Journals / Turkish Journal of Rheumatology(.)Archives of Rheumatology / 2011 / Cilt: 26 - Sayı: 1

ICF Bel Ağrısı Çekirdek Setinin Psikometrik Özellikleri ve Klinik Kullanımı

Psychometric Properties of the ICF Core Set for Low Back Pain and Its Clinical Use

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44–52
DOI
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Usually a reliability of 0.70 is required for analysis at the group level, and values of 0.85 and higher for individual use.[21]External construct validityThe external construct validity was assessed by testing for expected associations of ICF item sets with RMDQ and SF-36 through the process of convergent construct validity.[22] The degree of associations with these outcome measures was analyzed by Spearman's correlation coefficient.

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Objective & Hypothesis:score and the mental component summary score.
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Key Findings & Data:The Turkish version of the SF-36 was used in the study.[9]Internal construct validityThe internal construct validity of each component of the ICF Core Set for LBP '"BF and BS", AP and EF items' was assessed by Rasch analysis.
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Conclusion & Impact:Usually a reliability of 0.70 is required for analysis at the group level, and values of 0.85 and higher for individual use.[21]External construct validityThe external construct validity was assessed by testing for expected associations of ICF item sets with RMDQ and SF-36 through the process of convergent construct validity.[22] The degree of associations with these outcome measures was analyzed by Spearman's correlation coefficient.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

score and the mental component summary score. The Turkish version of the SF-36 was used in the study.[9]Internal construct validityThe internal construct validity of each component of the ICF Core Set for LBP '"BF and BS", AP and EF items' was assessed by Rasch analysis. Rasch analysis is the formal testing of an assessment or a scale against a mathematical measurement model which defines how interval scale measurements can be derived from ordinal questionnaires.[10-12] The Rasch model assumes that the probability of a given respondent affirming an item is a logistic function of the difference between the item difficulty and the person ability parameter. Master's partial credit model (PCM) which is an extension of the Rasch dichotomous model for polytomous (more than two response categories) items was used in this study.[13]Common fundamental attributes of the Rasch model were assessed.[14] These are (i) the appropriate stochastic ordering of response categories; (ii) fit of items and persons to the model; (iii) test of the assumption of the local independence of items, including response dependency and unidimensionality; and (iv) the presence of differential item functioning (DIF).As one of the most common sources of item misfit concerns respondents' inconsistent use of these response categories, the response categories should Performing a PCA analysis of the residuals obtained from PCM tested this assumption. If a pair of items had a residual correlation of 0.30 or more, one of the items that showed a higher accumulated residual correlation with the remaining items was eliminated.[17]Items are also tested for DIF. In the framework of Rasch measurement, the scale should be free of item bias or DIF.[18] Differential item functioning occurs when different groups within the sample (e.g., younger and older persons) respond in a different manner to an individual item, despite having equal levels of the underlying characteristic being measured. For example, younger and older patients with equal levels of disability may respond systematically differently to a self-care item such as getting dressed. DIF can be detected both statistically and graphically. In the current analysis, DIF was tested by age, gender, years of education and disease duration.ReliabilityAn estimate of the internal consistency reliability of the ICF item sets was tested by both Cronbach's alpha[19] and person separation index (PSI) from the Rasch analysis.[20] The PSI is equivalent to Cronbach's alpha. Usually a reliability of 0.70 is required for analysis at the group level, and values of 0.85 and higher for individual use.[21]External construct validityThe external construct validity was assessed by testing for expected associations of ICF item sets with RMDQ and SF-36 through the process of convergent construct validity.[22] The degree of associations with these outcome measures was analyzed by Spearman's correlation coefficient.

Özet

Amaç: Bu çalışmada "İşlevsellik, Yetiyitimi ve Sağlığın Uluslararası Sınıflandırması" (ICF) bel ağrısı çekirdek setinin psikometrik özellikleri incelendi.Hastalar ve yöntemler: Ayaktan tedavi olan bel ağrılı 100 hasta (73 kadın, 27 erkek; ort. yaş 55.3 yıl, dağılım 24-84 yıl), bel ağrılı hastalar için belirlenen ICF çekirdek seti ile değerlendirildi. Hastalar Roland-Morris disabilite anketi (RMDQ) ve Kısa Form-36 (KF-36) anketini de doldurdu. Bel ağrısına yönelik ICF çekirdek setinin iç yapısal geçerliliği Rasch analizi ile dış yapısal geçerliliği ise RMDQ ve KF-36 Sağlık Araştırması versiyon 1.0 ile ilişkileri incelenerek değerlendirildi. Güvenirlik, içsel tutarlılık ve birey ayırsama indeksi kullanılarak test edildi.Bulgular: Sıra takip etmeyen yanıt kategorileri yeniden skorlandıktan ve bazı maddeler çıkarıldıktan sonra, "vücut fonksiyonları ve vücut yapıları" ve "aktiviteler ve katılım" madde setleri Rasch modeli beklentilerini karşıladı ve ortalama madde uyumu sırasıyla 0.005 (SS 0.619) ve -0.006 (SS 0.730), ortalama birey uyumu ise sırasıyla -0.165 (SS 0.561) ve -0.084 (SS 0.806) bulundu. Her iki madde setinin de tek boyutlu olduğu, madde işlev farklılığı göstermediği belirlendi. Her iki setin de güvenilirlikleri yüksek olup, Cronbach'ın alfa katsayısı ve birey ayırsama indeksi değerleri 0.77'nin üzerindeydi. Her bir madde seti için, hastaların işlevsellik düzeyi ortalaması, maddelerin zorluk düzeyi ortalamasından düşük olsa da, maddelerin zorluk düzeylerinin dağılımı ile hastaların işlevsellik düzeylerinin dağılımı örtüştü. Her iki madde setinin de, RMDQ ve KF-36 ile beklenen düzeyde korelasyon göstermesi, dış yapısal geçerliliklerini göstermekte idi. "Çevresel faktörler" bileşeni Rasch analizinin varsayımlarını sağlamadı.Sonuç: Gerekli düzenlemeler sonrasında, 15 maddelik "vücut fonksiyonları ve vücut yapıları" seti ve 21 maddelik "aktiviteler ve katılım" seti, bel ağrılı hastalarda işlevselliğin değerlendirilmesinde güvenilir ve geçerli olarak bulundu.

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Cite This Article

ÖZTUNA, D., YANIK, B., KUTLAY, Ş., KURTAİŞ, Y. A., ELHAN, A. H., TENNANT, A., KÜÇÜKDEVECİ, A. A. (2011). ICF Bel Ağrısı Çekirdek Setinin Psikometrik Özellikleri ve Klinik Kullanımı. Turkish Journal of Rheumatology(.)Archives of Rheumatology, Cilt: 26 - Sayı: 1, 44–52. https://ajindex.com/articles/375992

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References (11)

  1. Hillman M, Wright A, Rajaratnam G, Tennant A, Chamberlain MA. Prevalence of low back pain in the community: implications for service provision in Bradford, UK. J Epidemiol Community Health 1996;50:347-52.
  2. Deyo RA, Battie M, Beurskens AJ, Bombardier C, Croft P, Koes B, et al. Outcome measures for low back pain research. A proposal for standardized use. Spine (Phila Pa 1976) 1998;23:2003-13. Katz NJ. Measures of adult back and neck function. Arthritis Rheum 2003;49:S43-9. World Health Organization: International Classification of Functioning, Disability and Health. Geneva: ICF: 2001.
  3. Cieza A, Stucki G, Weigl M, Disler P, Jäckel W, van der Linden S, et al. ICF Core Sets for low back pain. J Rehabil Med 2004;(44 Suppl):69-74.
  4. Roland M, Fairbank J. The Roland-Morris Disability Questionnaire and the Oswestry Disability Questionnaire. Spine (Phila Pa 1976) 2000;25:3115-24.
  5. Küçükdeveci AA, Tennant A, Elhan AH, Niyazoglu H. Validation of the Turkish version of the Roland-Morris Disability Questionnaire for use in low back pain. Spine (Phila Pa 1976) 2001;26:2738-43.
  6. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 1992;30:473-83.
  7. Koçyigit H, Aydemir O, Fişek G, Ölmez N, Memiş A. Kısa form-36 (KF-36)'nın Türkçe versiyonunun güvenilirliği ve geçerliliği. Romatizmal hastalıkları olan bir grup hasta ile çalışma. İlaç ve Tedavi Dergisi 1999; 12:102-6. Rasch G. Probabilistic models for some intelligence and attainment tests. Chicago: University of Chicago Press; 1960.
  8. Luce RD, Tukey JW. Simultaneous conjoint measurement: a new scale type of fundamental measurement. J Math Psychol 1964;1:1-27.
  9. Newby VA, Conner GR, Grant CP, Bunderson CV. The Rasch model and additive conjoint measurement. J Appl Meas 2009;10:348-54. Masters GN. A Rasch model for partial credit scoring. Psychometrika 1982; 47:149-74.
  10. Tennant A, Conaghan PG. The Rasch measurement model in rheumatology: what is it and why use it? When should it be applied, and what should one look for in a Rasch paper? Arthritis Rheum 2007;57:1358-62.
  11. Pallant JF, Tennant A. An introduction to the Rasch measurement model: an example using the Hospital Anxiety and Depression Scale (HADS). Br J Clin Psychol 2007;46:1-18. Smith EV Jr. Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. J Appl Meas 2002;3:205-31. Wright BD. Local dependency, correlations and principal comp