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Reliability and Validity of the Turkish Version of the Arthritis-work Spillover Scale in Individuals with Rheumatoid Arthritis

2025· article· en· W7106252380 on OpenAlexaboutno aff

Bibliographic record

VenueBezmialem Science · 2025
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsTurkishScale (ratio)Reliability (semiconductor)Internal consistencyConfirmatory factor analysisConvergent validityConcordance

Abstract

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Objective: The aim of this study is to adapt the arthritis-work spillover (AWS) scale for Turkish and to examine its validity and reliability.Methods: The study included 60 individuals with rheumatoid arthritis.AWS scale, disabilities of the arm, shoulder and hand questionnaire (DASH) and its subscale DASH-work module (DASH-W), arthritis impact measurement scales (AIMS2), disease activity score 28 (DAS28), and Canadian occupational performance measure (COPM) were administered to the participants.Internal consistency analysis, Cronbach's alpha coefficient, test-retest method, confirmatory factor analysis, convergent validity were used for validity and reliability analysis.Results: Cronbach's alpha coefficient was used for internal consistency and the result was 0.86.The test-retest reliability coefficient was 0.68 (p<0.05).In the convergent validity analysis, moderately significant correlations were observed between the AWS and DASH-W (r=0.528,p<0.05),AIMS2-role (r=0.486,p<0.05),COPM-performance (r=-0.416,p<0.05) and COPM-satisfaction scores (r=-0.435,p<0.05).The AWS demonstrated good structural fit.High correlations were observed between AWS and AIMS2symptom, moderate correlations with DASH, AIMS2-physical, AIMS2-affect, and low correlations with DAS28 (p<0.05). Conclusion:The results of this study showed that the Turkish version of the AWS was valid and reliable evaluation.The AWS scale should be used in clinics by clinicians such as physiotherapists, ÖZ Amaç: Bu çalışmanın amacı, artrit-aşırı iş yükü (AAİY) ölçeğinin geçerliğini ve güvenirliğini Türk toplumuna uyarlamaktır.Yöntemler: Çalışmaya romatoid artritli 60 birey dahil edildi.Katılımcılara AAİY ölçeği, kol, omuz ve el engellilik anketi (DASH) ve alt ölçeği DASH-iş modülü (DASH-W), artrit etki ölçüm ölçekleri (AIMS2), hastalık aktivite puanı (DAS28) ve Kanada aktivite ve performans ölçümü (COPM) uygulandı.Geçerlik ve güvenilirlik analizi için iç tutarlılık analizi, Cronbach alfa katsayısı, test-tekrar test yöntemi, doğrulayıcı faktör analizi, yakınsak geçerlilik kullanıldı.Bulgular: İç tutarlılık için Cronbach alfa katsayısı kullanıldı ve sonuç 0,86 olarak bulundu.Test-tekrar test güvenirlik katsayısı 0,68 (p<0,05) olarak bulundu.Yakınsak geçerlilik analizinde AAİY ölçeği ile DASH-W (r=0,528, p<0,05), AIMS2-rol (r=0,486, p<0,05), COPM performans (r=-0,416, p<0,05) ve COPM memnuniyet puanları (r=-0,435, p<0,05) arasında orta düzeyde anlamlı korelasyonlar gözlendi.AAİY, ölçek yapısının iyi uyumunun kanıtını sağladı.AAİY ile; AIMS2-belirti arasında yüksek korelasyon, DASH, AIMS2-fiziksel, AIMS2-etki arasında orta düzeyde korelasyonlar ve DAS28 ile düşük düzeyde korelasyonlar gözlendi (p<0,05).

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)0.004
metaresearch head score (Gemma)0.011
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 score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.009
GPT teacher head0.254
Teacher spread0.245 · 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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Citations0
Published2025
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