research-article

Trust in mHealth: How do Maternal Health Clients Accept and Use mHealth Interventions?

Authors:

Wallace ChigonaAuthors Info & Claims

SAICSIT '20: Conference of the South African Institute of Computer Scientists and Information Technologists 2020

Pages 189 - 197

https://doi.org/10.1145/3410886.3410895

Published: 14 September 2020 Publication History

Abstract

Trust has significant implications in explaining technology utilisation. It influences both the initial acceptance and continued use (defined as the continuum of use). However, there is dearth of literature examining how trust influences mHealth continued use and what mHealth users trust. This paper explores how trust shapes the continuum of use of maternal mHealth, thus determining their adoption and continued use. The study employed the Expectation Disconfirmation Theory and a case study approach. We collected data using interviews, focus group discussions and observations from 32 purposively sampled participants. Our results suggest that the risks and uncertainties of the maternal healthcare-seeking context play a critical role in how trust shapes mHealth continuum of use. Our findings underscore the need to mHealth designers and implementers to consider different factors that will facilitate the development of trust at the different phases of the continuum to ensure continued use.

References

[1]

Akter, S., D'Ambra, J., & Ray, P. (2011). Trustworthiness in mHealth information services: An assessment of a hierarchical model with mediating and moderating effects using partial least squares (PLS). Journal of the American Society for Information Science and Technology, 62 (1), 100–116.

Digital Library

[2]

Akter, S., & Ray, P. (2010). MHealth-an ultimate platform to serve the unserved. Yearbook of Medical Informatics, 2010 (Journal Article), 94–100.

[3]

Akter, S., Ray, P., & D'Ambra, J. (2013). Continuance of mHealth services at the bottom of the pyramid: The roles of service quality and trust. Electronic Markets, 23 (1), 29–47. https://doi.org/10.1007/s12525-012-0091-5

[4]

BBC News. (2018, July 20). Phone scam: How Kenyans are losing money. BBC News. https://www.bbc.com/news/world-africa-44899854

[5]

Beldad, A., De Jong, M., & Steehouder, M. (2010). How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Computers in Human Behavior, 26 (5), 857–869.

Digital Library

[6]

Benbasat, I., & Wang, W. (2005). Trust in and adoption of online recommendation agents. Journal of the Association for Information Systems, 6 (3), 4.

[7]

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 351–370.

[8]

Bhattacherjee, A., & Premkumar, G. (2004). Understanding Changes in Belief and Attitude Toward Information Technology Usage: A Theoretical Model and Longitudinal Test. Management Information Systems Quarterly, 28 (2). https://aisel.aisnet.org/misq/vol28/iss2/5

[9]

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3 (2), 77–101. https://doi.org/10.1191/1478088706qp063oa

[10]

Cain, M., & Mittman, R. (2002). Diffusion of innovation in health care. California Healthcare Foundation Oakland, CA.

[11]

Carter, L., & Liu, D. (2018). Technology humanness, trust and e-government adoption.

[12]

Chapman, R. (2006). Chikotsa—Secrets, silence, and hiding: Social risk and reproductive vulnerability in central Mozambique. Medical Anthropology Quarterly, 20 (4), 487–515.

[13]

Chen, H., Chai, Y., Dong, L., Niu, W., & Zhang, P. (2018). Effectiveness and Appropriateness of mHealth Interventions for Maternal and Child Health: Systematic Review. JMIR MHealth and UHealth, 6 (1), e7. https://doi.org/10.2196/mhealth.8998

[14]

Clark, S., Madhavan, S., Cotton, C., Beguy, D., & Kabiru, C. (2017). Who helps single mothers in Nairobi? The role of kin support. Journal of Marriage and Family, 79 (4), 1186–1204.

[15]

Dean, A., Makin, J., Kydd, A., Biriotti, M., & Forsyth, B. (2012). A pilot study using interactive SMS support groups to prevent mother-to-child HIV transmission in South Africa. Journal of Telemedicine and Telecare, 18 (7), 399–403.

[16]

Fjeldsoe, B., Marshall, A., & Miller, Y. (2009). Behavior change interventions delivered by mobile telephone short-message service. American Journal of Preventive Medicine, 36 (2), 165–173.

[17]

Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27 (1), 51–90.

[18]

Gourlay, A., Mshana, G., Birdthistle, I., Bulugu, G., Zaba, B., & Urassa, M. (2014). Using vignettes in qualitative research to explore barriers and facilitating factors to the uptake of prevention of mother-to-child transmission services in rural Tanzania: A critical analysis. BMC Medical Research Methodology, 14 (1), 21–32. https://doi.org/10.1186/1471-2288-14-21

[19]

Graner, S., Klingberg‐Allvin, M., Duong, L., Krantz, G., & Mogren, I. (2013). Pregnant women's perception on signs and symptoms during pregnancy and maternal health care in a rural low‐resource setting. Acta Obstetricia et Gynecologica Scandinavica, 92 (9), 1094–1100.

[20]

Hofstede, G., & Hofstede, G. J. (2005). Cultures and Organizations:Software of the Mind. (Rev. and expanded 2nd ed.). McGraw-Hill.

[21]

Huang, C.-K., Chen, C.-D., & Liu, Y.-T. (2019). To stay or not to stay? Discontinuance intention of gamification apps. Information Technology & People, 32 (6), 1423–1445. https://doi.org/10.1108/ITP-08-2017-0271

[22]

Jimison, H., Gorman, P., Woods, S., Nygren, P., Walker, M., Norris, S., & Hersh, W. (2008). Barriers and drivers of health information technology use for the elderly, chronically ill, and underserved. Evidence Report/Technology Assessment, (175) (175), 1–1422.

[23]

Kaium, M. A., Bao, Y., Alam, M. Z., & Hoque, M. R. (2020). Understanding continuance usage intention of mHealth in a developing country. International Journal of Pharmaceutical and Healthcare Marketing.

[24]

Katusiime, J., & Pinkwart, N. (2016). Supporting Maternal Health Education in Developing Countries Using Mobile Phones-Results of a Pilot Study. 48–57.

[25]

Kim, S. S., & Malhotra, N. K. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management Science, 51 (5), 741–755.

Digital Library

[26]

Lankton, N. K., & McKnight, D. H. (2011). What does it mean to trust facebook? Examining technology and interpersonal trust beliefs. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 42 (2), 32–54.

Digital Library

[27]

Lankton, N. K., McKnight, D. H., & Thatcher, J. B. (2014). Incorporating trust-in-technology into Expectation Disconfirmation Theory. The Journal of Strategic Information Systems, 23 (2), 128–145. https://doi.org/10.1016/j.jsis.2013.09.001

[28]

Lankton, N. K., McKnight, D. H., & Tripp, J. (2015). Technology, humanness, and trust: Rethinking trust in technology. Journal of the Association for Information Systems, 16 (10), 1.

[29]

Lankton, N. K., McKnight, D. H., Wright, R. T., & Thatcher, J. B. (2016). Research Note—Using Expectation Disconfirmation Theory and Polynomial Modeling to understand trust in technology. Information Systems Research, 27 (1), 197–213.

[30]

Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean's model perspective. Interacting with Computers, 21 (5–6), 385–392.

Digital Library

[31]

Lee, S., Cho, Y., & Kim, S.-Y. (2017). Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: An application of exploratory spatial data analysis. Globalization and Health, 13 (1), 63–74. https://doi.org/10.1186/s12992-017-0286-9

[32]

Lee, S.-G., Trimi, S., & Kim, C. (2013). The impact of cultural differences on technology adoption. Journal of World Business, 48 (1), 20–29.

[33]

Lewicki, R. J., Tomlinson, E. C., & Gillespie, N. (2006). Models of interpersonal trust development: Theoretical approaches, empirical evidence, and future directions. Journal of Management, 32 (6), 991–1022.

[34]

Mcknight, D. H., Carter, M., Thatcher, J. B., & Clay, P. F. (2011). Trust in a specific technology: An investigation of its components and measures. ACM Transactions on Management Information Systems (TMIS), 2 (2), 12:1–12:25. https://doi.org/10.1145/1985347.1985353

[35]

McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: A trust building model. The Journal of Strategic Information Systems, 11 (3), 297–323. https://doi.org/10.1016/S0963-8687(02)00020-3

[36]

McKnight, D. H., Cummings, L. L., & Chervany, N. L. (1998). Initial Trust Formation in New Organizational Relationships. Academy of Management Review, 23 (3), 473–490. https://doi.org/10.5465/amr.1998.926622

[37]

Mechael, P., Batavia, H., Kaonga, N., Searle, S., Kwan, A., Goldberger, A., Fu, L., & Ossman, J. (2010). Barriers and gaps affecting mHealth in low and middle income countries: Policy white paper. Columbia university. Earth institute. Center for global health and economic development (CGHED): with mHealth alliance.

[38]

Nocera, J. A., Dunckley, L., & Sharp, H. (2007). An Approach to the Evaluation of Usefulness as a Social Construct Using Technological Frames. International Journal of Human–Computer Interaction, 22 (1–2), 153–172. https://doi.org/10.1080/10447310709336959

[39]

Nyemba-Mudenda, M., & Chigona, W. (2018). mHealth outcomes for pregnant mothers in Malawi: A capability perspective. Information Technology for Development, 24 (2), 245–278. https://doi.org/10.1080/02681102.2017.1397594

[40]

Orlikowski, W. J., & Iacono, C. S. (2001). Research Commentary: Desperately Seeking the “IT” in IT Research—A Call to Theorizing the IT Artifact. Information Systems Research, 12 (2), 121–134. https://doi.org/10.1287/isre.12.2.121.9700

[41]

Rogers, E. M. (2010). Diffusion of Innovations (4th ed.). Simon and Schuster.

[42]

Ryan, P., & Lauver, D. R. (2002). The efficacy of tailored interventions. Journal of Nursing Scholarship, 34 (4), 331–337.

[43]

Shen, X.-L., Li, Y.-J., & Sun, Y. (2018). Wearable health information systems intermittent discontinuance. Industrial Management & Data Systems.

[44]

Sillence, E., Briggs, P., Harris, P., & Fishwick, L. (2007). Health websites that people can trust–the case of hypertension. Interacting with Computers, 19 (1), 32–42.

Digital Library

[45]

Simkhada, B., Teijlingen, E. R. van, Porter, M., & Simkhada, P. (2008). Factors affecting the utilization of antenatal care in developing countries: Systematic review of the literature. Journal of Advanced Nursing, 61 (3), 244–260.

[46]

Sondaal, S. F. V., Browne, J. L., Amoakoh-Coleman, M., Borgstein, A., Miltenburg, A. S., Verwijs, M., & Klipstein-Grobusch, K. (2016). Assessing the Effect of mHealth Interventions in Improving Maternal and Neonatal Care in Low- and Middle-Income Countries: A Systematic Review. PLOS ONE, 11 (5), e0154664. https://doi.org/10.1371/journal.pone.0154664

[47]

Straub, D., Keil, M., & Brenner, W. (1997). Testing the technology acceptance model across cultures: A three country study. Information & Management, 33 (1), 1–11.

Digital Library

[48]

Talwar, S., Dhir, A., Khalil, A., Mohan, G., & Islam, A. N. (2020). Point of adoption and beyond. Initial trust and mobile-payment continuation intention. Journal of Retailing and Consumer Services, 55, 102086.

[49]

Tao, D., Wang, T., Wang, T., Zhang, T., Zhang, X., & Qu, X. (2020). A systematic review and meta-analysis of user acceptance of consumer-oriented health information technologies. Computers in Human Behavior, 104, 106147. https://doi.org/10.1016/j.chb.2019.09.023

[50]

Thorsen, V. C., & Sundby, J. (2012). Piecing together the maternal death puzzle through narratives: The three delays model revisited. PLoS One, 7 (12), e52090.

[51]

Vance, A., Elie-Dit-Cosaque, C., & Straub, D. W. (2008). Examining trust in information technology artifacts: The effects of system quality and culture. Journal of Management Information Systems, 24 (4), 73–100.

Digital Library

[52]

Venkatesh, V., Davis, F., & Morris, M. G. (2007). Dead or alive? The development, trajectory and future of technology adoption research. Journal of the Association for Information Systems, 8 (4), 1.

[53]

Venkatesh, V., Thong, J. Y., Chan, F. K., Hu, P. J.-H., & Brown, S. A. (2011). Extending the two‐stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Information Systems Journal, 21 (6), 527–555.

[54]

Wanjohi, P. M. (2017). Curbing Mobile Phone Terrorism and Financial Fraud: A Kenyan Perspective. Journal of ICT Standardization, 4 (3), 237–246.

[55]

Yin, R. K. (2013). Case study research: Design and methods. Sage publications.

[56]

Zhou, T. (2011). An empirical examination of initial trust in mobile banking. Internet Research.

Cited By

Sowon KMaliwichi PChigona WMalata A(2024)The role of the community of purpose in maternal mHealth interventions in Sub-Saharan Africa contextFrontiers in Digital Health10.3389/fdgth.2024.13439656Online publication date: 12-Sep-2024
https://doi.org/10.3389/fdgth.2024.1343965
Khatun FDas NHoque MSaqeeb KRahman MPark KRasheed SReidpath D(2024)Users’ Perceived Service Quality of National Telemedicine Services During the COVID-19 Pandemic in Bangladesh: Cross-Sectional StudyJMIR Human Factors10.2196/4656611(e46566-e46566)Online publication date: 23-Dec-2024
https://doi.org/10.2196/46566
Pang WLiew TTan STeo SLee YLim T(2024)Analyzing Use Intentions for Health-Diagnostic Chatbots: An Extended Technology Acceptance Model ApproachProceedings of the 2024 The 6th World Symposium on Software Engineering (WSSE)10.1145/3698062.3698093(208-217)Online publication date: 13-Sep-2024
https://dl.acm.org/doi/10.1145/3698062.3698093
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SAICSIT '20: Conference of the South African Institute of Computer Scientists and Information Technologists 2020

September 2020

258 pages

ISBN:9781450388474

DOI:10.1145/3410886

Copyright © 2020 ACM.

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Published: 14 September 2020

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SAICSIT '20

SAICSIT '20: Conference of the South African Institute of Computer Scientists and Information Technologists 2020

September 14 - 16, 2020

Cape Town, South Africa

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Sowon KMaliwichi PChigona WMalata A(2024)The role of the community of purpose in maternal mHealth interventions in Sub-Saharan Africa contextFrontiers in Digital Health10.3389/fdgth.2024.13439656Online publication date: 12-Sep-2024
https://doi.org/10.3389/fdgth.2024.1343965
Khatun FDas NHoque MSaqeeb KRahman MPark KRasheed SReidpath D(2024)Users’ Perceived Service Quality of National Telemedicine Services During the COVID-19 Pandemic in Bangladesh: Cross-Sectional StudyJMIR Human Factors10.2196/4656611(e46566-e46566)Online publication date: 23-Dec-2024
https://doi.org/10.2196/46566
Pang WLiew TTan STeo SLee YLim T(2024)Analyzing Use Intentions for Health-Diagnostic Chatbots: An Extended Technology Acceptance Model ApproachProceedings of the 2024 The 6th World Symposium on Software Engineering (WSSE)10.1145/3698062.3698093(208-217)Online publication date: 13-Sep-2024
https://dl.acm.org/doi/10.1145/3698062.3698093
Sowon KLuhanga ECranor LFanti GTucker CGueye A(2024)The Role of User-Agent Interactions on Mobile Money Practices in Kenya and Tanzania2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00184(752-769)Online publication date: 19-May-2024
https://doi.org/10.1109/SP54263.2024.00184
Schulze ALindemann ABrand FGeppert JMenning AStehr PReifegerste DRossmann C(2023)Mobile Apps Aimed at Preventing and Handling Unintentional Injuries in Children Aged <7 Years: Systematic ReviewInteractive Journal of Medical Research10.2196/4525812(e45258)Online publication date: 6-Sep-2023
https://doi.org/10.2196/45258
Sowon KChigona W(2022)How the information system utilization context may lead to unintended technology use: A case of a maternal mHealth intervention in KenyaTHE ELECTRONIC JOURNAL OF INFORMATION SYSTEMS IN DEVELOPING COUNTRIES10.1002/isd2.1221288:4Online publication date: 11-Jan-2022
https://doi.org/10.1002/isd2.12212
Sowon KMaliwichi PChigona W(2020)The Influence of mHealth Design and Implementation Characteristics on the Use of Maternal mHealth Interventions in Kenya: Systematic Literature Review (Preprint)JMIR mHealth and uHealth10.2196/22093Online publication date: 3-Jul-2020
https://doi.org/10.2196/22093

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