Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective

•An adoption model of healthcare wearable technology was proposed and tested.•Individual’s wearable device adoption decision is determined by risk–benefit assessment.•Antecedents of individual’s privacy calculus for wearable device are identified and validated.•Theoretical contributions and practica...

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Vydané v:International journal of medical informatics (Shannon, Ireland) Ročník 88; s. 8 - 17
Hlavní autori: Li, He, Wu, Jing, Gao, Yiwen, Shi, Yao
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Ireland Elsevier Ireland Ltd 01.04.2016
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ISSN:1386-5056, 1872-8243, 1872-8243
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Abstract •An adoption model of healthcare wearable technology was proposed and tested.•Individual’s wearable device adoption decision is determined by risk–benefit assessment.•Antecedents of individual’s privacy calculus for wearable device are identified and validated.•Theoretical contributions and practical suggestions were also discussed. Wearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on healthcare wearable devices from technical perspective, this paper explores the predictors of individuals’ adoption of healthcare wearable devices. Considering the importance of individuals’ privacy perceptions in healthcare wearable devices adoption, this study proposes a model based on the privacy calculus theory to investigate how individuals adopt healthcare wearable devices. The proposed conceptual model was empirically tested by using data collected from a survey. The sample covers 333 actual users of healthcare wearable devices. Structural equation modeling (SEM) method was employed to estimate the significance of the path coefficients. This study reveals several main findings: (1) individuals’ decisions to adopt healthcare wearable devices are determined by their risk–benefit analyses (refer to privacy calculus). In short, if an individual’s perceived benefit is higher than perceived privacy risk, s/he is more likely to adopt the device. Otherwise, the device would not be adopted; (2) individuals’ perceived privacy risk is formed by health information sensitivity, personal innovativeness, legislative protection, and perceived prestige; and (3) individuals’ perceived benefit is determined by perceived informativeness and functional congruence. The theoretical and practical implications, limitations, and future research directions are then discussed.
AbstractList •An adoption model of healthcare wearable technology was proposed and tested.•Individual’s wearable device adoption decision is determined by risk–benefit assessment.•Antecedents of individual’s privacy calculus for wearable device are identified and validated.•Theoretical contributions and practical suggestions were also discussed. Wearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on healthcare wearable devices from technical perspective, this paper explores the predictors of individuals’ adoption of healthcare wearable devices. Considering the importance of individuals’ privacy perceptions in healthcare wearable devices adoption, this study proposes a model based on the privacy calculus theory to investigate how individuals adopt healthcare wearable devices. The proposed conceptual model was empirically tested by using data collected from a survey. The sample covers 333 actual users of healthcare wearable devices. Structural equation modeling (SEM) method was employed to estimate the significance of the path coefficients. This study reveals several main findings: (1) individuals’ decisions to adopt healthcare wearable devices are determined by their risk–benefit analyses (refer to privacy calculus). In short, if an individual’s perceived benefit is higher than perceived privacy risk, s/he is more likely to adopt the device. Otherwise, the device would not be adopted; (2) individuals’ perceived privacy risk is formed by health information sensitivity, personal innovativeness, legislative protection, and perceived prestige; and (3) individuals’ perceived benefit is determined by perceived informativeness and functional congruence. The theoretical and practical implications, limitations, and future research directions are then discussed.
Highlights • An adoption model of healthcare wearable technology was proposed and tested. • Individual’s wearable device adoption decision is determined by risk–benefit assessment. • Antecedents of individual’s privacy calculus for wearable device are identified and validated. • Theoretical contributions and practical suggestions were also discussed.
Wearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on healthcare wearable devices from technical perspective, this paper explores the predictors of individuals' adoption of healthcare wearable devices. Considering the importance of individuals' privacy perceptions in healthcare wearable devices adoption, this study proposes a model based on the privacy calculus theory to investigate how individuals adopt healthcare wearable devices.BACKGROUNDWearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on healthcare wearable devices from technical perspective, this paper explores the predictors of individuals' adoption of healthcare wearable devices. Considering the importance of individuals' privacy perceptions in healthcare wearable devices adoption, this study proposes a model based on the privacy calculus theory to investigate how individuals adopt healthcare wearable devices.The proposed conceptual model was empirically tested by using data collected from a survey. The sample covers 333 actual users of healthcare wearable devices. Structural equation modeling (SEM) method was employed to estimate the significance of the path coefficients.METHODThe proposed conceptual model was empirically tested by using data collected from a survey. The sample covers 333 actual users of healthcare wearable devices. Structural equation modeling (SEM) method was employed to estimate the significance of the path coefficients.This study reveals several main findings: (1) individuals' decisions to adopt healthcare wearable devices are determined by their risk-benefit analyses (refer to privacy calculus). In short, if an individual's perceived benefit is higher than perceived privacy risk, s/he is more likely to adopt the device. Otherwise, the device would not be adopted; (2) individuals' perceived privacy risk is formed by health information sensitivity, personal innovativeness, legislative protection, and perceived prestige; and (3) individuals' perceived benefit is determined by perceived informativeness and functional congruence. The theoretical and practical implications, limitations, and future research directions are then discussed.RESULTSThis study reveals several main findings: (1) individuals' decisions to adopt healthcare wearable devices are determined by their risk-benefit analyses (refer to privacy calculus). In short, if an individual's perceived benefit is higher than perceived privacy risk, s/he is more likely to adopt the device. Otherwise, the device would not be adopted; (2) individuals' perceived privacy risk is formed by health information sensitivity, personal innovativeness, legislative protection, and perceived prestige; and (3) individuals' perceived benefit is determined by perceived informativeness and functional congruence. The theoretical and practical implications, limitations, and future research directions are then discussed.
Background: Wearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on healthcare wearable devices from technical perspective, this paper explores the predictors of individuals' adoption of healthcare wearable devices. Considering the importance of individuals' privacy perceptions in healthcare wearable devices adoption, this study proposes a model based on the privacy calculus theory to investigate how individuals adopt healthcare wearable devices. Method: The proposed conceptual model was empirically tested by using data collected from a survey. The sample covers 333 actual users of healthcare wearable devices. Structural equation modeling (SEM) method was employed to estimate the significance of the path coefficients. Results: This study reveals several main findings: (1) individuals' decisions to adopt healthcare wearable devices are determined by their risk-benefit analyses (refer to privacy calculus). In short, if an individual's perceived benefit is higher than perceived privacy risk, s/he is more likely to adopt the device. Otherwise, the device would not be adopted; (2) individuals' perceived privacy risk is formed by health information sensitivity, personal innovativeness, legislative protection, and perceived prestige; and (3) individuals' perceived benefit is determined by perceived informativeness and functional congruence. The theoretical and practical implications, limitations, and future research directions are then discussed.
Wearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on healthcare wearable devices from technical perspective, this paper explores the predictors of individuals' adoption of healthcare wearable devices. Considering the importance of individuals' privacy perceptions in healthcare wearable devices adoption, this study proposes a model based on the privacy calculus theory to investigate how individuals adopt healthcare wearable devices. The proposed conceptual model was empirically tested by using data collected from a survey. The sample covers 333 actual users of healthcare wearable devices. Structural equation modeling (SEM) method was employed to estimate the significance of the path coefficients. This study reveals several main findings: (1) individuals' decisions to adopt healthcare wearable devices are determined by their risk-benefit analyses (refer to privacy calculus). In short, if an individual's perceived benefit is higher than perceived privacy risk, s/he is more likely to adopt the device. Otherwise, the device would not be adopted; (2) individuals' perceived privacy risk is formed by health information sensitivity, personal innovativeness, legislative protection, and perceived prestige; and (3) individuals' perceived benefit is determined by perceived informativeness and functional congruence. The theoretical and practical implications, limitations, and future research directions are then discussed.
Author Wu, Jing
Li, He
Gao, Yiwen
Shi, Yao
Author_xml – sequence: 1
  givenname: He
  surname: Li
  fullname: Li, He
  organization: Fogelman College of Business and Economics, The University of Memphis, United States
– sequence: 2
  givenname: Jing
  surname: Wu
  fullname: Wu, Jing
  email: kaitlynwu@swufe.edu.cn, kaitlynwu@gmail.com
  organization: School of Economic Information Engineering, Southwestern University of Finance and Economics, China
– sequence: 3
  givenname: Yiwen
  surname: Gao
  fullname: Gao, Yiwen
  organization: School of Economic Information Engineering, Southwestern University of Finance and Economics, China
– sequence: 4
  givenname: Yao
  surname: Shi
  fullname: Shi, Yao
  organization: Fogelman College of Business and Economics, The University of Memphis, United States
BackLink https://www.ncbi.nlm.nih.gov/pubmed/26878757$$D View this record in MEDLINE/PubMed
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Keywords Privacy calculus
Healthcare
Wearable devices
Adoption
Language English
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Snippet •An adoption model of healthcare wearable technology was proposed and tested.•Individual’s wearable device adoption decision is determined by risk–benefit...
Highlights • An adoption model of healthcare wearable technology was proposed and tested. • Individual’s wearable device adoption decision is determined by...
Wearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on healthcare...
Background: Wearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on...
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SubjectTerms Adaptation, Psychological
Adoption
Adult
Confidentiality - psychology
Female
Healthcare
Humans
Internal Medicine
Male
Middle Aged
Models, Theoretical
Other
Perception
Privacy - psychology
Privacy calculus
Telemedicine - instrumentation
Wearable devices
Title Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective
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https://www.clinicalkey.es/playcontent/1-s2.0-S1386505615300770
https://dx.doi.org/10.1016/j.ijmedinf.2015.12.010
https://www.ncbi.nlm.nih.gov/pubmed/26878757
https://www.proquest.com/docview/1765922806
https://www.proquest.com/docview/1790951898
Volume 88
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