An empirical study of wearable technology acceptance in healthcare

Date19 October 2015
Published date19 October 2015
AuthorYiwen Gao,He Li,Yan Luo
Subject MatterInformation & knowledge management,Information systems,Data management systems
An empirical study of wearable
technology acceptance
in healthcare
Yiwen Gao
School of Economic Information Engineering,
Southwestern University of Finance and Economics, Chengdu, China
He Li
Fogelman College of Business and Economics,
The University of Memphis, Memphis, Tennessee, USA, and
Yan Luo
Southwestern University of Finance and Economics, Chengdu, China
Purpose The purpose of this paper is to investigate the factors associated with consumers intention
to adopt wearable technology in healthcare, and to examine the moderating effects of product type on
consumers adoption intention.
Design/methodology/approach An integrated acceptance model was developed based on unified
theory of acceptance and use of technology 2 (UTAUT2), protection motivation theory (PMT), and
privacy calculus theory. The model was tested with 462 respondents using a survey.
Findings Consumers decision to adopt healthcare wearable technology is affected by factors from
technology, health, and privacy perspectives. Specially, fitness device users care more about hedonic
motivation, functional congruence, social influence, perceived privacy risk, and perceived
vulnerability, but medical device users pay more attention to perceived expectancy, self-efficacy,
effort expectancy, and perceived severity.
Originality/value This study is among the first to investigate healthcare wearable device from
behavioral perspective. It also helps to comprehensively understand emerging health information
technology (HIT) acceptance from technology, health, and privacy perspectives.
Keywords Healthcare, Wearable technology, Adoption intention, Fitness wearable device,
Medical wearable device
Paper type Research paper
1. Introduction
The electronic technology that is incorporatedinto accessories that can be directly worn
on the body is widely known as wearable technology (Tehrani et al., 2014). According to
Analysis Mason[1], the wearable device market will generate $22.9 billion in revenue by
2020. The marketis predicted to grow at a CAGR of 50 percentbetween the years of 2014
and 2020. The popularity of wearable technology not only can promote physiolytics
efficiency by linking them with data analytics (Wolff, 2013), but also can provide more
opportunities for back-end players such as App developers (Maisto, 2013).
Recently, a large number of wearable devices, ranging from smart glass such as
Google glass, smart watch including Geak Watch, iWatch, and Samsung Galaxy Gear,
to smart bracelet such as Jawbone, Fitbit, and Goodon, etc., are available for public
users. Wearable devices are primarily used in the field of military technology (Tehr ani
et al., 2014). However, they are more like fashionable accessories in the early stage for
Industrial Management & Data
Vol. 115 No. 9, 2015
pp. 1704-1723
©Emerald Group Publishing Limited
DOI 10.1108/IMDS-03-2015-0087
Received 21 March 2015
Revised 12 June 2015
Accepted 1 August 2015
The current issue and full text archive of this journal is available on Emerald Insight at:
the public. Up to now, the largest application of wearable devices is in the healthcare
and medicine fields as wearable technology exhibits natural advantages in healthcare
field (Chan et al., 2012). The healthcare data can be continuously collected and
transformed since users generally wear the device 24 hours a day. In addition,
depending on the capacities on providing unseen scanning and sensory features,
wearable devices have potentials to improve the quality of patientshealthcare seeking
and doctor-patient communications (Maisto, 2013).
There are two main kinds of healthcare wearable devices in the current market.
The first is fitness wearable devices, which help users to track and monitor their daily
fitness conditions such as steps, distance, calories burned, sleep, and diet. These fitness
wearable devices such as Fitbit, Jawbone, and 360 Kids Guardian, are more suitable for
the young and the healthy users. On the contrary, medical wearable devices are more
likely to be adopted by the elder and the unhealthy users. Wearable medical devices
are generally designed for certain disease such as diabetes and cancer. Various firms,
including Google, Apple, and Samsung, etc., are making efforts on researching various
kinds of medical wearable devices. For instance, although Google has several patents of
medical wearable devices, it still researches other related technologies like genetic
testing. Apple has shown interest in researching medical sensor-laden devices tha t can
analyze glucose levels via a persons tear. In addition, Samsung have announced a
project joint with medical professionals to create new medical sensors at the University
of California, San Francisco.
In addition to developthese amazing technologies,how to attract and keep their users
is also an important issue for business managers. However, pioneering extant studies
about users adoption of healthcare wearable devices just have conceptually stated some
critical factors or empirically examined a limited number of important roles from
technology perspective (Claes et al., 2015; Steele et al., 2009; Fraile et al.,2010).
An integrated framework that can comprehensively explain individuals adoption of
wearable device in healthcare is needed. Thus, we are going to fill this research gap by
proposing and validating an integrative model to explain individuals adoption of
healthcarewearable device from multiple perspectives. Since healthcarewearable devices
continuously collect users personal health information in real time, and individuals
personal health information is more sensitive than other types of information such as
demographic and general transaction information (Bansal et al.,2010),healthcare
wearable devices should not only be treated as an application of emerging technology in
healthcare, butalso should be regarded as a high privacy concern product.Therefore, we
develop an integrative framework that consists of technology, healthcare, and privacy
perspectives to examine users decisions to adopt healthcare wearable devices.
Furthermore, given that fitness and medical wearable devices have different targeted
user groups and functions, we also investigate the moderating effect of product type on
consumers adoption intention.
The proposed model was tested by analyzing data collected from 462 respondents
through a survey conducted at three large social network groups related to healthcare
wearable devices. Most hypotheses were validated by the empirical data. This study is
believed to present both theoretical and practical contributions. Theoretically, by
developing and validating an integrated framework that consists of technology
acceptance, health behavior, and privacy context, this study not only provides a more
comprehensive understanding of consumers acceptance of healthcare wearable device,
but also has potentials to provide theoretical foundations for future healthcare
wearable device adoption research. Practically, both wearable device managers and
acceptance in

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