An Android-Based mHealth App for Color Vision Screening and Career Guidance: Design and Validation
DOI:
https://doi.org/10.3991/ijoe.v21i14.58157Keywords:
Ishihara Test, Mobile Health Application, Color Vision Screening, Career Guidance, Color vision deficiencyAbstract
Color vision deficiency (CVD) affects learning outcomes, career opportunities, and daily life, but early screening in Vietnam remains limited. This study introduces an Android-based mobile health (mHealth) application for CVD screening, integrated with an artificial intelligence (AI) module for career guidance. The app was deployed with 527 high school students in Da Nang and validated against standard printed Ishihara plates. Results showed complete agreement with the traditional test, faster screening time, and positive feedback on ease of use and usefulness. The majority of students rated the CVD simulation and career guidance functions as valuable. This research contributes by (1) validating a CVD mHealth tool on a large student population in real educational settings, (2) integrating AI to link health screening with career orientation, and (3) demonstrating a cost-effective, scalable digital solution that supports both school health programs and personalized career counseling. The findings emphasize the role of engineering innovations in enhancing education and health support for students.
References
[1] M. A. Khizer, U. Ijaz, T. A. Khan, S. Khan, T. Liaqat, A. Jamal, I. Zahid, H. G. Shah, and M. A. Zahid, “Smartphone color vision testing as an alternative to the conventional Ishihara booklet,” Cureus, vol. 14, no. 10, p. e30747, Oct. 2022, doi: 10.7759/cureus.30747. PMID: 36457596; PMCID: PMC9705065.
[2] M. P. Simunovic, “Color vision deficiency,” Surv. Ophthalmol., vol. 61, no. 2, pp. 132–155, 2016, doi: 10.1016/j.survophthal.2015.07.001.
[3] S. R. Male, B. R. Shamanna, R. Bhardwaj, C. Bhagvati, and B. Theagarayan, “Color vision devices for color vision deficiency patients: A systematic review and meta-analysis,” Health Sci. Rep., vol. 5, no. 5, p. e842, Sep. 2022, doi: 10.1002/hsr2.842. PMID: 36189411; PMCID: PMC9498227.
[4] S. J. Dain, “Clinical color vision tests,” Clin. Exp. Optom., vol. 87, no. 4–5, pp. 276–293, 2004, doi: 10.1111/j.1444-0938.2004.tb05055.x.
[5] Fanlo-Zarazaga, J. I. Echevarría, J. Pinilla, A. Alejandre, T. Pérez-Roche, D. Gutiérrez, M. Ortín, and V. Pueyo, “Validation of a new digital and automated color perception test,” Diagnostics, vol. 14, no. 4, p. 396, 2024, doi: 10.3390/diagnostics14040396.
[6] T. Bano, J. S. Wolffsohn, and A. L. Sheppard, “Assessment of visual function using mobile apps,” Eye, vol. 38, pp. 2406–2414, 2024, doi: 10.1038/s41433-024-03031-2.
[7] C. Goh, M. Puah, Z. H. Toh, et al., “Mobile apps and visual function assessment: A comprehensive review of the latest advancements,” Ophthalmol. Ther., vol. 14, pp. 23–39, 2025, doi: 10.1007/s40123-024-01071-1.
[8] M. Abbas, M. Alzubaidi, and H. Alzubaidi, “Mobile health applications: Current state and future opportunities in healthcare systems,” Journal of Personalized Medicine, vol. 13, no. 5, p. 773, 2023, doi: 10.3390/jpm13050773.
[9] A. Haque and S. Rahman, “The role of mobile health (mHealth) in improving adolescent healthcare: Opportunities and challenges,” Healthcare, vol. 10, no. 8, p. 1472, 2022, doi: 10.3390/healthcare10081472.
[10] S. Morita, Y. Zhang, T. Yamauchi, S. Chen, J. Li, and K. Tei, “Augmented reality support for color vision deficiency using language models,” arXiv preprint, arXiv:2407.04362, 2024, doi: 10.48550/arXiv.2407.04362.
[11] E. J. Ticlavilca-Inche, M. I. Moreno-Lozano, P. Castañeda, S. Wong-Durand, and A. Oñate-Andino, “Mobile application based on convolutional neural networks for pterygium detection in anterior segment eye images at ophthalmological medical centers,” Int. J. Online Biomed. Eng. (iJOE), vol. 20, no. 8, pp. 115–138, 2024, doi: 10.3991/ijoe.v20i08.48421.
[12] M. I. Waly, F. Alshammari, M. E. Alshammari, and M. Algahtany, “Assessing subjective visual vertical reliability: A comparison of the ‘Bucket Test,’ a mobile app, and a virtual system,” Int. J. Online Biomed. Eng. (iJOE), vol. 20, no. 2, pp. 149–165, 2024, doi: 10.3991/ijoe.v20i02.45981.
[13] P. T. Yen, “Information technology–based model for school-based CVD surveys,” J. Syst. Eng. Electron., vol. 35, no. 5, pp. 215–232, 2025, doi: 10.14118/jsee.2025.V35I5.2255.
[14] L. M. Duc, Assessment of Visual Function in Students of People’s Security Academies and Universities in the Hanoi Area, Ph.D. dissertation, Hanoi Medical University, Hanoi, Vietnam, 2020.
[15] M. P. Simunovic, “Colour vision: A review of congenital and acquired disorders,” Eye, vol. 24, no. 5, pp. 747–755, 2010, doi: 10.1038/eye.2009.251.
[16] A. C. D. Almeida, J. E. A. S. Santos, and M. J. G. Silva, “Evaluation of a prototype mobile application based on expert system for diagnosis of Aedes-aegypti-transmitted diseases,” Int. J. Online Biomed. Eng. (iJOE), vol. 19, no. 11, pp. 90–105, 2023, doi: 10.3991/ijoe.v19i11.41431.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Thi Yen Phan, Vinh Dang, Dang Van Thanh
This work is licensed under a Creative Commons Attribution 4.0 International License.
