TARU PUBLICATIONS
 Journal of Statistics and Management Systems cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0014·ISSN (Print): 0972-0510

Monthly Journal: Publishes peer-reviewed aticles on theoretical and applied statistics and management systems, expoloring industrial statistics, actuarial and decision sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
submissions@tarupublications.com
Open Access Research Article

Factors influencing the acceptance of mobile health apps among Indians : A behavioral perspective

* , , ,

* Corresponding author · click or hover a name for details

pp. 1433–1442Vol. 28Issue 8November 2025DOI: 10.47974/JSMS-1506XML
Received:
14 Apr 2025
Published Online:
24 Nov 2025
Article type:
Research Article
Language:
EN
Article no.:
JSMS-1506
Pages:
1433–1442

Abstract

Access to healthcare could be drastically changed by the explosive development of mobile health (mHealth) applications, especially in developing nations like India. This study looks into the behavioral elements that affect Indian customers’ acceptance and usage of mHealth apps. Drawing upon established theoretical models such as the Unified Theory of Acceptance and Use of Technology (UTAUT), the research identifies key determinants such as perceived ease of use, perceived usefulness, trust, social influence, health awareness, and privacy concerns. A mixed-method approach was used to collect data from a wide sample of Indian urban customers, combining quantitative surveys and qualitative interviews. The results would emphasize how perceived utility and trust have a big influence on adoption, whereas privacy worries and low digital literacy serve as obstacles. The cultural dynamics specific to India were reflected in the mediating components that emerged: social influence and health awareness. To increase mHealth acceptance and maximize its advantages for a larger population, the study offers practical suggestions for app developers, legislators, and healthcare providers.

Keywords

Subject Classifications

11D03O33

References

[1] Statista Market Insights, “Mobile health (mHealth) apps – India,” Statista (2024). [Online]. Available: https://www.statista.com/outlook/dmo/digital-health/mhealth-apps/india
[Accessed: Mar. 13, 2025].
[2] V. Umaefulam, K. Premkumar, and M. Koole, “Perceptions on mobile health use for health education in an Indigenous population,” Digital Health, vol. 8 (2022). [Online]. Available: https://doi.org/10.1177/20552076221104708
[3] R. R. Pai and S. Alathur, “Bibliometric analysis and methodological review of mobile health services and applications in India,” Int. J. Med. Inform., vol. 145 (2021). [Online]. Available: https://doi.org/10.1016/j.ijmedinf.2020.104312
[4] S. Hajesmaeel-Gohari, F. Khordastan, F. Fatehi, H. Samzadeh, and K. Bahaadinbeigy, “The most used questionnaires for evaluating satisfaction, usability, acceptance, and quality outcomes of mobile health,” BMC Med. Inform. Decis. Mak., vol. 22, no. 1 (2022). [Online]. Available: https://doi.org/10.1186/s12911-022-01764-2
[5] V. Ramirez, E. Johnson, C. Gonzalez, and G. Rossetti, “Assessing the use of mobile health technology by patients: An observational study in primary care clinics,” JMIR MHealth UHealth, vol. 4, no. 2 (2016). [Online]. Available: https://doi.org/10.2196/mhealth.4928
[6] L. Simon, J. Reimann, L. S. Steubl, M. Stach, K. Spiegelhalder, L. B. Sander, H. Baumeister, E. M. Messner, and Y. Terhorst, “Help for insomnia from the app store? A standardized rating of mobile health applications claiming to target insomnia,” J. Sleep Res., vol. 32, no. 1 (2023). [Online]. Available: https://doi.org/10.1111/jsr.13758
[7] H. J. Mahanta and G. N. Sastry, “COVID-19 impact on socio-economic and health interventions: A gaps and peaks analysis using clustering approach,” J. Stat. Manag. Syst., vol. 18, no. 4, pp. 2123–2153 (2022).
[8] N. C. Malone, M. M. Williams, M. C. Smith Fawzi, and J. Bennet, “Mobile health clinics in the United States,” Int. J. Equity Health, vol. 19, no. 1 (2020). [Online]. Available: https://doi.org/10.1186/s12939-019-1116-2
[9] M. R. Hoque, M. S. Rahman, N. J. Nipa, and M. R. Hasan, “Mobile health interventions in developing countries: A systematic review,” Health Inform. J., vol. 26, no. 4 (2020). [Online]. Available: https://doi.org/10.1177/1460458219886353
[10] I. M. Pires, G. Marques, N. M. Garcia, F. Flórez-Revuelta, V. Ponciano, and S. Oniani, “A research on the classification and applicability of the mobile health applications,” J. Pers. Med., vol. 10, no. 1 (2020). [Online]. Available: https://doi.org/10.3390/jpm10010011
[11] S. Gaur, R. Gupta, and J. Kaur, “A factor analysis study on relationship across electronic-service quality & behavioral intent with structural equation modeling: Across algo-driven shopping apps & fintech platforms,” J. Stat. Manag. Syst., pp. 1061–1069 (Sep. 2023). [Online]. Available: https://doi.org/10.47974/JSMS-1158
[12] A. J. Naeemah and S. A. Al-Saadi, “The class of semi-modules with direct summands are stable,” J. Discrete Math. Sci. Cryptogr., pp. 1281–1289 (Jun. 2025). [Online]. Available: https://doi.org/10.1080/09720529.2025.2336789

Views: 135Downloads: 60Citations: 0