A systematic review into the assessment of medical apps:  motivations, challenges, recommendations and  methodological aspect

Alamoodi, A. H.

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Type :	article
Subject :	R Medicine (General)
Main Author :	Alamoodi, A. H.
Additional Authors :	Garfan, Salem Zaidan, B. B. Zaidan, A. A. Shuwandy, Moceheb Lazam Alsalem, M. A. Mohammed, Ali Aleesa, A. M. Albahri, O. S. Al-Hussein, Ward Ahmed Alobaidi, O. R.
Title :	A systematic review into the assessment of medical apps: motivations, challenges, recommendations and methodological aspect

Place of Production :	Tanjong Malim
Publisher :	Fakulti Seni, Komputeran dan Industri Kreatif
Year of Publication :	2020
Corporate Name :	Universiti Pendidikan Sultan Idris
PDF Full Text :	Login required to access this item.

Abstract : Universiti Pendidikan Sultan Idris

Recent years have shown significantly pervasive interest in mobile applications (hereinafter “apps”). The number and popularity of these apps are dramatically increasing. Even though mobile apps are diverse, countless ones are available through many platforms. Some of these apps are not useful nor do they possess rich content, which benefits end users as expected, especially in medical-related cases. This research aims to review and analyze articles associated with medical app assessment across different platforms. This research also aimed to provide the best practices and identify the academic challenges, motivations and recommendations related with quality assessments. In addition, a methodological approach followed in previous research in this domain was also discussed to give some insights for future comers with what to expect. We systematically searched articles on topics related to medical app assessment. The search was conducted on five major databases, namely, Science Direct, Springer, Web of Science, IEEE Xplore and PubMed from 2009 to September 2019. These indices were considered sufficiently extensive and reliable to cover our scope of the literature. Articles were selected on the basis of our inclusion and exclusion criteria (n = 72). Medical app assessment is considered a major topic which warrants attention. This study emphasizes the current standpoint and opportunities for research in this area and boosts additional efforts towards the understanding of this research field.

References

1. Holl K, Elberzhager F. Mobile application quality assurance. Adv Comput. 2019;112:1–77 Elsevier.

2. Bahadori S, Wainwright TW, Ahmed OH. Smartphone apps for total hip replacement and total knee replacement surgery patients: a systematic review. Disabil Rehabil. 2018:1–6.

3. Orsini G, Bade D, Lamersdorf W. Context-aware computation offloading for mobile cloud computing: requirements analysis, survey and design guideline. Procedia Comput Sci. 2015;56:10–7.

4. Beam L, Burrows B, Dobey Z, Poser R, Sopko M. RecycMe: the Ohio State University recycling phone application. 2013.

5. Ouhbi S, Fernández-Alemán JL, Pozo JR, El Bajta M, Toval A, Idri A. Compliance of blood donation apps with mobile OS usability guidelines. J Med Syst. 2015;39(6):63.

6. Kim MS, Park JH, Park K-Y. Development and effectiveness of a drug dosage calculation training program using cognitive loading theory based on smartphone application. J Korean Acad Nurs. 2012;42(5):689–98.

7. Nayebi F, Desharnais J-M, Abran A. The state of the art of mobile application usability evaluation. In 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE; 2012, p. 1–4.

8. Chen Z-S, Li R, Chen X, Xu H. A survey study on consumer perception of mobile-commerce applications. Procedia Environ Sci. 2011;11:118–24.

9. Tang AK. A systematic literature review and analysis on mobile apps in m-commerce: implications for future research. Electron Commer Res Appl. 2019;37:100885.

10. Darras KE, van Merriënboer JJG, Toom M, Roberson ND, de Bruin ABH, Nicolaou S, et al. Developing the evidence base for Mlearning in undergraduate radiology education: identifying learner preferences for Mobile apps. Can Assoc Radiol J. 2019;70(3):320–6.

11. Albrecht U-V, Hillebrand U, von Jan U. Relevance of trust marks and CE labels in German-language store descriptions of health apps: analysis. JMIR mHealth and uHealth. 2018;6(4):e10394.

12. Anderson N, Steele J, O'Neill L-A, Harden LA. Pokémon Go: mobile app user guides. Br J Sports Med. 2016;2016:096762.

13. Ahtinen A, Isomursu M, Huhtala Y, Kaasinen J, Salminen J, Häkkilä J. Tracking outdoor sports–user experience perspective. In: Aarts E, Crowley JL, Ruyter B, Gerhäuser H, Pflaum A, Schmidt J, Wichert R, editors. European Conference on Ambient Intelligence. Berlin: Springer; 2008. p. 192–209.

14. Lior LN. Writing for interaction: crafting the information experience for web and software apps. Newnes. 2013, Writing Text for Interaction.

15. Cortimiglia MN, Ghezzi A, Renga F. Mobile applications and their delivery platforms. IT Prof. 2011;13(5):51–6.

16. Beimborn D, Palitza M. Enterprise app stores for mobile applications-development of a benefits framework. 2013.

17. Harman M, Jia Y, Zhang Y. App store mining and analysis: MSR for app stores. In Proceedings of the 9th IEEE Working Conference on Mining Software Repositories. IEEE Press; 2012, p. 108–111.

18. Freier A. App revenue reaches $92.1 billion in 2018 driven by mobile gaming apps. Business Apps. 2018;13(09).

19. Cheney S, Thompson E. The 2017–2022 app economy forecast: 6 billion devices, $157 billion in spend & more. App Annie. 2018.

20. Chen J, Cade JE, Allman-Farinelli M. The most popular smartphone apps for weight loss: a quality assessment. JMIR mHealth uHealth. 2015;3(4):e104.

21. Kim BY, Sharafoddini A, Tran N, Wen EY, Lee J. 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.

22. Haskins BL, Lesperance D, Gibbons P, Boudreaux ED. A systematic review of smartphone applications for smoking cessation. Transl Behav Med. 2017;7(2):292–9.

23. Ali EE, Teo AKS, Goh SXL, Chew L, Yap KY-L. MedAd-AppQ: a quality assessment tool for medication adherence apps on iOS and android platforms. Res Soc Adm Pharm. 2018;14(12):1125–33.

24. Muntaner-Mas A, Martinez-Nicolas A, Lavie CJ, Blair SN, Ross R, Arena R, et al. A systematic review of fitness apps and their potential clinical and sports utility for objective and remote assessment of cardiorespiratory fitness. Sports Med. 2019;49(4):587–600.

25. Zhao J, Freeman B, Li M. How do infant feeding apps in China measure up? A Content Quality Assessment. JMIR mHealth uHealth. 2017;5(12):e186.

26. Weekly T, Walker N, Beck J, Akers S, Weaver M. A review of apps for calming, relaxation, and mindfulness interventions for pediatric palliative care patients. Children. 2018;5(2):16.

27. Nicholas J, Larsen ME, Proudfoot J, Christensen H. Mobile apps for bipolar disorder: a systematic review of features and content quality. J Med Internet Res. 2015;17(8):e198.

28. Huckvale K, Car M, Morrison C, Car J. Apps for asthma self-management: a systematic assessment of content and tools. BMC Med. 2012;10(1):144.

29. Zhang MW, Ho RC, Hawa R, Sockalingam S. Analysis of the information quality of bariatric surgery smartphone applications using the silberg scale. Obes Surg. 2016;26(1):163–8.

30. Bergeron D, et al. Mobile applications in neurosurgery: a systematic review, quality audit, and survey of Canadian neurosurgery residents. World neurosurg. 2019.

31. van Galen L, Xu X, Koh M, Thng S, Car J. Eczema apps conformance with clinical guidelines: a systematic assessment of functions, tools and content. Br J Dermatol. 2019.

32. Larco A, Enríquez F, Luján-Mora S. Review and evaluation of special education iOS Apps using MARS. In 2018 IEEE World Engineering Education Conference (EDUNINE). IEEE; 2018, p. 1–6.

33. Larco A, Montenegro C, Luján-Mora S, Quality improvement criteria of apps in Spanish for people with disabilities. In 2018 4th International Conference on Information Management (ICIM). IEEE; 2018, p. 260–264.

34. Alamoodi A, et al. A review of data analysis for early-childhood period: taxonomy, motivations, challenges, recommendation, and methodological aspects. IEEE Access. 2019;7:51069–103.

35. Burgers C, Brugman BC, Boeynaems A. Systematic literature reviews: four applications for interdisciplinary research. J Pragmat. 2019;145:102–9.

36. Loureiro SMC, Romero J, Bilro RG. Stakeholder engagement in co-creation processes for innovation: a systematic literature review and case stud. J Bus Res. 2019.

37. Kushwah S, Dhir A, Sagar M, Gupta B. Determinants of organic food consumption. A systematic literature review on motives and barriers. Appetite. 2019;143:104402.

38. Daigneault P-M, Jacob S, Ouimet M. Using systematic review methods within a Ph. D. Dissertation in political science: challenges and lessons learned from practice. Int J Soc Res Methodol. 2014;17(3):267–83.

39. Ain N, Vaia G, DeLone WH, Waheed M. Two decades of research on business intelligence system adoption, utilization and success – a systematic literature review. Decis Support Syst. 2019;125:113113.

40. Dani VS, Freitas CMDS, Thom LH. Ten years of visualization of business process models: a systematic literature review. Comput Stand Inter. 2019.

41. Owens OL, Beer JM, Reyes LI, Thomas TL. Systematic review of commercially available mobile phone applications for prostate cancer education. Am J Men ’s Health. 2019;13(1): 1557988318816912.

42. Huckvale K, Morrison C, Ouyang J, Ghaghda A, Car J. The evolution of mobile apps for asthma: an updated systematic assessment of content and tools. BMC Med. 2015;13(1):58.

43. El-Gayar O, Timsina P, Nawar N, Eid W. Mobile applications for diabetes self-management: status and potential. J Diabetes Sci Technol. 2013;7(1):247–62.

44. Huang Z, Lum E, Jimenez G, Semwal M, Sloot P, Car J. Medication management support in diabetes: a systematic assessment of diabetes self-management apps. BMC Med. 2019;17(1):127.

45. Dayer L, Heldenbrand S, Anderson P, Gubbins PO, Martin BC. Smartphone medication adherence apps: potential benefits to patients and providers. J Am Pharm Assoc. 2013;53(2):172–81.

46. Nguyen AD, Baysari MT, Kannangara DRW, Tariq A, Lau AYS, Westbrook JI, et al. Mobile applications to enhance selfmanagement of gout. Int J Med Inform. 2016;94:67–74.

47. Payo RM, Harris J, Armes J. Prescribing fitness apps for people with cancer: a preliminary assessment of content and quality of commercially available apps. J Cancer Surviv. 2019;13:1–9.

48. Rusin M, Årsand E, Hartvigsen G. Functionalities and input methods for recording food intake: a systematic review. Int J Med Inform. 2013;82(8):653–64.

49. Bhattarai P, Newton-John T, Phillips JL. Quality and usability of arthritic pain self-management apps for older adults: a systematic review. Pain Med. 2017;19(3):471–84.

50. Devan H, Farmery D, Peebles L, Grainger R. Evaluation of selfmanagement support functions in apps for people with persistent pain: systematic review. JMIR mHealth uHealth. 2019;7(2): e13080.

51. Metelmann B, Metelmann C, Schuffert L, Hahnenkamp K, Brinkrolf P. Medical correctness and user friendliness of available apps for cardiopulmonary resuscitation: systematic search combined with guideline adherence and usability evaluation. JMIR mHealth uHealth. 2018;6(11):e190.

52. Taki S, Campbell KJ, Russell CG, Elliott R, Laws R, DenneyWilson E. Infant feeding websites and apps: a systematic assessment of quality and content. Interact J Med Res. 2015;4(3):e18.

53. Lee H, Sullivan SJ, Schneiders AG, Ahmed OH, Balasundaram AP, Williams D, et al. Smartphone and tablet apps for concussion road warriors (team clinicians): a systematic review for practical users. Br J Sports Med. 2015;49(8):499–505.

54. Moglia ML, Nguyen HV, Chyjek K, Chen KT, Castaño PM. Evaluation of smartphone menstrual cycle tracking applications using an adapted APPLICATIONS scoring system. Obstet Gynecol. 2016;127(6):1153–60.

55. Brouard B, Bardo P, Bonnet C, Mounier N, Vignot M, Vignot S. Mobile applications in oncology: is it possible for patients and healthcare professionals to easily identify relevant tools? Ann Med. 2016;48(7):509–15.

56. Latorre GF, de Fraga R, Seleme MR, Mueller CV, Berghmans B. An ideal e-health system for pelvic floor muscle training adherence: systematic review. Neurourol Urodyn. 2019;38(1):63–80

57. Luo D, Wang P, Lu F, Elias J, Sparks JA, Lee YC. Mobile apps for individuals with rheumatoid arthritis: a systematic review. JCR: J Clin Rheumatol. 2019;25(3):133–41.

58. Sun C, Malcolm JC, Wong B, Shorr R, Doyle M-A. Improving glycemic control in adults and children with type 1 diabetes with the use of smartphone-based mobile applications: a systematic review. Can J Diabetes. 2019;43(1):51–8. e3.

59. Bry LJ, Chou T, Miguel E, Comer JS. Consumer smartphone apps marketed for child and adolescent anxiety: a systematic review and content analysis. Behav Ther. 2018;49(2):249–61.

60. Milani P, Coccetta CA, Rabini A, Sciarra T, Massazza G, Ferriero GJP. Mobile smartphone applications for body position measurement in rehabilitation: a review of goniometric tools. PM&R. 2014;6(11):1038–43.

61. Kalz M, et al. Smartphone apps for cardiopulmonary resuscitation training and real incident support: a mixed-methods evaluation study. J Med Internet Res. 2014;16(3):e89.

62. Piran P, et al. Medical mobile applications for stroke survivors and caregivers. J Stroke Cerebrovasc Dis. 2019;28(11):104318.

63. Adam A, Hellig JC, Perera M, Bolton D, Lawrentschuk N. ‘Prostate Cancer risk Calculator’ mobile applications (apps): a systematic review and scoring using the validated user version of the Mobile application rating scale (uMARS). World J Urol. 2018;36(4):565–73.

64. Schumer H, Amadi C, Joshi A. Evaluating the dietary and nutritional apps in the Google play store. Healthcare Inform Res. 2018;24(1):38–45.

65. Torous J, Levin ME, Ahern DK, Oser ML. Cognitive behavioral mobile applications: clinical studies, marketplace overview, and research agenda. Cogn Behav Pract. 2017;24(2):215–25.

66. Anthony Berauk VL, Murugiah MK, Soh YC, Chuan Sheng Y, Wong TW, Ming LC. Mobile health applications for caring of older people: review and comparison. Ther Innov Regul Sci. 2018;52(3):374–82.

67. Meghani SH, MacKenzie MA, Morgan B, Kang Y, Wasim A, Sayani S. Clinician-targeted mobile apps in palliative care: a systematic review. J Palliat Med. 2017;20(10):1139–47.

68. Rincon E, Monteiro-Guerra F, Rivera-Romero O, DorronzoroZubiete E, Sanchez-Bocanegra CL, Gabarron E. Mobile phone apps for quality of life and well-being assessment in breast and prostate cancer patients: systematic review. JMIR mHealth uHealth. 2017;5(12):e187.

69. Chen E, Mangone ER. A systematic review of apps using mobile criteria for adolescent pregnancy prevention (mCAPP). JMIR mHealth uHealth. 2016;4(4):e122.

70. Alyami M, Giri B, Alyami H, Sundram F. Social anxiety apps: a systematic review and assessment of app descriptors across mobile store platforms. Evid-Based Ment Health. 2017;20(3):65–70.

71. Park JYE, Li J, Howren A, Tsao NW, De Vera M. Mobile phone apps

targeting medication adherence: quality assessment and content analysis of user reviews. JMIR mHealth uHealth. 2019;7(1):e11919.

72. Byambasuren O, Sanders S, Beller E, Glasziou P. Prescribable mHealth apps identified from an overview of systematic reviews. Digit Med. 2018;1(1):12.

73. Short CE, Finlay A, Sanders I, Maher C. Development and pilot evaluation of a clinic-based mHealth app referral service to support adult cancer survivors increase their participation in physical activity using publicly available mobile apps. BMC Health Serv Res. 2018;18(1):27.

74. Bender JL, Yue RYK, To MJ, Deacken L, Jadad AR. A lot of action, but not in the right direction: systematic review and content analysis of smartphone applications for the prevention, detection, and management of cancer. J Med Internet Res. 2013;15(12):e287.

75. Bychkov D, Young SD. Facing up to nomophobia: a systematic review of mobile phone apps that reduce Smartphone usage. In Big data in engineering applications. Springer; 2018, p. 161–171.

76. Olivero E, Bert F, Thomas R, Scarmozzino A, Raciti IM, Gualano MR, et al. E-tools for hospital management: an overview of smartphone applications for health professionals. Int J Med Inform. 2019;124:58–67.

77. Rodríguez AQ, Wägner AM. Mobile phone applications for diabetes management: a systematic review. Endocrinol Diab Nutr. 2019;66(5):330–7.

78. Reynoldson C, Stones C, Allsop M, Gardner P, Bennett MI, Closs SJ, et al. Assessing the quality and usability of smartphone apps for pain self-management. Pain Med. 2014;15(6):898–909.

79. Rajani NB, Weth D, Mastellos N, Filippidis FT. Adherence of popular smoking cessation mobile applications to evidence-based guidelines. BMC Public Health. 2019;19(1):743.

80. Xiao Q, Wang Y, Sun L, Lu S, Wu Y. Current status and quality assessment of cardiovascular diseases related smartphone apps in China. Nurs Inform. 2016;225:1030–1.

81. Sedrati H, Nejjari C, Chaqsare S, Ghazal H. Mental and physical mobile health apps. Procedia Comput Sci. 2016;100:900–6.

82. Huckvale K, Prieto JT, Tilney M, Benghozi P-J, Car J. Unaddressed privacy risks in accredited health and wellness apps: a crosssectional systematic assessment. BMC Med. 2015;13(1):214.

83. Larco A, Yanez C, Almendáriz V, Luján-Mora S. Thinking about inclusion: Assessment of multiplatform apps for people with disability. In 2018 IEEE Global Engineering Education Conference (EDUCON). IEEE; 2018, pp. 350–354.

84. Seabrook HJ, Stromer JN, Shevkenek C, Bharwani A, de Grood J, Ghali WA. Medical applications: a database and characterization of apps in Apple iOS and Android platforms. BMC Res Notes. 2014;7(1):573.

85. Buechi R, et al. Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis. BMJ Open. 2017;7(12):e018280.

86. Mangone ER, Lebrun V, Muessig KE. Mobile phone apps for the prevention of unintended pregnancy: a systematic review and content analysis. JMIR mHealth uHealth. 2016;4(1):e6.

87. Williams JP, Schroeder D. Popular glucose tracking apps and use of mHealth by Latinos with diabetes. JMIR mHealth uHealth. 2015;3(3):e84.

88. Con D, De Cruz P. Mobile phone apps for inflammatory bowel disease self-management: a systematic assessment of content and tools. JMIR mHealth uHealth. 2016;4(1):e13.

89. Linares-Del Rey M, Vela-Desojo L, Cano-de la Cuerda R. Mobile phone applications in Parkinson’s disease: a systematic review. Neurología (English Edition). 2018.

90. Larsen ME, Nicholas J, Christensen H. A systematic assessment of smartphone tools for suicide prevention. PloS One. 2016;11(4): e0152285.

91. Huckvale K, Adomaviciute S, Prieto JT, Leow MK-S, Car J. Smartphone apps for calculating insulin dose: a systematic assessment. BMC Med. 2015;13(1):106.

92. Bachmann DJ, Jamison NK, Martin A, Delgado J, Kman NE. Emergency preparedness and disaster response: there’s an app for that. Prehosp Dis Med. 2015;30(5):486–90.

93. Bakker D, Kazantzis N, Rickwood D, Rickard N. Mental health smartphone apps: review and evidence-based recommendations for future developments. JMIR Ment Health. 2016;3(1):e7.

94. Wurzer P, Parvizi D, Lumenta DB, Giretzlehner M, Branski LK, Finnerty CC, et al. Smartphone applications in burns. Burns. 2015;41(5):977–89.

95. Hayes W, Naziri Q, De Tolla JE, Akamnonu CP, Merola AA, Paulino C. A systematic review of all smart phone applications specifically aimed for use as a scoliosis screening tool. Spine J. 2013;13(9):S38.

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