{"title":"Translation and validation of the traditional Chinese Mobile App Rating Scale (MARS-TW) for evaluating mHealth apps.","authors":"Shih-Ting Chen, Yi-Ting Lu, Stoyan Stoyanov, Pei-Ching Liu, King-Jen Chang, I-Ching Hou","doi":"10.21037/mhealth-25-10","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Mobile health (mHealth) applications are widely used in Taiwan, yet their quality remains unregulated. The Mobile App Rating Scale (MARS) is a validated tool for assessing mHealth app quality, but a Traditional Chinese version has not been developed and validated. This study aimed to translate and validate the traditional Chinese version of MARS (MARS-TW) and assess its reliability and validity using a cross-cultural adaptation framework.</p><p><strong>Methods: </strong>A three-phase cross-sectional study was conducted: (I) conceptual and item equivalence were evaluated by three experts; (II) semantic equivalence was assessed through forward and backward translation; (III) operational, measurement, and functional equivalence were tested on 44 mHealth apps related to cancer care (CC) and hypertension self-management (HTM), rated independently by two reviewers.</p><p><strong>Results: </strong>The expert review confirmed conceptual and item equivalence. Semantic equivalence was achieved through iterative refinements. Reliability testing demonstrated good internal consistency (Cronbach's α ≥0.80) and inter-rater reliability [intraclass correlation coefficient (ICC) ≥0.76]. Convergent validity was supported by strong correlations within subscales [item-subscale (I-S) correlation >0.3, item-total (I-T) correlation >0.2], while divergent validity was acceptable (subscale correlations <0.70, P<0.05).</p><p><strong>Conclusions: </strong>MARS-TW is a reliable and valid tool for evaluating Traditional Chinese mHealth apps. Future research should explore its applicability across broader health-related app categories.</p>","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"55"},"PeriodicalIF":3.3000,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12594015/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"mHealth","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21037/mhealth-25-10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Mobile health (mHealth) applications are widely used in Taiwan, yet their quality remains unregulated. The Mobile App Rating Scale (MARS) is a validated tool for assessing mHealth app quality, but a Traditional Chinese version has not been developed and validated. This study aimed to translate and validate the traditional Chinese version of MARS (MARS-TW) and assess its reliability and validity using a cross-cultural adaptation framework.
Methods: A three-phase cross-sectional study was conducted: (I) conceptual and item equivalence were evaluated by three experts; (II) semantic equivalence was assessed through forward and backward translation; (III) operational, measurement, and functional equivalence were tested on 44 mHealth apps related to cancer care (CC) and hypertension self-management (HTM), rated independently by two reviewers.
Results: The expert review confirmed conceptual and item equivalence. Semantic equivalence was achieved through iterative refinements. Reliability testing demonstrated good internal consistency (Cronbach's α ≥0.80) and inter-rater reliability [intraclass correlation coefficient (ICC) ≥0.76]. Convergent validity was supported by strong correlations within subscales [item-subscale (I-S) correlation >0.3, item-total (I-T) correlation >0.2], while divergent validity was acceptable (subscale correlations <0.70, P<0.05).
Conclusions: MARS-TW is a reliable and valid tool for evaluating Traditional Chinese mHealth apps. Future research should explore its applicability across broader health-related app categories.