Digital health and mobile health: a bibliometric analysis of the 100 most cited papers and their contributing authors

Andy Wai Kan Yeung , Olena Litvinova , Nicola Luigi Bragazzi , Yousef Khader , Md. Mostafizur Rahman , Zafar Said , Robert S. H. Istepanian , Anastasios Koulaouzidis , Adeyemi Oladapo Aremu , James M. Flanagan , Navid Rabiee , Sheikh Mohammed Shariful Islam , Devesh Tewari , Ganesh Venkatachalam , Giustino Orlando , Josef Niebauer , Alexandros G. Georgakilas , Mohammad Reza Saeb , Dalibor Hrg , Yufei Yuan , Muhammad Ali Imran , Huanyu Cheng , Eliana B. Souto , Hari Prasad Devkota , Maurizio Angelo Leone , Jamballi G. Manjunatha , Nikolay T. Tzvetkov , Maima Matin , Olga Adamska , Sabine Völkl-Kernstock , Fabian Peter Hammerle , Farhan Bin Matin , Bodrun Naher Siddiquea , Dongdong Wang , Jivko Stoyanov , Jarosław Olav Horbańczuk , Magdalena Koszarska , Emil Parvanov , Iga Bartel , Artur Jóźwik , Natalia Ksepka , Bogumila Zima-Kulisiewicz , Björn Schuller , Gaurav Pandey , David Bates , Tien Yin Wong , Benjamin S. Glicksberg , Maciej Banach , Cyprian Tomasik , Seifedine Kadry , Stephen T. Wong , Ronan Lordan , Faisal A. Nawaz , Rajeev K. Singla , ArunSundar MohanaSundaram , Himel Mondal , Ayesha Juhi , Shaikat Mondal , Merisa Cenanovic , Aleksandra Zielińska , Christos Tsagkaris , Ronita De , Siva Sai Chandragiri , Robertas Damaševičius , Mugisha Nsengiyumva , Artur Stolarczyk , Okyaz Eminağa , Marco Cascella , Harald Willschke , Atanas G. Atanasov

Exploration of Digital Health Technologies ›› 2024, Vol. 2 ›› Issue (2) : 86 -100.

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Exploration of Digital Health Technologies ›› 2024, Vol. 2 ›› Issue (2) :86 -100. DOI: 10.37349/edht.2024.00013
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Digital health and mobile health: a bibliometric analysis of the 100 most cited papers and their contributing authors
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Andy Wai Kan Yeung, Olena Litvinova, Nicola Luigi Bragazzi, Yousef Khader, Md. Mostafizur Rahman, Zafar Said, Robert S. H. Istepanian, Anastasios Koulaouzidis, Adeyemi Oladapo Aremu, James M. Flanagan, Navid Rabiee, Sheikh Mohammed Shariful Islam, Devesh Tewari, Ganesh Venkatachalam, Giustino Orlando, Josef Niebauer, Alexandros G. Georgakilas, Mohammad Reza Saeb, Dalibor Hrg, Yufei Yuan, Muhammad Ali Imran, Huanyu Cheng, Eliana B. Souto, Hari Prasad Devkota, Maurizio Angelo Leone, Jamballi G. Manjunatha, Nikolay T. Tzvetkov, Maima Matin, Olga Adamska, Sabine Völkl-Kernstock, Fabian Peter Hammerle, Farhan Bin Matin, Bodrun Naher Siddiquea, Dongdong Wang, Jivko Stoyanov, Jarosław Olav Horbańczuk, Magdalena Koszarska, Emil Parvanov, Iga Bartel, Artur Jóźwik, Natalia Ksepka, Bogumila Zima-Kulisiewicz, Björn Schuller, Gaurav Pandey, David Bates, Tien Yin Wong, Benjamin S. Glicksberg, Maciej Banach, Cyprian Tomasik, Seifedine Kadry, Stephen T. Wong, Ronan Lordan, Faisal A. Nawaz, Rajeev K. Singla, ArunSundar MohanaSundaram, Himel Mondal, Ayesha Juhi, Shaikat Mondal, Merisa Cenanovic, Aleksandra Zielińska, Christos Tsagkaris, Ronita De, Siva Sai Chandragiri, Robertas Damaševičius, Mugisha Nsengiyumva, Artur Stolarczyk, Okyaz Eminağa, Marco Cascella, Harald Willschke, Atanas G. Atanasov. Digital health and mobile health: a bibliometric analysis of the 100 most cited papers and their contributing authors. Exploration of Digital Health Technologies, 2024, 2 (2) : 86-100 DOI:10.37349/edht.2024.00013

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References

[1]

Chen CE, Harrington RA, Desai SA, Mahaffey KW, Turakhia MP. Characteristics of digital health studies registered in ClinicalTrials.gov. JAMA Intern Med. 2019; 179:838-40.

[2]

Global strategy on digital health 2020-2025 [Internet].World Health Organization; c2021 [cited 2023 Sep 12]. Available from:https://www.who.int/docs/default-source/documents/gs4dhdaa2a9f352b0445bafbc79ca799dce4d.pdf

[3]

Istepanian RSH. Mobile health (m-Health) in retrospect: the known unknowns. Int J Environ Res Public Health. 2022; 19:3747.

[4]

Inan DI, Win KT, Juita R. mHealth medical record to contribute to noncommunicable diseases in Indonesia. Procedia Comput Sci. 2019; 161:1283-91.

[5]

Meskó B, Drobni Z, Bényei É, Gergely B, Győrffy Z. Digital health is a cultural transformation of traditional healthcare. Mhealth. 2017; 3:38.

[6]

Farris RJ, Quintero HA, Murray SA, Ha KH, Hartigan C, Goldfarb M. A preliminary assessment of legged mobility provided by a lower limb exoskeleton for persons with paraplegia. IEEE Trans Neural Syst Rehabil Eng. 2014; 22:482-90.

[7]

Malmström PU, Agrawal S, Bläckberg M, Boström PJ, Malavaud B, Zaak D, et al. Non-muscle-invasive bladder cancer: a vision for the future. Scand J Urol. 2017; 51:87-94.

[8]

Rodriguez JA, Shachar C, Bates DW. Digital inclusion as health care - supporting health care equity with digital-infrastructure initiatives. N Engl J Med. 2022; 386:1101-3.

[9]

Ibrahim MS, Mohamed Yusoff H, Abu Bakar YI, Thwe Aung MM, Abas MI, Ramli RA. Digital health for quality healthcare: a systematic mapping of review studies. Digit Health. 2022; 8:20552076221085810.

[10]

Wahl B, Cossy-Gantner A, Germann S, Schwalbe NR. Artificial intelligence (AI) and global health: How can AI contribute to health in resource-poor settings? BMJ Glob Health. 2018; 3:e000798.

[11]

Bates DW, Levine D, Syrowatka A, Kuznetsova M, Craig KJT, Rui A, et al. The potential of artificial intelligence to improve patient safety: a scoping review. NPJ Digit Med. 2021; 4:54.

[12]

Sunarti S, Fadzlul Rahman F, Naufal M, Risky M, Febriyanto K, Masnina R. Artificial intelligence in healthcare: opportunities and risk for future. Gac Sanit. 2021; 35:S67-70.

[13]

Deloitte AI Institute. The generative AI dossier [Internet].Deloitte Development LLC; 2023 [cited 2023 Sep 16]. Available from:https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consulting/us-ai-institute-gen-ai-use-cases.pdf

[14]

Artificial intelligence (AI) market by offering (hardware, software), technology (ML (deep learning (LLM, transformers (GPT 1, 2, 3, 4)), NLP, computer vision), business function, vertical, and region - global forecast to 2030 [Internet].MarketsandMarkets Research Private Ltd.; c2024 [cited 2023 Sep 16]. Available from:https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-market-74851580.html?gclid=CjwKCAjwpJWoBhA8EiwAHZFzfmTHT3YQ9td488Z1HJ0tdc7XOi1wboGOXSkY-BsjEEx7QtEMmuQ-1hoCAyIQAvD_BwE

[15]

Borges do Nascimento IJ, Marcolino MS, Abdulazeem HM, Weerasekara I, Azzopardi-Muscat N, Gonçalves MA, et al. Impact of big data analytics on people’s health: overview of systematic reviews and recommendations for future studies. J Med Internet Res. 2021; 23:e27275.

[16]

Healthcare big data analytics market size worth USD 794.08 billion by 2030 at 24.26% CAGR - report by market research future (MRFR) [Internet]. [cited2023 Sep 16]. Available from:https://www.globenewswire.com/en/news-release/2023/06/14/2687890/0/en/Healthcare-Big-Data-Analytics-Market-Size-Worth-USD-794-08-Billion-by-2030-at-24-26-CAGR-Report-by-Market-Research-Future-MRFR.html

[17]

Vailshery LS. Internet of Things (IoT) - statistics & facts [Internet]. [cited2023 Sep 16]. Available from:https://www.statista.com/topics/2637/internet-of-things/#topicOverview

[18]

Medtech and the internet of medical things: How connected medical devices are transforming health care [Internet]. Deloitte LLP ; c2018 [cited 2023 Sep 16]. Available from:https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Life-Sciences-Health-Care/gx-lshc-medtech-iomt-brochure.pdf

[19]

Yu Z, Amin SU, Alhussein M, Lv Z. Research on disease prediction based on improved DeepFM and IoMT. IEEE Access. 2021; 9:39043-54.

[20]

Barbosa W, Zhou K, Waddell E, Myers T, Dorsey ER. Improving access to care: telemedicine across medical domains. Annu Rev Public Health. 2021; 42:463-81.

[21]

Mathews SC, McShea MJ, Hanley CL, Ravitz A, Labrique AB, Cohen AB. Digital health: a path to validation. NPJ Digit Med. 2019; 2:38.

[22]

Nacinovich M. Defining mHealth. J Commun Healthcare. 2011; 4:1-3.

[23]

Kline SJ, Rosenberg N. An overview of innovation. In: Rosenberg N, editor. Studies on science and the innovation process. World Scientific; 2009. pp. 173-203.

[24]

Favaretto M, De Clercq E, Schneble CO, Elger BS. What is your definition of big data? Researchers’ understanding of the phenomenon of the decade. PLoS One. 2020; 15:e0228987.

[25]

Ramesh AN, Kambhampati C, Monson JR, Drew PJ. Artificial intelligence in medicine. Ann R Coll Surg Engl. 2004; 86:334-8.

[26]

Note 2. Advancing national digital health strategies [Internet]. Source:USAID; [cited 2023 Oct 5]. Available from:https://www.usaid.gov/sites/default/files/2023-06/USAID_DHV_TGN2_508_06132023.pdf

[27]

Gallina S. Preparing Europe for future health threats and crises: the European Health Union. Euro Surveill. 2023; 28:2300066.

[28]

Ahmadvand A, Kavanagh D, Clark M, Drennan J, Nissen L. Trends and visibility of “digital health” as a keyword in articles by JMIR publications in the new millennium: bibliographic-bibliometric analysis. J Med Internet Res. 2019; 21:e10477.

[29]

Atanasov AG. Exploration of Digital Health Technologies . Explor Digit Health Technol. 2023;1:1-3.

[30]

Ellegaard O. The application of bibliometric analysis: disciplinary and user aspects. Scientometrics. 2018; 116:181-202.

[31]

van Raan AFJ. Advances in bibliometric analysis: research performance assessment and science mapping. In: Blockmans W, Engwall L, Weaire D, editors. Bibliometrics: use and abuse in the review of research performance. London: Portland Press Limited; 2014. pp. 17-28.

[32]

Taj F, Klein MCA, van Halteren A. Digital health behavior change technology: bibliometric and scoping review of two decades of research. JMIR Mhealth Uhealth. 2019; 7:e13311.

[33]

Fosso Wamba S, Queiroz MM. Responsible artificial intelligence as a secret ingredient for digital health: bibliometric analysis, insights, and research directions. Inf Syst Front. 2023; 25:2123-38.

[34]

Shaikh AK, Alhashmi SM, Khalique N, Khedr AM, Raahemifar K, Bukhari S. Bibliometric analysis on the adoption of artificial intelligence applications in the e-health sector. Digit Health. 2023; 9:20552076221149296.

[35]

Yang K, Hu Y, Qi H. Digital health literacy: bibliometric analysis. J Med Internet Res. 2022; 24:e35816.

[36]

Yeung AWK, Kulnik ST, Parvanov ED, Fassl A, Eibensteiner F, Völkl-Kernstock S, et al. Research on digital technology use in cardiology: bibliometric analysis. J Med Internet Res. 2022; 24:e36086.

[37]

Chen L, Zhen W, Peng D. Research on digital tool in cognitive assessment: a bibliometric analysis. Front Psychiatry. 2023; 14:1227261.

[38]

Peng C, He M, Cutrona SL, Kiefe CI, Liu F, Wang Z. Theme trends and knowledge structure on mobile health apps: bibliometric analysis. JMIR Mhealth Uhealth. 2020; 8:e18212.

[39]

Bastani P, Manchery N, Samadbeik M, Ha DH, Do LG. Digital health in children’s oral and dental health: an overview and a bibliometric analysis. Children (Basel). 2022; 9:1039.

[40]

Tian H, Chen J. A bibliometric analysis on global eHealth. Digit Health. 2022; 8:20552076221091352.

[41]

de Oliveira OJ, da Silva FF, Juliani F, Barbosa LCMF, Nunhes TV. Bibliometric method for mapping the state-of-the-art and identifying research gaps and trends in literature: an essential instrument to support the development of scientific projects. In: Kunosic S, Zerem E, editors.Scientometrics recent advances. Rijeka: IntechOpen; 2019.

[42]

Zhu J, Liu W. A tale of two databases: the use of Web of Science and Scopus in academic papers. Scientometrics. 2020; 123:321-35.

[43]

van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010; 84:523-38.

[44]

Ellegaard O, Wallin JA. The bibliometric analysis of scholarly production: How great is the impact? Scientometrics. 2015; 105:1809-31.

[45]

Vasti EC, Ouyang D, Ngo S, Sarraju A, Harrington RA, Rodriguez F. Gender disparities in cardiology-related COVID-19 publications. Cardiol Ther. 2021; 10:593-8.

[46]

Marescotti M, Loreto F, Spires-Jones TL. Gender representation in science publication: evidence from Brain Communications . Brain Commun. 2022; 4:fcac077.

[47]

Astegiano J, Sebastián-González E, Castanho CT. Unravelling the gender productivity gap in science: a meta-analytical review. R Soc Open Sci. 2019; 6:181566.

[48]

Firth J, Torous J, Nicholas J, Carney R, Rosenbaum S, Sarris J. Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials. J Affect Disord. 2017; 218:15-22.

[49]

Firth J, Torous J, Nicholas J, Carney R, Pratap A, Rosenbaum S, et al. The efficacy of smartphone-based mental health interventions for depressive symptoms: a meta-analysis of randomized controlled trials. World Psychiatry. 2017; 16:287-98.

[50]

Fitzpatrick KK, Darcy A, Vierhile M. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial. JMIR Ment Health. 2017; 4:e19.

[51]

Free C, Phillips G, Watson L, Galli L, Felix L, Edwards P, et al. The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis. PLoS Med. 2013; 10:e1001363.

[52]

Islam SMR, Kwak D, Kabir MH, Hossain M, Kwak KS. The Internet of Things for health care: a comprehensive survey. IEEE Access. 2015; 3:678-708.

[53]

Ting DSW, Cheung CY, Lim G, Tan GSW, Quang ND, Gan A, et al. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes. JAMA. 2017; 318:2211-23.

[54]

Cafazzo JA, Casselman M, Hamming N, Katzman DK, Palmert MR. Design of an mHealth app for the self-management of adolescent type 1 diabetes: a pilot study. J Med Internet Res. 2012; 14:e70.

[55]

Chow CK, Redfern J, Hillis GS, Thakkar J, Santo K, Hackett ML, et al. Effect of lifestyle-focused text messaging on risk factor modification in patients with coronary heart disease: a randomized clinical trial. JAMA. 2015; 314:1255-63.

[56]

Burke LE, Ma J, Azar KM, Bennett GG, Peterson ED, Zheng Y, et al. ; American Heart Association Publications Committee of the Council on Epidemiology and Prevention; Behavior Change Committee of the Council on Cardiometabolic Health; Council on Cardiovascular and Stroke Nursing, Council on Functional Genomics and Translational Biology, Council on Quality of Care and Outcomes Research, and Stroke Council. Current science on consumer use of mobile health for cardiovascular disease prevention: a scientific statement from the American Heart Association. Circulation. 2015; 132:1157-213. Erratum in: Circulation. 2015; 132:e233.

[57]

Bokolo Anthony Jnr. Use of telemedicine and virtual care for remote treatment in response to COVID-19 pandemic. J Med Syst. 2020; 44:132.

[58]

Ohannessian R, Duong TA, Odone A. Global telemedicine implementation and integration within health systems to fight the COVID-19 pandemic: a call to action. JMIR Public Health Surveill. 2020; 6:e18810.

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