Mobile health applications for the most prevalent conditions by the World Health Organization: review and analysis

Borja Martínez-Pérez, Isabel de la Torre-Díez, Miguel López-Coronado, Borja Martínez-Pérez, Isabel de la Torre-Díez, Miguel López-Coronado

Abstract

Background: New possibilities for mHealth have arisen by means of the latest advances in mobile communications and technologies. With more than 1 billion smartphones and 100 million tablets around the world, these devices can be a valuable tool in health care management. Every aid for health care is welcome and necessary as shown by the more than 50 million estimated deaths caused by illnesses or health conditions in 2008. Some of these conditions have additional importance depending on their prevalence.

Objective: To study the existing applications for mobile devices exclusively dedicated to the eight most prevalent health conditions by the latest update (2004) of the Global Burden of Disease (GBD) of the World Health Organization (WHO): iron-deficiency anemia, hearing loss, migraine, low vision, asthma, diabetes mellitus, osteoarthritis (OA), and unipolar depressive disorders.

Methods: Two reviews have been carried out. The first one is a review of mobile applications in published articles retrieved from the following systems: IEEE Xplore, Scopus, ScienceDirect, Web of Knowledge, and PubMed. The second review is carried out by searching the most important commercial app stores: Google play, iTunes, BlackBerry World, Windows Phone Apps+Games, and Nokia's Ovi store. Finally, two applications for each condition, one for each review, were selected for an in-depth analysis.

Results: Search queries up to April 2013 located 247 papers and more than 3673 apps related to the most prevalent conditions. The conditions in descending order by the number of applications found in literature are diabetes, asthma, depression, hearing loss, low vision, OA, anemia, and migraine. However when ordered by the number of commercial apps found, the list is diabetes, depression, migraine, asthma, low vision, hearing loss, OA, and anemia. Excluding OA from the former list, the four most prevalent conditions have fewer apps and research than the final four. Several results are extracted from the in-depth analysis: most of the apps are designed for monitoring, assisting, or informing about the condition. Typically an Internet connection is not required, and most of the apps are aimed for the general public and for nonclinical use. The preferred type of data visualization is text followed by charts and pictures. Assistive and monitoring apps are shown to be frequently used, whereas informative and educational apps are only occasionally used.

Conclusions: Distribution of work on mobile applications is not equal for the eight most prevalent conditions. Whereas some conditions such as diabetes and depression have an overwhelming number of apps and research, there is a lack of apps related to other conditions, such as anemia, hearing loss, or low vision, which must be filled.

Keywords: World Health Organization (WHO); apps; mHealth; mobile applications; prevalent conditions.

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
The 8 most prevalent conditions by the WHO.
Figure 2
Figure 2
Snapshot of MD Series: Anemia–Free.
Figure 3
Figure 3
Snapshot of Hearing Tests.
Figure 4
Figure 4
Snapshot of My Headache Log Pro.
Figure 5
Figure 5
Snapshot of AI type EZReader Theme Pack.
Figure 6
Figure 6
Snapshot of SIGN Asthma Patient Guide.
Figure 7
Figure 7
Snapshot of OnTrack Diabetes.
Figure 8
Figure 8
Snapshot of Osteoarthritis of knee.
Figure 9
Figure 9
Snapshot of Positive Thinking.

References

    1. Van De Belt TH, Engelen LJ, Berben SA, Schoonhoven L. Definition of Health 2.0 and Medicine 2.0: a systematic review. J Med Internet Res. 2010;12(2):e18. doi: 10.2196/jmir.1350.
    1. Mariani AW, Pêgo-Fernandes PM. Telemedicine: a technological revolution. Sao Paulo Med J. 2012;130(5):277–8.
    1. Oh H, Rizo C, Enkin M, Jadad A. What is eHealth (3): a systematic review of published definitions. J Med Internet Res. 2005;7(1):e1. doi: 10.2196/jmir.7.1.e1.
    1. Liu C, Zhu Q, Holroyd KA, Seng EK. Status and trends of mobile-health applications for iOS devices: A developer's perspective. J. Syst. Software. 2011;84(11):2022–2033. doi: 10.1016/j.jss.2011.06.049.
    1. El Khaddar MA, Harroud H, Boulmalf M, Elkoutbi M, Habbani A. Emerging wireless technologies in e-health trends, challenges, and framework design issues. Proceedings of International Conference on Multimedia Computing and Systems; International Conference on Multimedia Computing and Systems; Oct. 10-12, 2012; Tangiers, Morocco. 2012.
    1. Istepanian R, Jovanov E, Zhang YT. Introduction to the special section on M-Health: beyond seamless mobility and global wireless health-care connectivity. IEEE Trans Inf Technol Biomed. 2004 Dec;8(4):405–14.
    1. Yan H, Huo H, Xu Y, Gidlund M. Wireless sensor network based E-health system - implementation and experimental results. IEEE Trans. Consumer Electron. 2010 Nov;56(4):2288–2295. doi: 10.1109/TCE.2010.5681102.
    1. Alinejad A, Philip N, Istepanian RS. Mapping of multiple parameter m-health scenarios to mobile WiMAX QoS variables. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:1532–5. doi: 10.1109/IEMBS.2011.6090447.
    1. Alinejad A, Istepanian RS, Philip N. Dynamic subframe allocation for mobile broadband m-health using IEEE 802.16j mobile multihop relay networks. Conf Proc IEEE Eng Med Biol Soc. 2012 Aug;2012:284–7. doi: 10.1109/EMBC.2012.6345925.
    1. Yang SC. Mobile applications and 4G wireless networks: a framework for analysis. Campus-Wide Information Systems. 2012;29(5):344–357. doi: 10.1108/10650741211275107.
    1. Kumar B, Singh SP, Mohan A. Emerging mobile communication technologies for health. Proceedings of the International Conference on Computer and Communication Technology; International Conference on Computer and Communication Technology; September 17-19, 2010; Allahabad. 2010.
    1. Marinkovic S, Popovici E. Ultra low power signal oriented approach for wireless health monitoring. Sensors (Basel) 2012;12(6):7917–37. doi: 10.3390/s120607917.
    1. World Health Organization mHealth: New Horizons for Health through Mobile Technologies: Based on the Findings of the Second Global Survey on eHealth (Global Observatory for eHealth Series, Volume 3) 2011. [2013-05-23]. .
    1. Web Design Company Smartphone Users Around the World – Statistics and Facts Infographic. [2013-02-28].
    1. IDC. [2013-02-28]. IDC Raises Its Worldwide Tablet Forecast on Continued Strong Demand and Forthcoming New Product Launches .
    1. World Health Organization Disease and injury regional estimates, cause-specific mortality: regional estimates for 2008. [2013-02-28]. .
    1. World Health Organization The global burden of disease: 2004 update. 2008. [2013-05-23]. .
    1. Shaw JG, Friedman JF. Iron deficiency anemia: focus on infectious diseases in lesser developed countries. Anemia. 2011;2011:260380. doi: 10.1155/2011/260380.
    1. World Health Organization Worldwide prevalence of anaemia. 1993–2005: WHO Global Database on Anaemia. [2013-05-23]. .
    1. Clark SF. Iron deficiency anemia. Nutr Clin Pract. 2008;23(2):128–41. doi: 10.1177/0884533608314536.
    1. World Health Organization Health topics: Deafness and hearing impairment. [2013-02-28].
    1. Hearing Loss Association of America. [2013-02-28]. Basic Facts About Hearing Loss .
    1. World Health Organization Deafness and hearing loss - Fact Sheet No. 300. [2013-02-28]. .
    1. American Speech-Language-Hearing Association Hearing Loss. [2013-02-28].
    1. Donnet A, Becker H, Allaf B, Lantéri-Minet M. Migraine and migraines of specialists: perceptions and management. Headache. 2010 Jul;50(7):1115–25. doi: 10.1111/j.1526-4610.2010.01660.x.
    1. Leonardi M, Mathers C. Global burden of migraine in the Year 2000: summary of methods and data sources. [2013-02-28]. .
    1. World Health Organization Atlas of headache disorders and resources in the world. 2011. [2013-05-23]. .
    1. Sauro KM, Becker WJ. The stress and migraine interaction. Headache. 2009 Oct;49(9):1378–86. doi: 10.1111/j.1526-4610.2009.01486.x.
    1. Steiner TJ, Stovner LJ, Birbeck GL. Migraine: the seventh disabler. Headache. 2013 Feb;53(2):227–9. doi: 10.1111/head.12034.
    1. World Health Organization Headache disorders - Fact sheet No 277. [2013-02-28].
    1. World Health Organization Global data on visual impairments 2010. [2013-02-28]. .
    1. Chung ST, Bailey IL, Dagnelie G, Jackson JA, Legge GE, Rubin GS, Wood J. New challenges in low-vision research. Optom Vis Sci. 2012 Sep;89(9):1244–5. doi: 10.1097/OPX.0b013e31826ba359.
    1. World Health Organization Visual impairment and blindness - Fact Sheet No 282. [2013-02-28]. .
    1. Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010. Br J Ophthalmol. 2012 May;96(5):614–8. doi: 10.1136/bjophthalmol-2011-300539.
    1. World Health Organization Asthma Fact sheet No 307. [2013-02-28].
    1. Madore AM, Laprise C. Immunological and genetic aspects of asthma and allergy. J Asthma Allergy. 2010;3:107–21. doi: 10.2147/JAA.S8970.
    1. Shahidi N, Fitzgerald JM. Current recommendations for the treatment of mild asthma. J Asthma Allergy. 2010;3:169–76. doi: 10.2147/JAA.S14420.
    1. Clark NM, Griffiths C, Keteyian SR, Partridge MR. Educational and behavioral interventions for asthma: who achieves which outcomes? A systematic review. J Asthma Allergy. 2010;3:187–97. doi: 10.2147/JAA.S14772.
    1. World Health Organization Diabetes Fact Sheet No 312. [2013-03-01]. .
    1. MedicineNet Diabetes Insipidus. [2013-03-01]. .
    1. World Health Organization Diabetes Programme. [2013-03-01]. .
    1. Nelson SM, Freeman DJ, Sattar N, Johnstone FD, Lindsay RS. IGF-1 and leptin associate with fetal HDL cholesterol at birth: examination in offspring of mothers with type 1 diabetes. Diabetes. 2007 Nov;56(11):2705–9. doi: 10.2337/db07-0585.
    1. Chhoun JM, Voltzke KJ, Firpo MT. From cell culture to a cure: pancreatic β-cell replacement strategies for diabetes mellitus. Regen Med. 2012 Sep;7(5):685–95. doi: 10.2217/rme.12.39.
    1. Smyth DJ, Cooper JD, Howson JM, Walker NM, Plagnol V, Stevens H, Clayton DG, Todd JA. PTPN22 Trp620 explains the association of chromosome 1p13 with type 1 diabetes and shows a statistical interaction with HLA class II genotypes. Diabetes. 2008 Jun;57(6):1730–7. doi: 10.2337/db07-1131.
    1. Long AE, Gillespie KM, Aitken RJ, Goode JC, Bingley PJ, Williams AJ. Humoral responses to islet antigen-2 and zinc transporter 8 are attenuated in patients carrying HLA-A*24 alleles at the onset of type 1 diabetes. Diabetes. 2013 Feb 8;:-–-. doi: 10.2337/db12-1468.
    1. Molven A, Ringdal M, Nordbø AM, Raeder H, Støy J, Lipkind GM, Steiner DF, Philipson LH, Bergmann I, Aarskog D, Undlien DE, Joner G, Søvik O, Norwegian Childhood Diabetes Study Group. Bell GI, Njølstad PR. Mutations in the insulin gene can cause MODY and autoantibody-negative type 1 diabetes. Diabetes. 2008 Apr;57(4):1131–5. doi: 10.2337/db07-1467.
    1. Skyler JS, Ricordi C. Stopping type 1 diabetes: attempts to prevent or cure type 1 diabetes in man. Diabetes. 2011 Jan;60(1):1–8. doi: 10.2337/db10-1114.
    1. Barreda-Pérez M, de la Torre I, López-Coronado M, Rodrigues JJ, García de la Iglesia T. Development and evaluation of a Web-based tool to estimate type 2 diabetes risk: Diab_Alert. Telemed J E Health. 2013 Feb;19(2):81–7. doi: 10.1089/tmj.2012.0110.
    1. Galgani M, Nugnes R, Bruzzese D, Perna F, De Rosa V, Procaccini C, Mozzillo E, Cilio CM, Lernmark A, Larsson HE, La Cava A, Franzese A, Matarese G. Meta-immunological profiling of children with type 1 diabetes identifies new biomarkers to monitor disease progression. Diabetes. 2013 Feb 8;:-–-. doi: 10.2337/db12-1273.
    1. Anguela XM, Tafuro S, Roca C, Callejas D, Agudo J, Obach M, Ribera A, Ruzo A, Mann CJ, Casellas A, Bosch F. Nonviral-mediated hepatic expression of IGF-I increases Treg levels and suppresses autoimmune diabetes in mice. Diabetes. 2013 Feb;62(2):551–60. doi: 10.2337/db11-1776.
    1. Seicean S, Strohl KP, Seicean A, Gibby C, Marwick TH. Sleep disordered breathing as a risk of cardiac events in subjects with diabetes mellitus and normal exercise echocardiographic findings. Am J Cardiol. 2013 Apr 15;111(8):1214–20. doi: 10.1016/j.amjcard.2012.12.053.
    1. Bakker SF, Tushuizen ME, Stokvis-Brantsma WH, Aanstoot HJ, Winterdijk P, van Setten PA, von Blomberg BM, Mulder CJ, Simsek S. Frequent delay of coeliac disease diagnosis in symptomatic patients with type 1 diabetes mellitus: Clinical and genetic characteristics. Eur J Intern Med. 2013 Feb 12;:-–-. doi: 10.1016/j.ejim.2013.01.016.
    1. Lawrence YR, Morag O, Benderly M, Boyko V, Novikov I, Dicker AP, Goldbourt U, Behar S, Barchana M, Wolf I. Association between metabolic syndrome, diabetes mellitus and prostate cancer risk. Prostate Cancer Prostatic Dis. 2013 Jun;16(2):181–6. doi: 10.1038/pcan.2012.54.
    1. Lai CQ, Tucker KL, Parnell LD, Adiconis X, García-Bailo B, Griffith J, Meydani M, Ordovás JM. PPARGC1A variation associated with DNA damage, diabetes, and cardiovascular diseases: the Boston Puerto Rican Health Study. Diabetes. 2008 Apr;57(4):809–16. doi: 10.2337/db07-1238.
    1. World Health Organization Definition and diagnosis of diabetes mellitus and intermediate hyperglycaemia: report of a WHO/IDF consultation. 2006. [2013-05-23]. .
    1. Woolf AD, Pfleger B. Burden of major musculoskeletal conditions. Bull World Health Organ. 2003;81(9):646–56.
    1. World Health Organization Chronic diseases and health promotion: Chronic rheumatic conditions. [2013-03-01].
    1. Pereira D, Peleteiro B, Araújo J, Branco J, Santos RA, Ramos E. The effect of osteoarthritis definition on prevalence and incidence estimates: a systematic review. Osteoarthritis Cartilage. 2011 Nov;19(11):1270–85. doi: 10.1016/j.joca.2011.08.009.
    1. Brooks P. Inflammation as an important feature of osteoarthritis. Bull World Health Organ. 2003;81(9):689–90.
    1. World Health Organization Depression Fact sheet No 369. 2012. Oct, [2013-03-01].
    1. Ayuso-Mateos JL. Global burden of unipolar depressive disorders in the year 2000. [2013-03-01]. .
    1. Munafò MR. The serotonin transporter gene and depression. Depress Anxiety. 2012 Nov;29(11):915–7. doi: 10.1002/da.22009.
    1. Marcus SC, Olfson M. National trends in the treatment for depression from 1998 to 2007. Arch Gen Psychiatry. 2010 Dec;67(12):1265–73. doi: 10.1001/archgenpsychiatry.2010.151.
    1. Adibi S. Link technologies and BlackBerry mobile health (mHealth) solutions: a review. IEEE Trans Inf Technol Biomed. 2012 Jul;16(4):586–97. doi: 10.1109/TITB.2012.2191295.
    1. Morak J, Schwarz M, Hayn D, Schreier G. Feasibility of mHealth and Near Field Communication technology based medication adherence monitoring. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:272–5. doi: 10.1109/EMBC.2012.6345922.
    1. Rajput ZA, Mbugua S, Amadi D, Chepngeno V, Saleem JJ, Anokwa Y, Hartung C, Borriello G, Mamlin BW, Ndege SK, Were MC. Evaluation of an Android-based mHealth system for population surveillance in developing countries. J Am Med Inform Assoc. 2012 Aug;19(4):655–9. doi: 10.1136/amiajnl-2011-000476.
    1. Ferriero G, Vercelli S, Sartorio F, Muñoz Lasa S, Ilieva E, Brigatti E, Ruella C, Foti C. Reliability of a smartphone-based goniometer for knee joint goniometry. Int J Rehabil Res. 2013 Jun;36(2):146–151. doi: 10.1097/MRR.0b013e32835b8269.
    1. Baggott C, Gibson F, Coll B, Kletter R, Zeltzer P, Miaskowski C. Initial evaluation of an electronic symptom diary for adolescents with cancer. JMIR Res Protoc. 2012;1(2):e23. doi: 10.2196/resprot.2175.
    1. Chomutare T, Fernandez-Luque L, Arsand E, Hartvigsen G. Features of mobile diabetes applications: review of the literature and analysis of current applications compared against evidence-based guidelines. J Med Internet Res. 2011;13(3):e65. doi: 10.2196/jmir.1874.
    1. West JH, Hall PC, Hanson CL, Barnes MD, Giraud-Carrier C, Barrett J. There's an app for that: content analysis of paid health and fitness apps. J Med Internet Res. 2012;14(3):e72. doi: 10.2196/jmir.1977.
    1. Jones C. Apple and Google Continue to Gain US Smartphone Market Share. [2013-03-01].
    1. Google Google play. [2013-05-23]. .
    1. Apple iTunes. [2013-05-23].
    1. BlackBerry BlackBerry World. [2013-05-23].
    1. Microsoft Windows Phone Apps+Games. [2013-05-23]. .
    1. Nokia Ovi store. [2013-05-23].
    1. Venugopalan J, Brown C, Cheng C, Stokes TH, Wang MD. Activity and school attendance monitoring system for adolescents with sickle cell disease. Conf Proc IEEE Eng Med Biol Soc. 2012 Aug;2012:2456–9. doi: 10.1109/EMBC.2012.6346461.
    1. Beach-Rak Medicine LLC (Google play) MD Series: Anemia - Free. .
    1. Ellingson RM, Helt WJ, Helt PV, Wilmington DJ, Gordon JS, Fausti SA. Mobile software Apps support personalized-SRO and serial monitoring with results indicating early detection of hearing loss. Proceedings of the IEEE Instrumentation and Measurement Technology Conference (I2MTC); IEEE Instrumentation and Measurement Technology Conference (I2MTC); May 10-12, 2011; Hangzhou, China. 2011.
    1. mikecaroline2008 (Google play) Hearing Tests. .
    1. Zhu Q, Liu C, Holroyd KA. From a traditional behavioral management program to an m-health app: Lessons learned in developing m-health apps for existing health care programs. Proceedings of the 4th International Workshop on Software Engineering in Health Care (SEHC); 4th International Workshop on Software Engineering in Health Care (SEHC); June 4-5, 2012; Zurich. Lessons learned in developing m-health apps for existing health care programs. 2012 4th International Workshop on Software Engineering in Health Care (SEHC); 2012.
    1. Solar Embedded (Google play) My Headache Log Pro. .
    1. Burton MA, Brady E, Brewer R, Neylan C, Bigham JP, Hurst A. Crowdsourcing subjective fashion advice using VizWiz: challenges and opportunities. 14th international ACM SIGACCESS conference on Computers and accessibility ASSETS ’12; Oct. 22-24, 2012; Boulder, Colorado. 2012.
    1. ROC HCI Group. [2013-03-01]. VizWiz
    1. AI type (Google play) A.I.type EZReader Theme Pack. .
    1. Azevedo P, Correia de Sousa J, Bousquet J, Bugalho-Almeida A, Del Giacco SR, Demoly P, Haahtela T, Jacinto T, Garcia-Larsen V, van der Molen T, Morais-Almeida M, Nogueira-Silva L, Pereira AM, Rodríguez MR, Silva BG, Tsiligianni IG, Yaman H, Yawn B, Fonseca JA, WHO Collaborative Center for Asthma and Rhinitis‚ Montpellier Control of Allergic Rhinitis and Asthma Test (CARAT): dissemination and applications in primary care. Prim Care Respir J. 2013 Mar;22(1):112–6. doi: 10.4104/pcrj.2013.00012.
    1. Control of Allergic Rhinitis and Asthma Test. m.Carat. .
    1. SIGN Executive (Google play) SIGN Asthma Patient Guide .
    1. Hill J, Masding MG. The development of an innovative mobile phone App for Type 1 diabetes alcohol education. Diabet Med. 2013 Mar;30(1):112–112.
    1. APApps (Google play) T1D Friend: Alcohol Guide .
    1. AP Apps (iTunes) [2013-04-26]. Type 1 diabetes friend: alcohol guide .
    1. GExperts Inc (Google play) OnTrack Diabetes .
    1. Wagner R, Ganz A. PAGAS: Portable and Accurate Gait Analysis System. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:280–3. doi: 10.1109/EMBC.2012.6345924.
    1. Canny Technologies (Google play) Osteoarthritis of knee .
    1. Watts S, Mackenzie A, Thomas C, Griskaitis A, Mewton L, Williams A, Andrews G. CBT for depression: a pilot RCT comparing mobile phone vs. computer. BMC Psychiatry. 2013;13:49. doi: 10.1186/1471-244X-13-49.
    1. Global Media Empire (iTunes) [2013-03-01]. VirtualClinic - The Get Happy Program .
    1. Juniper Islet (Google play) Positive Thinking .
    1. Ofcom. [2013-04-26]. Adults media use and attitudes report .

Source: PubMed

3
Tilaa