Yixiang Huang: School of Public Health, Health Development Research Center, Sun Yat-Sen University, Guangzhou, 510080, China.
Paiyi Zhu: School of Public Health, Health Development Research Center, Sun Yat-Sen University, Guangzhou, 510080, China.
Lijin Chen: School of Public Health, Health Development Research Center, Sun Yat-Sen University, Guangzhou, 510080, China.
Xin Wang: School of Public Health, Health Development Research Center, Sun Yat-Sen University, Guangzhou, 510080, China. wangxin25@mail.sysu.edu.cn. ORCID
Pim Valentijn: Department of Health Services Research, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands.
BACKGROUND: The original Rainbow Model of Integrated Care Measurement Tool (RMIC-MT) is based on the Rainbow Model of Integrated Care (RMIC), which provides a comprehensive theoretical framework for integrated care. To translate and adapt the original care provider version of the RMIC-MT and evaluate its psychometric properties by a pilot study in Chinese primary care systems. METHODS: The translation and adaptation process were performed in four steps, forward and back-translation, experts review and pre-testing. We conducted a cross-sectional study with 1610 community care professionals in all 79 community health stations in the Nanshan district. We analyzed the distribution of responses to each item to study the psychometric sensitivity. Exploratory factor analysis with principal axis extraction method and promax rotation was used to assess the construct validity. Cronbach's alpha was utilized to ascertain the internal consistency reliability. Lastly, confirmation factor analysis was used to evaluate the exploratory factor analysis model fit. RESULTS: During the translation and adaptation process, all 48 items were retained with some detailed modifications. No item was found to have psychometric sensitivity problems. Six factors (person- & community-centeredness, care integration, professional integration, organizational integration, cultural competence and technical competence) with 45 items were determined by exploratory factor analysis, accounting for 61.46% of the total variance. A standard Cronbach's alpha of 0.940 and significant correlation among all items in the scale (> 0.4) showed good internal consistency reliability of the tool. And, the model passed the majority of goodness-to-fit test by confirmation factor analysis. CONCLUSIONS: The results showed initial satisfactory psychometric properties for the validation of the Chinese RMIC-MT provider version. Its application in China will promote the development of people-centered integrated primary care. However, further psychometric testing is needed in multiple primary care settings with both public and private community institutes.
