Global Research Trends in Mobile Health (Mhealth): A Bibliometric Analysis (2013-2023)

Over the past ten years, there has been a discernible increase in the number of mHealth publications. However, a lack of attention has been given to the Asian context. Therefore, this study presents a comprehensive overview of research landscape on mobile health applications (mHealth apps) by conducting a bibliometric analysis of the field over the years. The present review paper is employes bibliometric analysis in a nascent attempt to document the research and offers a rigorous analysis of journal papers on mHealth that have been published. A total of 207 research papers consisting of peer-reviewed articles from the Scopus database were retrieved and analyzed. Based on keyword co-occurrences and co-authorship mapping, the paper identifies emerging trends and research patterns by using the VOSviewer software. It is anticipated that applications of mHealth will be observed in numerous health services given the high volume of citations obtained in this subject. The findings of the current work may provide useful contribution for further research in this discipline that focuses on bringing attention to the nature of the subject matter. This overview could guide and be a central resource for researchers and practitioners looking for information that can help with cross-disciplinary projects by directing them to recognized peer-reviewed publications, journals, and networks and eventually in defining their research focus and aspects of mHealth to be explored.

Bibliometric Analysis, Mental Health, MHealth, Mobile Mental Health Apps, Mental Health App

1. Abaza, H., & Marschollek, M. (2017). mHealth application areas and technology combinations. Methods of information in medicine, 56(S 01), e105-e122. [Google Scholar] [Crossref]

2. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211. [Google Scholar] [Crossref]

3. Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological bulletin, 82(2), 261. [Google Scholar] [Crossref]

4. Akter, S., & Ray, P. (2010). mHealth-an ultimate platform to serve the unserved. Yearbook of medical informatics, 19(01), 94-100. [Google Scholar] [Crossref]

5. Alam, M. Z., Hu, W., Kaium, M. A., Hoque, M. R., & Alam, M. M. D. (2020). Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach. Technology in Society, 61, 101255. [Google Scholar] [Crossref]

6. Alqahtani F, Orji R. Insights from user reviews to improve mental health apps. Health Informatics J. (2020) 26:2042–66. doi: 10.1177/1460458219896492 [Google Scholar] [Crossref]

7. Amagai, S., Pila, S., Kaat, A. J., Nowinski, C. J., & Gershon, R. C. (2022). Challenges in participant engagement and retention using mobile health apps: literature review. Journal of medical Internet research, 24(4), e35120. [Google Scholar] [Crossref]

8. Anastasiadou, D., Folkvord, F., Serrano-Troncoso, E., & Lupiañez-Villanueva, F. (2019). Mobile health adoption in mental health: user experience of a mobile health app for patients with an eating disorder. JMIR mHealth and uHealth, 7(6), e12920. [Google Scholar] [Crossref]

9. Aschbrenner, K. A., Naslund, J. A., Tomlinson, E. F., Kinney, A., Pratt, S. I., & Brunette, M. F. (2019). Adolescents' use of digital technologies and preferences for mobile health coaching in public mental health settings. Frontiers in public health, 7, 178. [Google Scholar] [Crossref]

10. Atallah, N., Khalifa, M., El Metwally, A., & Househ, M. (2018). The prevalence and usage of mobile health applications among mental health patients in Saudi Arabia. Computer methods and programs in biomedicine, 156, 163-168. [Google Scholar] [Crossref]

11. Aydin, G. (2023). Increasing mobile health application usage among Generation Z members: evidence from the UTAUT model. International Journal of Pharmaceutical and Healthcare Marketing, 17(3), 353-379. [Google Scholar] [Crossref]

12. Bayu, A., Novia, D., Husaeni, A. L., & Fitria, D. (2021). A bibliometric analysis of chemical engineering research using. Journal of Engineering Science and Technology, 16(6). [Google Scholar] [Crossref]

13. Bendtsen, M., Müssener, U., Linderoth, C., & Thomas, K. (2020). A mobile health intervention for mental health promotion among university students: randomized controlled trial. JMIR mHealth and uHealth, 8(3), e17208. [Google Scholar] [Crossref]

14. Benny, V. (2021). A Study on Attitude of Women Investors towards Stock Market Investment in Kerala. anvesak. [Google Scholar] [Crossref]

15. Bidargaddi, N., Schrader, G., Klasnja, P., Licinio, J., & Murphy, S. (2020). Designing m-Health interventions for precision mental health support. Translational psychiatry, 10(1), 222. [Google Scholar] [Crossref]

16. Borghouts J, Eikey E, Mark G, De Leon C, Schueller SM, Schneider M, et al. Barriers to and facilitators of user engagement with digital mental health interventions: systematic review. J Med Internet Res. (2021) 23:e24387. doi: 10.2196/24387 [Google Scholar] [Crossref]

17. Briz-Ponce, L., Pereira, A., Carvalho, L., Juanes-Méndez, J. A., & García-Peñalvo, F. J. (2017). Learning with mobile technologies–Students’ behavior. Computers in human behavior, 72, 612-620. [Google Scholar] [Crossref]

18. Cao, J., Lim, Y., Sengoku, S., Guo, X., & Kodama, K. (2021). Exploring the shift in international trends in mobile health research from 2000 to 2020: bibliometric analysis. JMIR mHealth and uHealth, 9(9), e31097. [Google Scholar] [Crossref]

19. Chen, X., Zou, D., Xie, H., & Wang, F. L. (2021). Past, present, and future of smart learning: a topic-based bibliometric analysis. International Journal of Educational Technology in Higher Education, 18(1), 2. [Google Scholar] [Crossref]

20. Cheng, F. F., Huang, Y. W., Tsaih, D. C., & Wu, C. S. (2019). Trend analysis of co-authorship network in Library Hi Tech. Library Hi Tech, 37(1), 43-56. [Google Scholar] [Crossref]

21. Chib, A., Van Velthoven, M. H., & Car, J. (2015). mHealth adoption in low-resource environments: a review of the use of mobile healthcare in developing countries. Journal of health communication, 20(1), 4-34. [Google Scholar] [Crossref]

22. Chou, Y. H., Lin, C., Lee, S. H., Chang Chien, Y. W., & Cheng, L. C. (2023). Potential mobile health applications for improving the mental health of the elderly: A systematic review. Clinical Interventions in Aging, 1523-1534. [Google Scholar] [Crossref]

23. Cobelli, N., & Blasioli, E. (2023). To be or not to be digital? A bibliometric analysis of adoption of eHealth services. The TQM Journal, 35(9), 299-331. [Google Scholar] [Crossref]

24. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340. [Google Scholar] [Crossref]

25. De Moya-Anegon, F., Guerrero-Bote, V. P., Lopez-Illescas, C., & Moed, H. F. (2018). Statistical relationships between corresponding authorship, international co-authorship and citation impact of national research systems. Journal of informetrics, 12(4), 1251-1262. [Google Scholar] [Crossref]

26. Ding, X., Wuerth, K., Sakakibara, B., Schmidt, J., Parde, N., Holsti, L., & Barbic, S. (2023). Understanding mobile health and youth mental health: scoping review. JMIR mHealth and uHealth, 11, e44951. [Google Scholar] [Crossref]

27. Eze, E., Gleasure, R., & Heavin, C. (2020). Mobile health solutions in developing countries: a stakeholder perspective. Health Systems, 9(3), 179-201. [Google Scholar] [Crossref]

28. Foa EB, Franklin M, McLean C, McNally RJ, Pine D, Jane Costello E, et al. Defining anxiety disorders. In: Evans D, editor. Treating and Preventing Adolescent Mental Health Disorders: What We Know and What We Don't Know (2nd Edition). Oxford, UK: Oxford Academic; Sep 1, 2017:189-212. [Google Scholar] [Crossref]

29. Fox, G., Clohessy, T., van der Werff, L., Rosati, P., & Lynn, T. (2021). Exploring the competing influences of privacy concerns and positive beliefs on citizen acceptance of contact tracing mobile applications. Computers in Human Behavior, 121, 106806. [Google Scholar] [Crossref]

30. Gagnon, M. P., Ngangue, P., Payne-Gagnon, J., & Desmartis, M. (2016). m-Health adoption by healthcare professionals: a systematic review. Journal of the American Medical Informatics Association, 23(1), 212-220. [Google Scholar] [Crossref]

31. Galetsi, P., Katsaliaki, K., & Kumar, S. (2023). Exploring benefits and ethical challenges in the rise of mHealth (mobile healthcare) technology for the common good: An analysis of mobile applications for health specialists. Technovation, 121, 102598. [Google Scholar] [Crossref]

32. Geirhos, A., Domhardt, M., Lunkenheimer, F., Temming, S., Holl, R. W., Minden, K., ... & Baumeister, H. (2022). Feasibility and potential efficacy of a guided internet-and mobile-based CBT for adolescents and young adults with chronic medical conditions and comorbid depression or anxiety symptoms (youthCOACHCD): a randomized controlled pilot trial. BMC pediatrics, 22(1), 69. [Google Scholar] [Crossref]

33. Gordon, N. P., & Crouch, E. (2019). Digital information technology use and patient preferences for internet-based health education modalities: cross-sectional survey study of middle-aged and older adults with chronic health conditions. JMIR aging, 2(1), e12243. [Google Scholar] [Crossref]

34. Guo, B., Syufiza, N., & Ahmad Shukor, N. S. (2023). Systematic literature review of healthcare services for the elderly: trends, challenges, and application scenarios. Int J Public Health Sci, 12, 1637-46. [Google Scholar] [Crossref]

35. Haque, M. R., & Rubya, S. (2023). An overview of chatbot-based mobile mental health apps: insights from app description and user reviews. JMIR mHealth and uHealth, 11(1), e44838. [Google Scholar] [Crossref]

36. Helha, F. N. M., & Wang, Y. P. (2022). Trends in complementary and alternative medicine for the treatment of common mental disorders: A bibliometric analysis of two decades. Complementary Therapies in Clinical Practice, 46, 101531. [Google Scholar] [Crossref]

37. Higaki, A., Uetani, T., Ikeda, S., & Yamaguchi, O. (2020). Co-authorship network analysis in cardiovascular research utilizing machine learning (2009–2019). International Journal of Medical Informatics, 143, 104274. [Google Scholar] [Crossref]

38. Hoque, R., & Sorwar, G. (2017). Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. International journal of medical informatics, 101, 75-84. [Google Scholar] [Crossref]

39. Iribarren, S. J., Cato, K., Falzon, L., & Stone, P. W. (2017). What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions. PloS one, 12(2), e0170581. [Google Scholar] [Crossref]

40. Jembai, J. V. J., Wong, Y. L. C., Bakhtiar, N. A. M. A., Lazim, S. N. M., Ling, H. S., Kuan, P. X., & Chua, P. F. (2022). Mobile health applications: awareness, attitudes, and practices among medical students in Malaysia. BMC Medical Education, 22(1), 544. [Google Scholar] [Crossref]

41. Johnson, K. F., & Kalkbrenner, M. T. (2017). The utilization of technological innovations to support college student mental health: Mobile health communication. Journal of technology in human services, 35(4), 314-339. [Google Scholar] [Crossref]

42. Kamaruzaman, K. N., Hussein, Z., & Fikry, A. (2023). Factors Affecting BehaviouraláIntention to Use Mobile Health Applications among Obese People in Malaysia. European Journal of Business Science and Technology, 9(1), 92-117. [Google Scholar] [Crossref]

43. Khan, F., Sandelski, M. M., Rytlewski, J. D., Lamb, J., Pedro, C., Adjei, M. B., ... & Kacena, M. A. (2018). Bibliometric analysis of authorship trends and collaboration dynamics over the past three decades of BONE's publication history. Bone, 107, 27-35. [Google Scholar] [Crossref]

44. Khatun, F., Palas, J. U., & Ray, P. K. (2017). Using the unified theory of acceptance and use of technology model to analyze cloud-based mHealth service for primary care. Digital Medicine, 3(2), 69-75. [Google Scholar] [Crossref]

45. Kruse, C. S., Betancourt, J. A., Gonzales, M., Dickerson, K., & Neer, M. (2022). Leveraging mobile health to manage mental health/behavioral health disorders: systematic literature review. JMIR Mental Health, 9(12), e42301. [Google Scholar] [Crossref]

46. Litke, S. G., Resnikoff, A., Anil, A., Montgomery, M., Matta, R., Huh-Yoo, J., & Daly, B. P. (2023). Mobile technologies for supporting mental health in youths: scoping review of effectiveness, limitations, and inclusivity. JMIR mental health, 10(1), e46949. [Google Scholar] [Crossref]

47. McGorry, P. D., Mei, C., Chanen, A., Hodges, C., Alvarez‐Jimenez, M., & Killackey, E. (2022). Designing and scaling up integrated youth mental health care. World Psychiatry, 21(1), 61-76. [Google Scholar] [Crossref]

48. Meng, F., Guo, X., Peng, Z., Zhang, X., & Lai, K. H. (2022). Understanding the antecedents of the routine use of mobile health services: A person–technology–health framework. Frontiers in psychology, 13, 879760. [Google Scholar] [Crossref]

49. Milne-Ives, M., Lam, C., De Cock, C., Van Velthoven, M. H., & Meinert, E. (2020). Mobile apps for health behavior change in physical activity, diet, drug and alcohol use, and mental health: systematic review. JMIR mHealth and uHealth, 8(3), e17046. [Google Scholar] [Crossref]

50. Munos, B., Baker, P. C., Bot, B. M., Crouthamel, M., de Vries, G., Ferguson, I., ... & Wang, P. (2016). Mobile health: the power of wearables, sensors, and apps to transform clinical trials. Annals of the New York Academy of Sciences, 1375(1), 3-18. [Google Scholar] [Crossref]

51. Muñoz R. Depression Prevention: Research Directions. London, UK: Hemisphere Publishing Corp; 1987. [Google Scholar] [Crossref]

52. Nisha, N., Iqbal, M., Rifat, A., & Idrish, S. (2015). Mobile health services: A new paradigm for health care systems. International Journal of Asian Business and Information Management (IJABIM), 6(1), 1-17. [Google Scholar] [Crossref]

53. O'Grady, C., Melia, R., Bogue, J., O'Sullivan, M., Young, K., & Duggan, J. (2020). A mobile health approach for improving outcomes in suicide prevention (SafePlan). Journal of medical Internet research, 22(7), e17481. [Google Scholar] [Crossref]

54. Olawade, D. B., Wada, O. Z., Odetayo, A., David-Olawade, A. C., Asaolu, F., & Eberhardt, J. (2024). Enhancing mental health with Artificial Intelligence: Current trends and future prospects. Journal of medicine, surgery, and public health, 3, 100099. [Google Scholar] [Crossref]

55. Otu, A., Ebenso, B., Okuzu, O., & Osifo-Dawodu, E. (2016). Using a mHealth tutorial application to change knowledge and attitude of frontline health workers to Ebola virus disease in Nigeria: a before-and-after study. Human resources for health, 14(1), 5. [Google Scholar] [Crossref]

56. Peng, C., He, M., Cutrona, S. L., Kiefe, C. I., Liu, F., & Wang, Z. (2020). Theme trends and knowledge structure on mobile health apps: bibliometric analysis. JMIR mHealth and uHealth, 8(7), e18212. [Google Scholar] [Crossref]

57. Regmi, K., Kassim, N., Ahmad, N., & Tuah, N. A. (2017). Effectiveness of mobile apps for smoking cessation: a review. Tobacco Prevention & Cessation, 3, 12. [Google Scholar] [Crossref]

58. Saare, M. A., & Hussain, A. (2019). Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older Adults: From the Perspective of Expanded Technology Acceptance Model. International Journal of Interactive Mobile Technologies, 13(10). [Google Scholar] [Crossref]

59. Salgado, T., Tavares, J., & Oliveira, T. (2020). Drivers of mobile health acceptance and use from the patient perspective: survey study and quantitative model development. JMIR mHealth and uHealth, 8(7), e17588. [Google Scholar] [Crossref]

60. Samsuri, A. S., Hussin, S. M., Badaruddin, M. N. A., Arifin, T. R. T., Zainol, S. S., & Mohamad, Z. Z. (2022). Antecedents of user satisfaction and continuance usage of mobile health applications: a study on MySejahtera Apps in Malaysia. Asian Journal of Behavioural Sciences, 4(2), 91-105. [Google Scholar] [Crossref]

61. Sandström, J., Swanepoel, D. W., Carel Myburgh, H., & Laurent, C. (2016). Smartphone threshold audiometry in underserved primary health-care contexts. International Journal of Audiology, 55(4), 232-238. [Google Scholar] [Crossref]

62. Sari, H., Othman, M., & Al-Ghaili, A. M. (2018). A proposed conceptual framework for mobile health technology adoption among employees at workplaces in Malaysia. In International conference of reliable information and communication technology (pp. 736-748). Cham: Springer International Publishing. [Google Scholar] [Crossref]

63. Sweileh, W. M., Al-Jabi, S. W., AbuTaha, A. S., Zyoud, S. E. H., Anayah, F. M., & Sawalha, A. F. (2017). Bibliometric analysis of worldwide scientific literature in mobile-health: 2006–2016. BMC medical informatics and decision making, 17(1), 72. [Google Scholar] [Crossref]

64. Tajudeen, F. P., Bahar, N., Maw Pin, T., & Saedon, N. I. (2022). Mobile technologies and healthy ageing: A bibliometric analysis on publication trends and knowledge structure of mHealth research for older adults. International Journal of Human–Computer Interaction, 38(2), 118-130. [Google Scholar] [Crossref]

65. Thies, K., Anderson, D., & Cramer, B. (2017). Lack of adoption of a mobile app to support patient self-management of diabetes and hypertension in a federally qualified health center: interview analysis of staff and patients in a failed randomized trial. JMIR human factors, 4(4), e24. [Google Scholar] [Crossref]

66. Thornton, L. K., & Kay-Lambkin, F. J. (2018). Specific features of current and emerging mobile health apps: user views among people with and without mental health problems. Mhealth, 4, 56. [Google Scholar] [Crossref]

67. Torous, J., Staples, P., Slaters, L., Adams, J., Sandoval, L., Onnela, J. P., & Keshavan, M. (2017). Characterizing smartphone engagement for schizophrenia: results of a naturalist mobile health study. Clinical schizophrenia & related psychoses. [Google Scholar] [Crossref]

68. van Emmerik, A. A., Keijzer, R., & Schoenmakers, T. M. (2020). Integrating mindfulness into a routine schedule: The role of mobile-health mindfulness applications. In Nutrition, fitness, and mindfulness: An evidence-based guide for clinicians (pp. 217-222). Cham: Springer International Publishing. [Google Scholar] [Crossref]

69. Ventresca, M. J., & Mohr, J. W. (2017). Archival research methods. The Blackwell companion to organizations, 805-828. [Google Scholar] [Crossref]

70. Vesel, L., Hipgrave, D., Dowden, J., & Kariuki, W. (2015). Application of mHealth to improve service delivery and health outcomes: Opportunities and challenges. Etude de la Population Africaine, 29(1), 1683. [Google Scholar] [Crossref]

71. World Health Organization, Mental disorders. 〈https://www.who.int/news -room/fact-sheets/detail/mental-disorders/, 2022, [Google Scholar] [Crossref]

72. Zhang, B., Lau, L. Y., & Chen, Y. (2025). Trends in digital mental health interventions: A 20-year bibliometric analysis. Digital Health, 11, 20552076251403203. [Google Scholar] [Crossref]

73. Zhang, X., Liu, S., Wang, L., Zhang, Y., & Wang, J. (2020). Mobile health service adoption in China: integration of theory of planned behavior, protection motivation theory and personal health differences. Online Information Review, 44(1), 1-23. [Google Scholar] [Crossref]

74. Zheng, S., Edney, S. M., Goh, C. H., Tai, B. C., Mair, J. L., Castro, O., ... & Mueller-Riemenschneider, F. (2023). Effectiveness of holistic mobile health interventions on diet, and physical, and mental health outcomes: a systematic review and meta-analysis. EClinicalMedicine, 66. [Google Scholar] [Crossref]

• Marital Adjustment and Its Relationship with Stress, Mental Health, Expectation, and Body Image
• Global and Malaysian Perspectives on Mental Health and Digital Interventions (2020–2025): A Narrative Review
• Burden of Antipsychotic-induced Parkinsonism: A Case Report
• Mental Health in Cameroon: The Challenge of Treating Trauma. Case Study of Treatment Using the EMDR Protocol
• Reliability and Validity Assessment of a Psychological Adaptation Measurement Tool for College Students