Mobile Health Applications for Osteoporosis Support Available on the Market: A Systematic Review

Reza Safdari, Majid Alikhani, Foziyeh Tahmasbi, Zohreh Javanmard, Saeedeh Heydarian
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Abstract

Introduction: The use of mobile applications (apps) become widespread and Provide many benefits especially in healthcare. According to the World Health Organization, osteoporosis is one of the most common diseases of elderly in the world. Like other chronic conditions, disease self-management can prove fruitful. Using a mobile application for Osteoporosis can improve patient care and self-management by encouraging patients to take a more active role in their health.

Material and Methods: This study presents a systematic review of mHealth applications, available on Google Play Store, Bazaar market (as a local market) and also Apple App Store, for both the English and Persian speakers. The assessment criteria, including content, visual aids, reminders, health warnings, social and design of selected apps, were tested during July 2019.

Results: Reviewing the 19 included applications showed that the most and least focus of apps content was on exercise with 84% repetition and the osteoporosis fracture that no program addressed this issue separately. Findings on reminders, health warnings, and visual aids were not very encouraging (available in 11% apps). Reminders were more common in English-speaking apps than Persian-speaking ones, and Visual aids, one of the benefits of mobile apps over paper logbooks, were provided only in2 apps. The opportunity to share data in social networks was available in 26% of apps, and in the design section, most of the apps have no significant flaws, but 74% of cases did not provide any clear instructions required for the elderly.

Conclusion:The review shows that there are rather few products on offer and the ones that are available display low quality, poor performance, and evidence-based information is also insufficiently used. Further efforts are required to collect data that will support the design of validated evidence-based educational functions for mHealth apps.


Keywords

m-Health; Self-Management; Osteoporosis; Mobile Applications

References

Yavari K, Basakha M, Sadeghi H, Naseri AR. Economic Aspects of Ageing. Iranian Journal of Ageing 2015; 10(1): 92-105[Article in Persian].

Demontiero O, Vidal C, Duque G. Aging and bone loss new insights for the clinician. Therapeutic advances in musculoskeletal disease 2012; 4(2): 61-76.

who.org [Internet]. Judith Escribano: Aging and life course [Cited 2019 Aug 21]. Available from: https://www.who.int/ageing/en/

Sharifi N, Majlessi F, Montazeri A, Shojaeizadeh D, Sadeghi R. Prevention of osteoporosis in female students based on the Orem self-care model. Electron Physician 2017; 9(10): 5465-5471.

Choi W, Zheng H, Franklin P, Tulu B. mHealth technologies for osteoarthritis self-management and treatment: A systematic review. Health Informatics J 2019; 25(3): 984-1003.

Sözen T, Özışık L, Başaran NÇ. An overview and management of osteoporosis. Eur J Rheumatol 2017; 4(1): 46-56.

Hamine S, Gerth-Guyette E, Faulx D, Green BB, Ginsburg AS. Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. J Med Internet Res 2015; 17(2): e52.

Mohammadzadeh N, Safdari R. Patient monitoring in mobile health: opportunities and challenges. Medical archives 2014; 68(1): 57-60.

Haute Autorité de santé [Internet].Good Practice Guidelines on Health Apps and Smart Devices (Mobile Health or mHealth). Saint-Denis: Public Relations & Information Department. [Cited 2019 Dec 27] Available from: https://www.has-sante.fr/upload/docs/application/pdf/2017-03/dir1/good_practice_guidelines_on_health _apps_and_smart_devices_mobile_health_or_mhealth.pdf. 5 July 2019, 2016

Wu F, Laslett LL, Wills K, et al. Effects of individualized bone density feedback and educational interventions on osteoporosis knowledge and self-efficacy: a 12-yr prospective study. Journal of clinical densitometry 2014; 17(4): 466-72.

Zargarzadeh P, Ehteshami A, Mohammadi-Sichani M. A Contribution into Developing a Model for Prostate Cancer Self-Care Mobile Application. Medical archives 2018; 72(5): 344-7.

Lu J, Wu D, Mao M, et al. Recommender system application developments: A survey. Decision Support Systems 2015; 74: 12-32.

Heijmans M, Waverijn G, Rademakers J, et al. Functional, communicative and critical health literacy of chronic disease patients and their importance for self-management. Patient Education and Counseling 2015; 98(1): 41-8.

Ravn Jakobsen P, Hermann AP, Sondergaard J, et al. Help at hand: Women's experiences of using a mobile health application upon diagnosis of asymptomatic osteoporosis. SAGE open medicine 2018; 6(1):1-11.

Dagan N, Cohen-Stavi C, Leventer-Roberts M, et al. External validation and comparison of three prediction tools for risk of osteoporotic fractures using data from population based electronic health records: retrospective cohort study. British Medical Journal (Clinical research ed) 2017; 356:i6755

Wildenbos GA, Jaspers MWM, Schijven MP, et al. Mobile health for older adult patients: Using an aging barriers framework to classify usability problems. International Journal of Medical Informatics 2019; 124: 68-77

Charalambous CP, Mosey C, Johnstone E, et al. Improving osteoporosis assessment in the fracture clinic. The Annals of the Royal College of Surgeons of England 2009; 91(7): 596-8.

Van Velthoven MH, Smith J, Wells G, et al. Digital health app development standards: a systematic review protocol. BMJ Open 2018;8:e022969.

Rudin RS, Fanta CH, Predmore Z, et al. Core components for a clinically integrated mHealth app for asthma symptom monitoring. Applied clinical informatics 2017; 8(4): 1031-43.

Boudreaux ED, Waring ME, Hayes RB, et al. Evaluating and selecting mobile health apps: strategies for healthcare providers and healthcare organizations. Transl Behav Med. 2014; 4(4):363-71.

Formagini, T.D., Ervilha, R.R., Machado, N.M., et al. A review of smartphone apps for smoking cessation available in Portuguese. Cadernos de saude publica 2017; 33(2): e00178215.

Wolf JA, Moreau JF, Akilov O, et al. Diagnostic inaccuracy of smartphone applications for melanoma detection. JAMA Dermatol 2013; 149(4):422-6.

Zimbudzi E, Lo C, Misso M, et al. Effectiveness of management models for facilitating self-management and patient outcomes in adults with diabetes and chronic kidney disease. Syst Rev. 2015;4:81.

Weingarten SR, Henning JM, Badamgarav E, et al. Interventions used in disease management programmes for patients with chronic illness-which ones work? Meta-analysis of published reports. BMJ (Clinical research ed) 2002; 325(7370):925.

Rossi MG, Bigi S. mHealth for diabetes support: a systematic review of apps available on the Italian market. Mhealth 2017; 3:16.

Hoyt RE, Cruz RW, Fleury R. Mobile Technology and mHealth. Florida: informatics education; 2014: 268-9.

Bright TJ, Bakken S, Johnson SB. Heuristic evaluation of eNote: an electronic notes system. AMIA Annu Symp Proc 2006;2006:864.7

Nouri R, R Niakan Kalhori S, Ghazisaeedi M, Marchand G, Yasini M. Criteria for assessing the quality of mHealth apps: a systematic review. J Am Med Inform Assoc. 2018;25(8):1089-1098.

Dennis SM, Zwar N, Griffiths R, et al. Chronic disease management in primary care: from evidence to policy. Med J Aust. 2008;188(S8):S53-S56.

Grover A, Joshi A. An overview of chronic disease models: a systematic literature review. Glob J Health Sci. 2014; 7(2):210-227.

Albrecht UV, Von Jan U, Jungnickel T, et al. App-synopsis – standard reporting for medical apps. Stud Health Technol Inform 2013; 192:1154.

Raybould G, Babatunde O, Evans AL, et al. Expressed information needs of patients with osteoporosis and/or fragility fractures: a systematic review. Arch Osteoporos. 2018; 13(1):55.

Sànchez-Riera L, Wilson N. Fragility Fractures & Their Impact on Older People. Best Pract Res Clin Rheumatol 2017; 31(2):169-19.

Zimbudzi E, Lo C, Misso M, et al. Effectiveness of management models for facilitating self-management and patient outcomes in adults with diabetes and chronic kidney disease. Syst Rev. 2015; 4:81.

Reynolds R, Dennis S, Hasan I, et al. A systematic review of chronic disease management interventions in primary care. BMC Fam Pract. 2018; 19(1):11.

Kim BY, Sharafoddini A, Tran N, et al. Consumer Mobile Apps for Potential Drug-Drug Interaction Check: Systematic Review and Content Analysis Using the Mobile App Rating Scale (MARS). JMIR Mhealth Uhealth. 2018; 6(3):e74.

Wu Y, Zhou Y, Wang X, et al. A Comparison of Functional Features in Chinese and US Mobile Apps for Diabetes Self-Management: A Systematic Search in App Stores and Content Analysis. JMIR Mhealth Uhealth 2019 Aug 28;7(8):e13971.

Hood M, Wilson R, Corsica J, et al. What do we know about mobile applications for diabetes self-management? A review of reviews. J Behav Med 2016; 39(6):981-994.

El-Gayar O, Timsina P, Nawar N, et al. Mobile applications for diabetes self-management: status and potential. J Diabetes Sci Technol. 2013; 7(1):247-262.

Moore S, Tassé AM, Thorogood A, et al. Consent Processes for Mobile App Mediated Research: Systematic Review. JMIR Mhealth Uhealth. 2017 Aug 30;5(8):e126.

Wisniewski H, Liu G, Henson P, et al. Understanding the quality, effectiveness and attributes of top-rated smartphone health apps. Evid Based Ment Health 2019; 22(1):4-9.

Alessa T, Hawley MS, Hock ES, et al. Smartphone Apps to Support Self-Management of Hypertension:Review and Content Analysis. JMIR Mhealth Uhealth 2019; 7(5): 1-14.

Erfani M, Mesbah, A, Kruchten, P. Real Challenges in Mobile App Development. In: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement. Baltimore, MD, USA 2013: 15-24.

Miranda JJ, Kinra S, Casas JP, et al. Non-communicable diseases in low- and middle-income countries: context, determinants and health policy. Trop Med Int Health. 2008;13(10):1225-34




DOI: https://doi.org/10.30699/fhi.v9i1.240

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