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Facilitators and Barriers to Using mHealth from Users’ Attitudes: A Qualitative Meta-synthesis

Document Type : Review Articles

Authors

1 Department of Health Education and Health Promotion, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

2 Department of Health Education and Promotion, Research Center for Health Sciences, Institute of Health, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

3 Department of Medical Librarianship, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

Abstract

Background: Regarding demographic, socio-economic differences, and some other infrastructural factors, there are concerns about the access to and use of mobile health technology. This study aims to identify the facilitators and barriers to the use of mobile health from the perspective of users.
Methods: In this qualitative meta-synthesis, electronic databases were systematically searched. Studies included qualitative investigations published by 30th of December 2020 that examined the facilitators or barriers to using mobile health from the users’ point of view. The Critical Appraisal Skills Program checklist was used to evaluate the quality of each study. A steady comparison process has been used to identify similar structures in several studies that have been summarized in thematic constructs.
Results: Six factors were identified as barriers and seven factors as facilitators. Barriers included difficulty in use, inaccessibility, uselessness or inapplicability, lack of adequate skills, communication barriers, and security concerns; facilitating factors included motivational factors, documentation, degree of ease, provider credibility and source of information, perceived usability, social-cultural appropriateness, and perceived benefits.
Conclusion: The findings of this study provide a good basis for information and communication technology practitioners as well as health care services to improve access to and use of mobile health technology by adopting appropriate policies for infrastructure development and social empowerment. Further research focusing on technological, demographic, and geriatrics aspects is suggested.

Keywords

References
  1. Mitchell J, Robinson P, McEvoy M, Gates JJJot, telecare. Telemedicine for the delivery of professional development for health, education and welfare professionals in two remote mining towns. 2001;7(3):174-80. org/10.1258/1357633011936345. PubMed PMID: 11346478.
  2. Mulaydinov FJIO. Digital Economy Is A Guarantee Of Government And Society Development. 2021;20(3):1474-9. doi: 10.17051/ilkonline.2021.03.164.
  3. Beratarrechea A, Lee AG, Willner JM, Jahangir E, Ciapponi A, Rubinstein AJT, et al. The impact of mobile health interventions on chronic disease outcomes in developing countries: a systematic review. 2014;20(1):75-82. doi: 1089/tmj.2012.0328. Epub 2013 Nov 8. PubMed PMID: 24205809
  4. Wang B, Park J, Choi IJKCS. Acceptance of applications for smartphones healthcare key influencers. 2011;11:396-404.
  5. Sim Y-B, Seo Y-J, Kim J-M, Kim S-H, Sung D-HJHP, Management. Factors related to the intent to use the medical application (M-APP) of smart phone of hospital nurses. 2012;22(2):249-62. https://doi.org/10.4332/KJHPA.2012.22.2.249.
  6. Haberer JE, Kiwanuka J, Nansera D, Wilson IB, Bangsberg DRJA, Behavior. Challenges in using mobile phones for collection of antiretroviral therapy adherence data in a resource-limited setting. 2010;14(6):1294-301. DOI: 1007/s10461-010-9720-1. PMID: 20532605, PMCID: PMC2975780
  7. Zurovac D, Sudoi RK, Akhwale WS, Ndiritu M, Hamer DH, Rowe AK, et al. The effect of mobile phone text-message reminders on Kenyan health workers' adherence to malaria treatment guidelines: a cluster randomised trial. 2011;378(9793):795-803. DOI: 1016/S0140-6736(11)60783-6. PMID: 21820166, PMCID: PMC3163847.
  8. Zurovac D, Talisuna AO, Snow RWJPM. Mobile phone text messaging: tool for malaria control in Africa. 2012;9(2):e1001176. DOI: 1371/journal.pmed.1001176. PMID: 22363212, PMCID: PMC3283546.
  9. Becker S, Miron-Shatz T, Schumacher N, Krocza J, Diamantidis C, Albrecht U-VJJm, et al. mHealth 2.0: experiences, possibilities, and perspectives. 2014;2(2):e24. DOI: 2196/mhealth.3328. PMID: 25099752, PMCID: PMC4114478.
  10. Kay M, Santos J, Takane MJWHO. mHealth: New horizons for health through mobile technologies. 2011;64(7):66-71. https://www.who.int/ehealth/mhealth_summit.pdf.
  11. Mechael P, Batavia H, Kaonga N, Searle S, Kwan A, Goldberger A, et al. Barriers and gaps affecting mHealth in low and middle income countries: Policy white paper. 2010.
  12. Chan CV, Kaufman DRJJobi. A technology selection framework for supporting delivery of patient-oriented health interventions in developing countries. 2010;43(2):300-6. DOI: 1016/j.jbi.2009.09.006. PMID: 19796709, PMCID: PMC2838941.
  13. Chib A, van Velthoven MH, Car JJJohc. mHealth adoption in low-resource environments: a review of the use of mobile healthcare in developing countries. 2015;20(1):4-34. DOI: 1080/10810730.2013.864735. PMID: 24673171.
  14. Kabra SK, Lodha R. Management of unresponsive asthma. Indian J Pediatr. 2004 Aug;71(8):729-32. DOI: 1007/BF02730664. PMID: 15345875.
  15. Piette JD, Lun K, Moura Jr LA, Fraser HS, Mechael PN, Powell J, et al. Impacts of e-health on the outcomes of care in low-and middle-income countries: where do we go from here? 2012;90:365-72. DOI: 2471/BLT.11.099069. PMID: 22589570, PMCID: PMC3341688.
  16. Cafazzo JA, Casselman M, Hamming N, Katzman DK, Palmert MRJJomIr. Design of an mHealth app for the self-management of adolescent type 1 diabetes: a pilot study. 2012;14(3):e70. DOI: 2196/jmir.2058. PMID: 22564332, PMCID: PMC3799540.
  17. Kirwan M, Vandelanotte C, Fenning A, Duncan MJJJomIr. Diabetes self-management smartphone application for adults with type 1 diabetes: randomized controlled trial. 2013;15(11):e235. DOI: 2196/jmir.2588. PMID: 24225149, PMCID: PMC3841374.
  18. Stinson JN, Jibb LA, Nguyen C, Nathan PC, Maloney AM, Dupuis LL, et al. Development and testing of a multidimensional iPhone pain assessment application for adolescents with cancer. 2013;15(3):e51. DOI: 2196/jmir.2350. PMID: 23475457, PMCID: PMC3636147.
  19. Carter MC, Burley VJ, Nykjaer C, Cade JEJJomIr. Adherence to a smartphone application for weight loss compared to website and paper diary: pilot randomized controlled trial. 2013;15(4):e32. DOI: 2196/jmir.2283. PMID: 23587561, PMCID: PMC3636323.
  20. Turner-McGrievy GM, Beets MW, Moore JB, Kaczynski AT, Barr-Anderson DJ, Tate DFJJotAMIA. Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program. 2013;20(3):513-8. DOI: 1136/amiajnl-2012-001510. PMID: 23429637, PMCID: PMC3628067.
  21. Dennison L, Morrison L, Conway G, Yardley LJJomIr. Opportunities and challenges for smartphone applications in supporting health behavior change: qualitative study. 2013;15(4):e86. DOI: 2196/jmir.2583. PMID: 23598614, PMCID: PMC3636318.
  22. Liu C, Zhu Q, Holroyd KA, Seng EKJJoS, Software. Status and trends of mobile-health applications for iOS devices: A developer's perspective. 2011;84(11):2022-33. https://doi.org/10.1016/j.jss.2011.06.049.
  23. Connolly SL, Miller CJ, Koenig CJ, Zamora KA, Wright PB, Stanley RL, et al. Veterans’ attitudes toward smartphone app use for mental health care: qualitative study of rurality and age differences. 2018;6(8):e10748. DOI: 2196/10748. PMID: 30135050, PMCID: PMC6125614.
  24. Vogel RI, Niendorf K, Lee H, Petzel S, Lee HY, Geller MAJHcicp. A qualitative study of barriers to genetic counseling and potential for mobile technology education among women with ovarian cancer. 2018;16(1):1-7. DOI: 1186/s13053-018-0095-z. PMID: 29997716, PMCID: PMC6031189.
  25. Burgess K, Atkinson KM, Westeinde J, Crowcroft N, Deeks SL, Wilson KJJoPH. Barriers and facilitators to the use of an immunization application: a qualitative study supplemented with Google Analytics data. 2017;39(3):e118-e26. DOI: 1093/pubmed/fdw032. PMID: 27247122, PMCID: PMC5939700.
  26. Smith R, Menon J, Rajeev JG, Feinberg L, Kumar RK, Banerjee AJBo. Potential for the use of mHealth in the management of cardiovascular disease in Kerala: a qualitative study. 2015;5(11):e009367. DOI: 1136/bmjopen-2015-009367. PMID: 26576813, PMCID: PMC4654349.
  27. Huang KT, Lu TJ, Alizadeh F, Mostaghimi AJHhcsq. Homebound patients’ perspectives on technology and telemedicine: A qualitative analysis. 2016;35(3-4):172-81. DOI: 1080/01621424.2016.1264341. PMID: 27897466.
  28. Buman MP, Epstein DR, Gutierrez M, Herb C, Hollingshead K, Huberty JL, et al. BeWell24: development and process evaluation of a smartphone “app” to improve sleep, sedentary, and active behaviors in US Veterans with increased metabolic risk. 2016;6(3):438-48. DOI: 1007/s13142-015-0359-3. PMID: 27528532, PMCID: PMC4987607.
  29. Wilson PM, Petticrew M, Calnan MW, Nazareth IJIS. Disseminating research findings: what should researchers do? A systematic scoping review of conceptual frameworks. 2010;5(1):1-16. DOI: 1186/1748-5908-5-91. PMID: 21092164, PMCID: PMC2994786.
  30. Barnett-Page E, Thomas JJBmrm. Methods for the synthesis of qualitative research: a critical review. 2009;9(1):1-11. DOI: 1186/1471-2288-9-59. PMID: 19671152, PMCID: PMC3224695.
  31. Hossain LN, Fernandez-Llimos F, Luckett T, Moullin JC, Durks D, Franco-Trigo L, et al. Qualitative meta-synthesis of barriers and facilitators that influence the implementation of community pharmacy services: perspectives of patients, nurses and general medical practitioners. 2017;7(9):e015471. DOI: 1136/bmjopen-2016-015471. PMID: 28877940, PMCID: PMC5588935.
  32. Critical Appraisal Skills Programme, CASP (Qualitative) Checklist. 2018.
  33. Hannes K, Lockwood C, Pearson AJQhr. A comparative analysis of three online appraisal instruments’ ability to assess validity in qualitative research. 2010;20(12):1736-43. DOI: 1177/1049732310378656. PMID: 20671302.
  34. Ciliska D, Thomas H, Buffett CJl. A compendium of critical appraisal tools for public health practice. 2008.
  35. Peng W, Kanthawala S, Yuan S, Hussain SAJBph. A qualitative study of user perceptions of mobile health apps. 2016;16(1):1-11. DOI: 1186/s12889-016-3808-0. PMID: 27842533, PMCID: PMC5109835.
  36. Abelson JS, Kaufman E, Symer M, Peters A, Charlson M, Yeo HJS. Barriers and benefits to using mobile health technology after operation: A qualitative study. 2017;162(3):605-11. DOI: 1016/j.surg.2017.05.007. PMID: 28651777.
  37. Triantafillou V, Layfield E, Prasad A, Deng J, Shanti RM, Newman JG, et al. Patient perceptions of head and neck ambulatory telemedicine visits: a qualitative study. 2021;164(5):923-31. DOI: 1177/0194599820943523. PMID: 32662749.
  38. Hunting G, Shahid N, Sahakyan Y, Fan I, Moneypenny CR, Stanimirovic A, et al. A multi-level qualitative analysis of Telehomecare in Ontario: challenges and opportunities. 2015;15(1):1-15. DOI: 1186/s12913-015-1196-2. PMID: 26645639, PMCID: PMC4673764.
  39. Palcu P, Munce S, Jaglal S, Allin S, Chishtie J, Silverstein A, et al. Understanding patient experiences and challenges to osteoporosis care delivered virtually by telemedicine: a mixed methods study. 2020;31(2):351-61. DOI: 1007/s00198-019-05182-5. PMID: 31760454, PMCID: PMC7010610.
  40. Garnweidner-Holme L, Andersen TH, Sando MW, Noll J, Lukasse MJJm, uHealth. Health care professionals’ attitudes toward, and experiences of using, a culture-sensitive smartphone app for women with gestational diabetes mellitus: qualitative study. 2018;6(5):e9686. DOI: 2196/mhealth.9686. PMID: 29759959, PMCID: PMC5972202.
  41. O’Shea O, Woods C, McDermott L, Buys R, Cornelis N, Claes J, et al. A qualitative exploration of cardiovascular disease patients’ views and experiences with an eHealth cardiac rehabilitation intervention: The PATHway Project. 2020;15(7):e0235274. DOI: 1371/journal.pone.0235274. PMID: 32628688. PMCID: PMC7337342.
  42. Vergouw JW, Smits-Pelser H, Kars MC, van Houwelingen T, van Os-Medendorp H, Kort H, et al. Needs, barriers and facilitators of older adults towards eHealth in general practice: a qualitative study. 2020;21. DOI: 1017/S1463423620000547. PMID: 33263272, PMCID: PMC7737186.
  43. Asklund I, Samuelsson E, Hamberg K, Umefjord G, Sjöström MJJomIr. User experience of an app-based treatment for stress urinary incontinence: qualitative interview study. 2019;21(3):e11296. DOI: 2196/11296. PMID: 30869644, PMCID: PMC6437616.
  44. Slevin P, Kessie T, Cullen J, Butler M, Donnelly S, Caulfield BJQAIJoM. Exploring the barriers and facilitators for the use of digital health technologies for the management of COPD: a qualitative study of clinician perceptions. 2020;113(3):163-72. doi: 10.1093/qjmed/hcz241. PMID: 31545374.
  45. Khatun F, Heywood AE, Ray PK, Bhuiya A, Liaw S-TJIjomi. Community readiness for adopting mHealth in rural Bangladesh: a qualitative exploration. 2016;93:49-56. DOI: 1016/j.ijmedinf.2016.05.010. PMID: 27435947.
  46. Smillie K, Borek NV, Kop MLvd, Lukhwaro A, Li N, Karanja S, et al. Mobile health for early retention in HIV care: a qualitative study in Kenya (WelTel Retain). 2014;13(4):331-8. DOI: 2989/16085906.2014.961939. PMID: 25555099, PMCID: PMC5585007.
  47. Duclos V, Yé M, Moubassira K, Sanou H, Sawadogo NH, Bibeau G, et al. Situating mobile health: a qualitative study of mHealth expectations in the rural health district of Nouna, Burkina Faso. 2017;15(1):41-53. DOI: 1186/s12961-017-0211-y. PMID: 28722558, PMCID: PMC5516845.
  48. Al-Emadi KA, Kassim ZA, Razzaque A. User Friendly and User Satisfaction Model Aligned With FinTech. Innovative Strategies for Implementing FinTech in Banking: IGI Global; 2021. p. 291-301. DOI: 4018/978-1-7998-3257-7.ch017.
  49. Solem IKL, Varsi C, Eide H, Kristjansdottir OB, Mirkovic J, Børøsund E, et al. Patients’ needs and requirements for eHealth pain management interventions: Qualitative study. 2019;21(4):e13205. DOI: 2196/13205. PMID: 30877780, PMCID: PMC6462891.
  50. Cheung W, Chang MK, Lai VSJDss. Prediction of Internet and World Wide Web usage at work: a test of an extended Triandis model. 2000;30(1):83-100. https://doi.org/10.1016/S0167-9236(00)00125-1.
  51. Parker SJ, Jessel S, Richardson JE, Reid MCJBg. Older adults are mobile too! Identifying the barriers and facilitators to older adults’ use of mHealth for pain management. 2013;13(1):1-8. DOI: 1186/1471-2318-13-43. PMID: 23647949, PMCID: PMC3673892.
  52. Bradshaw YW, Fallon KM, Viterna JJRiSS, Mobility. Wiring the world: Access to information technology and development in poor countries. 2005;23:369-92. https://doi.org/10.1016/S0276-5624(05)23012-3.
  53. Hongsermeier TJHMT. Improved access to patient data and improved public perception are two potential benefits of technology-enabled clinical guidelines in electronic medical records. 1997;18(8):66-68.
  54. Mechael PNJIT, Governance, Globalization. The case for mHealth in developing countries. 2009;4(1):103-18.
  55. Dietrich DRJSI. Avatars of whiteness: Racial expression in video game characters. 2013;83(1):82-105.https://doi.org/10.1111/soin.12001.
  56. Spann A, Stewart EJHtaijohiIe. Barriers and facilitators of older people's mHealth usage: A qualitative review of older people's views. 2018;14(3):264-96. doi:10.17011/ht/urn.201811224834.
  57. Brian RM, Ben-Zeev DJAjop. Mobile health (mHealth) for mental health in Asia: objectives, strategies, and limitations. 2014; 10:96-100. doi: 1016/j.ajp.2014.04.006. PMID: 25042960.
  58. Jain N, Singh H, Koolwal GD, Kumar S, Gupta AJAjop. Opportunities and barriers in service delivery through mobile phones (mHealth) for severe mental illnesses in Rajasthan, India: a multi-site study. 2015;14:31-5. DOI: 1016/j.ajp.2015.01.008. PMID: 25701069.
  59. Rogers WA, Fisk AD, Mead SE, Walker N, Cabrera EFJHF. Training older adults to use automatic teller machines. 1996;38(3):425-33. DOI: 1518/001872096778701935. PMID: 8865767.
  60. Pramana G, Parmanto B, Kendall PC, Silk JSJT, e-Health. The SmartCAT: an m-health platform for ecological momentary intervention in child anxiety treatment. 2014;20(5):419-27. DOI: 1089/tmj.2013.0214. PMID: 24579913, PMCID: PMC4011472.
  61. Martin TJJohcftp, underserved. Assessing mHealth: opportunities and barriers to patient engagement. 2012;23(3):935-41. DOI: 1353/hpu.2012.0087. PMID: 24212144.
  62. De Tolly K, Alexander H, Cell-Life CJC-L, Cape Town. Innovative use of cellphone technology for HIV/AIDS behaviour change communications: 3 pilot projects. 2009.
  63. Chib AJMM, Communication. The promise and peril of mHealth in developing countries. 2013;1(1):69-75.https://doi.org/10.1177/2050157912459502.
  64. Skaria GJJoMTiM. MHealth in health information delivery: The Indian scenario. 2013;2(1):26-9. DOI:7309/jmtm.2.1.5.
  65. Thorsteinsen K, Vittersø J, Svendsen GBJIjot, applications. Increasing physical activity efficiently: an experimental pilot study of a website and mobile phone intervention. 2014;2014. DOI: 1155/2014/746232. PMID: 24963290, PMCID: PMC4055100.
  66. Cole SW, Yoo DJ, Knutson BJPo. Interactivity and reward-related neural activation during a serious videogame. 2012;7(3):e33909. DOI: 1371/journal.pone.0033909. PMID: 22442733, PMCID: PMC3307771.
  67. Brown-Johnson CG, Berrean B, Cataldo JKJPe, counseling. Development and usability evaluation of the mHealth Tool for Lung Cancer (mHealth TLC): a virtual world health game for lung cancer patients. 2015;98(4):506-11. DOI: 1016/j.pec.2014.12.006. PMID: 25620075, PMCID: PMC4451946.
  68. Akter S, D'Ambra J, Ray P. User perceived service quality of mHealth services in developing countries. 2010. https://aisel.aisnet.org/ecis2010/134.
  69. Ja-Chul G, Sang-Chul L, Yung-Ho S. Determinants of behavioral intention to mobile banking; Expert Systems with Applications. VoL; 2009. org/10.1016/j.eswa.2009.03.024.
  70. Kharbanda EO, Stockwell MS, Fox HW, Rickert VIJAjoph. Text4Health: a qualitative evaluation of parental readiness for text message immunization reminders. 2009;99(12):2176-8. DOI: 2105/AJPH.2009.161364. PMID: 19833982, PMCID: PMC2775765.
  71. Bezabhe WM, Chalmers L, Bereznicki LR, Peterson GM, Bimirew MA, Kassie DMJPo. Barriers and facilitators of adherence to antiretroviral drug therapy and retention in care among adult HIV-positive patients: a qualitative study from Ethiopia. 2014;9(5):e97353. DOI: 1371/journal.pone.0097353. PMID: 24828585, PMCID: PMC4020856.
  72. Al-Jabri IM, Sohail MSJJoECR. Mobile banking adoption: Application of diffusion of innovation theory. 2012;13(4):379-91.
  73. Moore GC, Benbasat IJIsr. Development of an instrument to measure the perceptions of adopting an information technology innovation. 1991;2(3):192-222.org/10.1287/isre.2.3.192.
  74. McCloskey DWJJoO, Computing EU. The importance of ease of use, usefulness, and trust to online consumers: An examination of the technology acceptance model with older customers. 2006;18(3):47-65. DOI: 10.4018/joeuc.2006070103.
  75. Rogers EMJNY. Diffusion of innovations. Free Press. 2003;551.
  76. Norris AC, Stockdale R, Sharma SJHij. A strategic approach to m-health. 2009;15(3):244-53. DOI: 10.1177/1460458209337445. PMID: 19713398.
  77. Becker AE, Kleinman AJNEJoM. Mental health and the global agenda. 2013;369(1):66-73. DOI: 10.1056/NEJMc1309899. PMID: 24088110.
  78. Atkinson NL, Gold RSJAJoHB. The promise and challenge of eHealth interventions. 2002;26(6):494-503. DOI: 5993/ajhb.26.6.10. PMID: 12437024.
  79. Gurley D, Cohen P, Pine DS, Brook JJJoAD. Discriminating depression and anxiety in youth: A role for diagnostic criteria. 1996;39(3):191-200. DOI: 1016/0165-0327(96)00020-1. PMID: 8856423.
  80. Blaya JA, Fraser HS, Holt BJHA. E-health technologies show promise in developing countries. 2010;29(2):244-51. DOI: 1377/hlthaff.2009.0894. PMID: 20348068.
  81. Razzouk D, Sharan P, Gallo C, Gureje O, Lamberte EE, de Jesus Mari J, et al. Scarcity and inequity of mental health research resources in low-and-middle income countries: a global survey. 2010;94(3):211-20. DOI: 10.1016/j.healthpol.2009.09.009. PMID: 19846235.
  82. Alonso J, Buron A, Bruffaerts R, He Y, Posada‐Villa J, Lepine JP, et al. Association of perceived stigma and mood and anxiety disorders: results from the World Mental Health Surveys. 2008;118(4):305-14. DOI: 1111/j.1600-0447.2008.01241.x. PMID: 18754833, PMCID: PMC3040096.
  83. Milner A, De Leo DJBotWHO. Suicide research and prevention in developing countries in Asia and the Pacific. 2010;88:795-6. DOI: 2471/BLT.09.070821. PMID: 20931067, PMCID: PMC2947038.
  84. Van Eerde W, Thierry HJJoap. Vroom's expectancy models and work-related criteria: A meta-analysis. 1996;81(5):575. org/10.1037/0021-9010.81.5.575
Journal of Health Sciences & Surveillance System
Volume 11, Issue 1
January 2023
Pages 9-25
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