Kadriye Peker1, Taha Emre Köse2, Beliz Güray2, Ömer Uysal3, Tamer Lütfi Erdem4. 1. a Department of Dental Public Health, Faculty of Dentistry , Istanbul University , Capa , Istanbul , Turkey. 2. b Department of Oral and Maxillofacial Radiology, Faculty of Dentistry , Istanbul University , Capa , Istanbul , Turkey. 3. c Department of Medical Statistics and Informatics , Medical School, Bezmialem Vakif University , Fatih , Istanbul , Turkey. 4. d Department of Oral and Maxillofacial Radiology, Faculty of Dentistry , Okan University , Tuzla , Istanbul , Turkey.
Abstract
OBJECTIVE: To culturally adapt the Turkish version of Rapid Estimate of Adult Literacy in Dentistry (TREALD-30) for Turkish-speaking adult dental patients and to evaluate its psychometric properties. MATERIAL AND METHODS: After translation and cross-cultural adaptation, TREALD-30 was tested in a sample of 127 adult patients who attended a dental school clinic in Istanbul. Data were collected through clinical examinations and self-completed questionnaires, including TREALD-30, the Oral Health Impact Profile (OHIP), the Rapid Estimate of Adult Literacy in Medicine (REALM), two health literacy screening questions, and socio-behavioral characteristics. Psychometric properties were examined using Classical Test Theory (CTT) and Rasch analysis. RESULTS: Internal consistency (Cronbach's Alpha = 0.91) and test-retest reliability (Intraclass correlation coefficient = 0.99) were satisfactory for TREALD-30. It exhibited good convergent and predictive validity. Monthly family income, years of education, dental flossing, health literacy, and health literacy skills were found as stronger predictors of patients'oral health literacy (OHL). Confirmatory factor analysis (CFA) confirmed a two-factor model. The Rasch model explained 37.9% of the total variance in this dataset. In addition, TREALD-30 had eleven misfitting items, which indicated evidence of multidimensionality. The reliability indeces provided in Rasch analysis (person separation reliability = 0.91 and expected-a-posteriori/plausible reliability = 0.94) indicated that TREALD-30 had acceptable reliability. CONCLUSION: TREALD-30 showed satisfactory psychometric properties. It may be used to identify patients with low OHL. Socio-demographic factors, oral health behaviors and health literacy skills should be taken into account when planning future studies to assess the OHL in both clinical and community settings.
OBJECTIVE: To culturally adapt the Turkish version of Rapid Estimate of Adult Literacy in Dentistry (TREALD-30) for Turkish-speaking adult dental patients and to evaluate its psychometric properties. MATERIAL AND METHODS: After translation and cross-cultural adaptation, TREALD-30 was tested in a sample of 127 adult patients who attended a dental school clinic in Istanbul. Data were collected through clinical examinations and self-completed questionnaires, including TREALD-30, the Oral Health Impact Profile (OHIP), the Rapid Estimate of Adult Literacy in Medicine (REALM), two health literacy screening questions, and socio-behavioral characteristics. Psychometric properties were examined using Classical Test Theory (CTT) and Rasch analysis. RESULTS: Internal consistency (Cronbach's Alpha = 0.91) and test-retest reliability (Intraclass correlation coefficient = 0.99) were satisfactory for TREALD-30. It exhibited good convergent and predictive validity. Monthly family income, years of education, dental flossing, health literacy, and health literacy skills were found as stronger predictors of patients'oral health literacy (OHL). Confirmatory factor analysis (CFA) confirmed a two-factor model. The Rasch model explained 37.9% of the total variance in this dataset. In addition, TREALD-30 had eleven misfitting items, which indicated evidence of multidimensionality. The reliability indeces provided in Rasch analysis (person separation reliability = 0.91 and expected-a-posteriori/plausible reliability = 0.94) indicated that TREALD-30 had acceptable reliability. CONCLUSION: TREALD-30 showed satisfactory psychometric properties. It may be used to identify patients with low OHL. Socio-demographic factors, oral health behaviors and health literacy skills should be taken into account when planning future studies to assess the OHL in both clinical and community settings.
Entities:
Keywords:
Oral health literacy; REALD-30; Turkish dental patients; literacy in dentistry; psychometric evaluation