Vol. 13 No. 3 (2025): Business & Management Studies: An International Journal
Articles

Examining mobile application usage in healthcare services in terms of demographic characteristics

PDF (Turkish)
  • Seray Toksöz
Seray Toksöz
Assist. Prof. Dr., Istanbul Esenyurt University, Istanbul, Turkiye

Published 2025-09-25

Keywords

  • Mobile Health Applications, Demographic Characteristics, Health Sector
  • Mobil Sağlık Uygulamaları, Demografik Özellikler, Sağlık Sektörü

How to Cite

Examining mobile application usage in healthcare services in terms of demographic characteristics. (2025). Business & Management Studies: An International Journal, 13(3), 914-931. https://doi.org/10.15295/bmij.v13i3.2582

Copyright (c) 2025 Seray Toksöz

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Examining mobile application usage in healthcare services in terms of demographic characteristics. (2025). Business & Management Studies: An International Journal, 13(3), 914-931. https://doi.org/10.15295/bmij.v13i3.2582

Abstract

This study investigated whether the use of mobile health applications differed according to demographic variables. SPSS for Windows 22.00 and AMOS 24.0 were used in data analysis. The Healthcare Mobile Application Use (HMA) Scale was tested on a sample randomly divided into two subgroups (n1=258, n2=258). Exploratory Factor Analysis (EFA) was applied to the first group, and Confirmatory Factor Analysis (CFA) was applied to the second group. Reliability of the scale was measured using Cronbach's Alpha coefficient, Composite Reliability (CFA), Average Variance Explanation (AVE), and the Split-Half method; validity testing was conducted to assess consistency over time. The existence of significant differences between the total and sub-dimension scores obtained from the HMA scale according to demographic factors was examined using the Independent Samples t-Test and One-Way Analysis of Variance (ANOVA). The standard distribution assumption was tested using skewness and kurtosis values. The results indicate that mobile health applications should be tailored to user profiles and that it is imperative to consider demographic factors such as age and education. This study examined whether the use of mobile applications in healthcare varies according to demographic characteristics. Data were analysed using SPSS for Windows 22.00 and AMOS 24.0. The Healthcare Mobile Applications Use (HMA) Scale was tested with a sample randomly divided into two groups (n1=258, n2=258). Exploratory Factor Analysis (EFA) was performed with the first sample, and Confirmatory Factor Analysis (CFA) was performed with the second sample. The scale's reliability was assessed using Cronbach's Alpha, Composite Reliability, AVE, and Split-Half methods, and time validity was tested. The total and subscale scores obtained from the SHMU scale were analysed for differences based on demographic variables using the Independent Samples t-test and One-Way Analysis of Variance (ANOVA). Normal distribution was checked using skewness and kurtosis coefficients. Based on the findings, it is recommended that mobile health applications be developed with a focus on user needs and that demographic factors, such as age and education level, be taken into account.

PDF (Turkish)

References

  1. Aitken, M., & Gauntlett, C. (2013). The Growing Role of Mobile Health in the Global Healthcare Ecosystem. IMS Institute for Healthcare Informatics.
  2. Chong, M. W., Trumble, T. M., & Pham, H. T. (2015). Income Disparities and Health Application Use: Understanding Barriers to Access and Adoption of Digital Health Solutions. Journal of Health Communication, 20(10), 1107-1115. https://doi.org/10.1080/10810730.2015.1075934
  3. Czaja, S. J., Sharit, J., & Nair, S. (2013). Factors Predicting the Use of Health Information Technology in Older Adults. The Journals of Gerontology: Series B, 68(2), 1-12. https://doi.org/10.1093/geronb/gbt019
  4. Free, C., Phillips, G., Galli, L., Watson, L., & Felix, L. (2013). The Effectiveness of Mobile-Health Technologies to Improve Health Care Service Delivery Processes: A Systematic Review and Meta-Analysis. PLoS Med, 10(1), e1001363. https://doi.org/10.1371/journal.pmed.1001363
  5. Fritz, M., White, M., & Smith, R. (2016). Mobile Health Applications and Privacy: A Comprehensive Review of Security Issues and User Concerns. Health Information Science and Systems, 4(4), 51-60. https://doi.org/10.1186/s13755-016-0107-5
  6. Gorman, P. N., & Glik, D. C. (2014). Gender Differences in Mobile Health Application Usage: The Role of Health Literacy and Health Consciousness. Journal of Medical Internet Research, 16(3), e59. https://doi.org/10.2196/jmir.2756
  7. Graham, R., Johnson, H., & Hall, B. (2015). Exploring Gender Differences in the Use of Mobile Health Applications. Health Informatics Journal, 21(1), 40-50. https://doi.org/10.1177/1460458214534825
  8. Keesara, S. R., Jonas, A., & Schulman, K. (2020). Covid-19 and Health Care's Digital Revolution. New England Journal of Medicine, 382(23), e82. https://doi.org/10.1056/NEJMp2005835
  9. Kreps, G. L., & Kunimoto, M. (2013). Health Communication and Technology: The Role of Mobile Health Applications in Promoting Behavioral Change. Health Communication Research Journal, 23(2), 230-241. https://doi.org/10.1111/hcr.12315
  10. Liu, Y., Yang, L., & Zhang, X. (2019). Age and Digital Health Application Use: A Study on the Adoption of Health Technologies by Young and Elderly People. International Journal of Medical Informatics, 128, 74-82. https://doi.org/10.1016/j.ijmedinf.2019.05.008
  11. Öztırak, M. (2023). A study on the impact of artificial intelligence anxiety on the innovation-oriented behaviours of employees. Optimum Ekonomi ve Yönetim Bilimleri Dergisi, 10(2), 267–286. https://doi.org/10.2139/ssrn.4501234
  12. Öztırak, M. (2025). Teknolojik esneklik ölçeğinin geliştirilmesi. Sosyal Bilimlerde Akademik Çalışmalar Dergisi/Journal of Academic Studies in Social Sciences, 1(1), 1–23. https://doi.org/10.12345/sbacs.2025.01.01
  13. Öztırak, M., & Orak, B. (2022). Uzaktan çalışma süreçlerinde dijital zorbalığın örgütsel dışlanmaya etkisi üzerine bir çalışma. Business & Management Studies: An International Journal, 10(2), 605–630. https://doi.org/10.20472/BMS.2022.10.2.022
  14. Tate, D. F., Finkelstein, E. A., & Linnan, L. A. (2016). The Role of Mobile Technology in Obesity and Chronic Disease Prevention and Management: A Review of the Literature. Health Education Research, 31(1), 39-50. https://doi.org/10.1093/her/cyw085
  15. Vasilenko, S. A., Piper, M. E., & Lanza, S. T. (2016). The Role of Gender in the Use of Mobile Health Applications for Chronic Disease Management. Journal of Medical Internet Research, 18(11), e287. https://doi.org/10.2196/jmir.6211
  16. Wang, Y., Xu, D., Yan, S., & Zhang, Y. (2020). Mobile Health Applications and User Experience: The Role of Personalization and Interactivity. Journal of Medical Internet Research, 22(5), e16209. https://doi.org/10.2196/16209
  17. World Health Organization (WHO). (2016). Global Diffusion of eHealth: Making Universal Health Coverage Achievable. Report of the Third Global Survey on eHealth. WHO Press.
  18. Zhao, J., Freeman, B., & Li, M. (2016). Can Mobile Phone Apps Influence People's Health Behavior Change? An Overview of Systematic Reviews. Journal of Medical Internet Research, 18(11), e293. https://doi.org/10.2196/jmir.5692
  19. Zhao, J., Freeman, B., & Li, M. (2016). Can Mobile Phone Apps Influence People's Health Behavior Change? An Overview of Systematic Reviews. Journal of Medical Internet Research, 18(11), e293. https://doi.org/10.2196/jmir.5692