbach's alphaArabicPhysical therapyMedicineCriterion validityPsychometricsPsychologyClinical psychologyInternal consistencyLinguistics

Abstract

fetched live from OpenAlex

Background: The Western Ontario Shoulder Instability Index (WOSI) score is a tool that helps with self-assessment of the shoulder’s functional status in patients experiencing instability problems.The purpose of this study was the cross-cultural adaptation of WOSI into Arabic and assessment of its psychometric properties in comparison to a gold standard-questionnaire, namely the Arabic Disability of the Arm, Shoulder and Hand (DASH) score. Material & Methods: 100 patients participated in this survey, tested initially and retest after two months. The internal consistency tests were performed using Cronbach's alpha. Besides, Pearson's Correlation and Standard response mean (SRM) were calculated to estimate criterion validity and responsiveness of the Arabic WOSI in comparison to the Arabic DASH. Results: The Arabic WOSI had a Cronbach's alpha score of 0.85 at the baseline and 0.91 at the follow-up time period. All subscales had an internal consistency greater than 0.7, except Sport/Work (0.69 at follow-up). A strong correlation with Arabic DASH score was observed (r = 0.79 at baseline & 0.87 at Follow-up) which suggested good validity. Also, moderately correlated changes of baseline to follow-up in DASH and WOSI indicated moderate responsiveness. No ceiling and floor effects were observed among the responses. Conclusion: Overall, the Arabic version of WOSI proved to be a good and reliable diagnostic tool for patients with shoulder instability.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.230
GPT teacher head0.486
Teacher spread0.256 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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