A Systematic Literature Review of Research on Smart Wearable Health Technology Users' Behaviors

  • Li Caining ,
  • Bi Xinhua ,
  • Yang Yihao ,
  • Tian Xiaoxu
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  • School of Business and Management, Jilin University, Changchun 130025

Received date: 2022-03-03

  Revised date: 2022-07-05

  Online published: 2022-09-09

Abstract

[Purpose/Significance] This study systematically sorts out and summarizes the research progress of user behaviors of smart wearable health technology, to provide references for promoting relevant theoretical research and practical development.[Method/Process] Following the paradigm of systematic literature review, seventy-four relevant papers were retrieved and selected from Web of Science, PsychINFO and CNKI. Combined with qualitative and quantitative methods, topic analysis, time series analysis and meta-analysis were used to analyze the literature.[Result/Conclusion] The research topics in the area include technology adoption, continuance, user involvement, and health behavior. In detail, the research on technology adoption is considered to have made some progress due to its large number and high degree of theoreticalization and explanation power, while research on other topics are still in the preliminary exploratory stage. Future research directions mainly include:expanding user behavior research from consumer-level products to medical-level products; strengthening the theoretical explanation of the continuous use; building new theory to describe the complex user involvement phenomenon; exploring the path and boundary conditions of smart wearable health technologies for promoting health-related behaviors.

Cite this article

Li Caining , Bi Xinhua , Yang Yihao , Tian Xiaoxu . A Systematic Literature Review of Research on Smart Wearable Health Technology Users' Behaviors[J]. Library and Information Service, 2022 , 66(17) : 141 -151 . DOI: 10.13266/j.issn.0252-3116.2022.17.013

References

[1] LI C, LIN S, CHIB A. The state of wearable health technologies:a transdisciplinary literature review[J]. Mobile media & communication, 2021, 9(2):353-376.
[2] ATTIG C, FRANKE T. Abandonment of personal quantification:a review and empirical study investigating reasons for wearable activity tracking attrition[J]. Computers in human behavior, 2020, 102(1):223-237.
[3] PATEL S, ASCH A, VOLPP G. Wearable devices as facilitators, not drivers, of health behavior change[J]. Journal of American Medical Association, 2015, 313(5):459-460.
[4] BINYAMIN S S, HOQUE M R. Understanding the drivers of wearable health monitoring technology:an extension of the unified theory of acceptance and use of technology[J]. Sustainability, 2020, 12(22):1-20.
[5] MEIER D Y, BARTHELMESS P, SUN W, et al. Wearable technology acceptance in health care based on national culture differences:cross-country analysis between Chinese and Swiss consumers[J]. Journal of medical Internet research, 2020, 22(10):e18801.
[6] FEEHAN L M, GELDMAN J, SAYRE E C, et al. Accuracy of Fitbit devices:systematic review and narrative syntheses of quantitative data[J]. JMIR mhealth and uhealth, 2018, 6(8):e10527.
[7] LI C, CHEN X, BI X. Wearable activity trackers for promoting physical activity:a systematic meta-analytic review[J]. International journal of medical informatics, 2021, 152:e104487.
[8] 吴江, 曾敏讷, 刘福珍,等. 基于元分析方法的可穿戴设备用户采纳行为研究[J]. 信息资源管理学报, 2017, 7(2):5-13.
[9] 夏恩君, 张真铭. 预防性技术采用元分析及其对创新鸿沟跨越的启示——以可穿戴医疗健康设备为例[J]. 技术经济, 2020, 39(2):134-143.
[10] HIGGINS J P, THOMAS J, CHANDLER J, et al. Cochrane handbook for systematic reviews of interventions[M]. Chichester:John Wiley & Sons, 2019.
[11] GRANT M J, BOOTH A. A typology of reviews:an analysis of 14 review types and associated methodologies[J]. Health information and libraries journal, 2009, 26(2):91-108.
[12] LIBERATI A, ALTMAN D G, TETZLAFF J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions:explanation and elaboration[J]. BMJ, 2009, 339:b2700.
[13] WAGNER J B, MINJE K, TASSÉ M J, et al. Technology tools:increasing our reach in national surveillance of intellectual and developmental disabilities[J]. Intellectual & developmental disabilities, 2019, 57(5):463-475.
[14] 朱亚琳,金灿灿. 黑暗三联征与攻击行为关系的元分析[J]. 心理科学进展, 2021, 29(7):1195-1209.
[15] SCHMIDT F L, HUNTER J E. Methods of meta-analysis:correcting error and bias in research findings[M]. 3rd ed.Thousand Oaks:SAGE, 2014.
[16] 严炜炜, 陈若瑜, 张敏. 基于元分析的在线知识付费意愿影响因素研究[J]. 情报学报, 2021, 40(2):204-212.
[17] LI J, MA Q, CHAN A H S, et al. Health monitoring through wearable technologies for older adults:smart wearables acceptance model[J]. Applied ergonomics, 2019, 75:162-169.
[18] CHOI B, HWANG S, LEE S. What drives construction workers' acceptance of wearable technologies in the workplace?:indoor localization and wearable health devices for occupational safety and health[J]. Automation in construction, 2017, 84:31-41.
[19] PARK E, KIM K J, KWON S J. Understanding the emergence of wearable devices as next-generation tools for health communication[J]. Information technology & people, 2016, 29(4):717-732.
[20] CHEUNG M L, CHAU K Y, LAM M H S, et al. Examining consumers' adoption of wearable healthcare technology:the role of health attributes[J]. International journal of environmental research and public health, 2019, 16(13):2257-2273.
[21] DAI B Z, LARNYO E, TETTEH E A, et al. Factors affecting caregivers' acceptance of the use of wearable devices by patients with dementia:an extension of the unified theory of acceptance and use of technology model[J]. American journal of alzheimers disease and other dementias, 2020, 35:19883493-19883504.
[22] SERGUEEVA K, SHAW N, LEE S H. Understanding the barriers and factors associated with consumer adoption of wearable technology devices in managing personal health[J]. Canadian journal of administrative sciences-revue canadienne des sciences de l administration, 2020, 37(1):45-60.
[23] WANG H L, TAO D, YU N, et al. Understanding consumer acceptance of healthcare wearable devices:an integrated model of UTAUT and TTF[J]. International journal of medical informatics, 2020, 139:104156-104166.
[24] PAPA A, MITAL M, PISANO P, et al. E-health and wellbeing monitoring using smart healthcare devices:an empirical investigation[J]. Technological forecasting and social change, 2020, 153:119226-119236.
[25] TALUKDER M S, SORWAR G, BAO Y K, et al. Predicting antecedents of wearable healthcare technology acceptance by elderly:a combined SEM-Neural network approach[J]. Technological forecasting and social change, 2020, 150:119793-119806.
[26] NIKNEJAD N, HUSSIN A C, GHANI I, et al. A confirmatory factor analysis of the behavioral intention to use smart wellness wearables in Malaysia[J]. Universal access in the information society, 2020, 19(3):633-653.
[27] SERGUEEVA K, SHAW N, LEE S H. Understanding the barriers and factors associated with consumer adoption of wearable technology devices in managing personal health[J]. Canadian journal of administrative sciences, 2019, 37(1):45-60.
[28] KIM T B, HO C T B. Validating the moderating role of age in multi-perspective acceptance model of wearable healthcare technology[J]. Telematics and informatics, 2021, 61:101603-101615.
[29] GAO Y W, LI H, LUO Y. An empirical study of wearable technology acceptance in healthcare[J]. Industrial management & data systems, 2015, 115(9):1704-1723.
[30] LI H, WU J, GAO Y W, et al. Examining individuals' adoption of healthcare wearable devices:an empirical study from privacy calculus perspective[J]. International journal of medical informatics, 2016, 88:8-17.
[31] BIANCHI C, TUZOVIC S, KUPPELWIESER V G. Investigating the drivers of wearable technology adoption for healthcare in South America[J]. Information technology & people, 2022, ahead-of-print. DOI:10.1108/ITP-01-2021-0049.
[32] YANG Q, AL Mamun A, HAYAT N, et al. Modelling the mass adoption potential of wearable medical devices[J]. Plos one, 2022, 17(6):e0269256.
[33] 张敏, 罗梅芬, 聂瑞, 等. 信息生态视域下移动健康信息消费行为分析——以健康可穿戴技术为例[J]. 图书情报知识, 2017, 40(3):61-70.
[34] 张敏, 罗梅芬, 聂瑞. 健康可穿戴技术的用户使用意愿影响因素分析——基于使用经验和健康知识的调节作用[J]. 信息资源管理学报, 2017, 7(2):14-21.
[35] HUARNG K H, YU T H K, LEE C F. Adoption model of healthcare wearable devices[J]. Technological forecasting and social change, 2022, 174:1-7.
[36] JENG M Y, PAI F Y, YEH T M. Antecedents for older adults' intention to use smart health wearable devices-technology anxiety as a moderator[J]. Behavior science (basel), 2022, 12(4):1-16.
[37] PANCAR T, YILDIRIM S O. Exploring factors affecting consumers' adoption of wearable devices to track health data[J]. Universal access in the information society. ahead-of-print. DOI:0.1007/s10209-021-00848-6.
[38] ZHU Y, LU Y, GUPTA S, et al. Promoting smart wearable devices in the health-ai market:the role of health consciousness and privacy protection[J]. Journal of research in interactive marketing, ahead-of-print. DOI:10.1108/JRIM-10-2021-0246.
[39] CHEN P, SHEN Y, LI Z M, et al. What factors predict the adoption of type 2 diabetes patients to wearable activity trackers-application of diffusion of innovation theory[J]. Front public health, 2022, 9:773293-773304.
[40] 吴江, 李姗姗, 胡仙, 等. 健康类可穿戴设备用户融入意向影响因素的实证研究[J]. 信息资源管理学报, 2017, 7(2):22-30.
[41] KIM M. Conceptualization of e-service scapes in the fitness applications and wearable devices context:multi-dimensions, consumer satisfaction, and behavioral intention[J]. Journal of retailing and consumer services, 2021, 61:102562-102577.
[42] LUNNEY A, CUNNINGHAM N R, EASTIN M S. Wearable fitness technology:a structural investigation into acceptance and perceived fitness outcomes[J]. Computers in human behavior, 2016, 65:114-120.
[43] SHIN D H, BIOCCA F. Health experience model of personal informatics:the case of a quantified self[J]. Computers in human behavior, 2017, 69:62-74.
[44] DERANEK K, HEWITT B, GUDI A, et al. The impact of exercise motives on adolescents' sustained use of wearable technology[J]. Behaviour & information technology, 2021, 40(7):691-705.
[45] OC Y, PLANGGER K. Gist do it! How motivational mechanisms help wearable users develop healthy habits[J]. Computers in human behavior, 2022, 128:107089-107102.
[46] MISHRA A, BAKER-EVELETH L, GALA P, et al. Factors influencing actual usage of fitness tracking devices:empirical evidence from the UTAUT model[J]. Health marketing quarterly, ahead-of-print. DOI:10.1080/07359683.2021.1994170
[47] JAMES T, WALLACE L, DEANE J. Using organismic integration theory to explore the associations between users' exercise motivations and fitness technology feature set use[J]. Management information systems quarterly, 2019, 43(1):287-312.
[48] 赵延昇, 王仲杰. 可穿戴设备用户持续使用意愿研究——基于ECM-IS的拓展模型[J]. 东北大学学报(社会科学版), 2018, 20(4):366-372.
[49] JAMES T L, WALLACE L, DEANE J K. Using organismic integration theory to explore the associations between users' exercise motivations and fitness technology feature set use[J]. Management information systems quarterly, 2019, 43(1):287-312.
[50] SIEPMANN C, KOWALCZUK P. Understanding continued smartwatch usage:the role of emotional as well as health and fitness factors[J]. Electronic marketing, 2021, 31(4):795-809.
[51] TALUKDER M S, LAATO S, ISLAM A, et al. Continued use intention of wearable health technologies among the elderly:an enablers and inhibitors perspective[J]. Internet research, 2021, 31(5):1611-1640.
[52] CHAMORRO-KOC M, PEAKE J, MEEK A, et al. Self-efficacy and trust in consumers' use of health-technologies devices for sports[J]. Heliyon, 2021, 7(8):e07794.
[53] WINDASARI N A, LIN F R, KATO-LIN Y C. Continued use of wearable fitness technology:a value co-creation perspective[J]. International journal of information management, 2021, 57:102292-102307.
[54] PENG W, LI L, KONONOVA A, et al. Habit formation in wearable activity tracker use among older adults:qualitative study[J]. JMIR mhealth and uhealth, 2021, 9(1):e22488.
[55] WANG N, XIE W X, ALI A, et al. How do individual characteristics and social capital shape users' continuance intentions of smart wearable products?[J]. Technology in society, 2022, 68:101818-101829.
[56] KANG H, OH J. Beyond user control and two-way communication:the four-factor model of interactivity of wrist-worn smart devices[J]. Media psychology, 2022, 25(2):234-261.
[57] WHELAN M E, DENTON F, BOURNE C L A, et al. A digital lifestyle behaviour change intervention for the prevention of type 2 diabetes:a qualitative study exploring intuitive engagement with real-time glucose and physical activity feedback[J]. BMC public health, 2021, 21(1):130-141.
[58] RIEDER A, ESERYEL U Y, LEHRER C, et al. Why users comply with wearables:the role of contextual self-efficacy in behavioral change[J]. International journal of human-computer interaction, 2021, 37(3):281-294.
[59] NELSON E C, SOOLS A M, VOLLENBROEK-HUTTEN M M R, et al. Embodiment of wearable technology:qualitative longitudinal study[J]. JMIR mhealth and uhealth, 2020, 8(11):e16973.
[60] ANDERSEN T O, LANGSTRUP H, LOMBORG S. Experiences with wearable activity data during self-care by chronic heart patients:qualitative study[J]. Journal of medical Internet research, 2020, 22(7):e15873.
[61] PINGO Z, NARAYAN B. "My smartwatch told me to see a sleep doctor":a study of activity tracker use[J]. Online information review, 2020, 44(2):503-519.
[62] ZIMMER M, KUMAR P, VITAK J, et al. 'There's nothing really they can do with this information':unpacking how users manage privacy boundaries for personal fitness information[J]. Information communication & society, 2020, 23(7):1020-1037.
[63] GOODYEAR V A, KERNER C, QUENNERSTEDT M. Young people's uses of wearable healthy lifestyle technologies; surveillance, self-surveillance and resistance[J]. Sport education and society, 2019, 24(3):212-225.
[64] GITTUS M, FULLER-TYSZKIEWICZ M, BROWN H E, et al. Are Fitbits implicated in body image concerns and disordered eating in women?[J]. Health psychology, 2020, 39(10):900-904.
[65] FENG Y, AGOSTO E. Revisiting personal information management through information practices with activity tracking technology[J]. Journal of the Association for Information Science and Technology, 2019, 70(12):1352-1367.
[66] ESMONDE K. 'There's only so much data you can handle in your life':accommodating and resisting self-surveillance in women's running and fitness tracking practices[J]. Qualitative research in sport exercise and health, 2020, 12(1):76-90.
[67] ZHANG Z J, GIORDANI B, MARGULIS A, et al. Efficacy and acceptability of using wearable activity trackers in older adults living in retirement communities:a mixed method study[J]. BMC geriatrics, 2022, 22(1):1-9.
[68] BURFORD K, GOLASZEWSKI N M, BARTHOLOMEW J. "I shy away from them because they are very identifiable":a qualitative study exploring user and non-user's perceptions of wearable activity trackers[J]. Digital health, 2021, 7:1-10.
[69] FENG Y, AGOSTO E. From health to performance:Amateur runners' personal health information management with activity tracking technology[J]. ASLIB journal of information management, 2019, 71(2):217-240.
[70] STIGLBAUER B, WEBER S, BATINIC B. Does your health really benefit from using a self-tracking device? evidence from a longitudinal randomized control trial[J]. Computers in human behavior, 2019, 94:131-139.
[71] ATTIG C, FRANKE T. I track, therefore i walk-exploring the motivational costs of wearing activity trackers in actual users[J]. International journal of human-computer studies, 2019, 127:211-224.
[72] SOBKO T, BROWN G. Reflecting on personal data in a health course:integrating wearable technology and eportfolio for ehealth[J]. Australasian journal of educational technology, 2019, 35(3):55-70.
[73] HADI R, VALENZUELA A. Good vibrations:Consumer responses to technology-mediated haptic feedback[J]. Journal of consumer research, 2020, 47(2):256-271.
[74] OH J, KANG H. User engagement with smart wearables:four defining factors and a process model[J]. Mobile media & communication, 2021, 9(2):314-335.
[75] JUNG E H, KANG H. Self-determination in wearable fitness technology:the moderating effect of age[J]. International journal of human-computer interaction, ahead-of-print. DOI:10.1080/10447318.2021.2002048.
[76] 贾宁. 高校图书馆阅读推广活动用户卷入度研究——以上海师范大学图书馆为例[C]//中国图书馆学会年会论文集. 北京:中国图书馆学会年会, 2016.
[77] O'BRIEN H L, TOMS E G. The development and evaluation of a survey to measure user engagement[J]. Journal of the American Society for Information Science and Technology, 2010, 61(1):50-69.
[78] O'BRIEN H L, TOMS E G. What is user engagement? a conceptual framework for defining user engagement with technology[J]. Journal of the American Society for Information Science and Technology, 2008, 59(6):938-955.
[79] O'BRIEN H L, TOMS E G. Examining the generalizability of the user engagement scale (ues) in exploratory search[J]. Information processing & management, 2013, 49(5):1092-1107.
[80] OH J. User engagement with smart wearables:four defining factors and a process model[J]. Mobile media & communication, 2020, 9(2):314-335.
[81] NELSON E, VERHAGEN T, NOORDZIJ M. Health empowerment through activity trackers:an empirical smart wristband study[J]. Computers in human behavior, 2016, 62:364-74.
[82] JANG J, KIM J. Healthier life with digital companions:effects of reflection-level and statement-type of messages on behavior change via a perceived companion[J]. International journal of human-computer interaction, 2019, 36 (2):172-189.
[83] RATZ T, LIPPKE S, MUELLMANN S, et al. Effects of two Web-based interventions and mediating mechanisms on stage of change regarding physical activity in older adults[J]. Applied psychology:health and well-being, 2020, 12(1):1-17.
[84] 李彩宁, 毕新华, 王雅薇. 个人健康信息管理技术促进用户健康行为的心理机制:基于智能可穿戴健康产品的实证研究[J]. 图书情报工作, 2021, 65(19):72-83.
[85] LEHRER C, ESERYEL U Y, RIEDER A, et al. Behavior change through wearables:the interplay between self-leadership and it-based leadership[J]. Electronic marketing, 2021, 31(4):747-764.
[86] ABOUZAHRA M, GHASEMAGHAEI M. Effective use of information technologies by seniors:the case of wearable device use[J]. European journal of information systems, 2022, 31(2):241-255.
[87] PAUL G, IRVINE J. Privacy implications of wearable health devices[C]//Proceedings of the 7th international conference on security of information and networks. New York:Association for Computing Machinery, 2014:117-121.
[88] SANCHEZ O R, TORRE I, HE Y Y, et al. A recommendation approach for user privacy preferences in the fitness domain[J]. User modeling and user-adapted interaction, 2020, 30(3):513-565.
[89] CAN Y S, ERSOY C. Privacy-preserving federated deep learning for wearable IoT-based biomedical monitoring[J]. ACM transactions on Internet technology, 2021, 21(1):1-17.
[90] LANGLEY M R. Hide your health:addressing the new privacy problem of consumer wearables[J]. Georgetown law journal, 2015, 103(6):1641-1659.
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