Translation, cross-cultural adaptation and validation of User Mobile App Rating Scale (uMARS)

Authors

  • Tuan Yuswana Tuan Soh Centre of Population Oral Health and Clinical Prevention, Faculty of Dentistry, Universiti Teknologi MARA, 47000 Sungai Buloh, Selangor, Malaysia & Alor Gajah District Dental Health Office, Melaka
  • Nik Mohd Mazuan Nik Mohd Rosdy Centre of Oral and Maxillofacial, Diagnostics & Medicine Studies, Faculty of Dentistry, Universiti Teknologi MARA, 47000 Sungai Buloh, Selangor, Malaysia.
  • Budi Aslinie Md Sabri Centre of Population Oral Health and Clinical Prevention, Faculty of Dentistry, Universiti Teknologi MARA, 47000 Sungai Buloh, Selangor, Malaysia

DOI:

https://doi.org/10.31436/ijohs.v6i1.306

Keywords:

digital dentistry, digital health records, mobile health, mobile application rating scale, reliability and validity

Abstract

The user Version Mobile apps rating scale was established to evaluate the mobile apps. However, to date, there is no uMARS in the Malay version. This study aims to develop a Malay language alternative to the existing version of the Mobile Apps Rating Scale. The initial version of uMARS had previously underwent cross-cultural adaptation, and forward-backward translation with synthesis discussion through a development phase. The upgraded Malay version has been screened and rated by 10 respondents for face validation and a total of 36 respondents contributed to the internal reliability assessment by answering the pilot study question. All items and constructs in the uMARS version were fully adapted. All items and constructs from the prior version of uMARS were fully incorporated into the recent version. The Malay language version of uMARS was subsequently assessed for validity as well as reliability after undergoing forward backward translation. Scale level face validity index based on average method (S-FVI/Ave): 0.99, and S-FVI based on universal agreement method (S-FVI/UA): 0.89 showed that uMARS Malay Version has achieved a satisfactory level of response process validity. Whereas all items and construct presented with excellent internal reliability, Cronbach alpha (?) = 0.918, 0.857, 0.984 for objective quality, subjective quality and perceived impact. The Malay language of uMARS represents the outcome produced through proper development and validation of questionnaires; all of which favourably resulted in an updated version of uMARS that has been deemed competent to be utilized for qualitative measurement of mobile health apps in the Malay language.

References

Barbosa, S. d. F. F., & Marin, H. d. F. (2009). Web-based simulation: a tool for teaching critical care nursing. Revista Latino-Americana de Enfermagem, 17, 7-13. DOI: https://doi.org/10.1590/S0104-11692009000100002

Bardus, M., Awada, N., Ghandour, L. A., Fares, E.-J., Gherbal, T., Al-Zanati, T., & Stoyanov, S. R. (2020). The Arabic version of the Mobile App Rating Scale: development and validation study. JMIR mHealth and uHealth, 8(3), e16956. DOI: https://doi.org/10.2196/16956

Beaton, D. E., Bombardier, C., Guillemin, F., & Ferraz, M. B. (2000). Guidelines for the process of cross-cultural adaptation of self-report measures. Spine, 25(24), 3186-3191. DOI: https://doi.org/10.1097/00007632-200012150-00014

Bendotti, H., Lawler, S., Ireland, D., Gartner, C., Hides, L., & Marshall, H. M. (2022). What do people want in a smoking cessation app? An analysis of user reviews and app quality. Nicotine and Tobacco Research, 24(2), 169-177. DOI: https://doi.org/10.1093/ntr/ntab174

Berhanuddin, M. A., Mohamad, N. F., & Hassan, E. H. (2017). Development and evaluation of an evidence based smoking cessation app for the Malaysian population: the self-determination theory approach. ESTEEM Academic Journal, 13, 28-39.

Bujang, M. A., Omar, E. D., & Baharum, N. A. (2018). A review on sample size determination for Cronbach’s alpha test: a simple guide for researchers. The Malaysian Journal of Medical Sciences, 25(6), 85. DOI: https://doi.org/10.21315/mjms2018.25.6.9

Cha, E. S., Kim, K. H., & Erlen, J. A. (2007). Translation of scales in cross?cultural research: issues and techniques. Journal of Advanced Nursing, 58(4), 386-395. DOI: https://doi.org/10.1111/j.1365-2648.2007.04242.x

Chin, R. W. A., Chua, Y. Y., Chu, M. N., Mahadi, N. F., Wong, M. S., Yusoff, M. S., & Lee, Y. Y. (2018). Investigating validity evidence of the Malay translation of the Copenhagen Burnout Inventory. Journal of Taibah University Medical Sciences, 13(1), 1-9. DOI: https://doi.org/10.1016/j.jtumed.2017.06.003

DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60-95. DOI: https://doi.org/10.1287/isre.3.1.60

Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4), 9-30. DOI: https://doi.org/10.1080/07421222.2003.11045748

Heifetz, M., & Lunsky, Y. (2018). Implementation and evaluation of health passport communication tools in emergency departments. Research in Developmental Disabilities, 72, 23-32. https://www.sciencedirect.com/science/article/abs/pii/S089142221730255X?via%3Dihub DOI: https://doi.org/10.1016/j.ridd.2017.10.010

Hernández, A., Hidalgo, M. D., Hambleton, R. K., & Gómez Benito, J. (2020). International test commission guidelines for test adaptation: A criterion checklist. Psicothema, 32 (3), 390-398. DOI: https://doi.org/10.7334/psicothema2019.306

Jain, S., & Angural, V. (2017). Use of Cronbach's alpha in dental research. Medico Research Chronicles, 4(3), 285-291.

Karlsen, I. L., Svendsen, P. A., & Abildgaard, J. S. (2022). A review of smartphone applications designed to improve occupational health, safety, and well-being at workplaces. BMC Public Health, 22(1), 1-13. DOI: https://doi.org/10.1186/s12889-022-13821-6

Lu, D. J., Girgis, M., David, J. M., Chung, E. M., Atkins, K. M., & Kamrava, M. (2021). Evaluation of mobile health applications to track patient-reported outcomes for oncology patients: a systematic review. Advances in Radiation Oncology, 6(1), 100576. DOI: https://doi.org/10.1016/j.adro.2020.09.016

Mang, J. M., Seuchter, S. A., Gulden, C., Schild, S., Kraska, D., Prokosch, H.-U., & Kapsner, L.A. (2022). DQAgui: a graphical user interface for the MIRACUM data quality assessment tool. BMC Medical Informatics and Decision Making, 22(1), 1-11. DOI: https://doi.org/10.1186/s12911-022-01961-z

Martin-Payo, R., Carrasco-Santos, S., Cuesta, M., Stoyan, S., Gonzalez-Mendez, X., & Fernandez-Alvarez, M. d. M. (2021). Spanish adaptation and validation of the User Version of the Mobile Application Rating Scale (uMARS). Journal of the American Medical Informatics Association, 28(12), 2681-2686. DOI: https://doi.org/10.1093/jamia/ocab216

Marzuki, M. F. M., Yaacob, N. A., & Yaacob, N. M. (2018). Translation, cross-cultural adaptation, and validation of the Malay version of the system usability scale questionnaire for the assessment of mobile apps. JMIR Human Factors, 5(2), e10308. DOI: https://doi.org/10.2196/10308

Morselli, S., Sebastianelli, A., Domnich, A., Bucchi, C., Spatafora, P., Liaci, A., et al. (2021). Translation and validation of the Italian version of the user version of the Mobile Application Rating Scale (uMARS). Journal of Preventive Medicine and Hygiene, 62(1), E243. DOI: https://doi.org/10.2196/preprints.24427

Park, H. S., Cho, H., & Kim, H. S. (2016). Development of a multi-agent m-health application based on various protocols for chronic disease self-management. Journal of Medical Systems, 40(1), 36. DOI: https://doi.org/10.1007/s10916-015-0401-5

Perez-Jover, V., Sala-González, M., Guilabert, M., & Mira, J. J. (2019). Mobile apps for increasing treatment adherence: systematic review. Journal of Medical Internet Research, 21(6), e12505. DOI: https://doi.org/10.2196/12505

Polit, D. F., & Beck, C. T. (2006). The content validity index: are you sure you know what's being reported? Critique and recommendations. Research in Nursing & Health, 29, 489-497. DOI: https://doi.org/10.1002/nur.20147

Pretlow, R., Stock, C., Allison, S., & Roeger, L. (2015). Treatment of child/adolescent obesity using the addiction model: a smartphone app pilot study. Child Obesity, 11 (3), 248–259. DOI: https://doi.org/10.1089/chi.2014.0124

Price, P. C., Jhangiani, R. S., & Chiang, I.-C. A. (2015). Reliability and validity of measurement. Research Methods in Psychology.

Sereda, M., Smith, S., Newton, K., & Stockdale, D. (2019). Mobile apps for management of tinnitus: users’ survey, quality assessment, and content analysis. JMIR mHealth and uHealth, 7(1), e10353. DOI: https://doi.org/10.2196/10353

Shao, K., Huang, J., Song, H., Li, R., & Wu, J. (2014). DAYA: a system for monitoring and enhancing children's oral hygiene. In CHI'14 Extended Abstracts on Human Factors in Computing Systems (pp. 251-256). DOI: https://doi.org/10.1145/2559206.2580927

Sharma, H., Suprabha, B. S., & Rao, A. (2021). Teledentistry and its applications in paediatric dentistry: A literature review. Pediatric Dental Journal, 31(3), 203-215. DOI: https://doi.org/10.1016/j.pdj.2021.08.003

Sharpe, J. D., & Kamara, M. T. (2018). A systematic evaluation of mobile apps to improve the uptake of and adherence to HIV pre-exposure prophylaxis. Sexual Health, 15(6), 587-594. DOI: https://doi.org/10.1071/SH18120

Shinohara, Y., Yamamoto, K., Ito, M., Sakata, M., Koizumi, S., Hashisako, M., et al. (2022). Development and validation of the Japanese version of the uMARS (user version of the mobile app rating system). International Journal of Medical Informatics, 165, 104809. DOI: https://doi.org/10.1016/j.ijmedinf.2022.104809

Soler, C., Zacarías, A., & Lucero, A. (2009). Molarcropolis: a mobile persuasive game to raise oral health and dental hygiene awareness. Proceedings of the International Conference on Advances in Computer Enterntainment Technology DOI: https://doi.org/10.1145/1690388.1690468

Sousa, V. D., & Rojjanasrirat, W. (2011). Translation, adaptation and validation of instruments or scales for use in cross?cultural health care research: a clear and user?friendly guideline. Journal of Evaluation in Clinical Practice, 17(2), 268-274. DOI: https://doi.org/10.1111/j.1365-2753.2010.01434.x

Sousa, V.E., Matson, J., & Dunn Lopez, K. (2017). Questionnaire adapting: little changes mean a lot. Western Journal of Nursing Research, 39, 1289-1300. (0193-9459) DOI: https://doi.org/10.1177/0193945916678212

Stoyanov, S. R., Hides, L., Kavanagh, D. J., & Wilson, H. (2016). Development and validation of the user version of the Mobile Application Rating Scale (uMARS). JMIR mHealth and uHealth, 4(2), e5849. DOI: https://doi.org/10.2196/mhealth.5849

Strodl, E., Shakespeare-Finch, J., Alichniewicz, K. K., Brown, K., Quinn, C., Hides, L., White, A., Gossage, G., Poerio, L., & Batras, D. (2020). Clinicians' perceptions of PTSD coach australia. Internet Interventions, 21, 100333. DOI: https://doi.org/10.1016/j.invent.2020.100333

Subramani Parasuraman, A. T. S., Yee, S. W. K., Chuon, B. L. C., & Ren, L. Y. (2017). Smartphone usage and increased risk of mobile phone addiction: A concurrent study. International Journal of Pharmaceutical Investigation, 7(3), 125. DOI: https://doi.org/10.4103/jphi.JPHI_56_17

Underwood, B., Birdsall, J., & Kay, E. (2015). The use of a mobile app to motivate evidence-based oral hygiene behaviour. British Dental Journal, 219(4), E2-E2. DOI: https://doi.org/10.1038/sj.bdj.2015.660

Yusoff, M. S. B. (2019). ABC of response process validation and face validity index calculation. Education in Medicine Journal, 11(10.21315) DOI: https://doi.org/10.21315/eimj2019.11.3.6

Yusoff, M. S. B., Arifin, W. N., & Hadie, S. N. H. (2021). ABC of questionnaire development and validation for survey research. Education in Medicine Journal, 13(1). DOI: https://doi.org/10.21315/eimj2021.13.1.10

Zamanzadeh, V., Ghahramanian, A., Rassouli, M., Abbaszadeh, A., Alavi-Majd, H., & Nikanfar, A.-R. (2015). Design and implementation content validity study: development of an instrument for measuring patient-centered communication. Journal of Caring Sciences, 4(2), 165. DOI: https://doi.org/10.15171/jcs.2015.017

Zhang, X., Chou, J., & Wang, F. (2018). Integrative analysis of patient health records and neuroimages via memory-based graph convolutional network. 2018 IEEE International Conference on Data Mining (ICDM) DOI: https://doi.org/10.1109/ICDM.2018.00092

Zijlmans, E. A., Tijmstra, J., Van der Ark, L. A., & Sijtsma, K. (2019). Item-score reliability as a selection tool in test construction. Frontiers in Psychology, 9, 2298. DOI: https://doi.org/10.3389/fpsyg.2018.02298

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Published

2025-02-28

How to Cite

Tuan Soh, T. Y., Nik Mohd Rosdy, N. M. M. ., & Md Sabri, B. A. (2025). Translation, cross-cultural adaptation and validation of User Mobile App Rating Scale (uMARS). IIUM Journal of Orofacial and Health Sciences, 6(1), 15–25. https://doi.org/10.31436/ijohs.v6i1.306