797
Views
4
CrossRef citations to date
0
Altmetric
Original Articles

Examining the antecedents and health outcomes of health apps and wearables use: an integration of the technology acceptance model and communication inequality

ORCID Icon & ORCID Icon
Pages 695-716 | Received 16 May 2022, Accepted 25 Jan 2023, Published online: 23 Feb 2023

References

  • Aakvik, A., K. G. Salvanes, and K. Vaage. 2010. “Measuring Heterogeneity in the Returns to Education Using an Education Reform.” European Economic Review 54 (4): 483–500. doi:10.1016/j.euroecorev.2009.09.001.
  • Ahmad, A., T. Rasul, A. Yousaf, and U. Zaman. 2020. “Understanding Factors Influencing Elderly Diabetic Patients’ Continuance Intention to Use Digital Health Wearables: Extending the Technology Acceptance Model (TAM).” Journal of Open Innovation: Technology, Market, and Complexity 6 (3): 81. doi:10.3390/joitmc6030081.
  • Alaiad, A., M. Alsharo, and Y. Alnsour. 2019. “The Determinants of M-Health Adoption in Developing Countries: An Empirical Investigation.” Applied Clinical Informatics 10 (5): 820–840. doi:10.1055/s-0039-1697906.
  • Albuja, A. F., M. A. Lara, L. Navarrete, and L. Nieto. 2017. “Social Support and Postpartum Depression Revisited: The Traditional Female Role as Moderator among Mexican Women.” Sex Roles 77 (3): 209–220. doi:10.1007/s11199-016-0705-z.
  • Anderson-Lewis, C., G. Darville, R. E. Mercado, S. Howell, and S. Di Maggio. 2018. “mHealth Technology Use and Implications in Historically Underserved and Minority Populations in the United States: Systematic Literature Review.” JMIR MHealth and UHealth 6 (6): e128. doi:10.2196/mhealth.8383.
  • Antonovics, K., and R. Town. 2004. “Are All the Good Men Married? Uncovering the Sources of the Marital Wage Premium.” American Economic Review 94 (2): 317–321. doi:10.1257/0002828041301876.
  • Arkorful, V. E., A. Hammond, B. K. Lugu, I. Basiru, K. K. Sunguh, and P. Charmaine-Kwade. 2020. “Investigating the Intention to use Technology among Medical Students: An Application of an Extended Model of the Theory of Planned Behavior.” Journal of Public Affairs, e2460. doi:10.1002/pa.2460.
  • Baabdullah, A. M. 2018. “Consumer Adoption of Mobile Social Network Games (M-SNGs) in Saudi Arabia: The Role of Social Influence, Hedonic Motivation and Trust.” Technology in Society 53: 91–102. doi:10.1016/j.techsoc.2018.01.004.
  • Bardus, M., S. B. van Beurden, J. R. Smith, and C. Abraham. 2016. “A Review and Content Analysis of Engagement, Functionality, Aesthetics, Information Quality, and Change Techniques in the Most Popular Commercial Apps for Weight Management.” International Journal of Behavioral Nutrition and Physical Activity 13 (1): 35. doi:10.1186/s12966-016-0359-9.
  • Beh, P. K., Y. Ganesan, M. Iranmanesh, and B. Foroughi. 2021. “Using Smartwatches for Fitness and Health Monitoring: The UTAUT2 Combined with Threat Appraisal as Moderators.” Behaviour & Information Technology 40 (3): 282–299. doi:10.1080/0144929X.2019.1685597.
  • Bekalu, M. A. 2014. “Communication Inequalities and Health Disparities.” Information Development 30 (2): 189–191. doi:10.1177/0266666914527412.
  • Bekalu, M. A., and S. Eggermont. 2014. “The Role of Communication Inequality in Mediating the Impacts of Socioecological and Socioeconomic Disparities on HIV/AIDS Knowledge and Risk Perception.” International Journal for Equity in Health 13 (1): 16. doi:10.1186/1475-9276-13-16.
  • Beldad, A. D., and S. M. Hegner. 2018. “Expanding the Technology Acceptance Model with the Inclusion of Trust, Social Influence, and Health Valuation to Determine the Predictors of German Users’ Willingness to Continue Using a Fitness App: A Structural Equation Modeling Approach.” International Journal of Human–Computer Interaction 34 (9): 882–893. doi:10.1080/10447318.2017.1403220.
  • Bellur, S., and C. DeVoss. 2018. “Apps and Autonomy: Perceived Interactivity and Autonomous Regulation in MHealth Applications.” Communication Research Reports 35 (4): 314–324. doi:10.1080/08824096.2018.1501672.
  • Beratarrechea, A., A. G. Lee, J. M. Willner, E. Jahangir, A. Ciapponi, and A. Rubinstein. 2013. “The Impact of Mobile Health Interventions on Chronic Disease Outcomes in Developing Countries: A Systematic Review.” Telemedicine and e-Health 20 (1): 75–82. doi:10.1089/tmj.2012.0328.
  • Bergström, A. 2015. “Online Privacy Concerns: A Broad Approach to Understanding the Concerns of Different Groups for Different Uses.” Computers in Human Behavior 53: 419–426. doi:10.1016/j.chb.2015.07.025.
  • Binyamin, S. S., and M. R. Hoque. 2020. “Understanding the Drivers of Wearable Health Monitoring Technology: An Extension of the Unified Theory of Acceptance and Use of Technology.” Sustainability 12 (22), 9605. doi:10.3390/su12229605.
  • Bol, N., N. Helberger, and J. C. M. Weert. 2018. “Differences in Mobile Health App Use: A Source of New Digital Inequalities?” The Information Society 34 (3): 183–193. doi:10.1080/01972243.2018.1438550.
  • Brewer, L. C., K. L. Fortuna, C. Jones, R. Walker, S. N. Hayes, C. A. Patten, and L. A. Cooper. 2020. “Back to the Future: Achieving Health Equity Through Health Informatics and Digital Health.” JMIR MHealth and UHealth 8 (1): e14512. doi:10.2196/14512.
  • Brooks-Russell, A., B. Simons-Morton, D. Haynie, T. Farhat, and J. Wang. 2014. “Longitudinal Relationship Between Drinking with Peers, Descriptive Norms, and Adolescent Alcohol Use.” Prevention Science 15 (4): 497–505. doi:10.1007/s11121-013-0391-9.
  • Chen, M.-F., and N.-P. Lin. 2018. “Incorporation of Health Consciousness Into the Technology Readiness and Acceptance Model to Predict App Download and Usage Intentions.” Internet Research 28 (2): 351–373. doi:10.1108/IntR-03-2017-0099.
  • Chib, A., M. H. van Velthoven, and J. Car. 2015. “mHealth Adoption in Low-Resource Environments: A Review of the Use of Mobile Healthcare in Developing Countries.” Journal of Health Communication 20 (1): 4–34. doi:10.1080/10810730.2013.864735.
  • Cho, H., C. Chi, and W. Chiu. 2020. “Understanding Sustained Usage of Health and Fitness Apps: Incorporating the Technology Acceptance Model with the Investment Model.” Technology in Society 63: 101429. doi:10.1016/j.techsoc.2020.101429.
  • Cho, J., D. Park, and H. E. Lee. 2014. “Cognitive Factors of Using Health Apps: Systematic Analysis of Relationships Among Health Consciousness, Health Information Orientation, eHealth Literacy, and Health App Use Efficacy.” Journal of Medical Internet Research 16 (5): e125. doi:10.2196/jmir.3283.
  • Cho, S. J., and Y. Tian. 2021. “Investigating the Role of Communication Between Descriptive Norms and Exercise Intentions and Behaviors: Findings among Fitness Tracker Users.” Journal of American College Health 69 (4): 452–458. doi:10.1080/07448481.2019.1679819.
  • Choe, M., and G. Noh. 2017. “Technology Acceptance of the Smartwatch: Health Consciousness, Self-Efficacy, Innovativeness.” Advanced Science Letters 23 (10): 10152–10155. doi:10.1166/asl.2017.10408.
  • Chung, S., and A. Park. 2018. “The Longitudinal Effects of Grandchild Care on Depressive Symptoms and Physical Health of Grandmothers in South Korea: A Latent Growth Approach.” Aging & Mental Health 22 (12): 1556–1563. doi:10.1080/13607863.2017.1376312.
  • Cohen, P., S. G. West, and L. S. Aiken. 2014. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. New York: Psychology Press. doi:10.4324/9781410606266.
  • Creusen, M. E. H., and J. P. L. Schoormans. 2005. “The Different Roles of Product Appearance in Consumer Choice*.” Journal of Product Innovation Management 22 (1): 63–81. doi:10.1111/j.0737-6782.2005.00103.x.
  • Cugelman, B. 2013. “Gamification: What it is and Why it Matters to Digital Health Behavior Change Developers.” JMIR Serious Games 1 (1): e3. doi:10.2196/games.3139.
  • Curto, J. D., and J. C. Pinto. 2011. “The Corrected VIF (CVIF).” Journal of Applied Statistics 38 (7): 1499–1507. doi:10.1080/02664763.2010.505956.
  • Davis, F. D. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly 13 (3): 319–340. doi:10.2307/249008.
  • Davis, F. D., R. P. Bagozzi, and P. R. Warshaw. 1989. “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models.” Management Science 35 (8): 982–1003. doi:10.1287/mnsc.35.8.982.
  • Deady, M., D. Johnston, D. Milne, N. Glozier, D. Peters, R. Calvo, and S. Harvey. 2018. “Preliminary Effectiveness of a Smartphone App to Reduce Depressive Symptoms in the Workplace: Feasibility and Acceptability Study.” JMIR MHealth and UHealth 6 (12): e11661. doi:10.2196/11661.
  • Department of Statistics Singapore. 2020a. Singapore Census of Population 2020, Administrative Report. https://www.singstat.gov.sg/-/media/files/publications/cop2020/admin/cop2020admin.pdf.
  • Department of Statistics Singapore. 2020b. Singapore Standard Educational Classification (SSEC) 2020. https://www.singstat.gov.sg/standards/standards-and-classifications/ssec.
  • Doherty, K., M. Barry, J. Marcano-Belisario, B. Arnaud, C. Morrison, J. Car, and G. Doherty. 2018. “A Mobile App for the Self-Report of Psychological Well-Being During Pregnancy (BrightSelf): Qualitative Design Study.” JMIR Mental Health 5 (4): e10007. doi:10.2196/10007.
  • Dohnke, B., E. Weiss-Gerlach, and C. D. Spies. 2011. “Social Influences on the Motivation to Quit Smoking: Main and Moderating Effects of Social Norms.” Addictive Behaviors 36 (4): 286–293. doi:10.1016/j.addbeh.2010.11.001.
  • Dym, B., and C. Fiesler. 2020. “Social Norm Vulnerability and its Consequences for Privacy and Safety in an Online Community.” Proceedings of the ACM on Human-Computer Interaction 4 (CSCW2): Article 155. doi:10.1145/3415226.
  • Emaus, A., J. Degerstrøm, T. Wilsgaard, B. H. Hansen, C. M. Dieli-Conwright, A.-S. Furberg, S. A. Pettersen, et al. 2010. “Does a Variation in Self-Reported Physical Activity Reflect Variation in Objectively Measured Physical Activity, Resting Heart Rate, and Physical Fitness? Results from the Tromsø Study.” Scandinavian Journal of Public Health 38 (5_suppl): 105–118. doi:10.1177/1403494810378919.
  • Espay, A. J., J. M. Hausdorff, Á Sánchez-Ferro, J. Klucken, A. Merola, P. Bonato, S. S. Paul, et al. 2019. “A Roadmap for Implementation of Patient-Centered Digital Outcome Measures in Parkinson's Disease Obtained Using Mobile Health Technologies.” Movement Disorders 34 (5): 657–663. doi:10.1002/mds.27671.
  • Ettema, J. S., and F. G. Kline. 1977. “Deficits, Differences, and Ceilings: Contingent Conditions for Understanding the Knowledge gap.” Communication Research 4 (2): 179–202. doi:10.1177/009365027700400204.
  • Feng, G. C., X. Su, Z. Lin, Y. He, N. Luo, and Y. Zhang. 2020. “Determinants of Technology Acceptance: Two Model-Based Meta-Analytic Reviews.” Journalism & Mass Communication Quarterly 98 (1): 83–104. doi:10.1177/1077699020952400.
  • Fernandes, A., F. J. Van Lenthe, J. Vallee, C. Sueur, and B. Chaix. 2021. “Linking Physical and Social Environments with Mental Health in Old age: Amultisensor Approach for Continuous Real-Life Ecological and Emotional Assessment.” Journal of Epidemiology and Community Health 75 (5): 477–483. doi:10.1136/jech-2020-214274.
  • Fingerman, K. L., K. S. Birditt, and D. J. Umberson. 2020. “Use of Technologies for Social Connectedness and Well-Being and as a Tool for Research Data Collection in Older Adults.” Mobile Technology for Adaptive Aging: Proceedings of a Workshop.
  • Floryan, M., P. I. Chow, S. M. Schueller, and L. M. Ritterband. 2020. “The Model of Gamification Principles for Digital Health Interventions: Evaluation of Validity and Potential Utility.” Journal of Medical Internet Research 22 (6): e16506. doi:10.2196/16506.
  • Francis, J., D. Cross, A. Schultz, D. Armstrong, R. Nguyen, and C. Branch-Smith. 2020. “Developing a Smartphone Application to Support Social Connectedness and Wellbeing in Young People with Cystic Fibrosis.” Journal of Cystic Fibrosis 19 (2): 277–283. doi:10.1016/j.jcf.2019.12.011.
  • Gao, Y., H. Li, and Y. Luo. 2015. “An Empirical Study of Wearable Technology Acceptance in Healthcare.” Industrial Management & Data Systems 115 (9): 1704–1723. doi:10.1108/IMDS-03-2015-0087.
  • Gaziano, C. 1997. “Forecast 2000: Widening Knowledge Gaps.” Journalism & Mass Communication Quarterly 74 (2): 237–264. doi:10.1177/107769909707400202.
  • Gibson, J. J. 1978. “The Ecological Approach to the Visual Perception of Pictures.” Leonardo 11 (3): 227–235. doi:10.2307/1574154
  • Godleski, S., B. A. Z. Abu, and A. Kothari. 2021. “A Qualitative Needs Assessment and Analysis of Perceptions of a Mobile Health App for Low-Income, At-Risk Mothers.” Journal of Technology in Behavioral Science 6 (1): 100–105. doi:10.1007/s41347-020-00151-w.
  • Goggin, G., and K. V. Zhuang. 2022. “Disability as Smart Equality: Inclusive Technology in a Digitally Advanced Nation.” In Vulnerable People and Digital Inclusion: Theoretical and Applied Perspectives, edited by P. Tsatsou, 257–275. Springer International Publishing. doi:10.1007/978-3-030-94122-2_14
  • Grossman, L. V., R. M. Masterson Creber, N. C. Benda, D. Wright, D. K. Vawdrey, and J. S. Ancker. 2019. “Interventions to Increase Patient Portal use in Vulnerable Populations: A Systematic Review.” Journal of the American Medical Informatics Association 26 (8-9): 855–870. doi:10.1093/jamia/ocz023.
  • Gu, J., Y. Xu, H. Xu, C. Zhang, and H. Ling. 2017. “Privacy Concerns for Mobile App Download: An Elaboration Likelihood Model Perspective.” Decision Support Systems 94: 19–28. doi:10.1016/j.dss.2016.10.002.
  • Guo, X., X. Zhang, and Y. Sun. 2016. “The Privacy–Personalization Paradox in MHealth Services Acceptance of Different Age Groups.” Electronic Commerce Research and Applications 16: 55–65. doi:10.1016/j.elerap.2015.11.001.
  • Hogg, M. A., and S. A. Reid. 2006. “Social Identity, Self-Categorization, and the Communication of Group Norms.” Communication Theory 16 (1): 7–30. doi:10.1111/j.1468-2885.2006.00003.x.
  • Hong, W., and J. Y. L. Thong. 2013. “Internet Privacy Concerns: An Integrated Conceptualization and Four Empirical Studies.” MIS Quarterly 37 (1): 275–298. http://www.jstor.org/stable/43825946. doi:10.25300/MISQ/2013/37.1.12
  • Hsiao, K.-L., and C.-C. Chen. 2018. “What Drives Smartwatch Purchase Intention? Perspectives from Hardware, Software, Design, and Value.” Telematics and Informatics 35 (1): 103–113. doi:10.1016/j.tele.2017.10.002.
  • Hwang, Y., and S.-H. Jeong. 2009. “Revisiting the Knowledge gap Hypothesis: A Meta-Analysis of Thirty-Five Years of Research.” Journalism & Mass Communication Quarterly 86 (3): 513–532. doi:10.1177/107769900908600304.
  • Ishikawa, Y., N. Kondo, I. Kawachi, and K. Viswanath. 2016. “Are Socioeconomic Disparities in Health Behavior Mediated by Differential Media use? Test of the Communication Inequality Theory.” Patient Education and Counseling 99 (11): 1803–1807. doi:10.1016/j.pec.2016.05.018.
  • Jang, S. A., R. N. Rimal, and N. Cho. 2011. “Exploring Parental Influences in the Theory of Normative Social Behavior.” Communication Research 40 (1): 52–72. doi:10.1177/0093650211407061.
  • Jiang, Y., D. Chen, and F. Lai. 2010. “Technological-personal-environmental (TPE) Framework: A Conceptual Model for Technology Acceptance at the Individual Level.” Journal of International Technology and Information Management 19 (3): 5. https://scholarworks.lib.csusb.edu/jitim/vol19/iss3/5; doi:10.58729/1941-6679.1087
  • Jung, Y., S. Kim, and B. Choi. 2016. “Consumer Valuation of the Wearables: The Case of Smartwatches.” Computers in Human Behavior 63: 899–905. doi:10.1016/j.chb.2016.06.040.
  • Kanstrup, A. M., P. S. Bertelsen, and C. Knudsen. 2020. “Changing Health Behavior with Social Technology? A Pilot Test of a Mobile App Designed for Social Support of Physical Activity.” International Journal of Environmental Research and Public Health 17 (22), 8383. doi:10.3390/ijerph17228383
  • Kao, C.-K., and D. M. Liebovitz. 2017. “Consumer Mobile Health Apps: Current State, Barriers, and Future Directions.” PM&R 9 (5, Supplement): S106–S115. doi:10.1016/j.pmrj.2017.02.018.
  • Kim, K., C.-J. Lee, and R. C. Hornik. 2020. “Exploring the Effect of Health App Use on Fruit and Vegetable Consumption.” Journal of Health Communication 25: 283–290. doi:10.1080/10810730.2020.1745962.
  • Kim, H., C. D. Ray, and A. M. Veluscek. 2017. “Complementary Support from Facilitators and Peers for Promoting MHealth Engagement and Weight Loss.” Journal of Health Communication 22 (11): 905–912. doi:10.1080/10810730.2017.1373876.
  • Kim, J.-W., B. Ryu, S. Cho, E. Heo, Y. Kim, J. Lee, S. Y. Jung, and S. Yoo. 2019. “Impact of Personal Health Records and Wearables on Health Outcomes and Patient Response: Three-arm Randomized Controlled Trial.” JMIR MHealth and UHealth 7 (1): e12070. doi:10.2196/12070.
  • King, W. R., and J. He. 2006. “A Meta-Analysis of the Technology Acceptance Model.” Information & Management 43 (6): 740–755. doi:10.1016/j.im.2006.05.003.
  • Kwang, K. 2018. “Singapore Health System Hit by ‘Most Serious Breach of Personal Data’ in Cyberattack; PM Lee’s Data Targeted.” https://www.channelnewsasia.com/news/singapore/singhealth-health-system-hit-serious-cyberattack-pm-lee-target-10548318.
  • Lamers, S. M., C. A. Glas, G. J. Westerhof, and E. T. Bohlmeijer. 2012. “Longitudinal Evaluation of the Mental Health Continuum- Short Form (MHC-SF).” European Journal of Psychological Assessment, 28: 290–296. doi:10.1027/1015-5759/a000109.
  • Lamers, S. M., G. J. Westerhof, E. T. Bohlmeijer, P. M. ten Klooster, and C. L. Keyes. 2011. “Evaluating the Psychometric Properties of the Mental Health Continuum-Short Form (MHC-SF).” Journal of Clinical Psychology 67 (1): 99–110. doi:10.1002/jclp.20741.
  • Lawrence, N. K. 2015. “Highlighting the Injunctive Norm to Reduce Phone-Related Distracted Driving.” Social Influence 10 (2): 109–118. doi:10.1080/15534510.2015.1007082.
  • Lazard, A. J., J. S. Brennen, E. Troutman Adams, and B. Love. 2020. “Cues for Increasing Social Presence for Mobile Health App Adoption.” Journal of Health Communication 25 (2): 136–149. doi:10.1080/10810730.2020.1719241.
  • Lee, C.-J. 2009. “The Role of Internet Engagement in the Health-Knowledge gap.” Journal of Broadcasting & Electronic Media 53 (3): 365–382. doi:10.1080/08838150903102758.
  • Lee, H. E., and J. Cho. 2017. “What Motivates Users to Continue Using Diet and Fitness Apps? Application of the Uses and Gratifications Approach.” Health Communication 32 (12): 1445–1453. doi:10.1080/10410236.2016.1167998.
  • Lee, E. W. J., and S. S. Ho. 2015. “The Perceived Familiarity gap Hypothesis: Examining how Media Attention and Reflective Integration Relate to Perceived Familiarity with Nanotechnology in Singapore.” Journal of Nanoparticle Research 17 (5): 1–15. doi:10.1007/s11051-015-3036-z.
  • Lee, E. W. J., R. F. McCloud, and K. Viswanath. 2022. “Designing Effective eHealth Interventions for Underserved Groups: Five Lessons From a Decade of eHealth Intervention Design and Deployment.” Journal of Medical Internet Research 24 (1): e25419. doi:10.2196/25419.
  • Lee, E. W. J., and K. Viswanath. 2020. “Big Data in Context: Addressing the Twin Perils of Data Absenteeism and Chauvinism in the Context of Health Disparities Research.” Journal of Medical Internet Research 22 (1): e16377. doi:10.2196/16377.
  • Legris, P., J. Ingham, and P. Collerette. 2003. “Why Do People Use Information Technology? A Critical Review of the Technology Acceptance Model.” Information & Management 40 (3): 191–204. doi:10.1016/S0378-7206(01)00143-4.
  • Lei, S. I., D. Wang, and R. Law. 2019. “Perceived Technology Affordance and Value of Hotel Mobile Apps: A Comparison of Hoteliers and Customers.” Journal of Hospitality and Tourism Management 39: 201–211. doi:10.1016/j.jhtm.2019.02.006.
  • Li, C., S. H. Lin, and A. Chib. 2020. “The State of Wearable Health Technologies: A Transdisciplinary Literature Review.” Mobile Media & Communication 9 (2): 353–376. doi:10.1177/2050157920966023.
  • Loh, Y. A.-C., and A. Chib. 2021. “Reconsidering the Digital Divide: An Analytical Framework from Access to Appropriation.” Information Technology & People 35: 647–676. ahead-of-print (ahead-of-print). doi:10.1108/ITP-09-2019-0505
  • Luijten, C. C., S. Kuppens, D. van de Bongardt, and A. P. Nieboer. 2019. “Evaluating the Psychometric Properties of the Mental Health Continuum-Short Form (MHC-SF) in Dutch Adolescents.” Health and Quality of Life Outcomes 17 (1): 1–10. doi:10.1186/s12955-019-1221-y.
  • Mabry, P. L., D. H. Olster, G. D. Morgan, and D. B. Abrams. 2008. “Interdisciplinarity and Systems Science to Improve Population Health: A View from the NIH Office of Behavioral and Social Sciences Research.” American Journal of Preventive Medicine 35 (2, Supplement): S211–S224. doi:10.1016/j.amepre.2008.05.018.
  • Macy, J. T., C. Owens, K. Mullis, and S. E. Middlestadt. 2021. “The Role of Self-Efficacy and Injunctive Norms in Helping Older Adults Decide to Stay Home During the COVID-19 Pandemic.” Frontiers in Public Health 9 (721). doi:10.3389/fpubh.2021.660813.
  • Marangunić, N., and A. Granić. 2015. “Technology Acceptance Model: A Literature Review from 1986 to 2013.” Universal Access in the Information Society 14 (1): 81–95. doi:10.1007/s10209-014-0348-1.
  • Mazzulla, E. C., K. M. Fondacaro, H. Weldon, M. Dibble, and M. Price. 2021. “Addressing the Disparity in Refugee Mental Health Services: A Pilot Study of a Traumatic Stress Intervention Utilizing a Language-Free mHealth Application.” Journal of Technology in Behavioral Science 6 (4): 599–608. doi:10.1007/s41347-021-00213-7.
  • McDonald, R. I., and C. S. Crandall. 2015. “Social Norms and Social Influence.” Current Opinion in Behavioral Sciences 3: 147–151. doi:10.1016/j.cobeha.2015.04.006.
  • Mitchell, U. A., P. G. Chebli, L. Ruggiero, and N. Muramatsu. 2019. “The Digital Divide in Health-Related Technology Use: The Significance of Race/Ethnicity.” The Gerontologist 59 (1): 6–14. doi:10.1093/geront/gny138.
  • Mohamed, N., and I. H. Ahmad. 2012. “Information Privacy Concerns, Antecedents and Privacy Measure Use in Social Networking Sites: Evidence from Malaysia.” Computers in Human Behavior 28 (6): 2366–2375. doi:10.1016/j.chb.2012.07.008.
  • Mönninghoff, A., J. N. Kramer, A. J. Hess, K. Ismailova, G. W. Teepe, L. T. Car, F. Müller-Riemenschneider, and T. Kowatsch. 2021. “Long-term Effectiveness of mHealth Physical Activity Interventions: Systematic Review and Meta-analysis of Randomized Controlled Trials.” Journal of Medical Internet Research 23 (4): e26699. doi:10.2196/26699.
  • Mora, L., R. K. R. Kummitha, and G. Esposito. 2021. “Not Everything is as it Seems: Digital Technology Affordance, Pandemic Control, and the Mediating Role of Sociomaterial Arrangements.” Government Information Quarterly 38 (4): 101599. doi:10.1016/j.giq.2021.101599.
  • Moran, M. B., L. B. Frank, N. Zhao, C. Gonzalez, P. Thainiyom, S. T. Murphy, and S. J. Ball-Rokeach. 2016. “An Argument for Ecological Research and Intervention in Health Communication.” Journal of Health Communication 21 (2): 135–138. doi:10.1080/10810730.2015.1128021.
  • Mueller, N. E., T. Panch, C. Macias, B. M. Cohen, D. Ongur, and J. T. Baker. 2018. “Using Smartphone Apps to Promote Psychiatric Rehabilitation in a Peer-Led Community Support Program: Pilot Study.” JMIR Mental Health 5 (3): e10092. doi:10.2196/10092.
  • Muller, C., and N. de Klerk. 2020. “Influence of Design Aesthetics and Brand Name on Generation Y Students’ Intention to Use Wearable Activity-Tracking Devices.” International Journal of EBusiness and EGovernment Studies 12 (2): 107–121. doi:10.34111/ijebeg.202012202.
  • Nagy, P., and G. Neff. 2015. “Imagined Affordance: Reconstructing a Keyword for Communication Theory.” Social Media + Society 1 (2): 205630511560338. doi:10.1177/2056305115603385.
  • Nguyen, M. H., E. Hargittai, and W. Marler. 2021. “Digital Inequality in Communication During a Time of Physical Distancing: The Case of COVID-19.” Computers in Human Behavior 120: 106717. doi:10.1016/j.chb.2021.106717.
  • Okunade, K., K. Bashan Nkhoma, O. Salako, D. Akeju, B. Ebenso, E. Namisango, O. Soyannwo, et al. 2019. “Understanding Data and Information Needs for Palliative Cancer Care to Inform Digital Health Intervention Development in Nigeria, Uganda and Zimbabwe: Protocol for a Multicountry Qualitative Study.” BMJ Open 9 (10): e032166. doi:10.1136/bmjopen-2019-032166.
  • Piwek, L., D. A. Ellis, S. Andrews, and A. Joinson. 2016. “The Rise of Consumer Health Wearables: Promises and Barriers.” PLoS Medicine 13 (2): e1001953. doi:10.1371/journal.pmed.1001953.
  • Powell, A. C., P. Singh, and J. Torous. 2018. “The Complexity of Mental Health App Privacy Policies: A Potential Barrier to Privacy.” JMIR MHealth and UHealth 6 (7): e158. doi:10.2196/mhealth.9871.
  • Prince, S. A., K. B. Adamo, M. E. Hamel, J. Hardt, S. Connor Gorber, and M. Tremblay. 2008. “A Comparison of Direct Versus Self-Report Measures for Assessing Physical Activity in Adults: A Systematic Review.” International Journal of Behavioral Nutrition and Physical Activity 5: 56–56. doi:10.1186/1479-5868-5-56.
  • Rafique, H., A. O. Almagrabi, A. Shamim, F. Anwar, and A. K. Bashir. 2020. “Investigating the Acceptance of Mobile Library Applications with an Extended Technology Acceptance Model (TAM).” Computers & Education 145: 103732. doi:10.1016/j.compedu.2019.103732.
  • Raghavan, A., M. A. Demircioglu, and A. Taeihagh. 2021. “Public Health Innovation Through Cloud Adoption: A Comparative Analysis of Drivers and Barriers in Japan, South Korea, and Singapore.” International Journal of Environmental Research and Public Health 18 (1). doi:10.3390/ijerph18010334.
  • Ralston, A. L., A. R. Andrews Iii, and D. A. Hope. 2019. “Fulfilling the Promise of Mental Health Technology to Reduce Public Health Disparities: Review and Research Agenda.” Clinical Psychology: Science and Practice 26 (1): e12277. doi:10.1111/cpsp.12277.
  • Ramanadhan, S., and K. Viswanath. 2008. “Communication Inequality.” In The International Encyclopedia of Communication. https://doi.org/10.1002/9781405186407.wbiecc076 (Major Reference Works)
  • Ramsetty, A., and C. Adams. 2020. “Impact of the Digital Divide in the Age of COVID-19.” Journal of the American Medical Informatics Association 27 (7): 1147–1148. doi:10.1093/jamia/ocaa078.
  • Raza, S. A., K. A. Khan, and J. Salam. 2021. “Impact of Environmental Triggers on Students’ Behavior to Use Ride-Sharing Services: The Moderating Role of Perceived Risk.” Current Psychology. doi:10.1007/s12144-021-02405-z.
  • Rickard, N., H.-A. Arjmand, D. Bakker, and E. Seabrook. 2016. “Development of a Mobile Phone App to Support Self-Monitoring of Emotional Well-Being: A Mental Health Digital Innovation.” JMIR Mental Health 3 (4): e49. doi:10.2196/mental.6202.
  • Rimal, R. N. 2008. “Modeling the Relationship Between Descriptive Norms and Behaviors: A Test and Extension of the Theory of Normative Social Behavior (TNSB)∗.” Health Communication 23 (2): 103–116. doi:10.1080/10410230801967791.
  • Russell, E., A. Lloyd-Houldey, A. Memon, and J. Yarker. 2018. “Factors Influencing Uptake and Use of a New Health Information App for Young People.” Journal of Technology in Human Services 36 (4): 222–240. doi:10.1080/15228835.2018.1536911.
  • Saksono, H., C. Castaneda-Sceppa, J. Hoffman, M. S. El-Nasr, V. Morris, and A. G. Parker. 2019. “Social Reflections on Fitness Tracking Data: A Study with Families in Low-SES Neighborhoods.” In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Paper 313. Association for Computing Machinery. https://doi.org/10.1145/3290605.3300543
  • Scherer, R., F. Siddiq, and J. Tondeur. 2019. “The Technology Acceptance Model (TAM): A Meta-Analytic Structural Equation Modeling Approach to Explaining Teachers’ Adoption of Digital Technology in Education.” Computers & Education 128: 13–35. doi:10.1016/j.compedu.2018.09.009.
  • Selwyn, N. 2004. “Reconsidering Political and Popular Understandings of the Digital Divide.” New Media & Society 6 (3): 341–362. doi:10.1177/1461444804042519.
  • Statista. 2022. eHealth. https://www.statista.com/outlook/dmo/digital-health/ehealth/worldwide.
  • Streichan, C. 2020. Continuous Usage of Fitness Tracker Systems: Expanding the UTAUT2 Model with Perceived Privacy Risk, Health Valuation, and Satisfaction.
  • Šumak, B., M. Heričko, and M. Pušnik. 2011. “A Meta-Analysis of e-Learning Technology Acceptance: The Role of User Types and e-Learning Technology Types.” Computers in Human Behavior 27 (6): 2067–2077. doi:10.1016/j.chb.2011.08.005.
  • Sun, R.-T., W. Han, H.-L. Chang, and M. J. Shaw. 2021. “Motivating Adherence to Exercise Plans Through a Personalized Mobile Health App: Enhanced Action Design Research Approach.” JMIR MHealth and UHealth 9 (6): e19941. doi:10.2196/19941.
  • Taherdoost, H. 2016. “Sampling Methods in Research Methodology; How to Choose a Sampling Technique for Research.” How to Choose a Sampling Technique for Research (April 10, 2016). https://doi.org/10.2139/ssrn.3205035.
  • Taherdoost, H. 2018. “Development of an adoption model to assess user acceptance of e-service technology: E-Service Technology Acceptance Model.” Behaviour & Information Technology 37 (2): 173–197. doi:10.1080/0144929X.2018.1427793.
  • Talukder, M. S., R. Chiong, Y. Bao, and B. H. Malik. 2019. “Acceptance and Use Predictors of Fitness Wearable Technology and Intention to Recommend.” Industrial Management & Data Systems. doi:10.1108/IMDS-01-2018-0009.
  • Talukder, M. S., G. Sorwar, Y. Bao, J. U. Ahmed, and M. A. S. Palash. 2020. “Predicting Antecedents of Wearable Healthcare Technology Acceptance by Elderly: A Combined SEM-Neural Network Approach.” Technological Forecasting and Social Change 150: 119793. doi:10.1016/j.techfore.2019.119793.
  • Tamilmani, K., N. P. Rana, N. Prakasam, and Y. K. Dwivedi. 2019. “The Battle of Brain vs. Heart: A Literature Review and Meta-Analysis of “Hedonic Motivation” Use in UTAUT2.” International Journal of Information Management 46: 222–235. doi:10.1016/j.ijinfomgt.2019.01.008.
  • Tan, S. Y., and A. Taeihagh. 2020. “Governing the Adoption of Robotics and Autonomous Systems in Long-Term Care in Singapore.” Policy and Society 40: 211–231. doi:10.1080/14494035.2020.1782627.
  • Tao, D., T. Wang, T. Wang, T. Zhang, X. Zhang, and X. Qu. 2020. “A Systematic Review and Meta-Analysis of User Acceptance of Consumer-Oriented Health Information Technologies.” Computers in Human Behavior 104: 106147. doi:10.1016/j.chb.2019.09.023.
  • Tewathia, N., A. Kamath, and P. V. Ilavarasan. 2020. “Social Inequalities, Fundamental Inequities, and Recurring of the Digital Divide: Insights from India.” Technology in Society 61: 101251. doi:10.1016/j.techsoc.2020.101251.
  • Torous, J., J. Nicholas, M. E. Larsen, J. Firth, and H. Christensen. 2018. “Clinical Review of User Engagement with Mental Health Smartphone Apps: Evidence, Theory and Improvements.” Evidence Based Mental Health 21 (3): 116. doi:10.1136/eb-2018-102891.
  • Van Dijk, J. A. 2005. The Deepening Divide: Inequality in the Information Society. London: Sage Publications.
  • Viswanath, K., and K. M. Emmons. 2006. “Message Effects and Social Determinants of Health: Its Application to Cancer Disparities.” Journal of Communication 56 (suppl_1): S238–S264. doi:10.1111/j.1460-2466.2006.00292.x.
  • Viswanath, K., and J. R. Finnegan Jr. 1996. “The Knowledge Gap Hypothesis: Twenty-Five Years Later.” Annals of the International Communication Association 19 (1): 187–228. doi:10.1080/23808985.1996.11678931.
  • Viswanath, K., and M. W. Kreuter. 2007. “Health Disparities, Communication Inequalities, and eHealth.” American Journal of Preventive Medicine 32 (5): S131–S133. doi:10.1016/j.amepre.2007.02.012.
  • Viswanath, K., E. W. J. Lee, and R. Pinnamaneni. 2020. “We Need the Lens of Equity in COVID-19 Communication.” Health Communication 35 (14): 1743–1746. doi:10.1080/10410236.2020.1837445.
  • Viswanath, K., R. H. Nagler, C. A. Bigman-Galimore, M. P. McCauley, M. Jung, and S. Ramanadhan. 2012. “The Communications Revolution and Health Inequalities in the 21st Century: Implications for Cancer Control.” Cancer Epidemiology, Biomarkers & Prevention 21 (10): 1701–1708. doi:10.1158/1055-9965.EPI-12-0852.
  • Wang, T., L. Fan, X. Zheng, W. Wang, J. Liang, K. An, M. Ju, and J. Lei. 2021. “The Impact of Gamification-Induced Users’ Feelings on the Continued Use of mHealth Apps: A Structural Equation Model with the Self-Determination Theory Approach.” Journal of Medical Internet Research 23 (8): e24546. doi:10.2196/24546.
  • Wetzel, B., R. Pryss, H. Baumeister, J.-S. Edler, A. S. Gonçalves, and C. Cohrdes. 2021. ““How Come You Don’t Call Me?” Smartphone Communication App Usage as an Indicator of Loneliness and Social Well-Being Across the Adult Lifespan During the COVID-19 Pandemic.” International Journal of Environmental Research and Public Health 18 (12). doi:10.3390/ijerph18126212
  • Woltman, H., A. Feldstain, J. C. MacKay, and M. Rocchi. 2012. “An Introduction to Hierarchical Linear Modeling.” Tutorials in Quantitative Methods for Psychology 8 (1): 52–69. doi:10.20982/tqmp.08.1.p052.
  • Wu, L.-H., L.-C. Wu, and S.-C. Chang. 2016. “Exploring Consumers’ Intention to Accept Smartwatch.” Computers in Human Behavior 64: 383–392. doi:10.1016/j.chb.2016.07.005.
  • Xu, Z., X. Shen, W. Pan, and I. Alzheimer’s Disease Neuroimaging. 2014. “Longitudinal Analysis is More Powerful Than Cross-Sectional Analysis in Detecting Genetic Association with Neuroimaging Phenotypes.” PloS one 9 (8): e102312–e102312. doi:10.1371/journal.pone.0102312.
  • Yen, H.-Y., and H.-L. Chiu. 2019. “The Effectiveness of Wearable Technologies as Physical Activity Interventions in Weight Control: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.” Obesity Reviews 20 (10): 1485–1493. doi:10.1111/obr.12909.
  • Yerrakalva, D., D. Yerrakalva, S. Hajna, and S. Griffin. 2019. “Effects of Mobile Health app Interventions on Sedentary Time, Physical Activity, and Fitness in Older Adults: Systematic Review and Meta-Analysis.” Journal of Medical Internet Research 21 (11): e14343. doi:10.2196/14343.
  • Yuan, S., W. Ma, S. Kanthawala, and W. Peng. 2015. “Keep Using my Health Apps: Discover Users’ Perception of Health and Fitness Apps with the UTAUT2 Model.” Telemedicine and e-Health 21 (9): 735–741. doi:10.1089/tmj.2014.0148.
  • Yun, D., and K. J. Silk. 2011. “Social Norms, Self-Identity, and Attention to Social Comparison Information in the Context of Exercise and Healthy Diet Behavior.” Health Communication 26 (3): 275–285. doi:10.1080/10410236.2010.549814.
  • Zaleski, A. C., and P. A. Aloise-Young. 2013. “Using Peer Injunctive Norms to Predict Early Adolescent Cigarette Smoking Intentions.” Journal of Applied Social Psychology 43: E124–E131. doi:10.1111/jasp.12080.
  • Zhang, X., X. Han, Y. Dang, F. Meng, X. Guo, and J. Lin. 2017. “User Acceptance of Mobile Health Services from Users’ Perspectives: The Role of Self-Efficacy and Response-Efficacy in Technology Acceptance.” Informatics for Health and Social Care 42 (2): 194–206. doi:10.1080/17538157.2016.1200053.
  • Zhang, X., S. Liu, X. Chen, L. Wang, B. Gao, and Q. Zhu. 2018. “Health Information Privacy Concerns, Antecedents, and Information Disclosure Intention in Online Health Communities.” Information & Management 55 (4): 482–493. doi:10.1016/j.im.2017.11.003.
  • Zhang, M., M. Luo, R. Nie, and Y. Zhang. 2017. “Technical Attributes, Health Attribute, Consumer Attributes and Their Roles in Adoption Intention of Healthcare Wearable Technology.” International Journal of Medical Informatics 108: 97–109. doi:10.1016/j.ijmedinf.2017.09.016.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.