1. Introduction
Health care is a topic closely related to the public interest and the sustainability of our society, and thereafter has always been a matter of concern. Nowadays, the global health care industry faces many challenges, such as an aging population, a higher rate of chronic diseases, and rejuvenation of chronic disease patients [
1]. These challenges increase the burden of our medical systems. However, the overall medical resources are insufficient [
2] and their allocation is uneven because of disproportionate development [
3]. This extends patients’ waiting time, increases the workloads of physicians, and enhances medical expenditures [
4]. Healthcare organizations started to consider how to apply information technology (IT) in the health care system to improve its automation level and efficiency [
5]. Proper use of IT in the health care system will improve our ability to collect, store, handle, analyze and transmit medical data in a secure and efficient manner, and help relieve current challenges [
6,
7]. With this in mind, many countries released their new health care systems. For example, the department of health in the UK launched “telemedicine”, a national service framework for the elderly. It is a comprehensive sociotechnical model for medical service delivery with the help of software solutions [
4]. “Telemedicine” is also the prototype of connected health, which aims to “bring the right information to the right person at the right time” [
7].
Connected health can bring benefits for patients, medical organizations, and society. For patients, it allows them to remotely access medical organizations and thereafter provides convenience and flexibility for patients. Additionally, it provides patients with timely health conditions and contributes to disease prevention [
6]. Moreover, patients can authorize medical institutions to share their information with other organizations to customize services they need. For medical organizations, connected health will change the approach of patient management and disease prevention and help develop a more effective and efficient medical system through pervasive computing technologies [
8]. For society, connected health facilitates promotes the coordination among different stakeholders of medical systems and fosters the achievement of sustainability [
5].
There exists an optimistic forecast for the development of connected health. For example, Allaert et al. [
8] predicted that connected health would face a rapid development and reap a reward of several billion euro in the coming years. However, individuals’ acceptance of connected health is still low. According to a public survey conducted in the U.S. and Canada, only 8.9% to 18.2% of individuals are familiar with connected health, and most people are not aware of it. Meanwhile, people do not understand what connected health can bring to our medical industry, and other stakeholders in the health care system do not understand citizens’ opinions and needs towards connected health [
4]. More studies are needed to explore factors affecting individuals’ acceptance of connected health to facilitate user involvement and expand the use of connected health [
9].
Past literature on connected health mainly concentrates on its possibility from the perspective of technology. For example, Rose [
10] summarized technologies that can be used in the connected health system and described the challenges to apply those technologies in connected health. Skiba [
11] investigated the state-of-the-art technologies relevant to connected health and analyzed their potential in supporting connected health. However, technology is not the whole story although it serves as the infrastructure of the connected health system. There are factors other than technology that will affect the success of connected health. For example, both the Food and Drug Administration (FDA) and the Agency for Healthcare Research and Quality in the U.S.A have requested more attention be made to human factors when designing medical devices and systems [
12].
To bridge the gap mentioned above, this study adopted the technology–organization–environment (TOE) framework and explored factors affecting individuals’ acceptance of connected health. This study has three research questions: first, what are potential factors that will affect individuals’ acceptance of connected health; second, what is the ranking of their importance; and third, how do these factors affect individuals’ acceptance of connected health. Specifically, this study summarized 25 potential factors by performing a thorough literature review and a group discussion with 27 undergraduate students. The factors were categorized into technology, individuals, and environmental factors. Then, the study relied on the balanced incomplete block design (BIBD) algorithm to design a best–worst scaling instrument to collect data and rank the importance of factors based on their average B–W scores. In addition, a semi-structured interview was performed to collect text contents and a qualitative study based on grounded theory was conducted to explore how different factors affect individuals’ intention to use connected health services. Conclusions were also discussed.
3. Further Development of the Factor List
This study performed a review of relevant literature and summarized some factors affecting individuals’ acceptance of connected health. However, past literature paid much attention to technology factors while neglecting human factors. To make the factor list more comprehensive, we invited a group of 27 undergraduates to conduct an in-depth discussion. We introduced the purpose of the discussion, explained the definition of connected health and the TOE framework, and presented some practical examples of connected health from both the U.S. and China. First, this study separated participants into 10 groups with 2–3 students in each group. Then, they discussed factors affecting their acceptance of connected health and listed the three most important factors for each dimension of the TOE framework. Third, we read their results group by group in front of all participants without mentioning which group it was, and asked participants to make comments. After the discussion, we asked all respondents to vote whether each factor we obtained affected their acceptance of connected health. All factors obtained from the literature review appeared in the discussion. Finally, we obtained 25 potential factors that may affect individuals’ acceptance of connected health, with 12 technological factors, 8 individual factors, and 5 environmental factors (
Table 2).
In the following sections, we performed a mixed method study to explore our research questions. To answer the first two questions, we performed a best–worst scaling experiment to rank the importance of factors. To answer the third question, we conducted a semi-structured interview and performed a qualitative study based on grounded theory to explore how different factors affect individuals’ acceptance of connected health.
Figure 1 indicates the logic of the current study.
6. Development of Theoretical Model
To explore how factors affected users’ acceptance of connected health, we conducted a qualitative study based on grounded theory (GT). Its core purpose is to generate theory from data through robust and systematic processes, analytical skills, and theoretical sensitivity [
35,
36,
37,
38]. Past literature has verified its suitability in building theoretical models in the emerging research field [
39]. Considering that connected health is relatively new and there are few relevant studies, we chose GT as our research method. GT has three main coding techniques including open coding, axial coding, and selective coding [
36]. Open coding involves a deep reading to identify concepts among information and data; axial coding requires researchers to classify these concepts, integrate them into categories and explore the relationships among the categories; selective coding involves clustering categories into core categories, further exploration in the relationships among core categories, and refining the theoretical model [
40].
6.1. Data Collection
Grounded theory requires us to conduct content analysis with an “open mind,” but not with an “empty head” [
41]. A key guideline of past literature using grounded theory is that we should relate the current study to the broader literature and adopt a “low level theory” to start the content analysis [
37]. This study adopted the lens of the TOE framework to start our content analysis since it is a “low level theory” that is well accepted and we have obtained the relative importance of factors in different categories as listed in
Table 6. When we chose the initial nodes, we preferred to select a balanced factor panel from all three dimensions of the framework. It is reasonable to choose top ranking factors in each dimension. However, there is no rule of thumb to decide how many factors we should include in each dimension. We used the following criteria to select initial nodes that will be used in the semi-structured interview. First, the factor should have a positive B–W score; second, more than half the respondents have chosen the factor as the most important factor at least once; and third, the number of total worst should be contributed by at most one half of the total number of respondents. Finally, eight factors were included in the interview as initial nodes, which were health damage, active feedback, device accuracy, analytical reliability, basic service, trust, privacy concern, and institutional architecture. These initial nodes match the ranking of most important factors in each dimension in
Table 6.
Data was collected through semi-structured interviews. At the beginning, we explained the definitions of connected health and initial nodes, and introduced some examples of connected health. Then, we conducted in-depth interviews to explore whether and how these eight factors affect interviewees’ acceptance of connected health. We welcomed additional variables that would affect their adoption during the interview. We selected 40 interviewees aged between 30 and 50. Among the 40 interviewees, 17 were male (42.5%) and 23 were female (57.5%); 3 were under 20 years old (7.5%), 32 were between 20 and 30 years old (80%), 4 were between 30 and 50 years old (10%) and 1 was over 50 years old (2.5%). Each interview lasted for 30 to 40 min, and we recorded the interviews with the consent of the interviewees. After all interviews were completed, we transcribed the recording into text materials for further coding.
6.2. Data Analysis
NVivo 11, a popular content analysis software, was used to analyze the transcribed interviews. The current study adopted three coding techniques of GT. In the first step of open coding, we selected six interviews and four co-authors coded them together to develop the coding protocol. They discussed the identified concepts to reach an agreement on concept definitions. This guaranteed that all coders have the same understanding of the same concepts. Subsequently, the four co-authors were separated into two groups. Each group coded one-half of the remaining 34 interviews. We relied on inter-coder agreement and consensus to validate new codes, if any. To ensure the reliability and consistency of our coding, we calculated the reliability according to the formula of Boyatzis [
42]:
where
is the reliability;
n is the sample number;
is the mutual agreement between two researchers. This study adopted the average of the mutual agreement of the four researchers, and its formula is as follows:
where
is the completely unified coding number of two researchers;
and
represent the total coding number of the first and second researchers. The reliability calculated by the above formula is 0.99, higher than the critical value of 0.7, indicating that our coding is reliable after discussion.
After open coding, axial coding was conducted to cluster concepts coded in the open coding period into different categories and discover relationships between concepts and categories. Twenty categories of concepts were summarized based on a thorough discussion of the four co-authors, and each category included concepts that are closely related. Then, we performed the first section of selective coding and clustered the 20 categories into 10 core categories as displayed in
Figure 4. Each of these 10 core categories will be discussed in the following section.
6.2.1. Technology Adoption
Given that the current study hopes to explore factors affecting individuals’ acceptance of connected health, we view technology adoption as the dependent variable. Technology adoption represents people’s willingness to use connected health, which includes two aspects of meanings. First, individuals intend to accept the connected health model as a medical service mode, and second, they prefer to share information when using the connected health since information sharing is essential in connected health.
6.2.2. Privacy and Security
The term privacy and security represents individuals’ concern on different aspects of the safety of their information shared in the process of connected health. The first one is inappropriate use of their personal information. For example, they worry that third parties will use their information to conduct harassing calls or disturbing marketing. For example, one interviewee mentioned that, “I do not want to give my information to insurance companies because they often call to introduce a variety of their products. I feel that they will not protect my privacy”. The second aspect is individuals’ concern on the status of privacy and security protection in our society. Information leakage in the real world will decrease individuals’ intention to use connected health service. The third aspect is individuals’ requirement of privacy and security protection. They mentioned that they would try connected health if it protects their privacy and security.
6.2.3. Business Intelligence
Business intelligence here refers to the capacity of connected health to collect personal data, integrate data of the whole medical process, and analyze the integrated dataset to provide medical suggestions for patients. We distinguished three aspects of business intelligence that will affect their acceptance of connected health, which are data collection, data processing, and data sharing. Data collection refers to individuals’ concern of whether connected health can rely on techniques such as wearable devices to accurately collect personal information, especially health related indications. The value of connected health rests on information sharing among different stakeholders in the medical industry such as clinics, hospital, and gyms. For example, many applications such as Nike+ record how many steps their users walk every day. If an individual shared this information with insurance companies, insurance companies can offer a better rate for his or her insurance. Thus, data sharing determines whether we can obtain a whole picture of an individual’s health condition. Data processing refers whether connected health is capable of turning integrated data into insights. For example, one interviewee mentioned that, “if there are any techniques and algorithms that can analyze the data and give us a suggestion, we may believe it is reliable”.
6.2.4. User Benefits
User benefits refer to basic functions and medical suggestions that connected health can offer users. Connected health can offer different types of basic services, such as providing basic information about users’ health condition and allowing users to know their health status. Apart from these basic services, connected health can offer its users some advanced services. For example, connected health can help people distinguish potential diseases and health risks by continuously collecting health medications. Apart from this, connected health can also alert individuals to the consequences of their bad habits and offer individuals suggestions on self-adjustment. For patients who use connected health, the service can also help physicians verify the effectiveness of therapy and distinguish better treatment if any.
6.2.5. User Experience
User experience refers to user’s perception and evaluation of connected health service. The current study obtains users’ major concern of the connected health service. They expect that connected health can offer personalized and high-quality services and increase their service satisfaction. Meanwhile, they hope that connected health can offer feedback and suggestions in a comprehensive and timely manner.
6.2.6. User Knowledge
The current study distinguished two types of user knowledge that affect individuals’ acceptance of connected health. The first is their professional knowledge of medical care and techniques related to connected health such as wearable devices. The other one is knowledge on their motivation to use connected health and expectations towards connected health. According to our coding, we found that interviewees who know better about their motivation and expectations towards connected health express a higher level of intention to use connected health service.
6.2.7. External Factors
This study summarized two types of influences that come from the external environment, which are laws and regulations and social influence. Law and regulations refer to whether the government establishes laws and regulations to protect the rights and interests of connected health users. Some interviewees mentioned that they are more likely to use connected health if current laws protect their rights when using connected health. For example, “If there are no necessary laws and regulations about connected health, it will not make a big difference to the current situation of connected health. Thus, it is good to promote the introduction of relevant laws and regulations”. Social influence refers to recommendation from important others. An individual is more likely to accept connected health if important others are using it or recommend him or her to use it.
6.2.8. Trust in Connected Health
Past literature has demonstrated that potential users’ trust in an IT artifact is an important predictor of technology acceptance. When it comes to the context of connected health, trust also matters to the acceptance of connected health. Interviewees mentioned that they are less likely to choose the product if they do not trust connected health.
6.2.9. Technical Support
Technical support involves health damage, brand reputation, and mature technology architecture. Users need to wear devices to collect health information. Interviewees pay attention to whether these technologies will bring damage for their health. For example, some manufacturers may use toxic materials and some products may cause radiation. Brand reputation is another feature that interviewees consider because products with a high reputation are less likely to cause damage for users. In addition, some interviewees also mentioned that mature technology architecture determines the reliability of connected health and thereafter affects users’ acceptance of connected health.
6.2.10. Pattern of Usage
Pattern of usage refers to how connected health collects personal body indications. For example, as an essential component of connected health, wearable devices collect data by touching specific parts of the human body. Different types of wearable devices have different wearing patterns. For example, where to wear the devices and whether users should wear the devices continuously.
6.3. Conceptual Model from Selective Coding
After the first step of selective coding, the four co-authors went back to the transcribed text to distinguish the relationships among core categories. We concentrated on relationships that occurred more than five times in transcribed texts and obtained the conceptual model in
Figure 5. According to the model, business intelligence and technical support belongs to the technological dimension; user benefits, user experience, trust in connected health, user knowledge, and privacy/security pertains to the individual dimension; and external factors reflect the environmental dimension. The TOE framework supports the explanation power of the proposed conceptual model.
Our study also clarified the correlations among different factors and their paths of affecting individuals’ acceptance of connected health. According to the model, seven core categories directly affect individuals’ acceptance of connected health; they include user knowledge, external factors, business intelligence, privacy/security, user experience, trust in connected health, and technical support. In addition, three core categories will indirectly affect users’ acceptance decision, including external factors, business intelligence, and technical support. External factors not only have a direct impact on adoption of connected health, but also has an indirect relationship with adoption of connected health via privacy and security. In addition, technical support will affect individuals’ trust in connected health and thereafter influence their acceptance of connected health. Based on the transcribed text, business intelligence of connected health is the most important core category since it not only directly affects adoption decision, but also influences adoption in different approaches. Business intelligence will change individuals’ perception in privacy/security and trust in connected health, which will affect their acceptance of connected health. Meanwhile, business intelligence will influence users’ benefits, which will improve their user experience and thereafter affect their adoption decision.
Apart from the direct and indirect relationship we mentioned above, we also distinguished a moderation effect of usage pattern. Some interviewees mentioned that the importance of technical support depends on the usage pattern. For example, if users should wear wearable devices at all times, they will pay more attention to technical support such as device damage when they make acceptance decisions.
7. Discussion
This study summarized 25 potential factors that may affect Chinese young adults’ acceptance of connected health. We ranked the importance of those factors by analyzing data collected from an online survey using the BWS method. We found that health damage of wearable devices is the most important factor in technological dimension. This is reasonable since connected health system is proposed to provide quality medical care in an effective and efficient approach. Individuals will not be likely to accept an IT artifact if it will lead to health damage. Individuals’ trust in connected health is the most important factor in individual dimension. This is because connected health is relatively new and individuals have a high level of uncertainty towards connected health. Trust is necessary under this circumstance to facilitate individuals to accept connected health. Only one environmental factor, institutional architecture, will affect individuals’ acceptance of connected health. This suggests that our government should develop legislation and technological architecture that can guarantee user concerns. This serves as an endorsement by the government and facilitates individuals to accept connected health. The current study also conducted a qualitative study based on grounded theory to explore how different nodes affect individuals’ acceptance of connected health. Finally, we distinguished nine core categories that will affect individuals’ acceptance of connected health as displayed in
Figure 5.
7.1. Theoretical Implication
This study contributes to research on acceptance of connected health. The term connected health is relatively new in China, although it is promising in coping with healthcare challenges. The advancement of technology facilitates the feasibility of connected health system. However, there is a lack of systematic research on factors affecting individuals’ acceptance of connected health. This is not good for realizing the great potential of connected health. In this study, 25 factors are summarized as potential factors that will affect connected health acceptance based on a thorough literature review and in-depth discussion. This provides a factor list for future academic research on the acceptance of connected health.
In addition, past literature primarily focuses on technology aspects, such as how to achieve data analysis ability of connected health and how to guarantee wearable technology security and information safety. However, patients, not technology, are the focal stakeholders in medical care industry. Technology is just a tool that can help realize the objectives of connected health. More studies should explore human factors affecting individuals’ acceptance of connected health. This study introduces two additional dimensions other than technological factors, which are individual factors and environment factors by adopting the technology–organization–environment framework. Apart from twelve technological factors, the individual factors include nine potential factors and the environment factors include five potential factors.
This study applies the BWS method to rank the importance of those 25 factors. The study demonstrates fifteen factors with positive B–W scores, including nine technological factors, five individual factors, and one environmental factor. We can see that technological factors are important, but individual factors are also important in determining individuals’ acceptance of connected health. However, Chinese young adults do not think the environmental factor is important. The results deepen our understanding of important factors affecting Chinese young adults’ acceptance of connected health. The categorization of important factors in three dimensions of the TOE framework also provides theoretical support for future research on acceptance of connected health.
The study also depends our understanding of how different factors affect individuals’ acceptance of connected health. This study proposes a conceptual model as indicated in
Figure 5. The model suggests that seven factors will directly affect individuals’ acceptance of connected health. Meanwhile, three factors will indirectly influence individuals’ acceptance decisions. Also, the model includes a usage pattern as a moderator that will affect the importance of technical support in affecting acceptance decisions. This study is among the first wave of articles that try to explore factors affecting consumers’ intention to use connected health.
7.2. Practical Implication
The current medical care industry faces several challenges, while health authorities are trying to make a balance between quality and cost of medical service. It is important to facilitate the collaboration among stakeholders in the medical care industry to realize the sustainability of a medical care system that will meet the three-bottom line, or economic, environmental, and social factors [
34]. In connected health, different stakeholders are connected through timely information sharing [
17]. This full connection makes it possible for patients to receive care in a proactive and efficient manner. Thus, connected health helps build a sustainable medical care industry. This study explores important factors affecting connected health acceptance, supporting the building of sustainable medical care system and a sustainable society.
Hospital suppliers such as device manufacturers, the government, and patients are the main stakeholders of the medical care delivery process [
16]. Our results provide some suggestions for these main stakeholders. From the perspective of infrastructure manufacturers, they should know that Chinese young adults emphasize whether wearable devices will cause health damage to users, whether the test results of wearable devices are accurate, whether technology can guarantee data security in data transfer process, whether devices are affordable to common users, and whether the device is of high function performance. For medical organizations such as hospitals, they should realize that basic services such as blood glucose monitoring, chronic disease management, and identification of hidden health risks are more attractive than personalized services, such as customized medical service and treatment protocols. Moreover, medical organizations should perform reliable analysis using the data collected and integrated in the connected health systems and provide active feedback for connected health users.
In China, most medical organizations are state-owned, and our government affords a large part of the medical expenses of citizens. Health authorities are trying to find a feasible solution to balance quality and cost of medical services, and connected health is a promising solution. They should consider factors that concerned respondents when designing the connected health system. For example, institutional architecture is the only important environmental factor that will affect Chinese young adults’ acceptance of connected health. The government should pay attention to legislation and technological architecture.
The study also provides some suggestions on how to distinguish potential users of connected health services. Results indicate that trust, health concern, purchasing power, privacy concern, and optimism are important individual factors that will affect their acceptance of connected health. People who trust in connected health, put more emphasis on their health, have a purchasing power, and are optimistic in new technology artifacts are more likely to accept connected health. For example, exercisers are usually more concerned with their health and thereafter may be more likely to adopt connected health.
7.3. Limitations
The results should be interpreted with several limitations in mind. First, our samples are young adults exclusively from China. This may affect the generalizability of relevant results. Future research should collect data from the elderly and from other countries to test the validity of our results. Second, the study ranks the importance of 25 factors by using the best–worst scaling method. Thus, our study has some intrinsic limitations of BWS. For example, factors in a choice combination of the BWS questionnaire may be correlated and exhibit a degree of similarity. This issue may affect respondents’ decision rules and affect the results of BWS [
43]. In addition, respondents should select one most important choice and one least important choice from each choice combinations listed in
Table 4. We may obtain alternative sets of BWS items by performing BIBD. The results may alter if we use an alternative BWS question list. Third, this study further explores how different factors affect consumers’ acceptance of connected health by performing a qualitative study based on grounded theory. The current study therefore has limitations inherent in grounded theory research, such as “not being able to produce statistical generalizability and to be limited to the observed case, and thus running the risk of missing aspects of the phenomenon that can be significant” (p. 32) [
44]. However, our target of using grounded theory is to explain what we observe and propose a conceptual model based on the obtained contents. Future study should test the model using empirical methods such as a survey. Fourth, this study adopts the TOE framework as the theoretical lens. There are different theories that can explain individuals’ acceptance of IT artifacts. Adopting an alternative theoretical lens in a future study may lead to additional insights regarding the mechanisms through which different factors affect individuals’ acceptance of connected health. More studies are needed to enhance the conceptual model of connected health adoption.
8. Conclusions
The global health care industry faces challenges such as an aging population, a higher rate of chronic diseases, rejuvenation of chronic disease patients, insufficient medical resources, and uneven allocation of high-quality medical resources. These challenges impede the establishment of a sustainable medical care system. Connected health is able to help cope with these challenges and has attracted more and more attention of academic researchers and practical managers. However, there is a lack of research on the adoption of connected health, and therefore its acceptance rate is still low. In addition, past literature on connected health primarily focused on technological factors while neglecting human factors. This study summarized 25 potential factors that may affect the acceptance of connected health and introduced two additional dimensions other than technological factors, which are individual factors and environmental factors, by adopting the TOE framework. To verify the importance of those 25 potential factors, this study used the best–worst scaling method to collect data and rank the absolute importance of those factors based on their average B–W scores. Finally, 15 important factors were distinguished, which included nine technological factors, five individual factors, and one environmental factor. We further performed a qualitative study based on grounded theory to explore how different factors affect individuals’ acceptance of connected health. According to content analysis, we proposed a conceptual model explaining how different factors affect individuals’ acceptance of connected health. This study depends on our understanding of the acceptance of connected health, and inspires more researchers to explore mechanisms through which important factors affect individuals’ acceptance decision. This study also helps build a sustainable medical care system that will benefit both patients and society.