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Investigating the attitude of patients with chronic diseases about using mobile health

Published online by Cambridge University Press:  13 February 2020

Reza Abbasi Open the ORCID record for Reza Abbasi [Opens in a new window] ,
Sahar Zare  and
Leila Ahmadian
Reza Abbasi
Affiliation:
Health Information Management Research Center, Kashan University of Medical Sciences, Kashan, Iran Department of Health Information Sciences, Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran
Sahar Zare
Affiliation:
Health Information Management Research Center, Kashan University of Medical Sciences, Kashan, Iran
Leila Ahmadian*
Affiliation:
Department of Health Information Sciences, Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
*
Author for correspondence: Leila Ahmadian, E-mail: AhmadianLe@yahoo.com
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Abstract

Background

Mobile health (mHealth) due to its popularity and accessibility can be widely applied in different health areas such as the management of chronic diseases. However, its success depends on the acceptance of their users. Therefore, the aim of this study was to survey the attitudes of patients with chronic disease toward mHealth technology and their willingness to use it.

Methods

This study was conducted within a 2-year period (2016–2018) to determine and compare the attitude and willingness of patients with asthma, diabetes, and multiple sclerosis (MS) toward using mHealth technology in a province in Iran.

Results

In total, 222 patients participated in this study. More than 93 percent of the patients with diabetes and MS, and 65 percent of the asthmatic patients preferred using mHealth services rather than consulting a physician (p < .0001). About 98, 94, and 49 percent of the MS, diabetic, and asthmatic patients, respectively felt comfortable if their health conditions checked by physicians through mHealth technology (p < .0001).

Conclusions

Our results showed that the majority of the patients felt comfortable and preferred using mHealth technology rather than consulting the physicians. The attitudes of diabetic and MS patients toward mHealth technology were rather more positive compared to asthmatic patient attitude. These results may be helpful for the developers of mHealth technology, and researchers who design mHelath interventions for patients with chronic disease.

Keywords

Mobile healthmHealthchronic diseasediabetesasthmamultiple sclerosisattitude

Information

Type
Assessment
Information
International Journal of Technology Assessment in Health Care , Volume 36 , Issue 2 , April 2020 , pp. 139 - 144
Copyright
Copyright © Cambridge University Press 2020

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References

Pathman, DE, Konrad, TR, Freed, GL et al. (1996) The awareness-to-adherence model of the steps to clinical guideline compliance. The case of pediatric vaccine recommendations. Med Care. 34, 873–889.CrossRefGoogle ScholarPubMed
Institute of Medicine Committee on Identifying Priority Areas for Quality Improvement (2003). In: Adams, K, Corrigan, JM, eds. Priority areas for national action: Transforming health care quality. Washington, DC: National Academies Press (US). Chapter 3: Priority areas for quality improvement, pp. 48–54.Google Scholar
Brown, M, Bussel, LJ (2010) Medication adherence: WHO cares? Mayo Clin Proc. 86, 304–314.CrossRefGoogle Scholar
World Health Organization (WHO) (2018) Management of noncommunicable diseases. Geneva: World Health Organization. https://www.who.int/activities/management-of-noncommunicable-diseases (Accessed April 2018).Google Scholar
Viswanathan, M, Golin, CE, Jones, CD et al. (2012) Interventions to improve adherence to self-administered medications for chronic diseases in the United States: A systematic review. Ann Intern Med. 157, 785–795.CrossRefGoogle ScholarPubMed
Abbasi, R, Ahmadian, L, Baloochi, M et al. (2018) Readiness of patients with Multiple Sclerosis (MS) to use mobile health technology. Shiraz E-Medical Journal. 19 (Suppl), e66339.Google Scholar
Ross, A (2013) Management of multiple sclerosis. Am J Manag Care. 19, 301–306.Google Scholar
Akter, S, Ray, P (2010) mHealth – an ultimate platform to serve the unserved. Yearb Med Inform., 19, 94–100.Google Scholar
Free, C, Phillips, G, Galli, L et al. (2013) The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: A systematic review. PLoS Med. 10, e1001362.CrossRefGoogle ScholarPubMed
Schaffer, S, Tian, L (2004) Promoting adherence: Effects of theory-based asthma education. Clin Nurs Res. 13, 69–89.CrossRefGoogle ScholarPubMed
Kay, M, Santos, J, Takane, M (2011) Mhealth: New horizons for health through mobile technologies. WHO. 64, 66–71.Google Scholar
Beratarrechea, A, Lee, AG, Willner, JM et al. (2014) The impact of mobile health interventions on chronic disease outcomes in developing countries: A systematic review. Telemed J E Health. 20, 75–82.CrossRefGoogle ScholarPubMed
Hossain, I, Lim, ZZ, Ng, JJL et al. (2018) Public attitudes towards mobile health in Singapore: A cross-sectional study. mHealth. 4, 1–10.CrossRefGoogle ScholarPubMed
Humble, JR, Tolley, EA, Krukowski, RA et al. (2016) Use of and interest in mobile health for diabetes self-care in vulnerable populations. J Telemed Telecare. 22, 32–38.CrossRefGoogle ScholarPubMed
Lee, J-A, Nguyen, AL, Berg, J et al. (2014) Attitudes and preferences on the use of mobile health technology and health games for self-management: Interviews with older adults on anticoagulation therapy. JMIR Mhealth Uhealth. 2, e32–e32.CrossRefGoogle ScholarPubMed
Alenazi, H, Alradhi, S, Alghamdi, M et al. (2017) Readiness to Use Mobile Health Features among Diabetic Patients in Saudi Arabia: Survey Validation. Age. 18, 36–55.Google Scholar
Ebrahimi, S, Mehdipour, Y, Karimi, A et al. (2018) Determinants of Physicians' Technology Acceptance for Mobile Health Services in Healthcare Settings. Journal of Health Management & Informatics. 5, 9–15Google Scholar
Jindal, D, Gupta, P, Jha, D et al. (2018) Development of mWellcare: An mHealth intervention for integrated management of hypertension and diabetes in low-resource settings. Glob Health Action. 11, 1517930.CrossRefGoogle ScholarPubMed
Dai, M, Xu, J, Lin, J et al. (2017) Willingness to use mobile health in glaucoma patients. Telemed J E Health. 23, 822–827.CrossRefGoogle ScholarPubMed
Adebara, O, Adebara, O, Olaide, R et al. (2017) Knowledge, attitude and willingness to use mHealth technology among doctors at a semi urban tertiary hospital in Nigeria. J Adv Med Med Res. 22, 1–10.CrossRefGoogle Scholar
McGillicuddy, JW, Weiland, AK, Frenzel, RM et al. (2013) Patient attitudes toward mobile phone-based health monitoring: Questionnaire study among kidney transplant recipients. J Med Internet Res. 15, e6–e6.CrossRefGoogle ScholarPubMed
Park, MJ, Kim, HS, Kim, KS (2009) Cellular phone and internet-based individual intervention on blood pressure and obesity in obese patients with hypertension. Int J Med Inf. 78, 704–710.CrossRefGoogle ScholarPubMed
Maslakpak, MH, Safaie, M (2016) A comparison between the effectiveness of short message service and reminder cards regarding medication adherence in patients with hypertension: A randomized controlled clinical trial. Int J Community Based Nurs Midwifery. 4, 209.Google ScholarPubMed
Mohammadzadeh, N, Safdari, R (2014) Patient monitoring in mobile health: Opportunities and challenges. Med Arch. 68, 57–60.CrossRefGoogle ScholarPubMed
Khatun, F, Heywood, AE, Hanifi, SMA et al. (2017) Gender differentials in readiness and use of mHealth services in a rural area of Bangladesh. BMC Health Serv Res. 17, 573.CrossRefGoogle Scholar
Peek, S, Wouters, E, Hoof, J et al. (2014) Factors influencing acceptance of technology for aging in place: A systematic review. Int J Med Inform. 83(4), 235–248.CrossRefGoogle ScholarPubMed
Rabiei, M, Ganji, A, Shamsi, M (2012) Mobile advertising acceptance model: Evaluation of key effective factors in Iran. Middle-East Journal of Scientific Research 11, 740–747.Google Scholar
Zhang, X, Guo, X, Lai, KH et al. (2014) Understanding gender differences in m-health adoption: A modified theory of reasoned action model. Telemed J E Health. 20, 39–46.CrossRefGoogle ScholarPubMed
Shieh, YY, Tsai, FY, Anavim, A et al. (2008) Mobile healthcare: The opportunities and challenges. Int J Electron Healthc. 4, 208–219.CrossRefGoogle ScholarPubMed
Lin, C, Shih, H, Sher, PJ (2007) Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing. 24, 641–657.CrossRefGoogle Scholar
Chen, M, Lin, N (2018) Incorporation of health consciousness into the technology readiness and acceptance model to predict app download and usage intentions. Internet Res. 82, 351–373.CrossRefGoogle Scholar