Informatics for Health and Social Care

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Investigating factors influencing the adoption of e-Health in developing countries: A patient’s perspective M. Rakibul Hoque, Yukun Bao & Golam Sorwar To cite this article: M. Rakibul Hoque, Yukun Bao & Golam Sorwar (2016): Investigating factors influencing the adoption of e-Health in developing countries: A patient’s perspective, Informatics for Health and Social Care, DOI: 10.3109/17538157.2015.1075541 To link to this article: http://dx.doi.org/10.3109/17538157.2015.1075541

Published online: 11 Feb 2016.

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Date: 22 February 2016, At: 22:00

INFORMATICS FOR HEALTH AND SOCIAL CARE http://dx.doi.org/10.3109/17538157.2015.1075541

Investigating factors influencing the adoption of e-Health in developing countries: A patient’s perspective M. Rakibul Hoquea, Yukun Bao

a

, and Golam Sorwarb

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a Center for Modern Information Management, School of Management, Huazhong University of Science and Technology, Wuhan, P. R. China; bSchool of Business and Tourism, Southern Cross University, Coffs Harbour NSW, Australia

ABSTRACT

KEYWORDS

Purpose: The aim of the study was to investigate factors that influence the adoption and use of e-Health applications in Bangladesh from citizens’ (patients’) perspectives by extending the technology acceptance model (TAM) to include privacy and trust. Methods: A structured questionnaire survey was used to collect data from more than 350 participants in various private and public hospitals in Dhaka, the capital city of Bangladesh. The data were analyzed using the partial least-squares (PLS) method, a statistical analysis technique based on structural equation modeling (SEM). Results: The study determined that perceived ease of use and perceived usefulness and trust (p < 0.05) were significant factors influencing the intention to adopt e-Health. Privacy (p > 0.05) was identified as a less significant factor in the context of e-Health in Bangladesh. The findings also revealed that gender was strongly associated with the adoption and use of e-Health services. Conclusions: The findings of the present study contribute to the development of strategies and policies to enhance e-Health services in Bangladesh. Furthermore, as a result of the generic approach used in this study, the acceptance model developed can be easily modified to investigate the adoption of e-Health in other developing countries.

Bangladesh; e-health; privacy; technology acceptance model (TAM)

Introduction Due to the exponential growth of Internet penetration coupled with advances in networking and information communication technologies, the e-Health movement has been introduced and accepted as an essential and important element in the health care sector. The World Health Organization (WHO) defines e-Health as “the leveraging of information and communication technology (ICT) to connect providers, patients and governments; to educate and inform health care professionals, managers and consumers; to stimulate innovation in care delivery and health system management; and to improve our health care system” (1). e-Health initiatives have been widely viewed as an opportunity for a fundamental improvement in the public health care sector to mitigate the enormous demand and supply of health care in both developed and developing nations (2–3). The Global Observatory for Health, which is part of the WHO, conducted a survey of 96 nations to study the needs of the e-Health tools and concluded that e-Health tools are extremely useful for more than 70% of non-Organization for Economic Co-operation and Development (nonOECD) countries (4). Developed countries have invested and will continue to invest substantial resources in implementing e-Health systems to lower the cost and improve the quality of care (5–7). In recent years, the identification of factors that influence the adoption and acceptance of e-Health systems has CONTACT Yukun Bao [email protected] or [email protected] Center for Modern Information Management, School of Management, Huazhong University of Science and Technology, Wuhan 430074, P. R. China. © 2016 Taylor & Francis

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drawn considerable attention from the academic and non-academic research communities (8). Among other factors, one of the critical aspects for the successful implementation of e-Health is the necessary infrastructure. This area has been thoroughly researched and documented by a number of researchers (9–11). The details of the role of the ICT infrastructure, including Internet adoption, hardware and software, as well as IT professional training and education, and its current status on e-Health implementation have been documented. However, previous research indicates that data security and privacy concerns remain important issues, and the uptake of e-Health, including the uptake of Personal Health Records, suffers from a low adoption rate, particularly in developed nations (12–15). To address these security and privacy issues, many countries, particularly developed nations, have established or are establishing corresponding laws and legislations to protect their citizens’ health data, e.g., Personally Controlled Electronic Health Records Act 2012 (16) and Health Insurance Portability and Accountability Act (17). Similar to the findings observed in developed countries, ICT can play a critical role in the improvement of health and health care systems in developing countries (18). A recent study conducted by Hoque et al. (19) indicated that e-Health is the product of ICT and has a major effect on improving the health care sector in developing countries. The governments in many developing countries have high expectation that the e-Health system will improve health care quality, accessibility, and affordability (20). e-Health can provide better access to health care facilities for everyone, including patients, physician, nurses, and other health care personnel, and can increase health care quality and improve collaboration (21). Due to the well-documented potential benefits, developing countries, including Bangladesh, are also embracing ICT when addressing the problems of access, quality, and cost of health care. Furthermore, the adoption of ICT in the health care sector in developing countries will also accelerate knowledge diffusion and increase access to health information (22). Despite the potential benefits of e-Health, however, its adoption remains a challenge, particularly in developing countries, such as Bangladesh. Bangladesh is a developing country in South East Asia with a population of 156 million. A mixed health system operated by the government and private sectors provide health services to its citizens (23). Currently, there are 593 government hospitals, 467 Upazila- (the second-lowest tier of regional administration in Bangladesh) and Union-level (the lowest tier of the local government) hospitals, and 126 secondary- and tertiary-level hospitals in Bangladesh. Furthermore, 2983 private hospitals and 5220 private diagnostic centers are continuously working to ensure better health services in Bangladesh (24). Although Bangladesh is one of few countries in the world where public hospitals offer free medical services to their citizens at a community level, it has been identified as one of 57 countries in the world with an imbalanced health system characterized by a critical shortage of the health workforce (the number of doctors, nurses, and midwives is below 2.28 per 10,000 individuals) and beds (only four beds per 10,000 individuals) in the hospitals (25). To improve health care services, the e-Health initiative in Bangladesh began in 1998, when the Ministry of Health and Family Welfare (MOHFW) undertook the Health and Population Sector programs (HPSP) to enhance the efficiency of the implemented programs. The government of Bangladesh considers the e-Health system to be a highly significant method for improving the health care level in regular medical practices. Special emphasis is being given to e-Health due to the Digital Bangladesh campaign launched by the present government, which favors the delivery of health services to citizens through ICT (26). Different public and private hospitals, nongovernment organizations (NGOs), and private organizations have introduced a number of e-Health programs and services in the health sectors of the country (27). The Bangladesh Government allocated BDT 11,025.00 lakhs (USD 13 million) for e-Health systems for the period of July 2012 to June 2013. Another 12,500.00 lakhs (USD 16 million) were allocated for the period of July 2013 to June 2014. In addition, the government has extended their resources to the training of doctors and nurses to ensure the effective utilization of e-Health services (24). However, low citizen involvement in e-Health systems has resulted in the observers doubting that the systems would be able to achieve the goals set by the government (28). Based on the

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current e-Health infrastructure, the supply side of e-Health (e.g., providing infrastructure) proves to be promising, but few studies have investigated the demand side (e.g., adoption) (29). It is, therefore, imperative to investigate how these new systems failed to achieve their predefined objectives. Health systems are complex social systems comprising stakeholders with different backgrounds, experiences, and values. The successful adoption of e-Health systems, similar to the adoption of other information systems, depends not only on the supply side but also on the demand side (i.e., end-user perspectives). It is important to understand the impact of social and human factors, such as attitude and perceived ease of use, on adoption attitudes (30–32). A recent study (33) explored the users’ hopes and fears during the implementation of e-Health in Bangladesh. This study indicated that most users were reluctant to use ICT in health services due to their negative perception of its effectiveness and efficacy. However, the study focused on the adoption-related issues from the physicians’ perspective and did not include the patients’ perspective. Based on the above-described findings, it can be concluded that most of the research efforts focused on the users’ attitudes toward e-Health adoption and other factors from the providers’— such as physicians and nurses—perspectives. To the best of our knowledge, no studies, if any, have been conducted from the patients’ perspectives, even though patients play significant roles in the successful adoption of e-Health. In addition, most previous studies have been conducted in the context of developed nations. Therefore, this study attempted to fill the above-identified gaps by investigating the issues associated with the adoption and acceptance of e-Health in the context of Bangladesh from the patients’ perspectives. Along with various social and human factors, privacy and trust have been identified as other challenges to the successful adoption and use of e-Health. Previous research has also shown that gender is another significant factor in the adoption of technology, including e-Health, in developing countries. A previous study suggested that gender exerts a strong moderating effect on the relationship between ease of use, perceptions of relative advantage, and use intentions (34). Another study found that gender is an important moderating factor in the adoption of technology in developing countries (35). Researchers have also revealed that the effective use of ICT in developing countries is influenced by gender (36). However, few or no studies have examined the role of gender in e-Health adoption in Bangladesh. To analyze the acceptance and adoption of e-Health applications in Bangladesh and in agreement with previous research in technology acceptance, this study investigated the basic constructs using the widely accepted model, the technology acceptance model (TAM), with additional variables, i.e., trust, privacy, and gender, as the theoretical basis.

Theoretical framework and hypothesis A number of theories, including the bass diffusion model (37), diffusion of innovations theory (38), technology life cycle (39), theory of reasoned action (40), TAM (41), matching person and technology model (42), social cognitive theory (43), hype cycle (44), and theory of planned behavior (45), have been developed to explain the intention and use of new technologies. Among these models, the TAM is one of the most influential models for information system adoption. It is a well-established theory for the evaluation of technology acceptance and has become an important theoretical tool for health information system research (46). Although an extension of TAM called the unified theory of acceptance and use of technology (UTAUT) model has been tested in the context of health care, the validity of the TAM constructs remains supported by evidence from previous studies (47). Aggelidis and Chatzoglou (48) found that TAM predicts a significant portion of the acceptance of health IT. A number of other theoretical and empirical e-Health studies testing TAM in health care demonstrated that TAM is increasingly depicted as a suitable theory for the health care context (49). A brief review of the basic TAM and its applications to e-Health systems is presented in the next section.

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Technology acceptance model The TAM, derived from the theory of reasoned action, explains users’ acceptance and usage behaviour with regard to information technology (40). According to the TAM, the actual use of a system depends on the intention to use it. The model explains that perceived usefulness (PU) and perceived ease of use (PEU) directly influence the intention to use the technology (50). PU is defined as “the degree to which a person believes that using a particular technology will enhance his/her performance,” and PEU is defined as “the degree to which a person believes that using a particular system would be free of effort (41).” Many published studies have described the role of TAM in the adoption of technology, such as e-Health (51). Jung and Loria (52) implemented the TAM model to investigate the acceptance of e-Health among older people in Sweden and found that the PU and PEU are the main determinants of older peoples’ intention to use e-Health services. Wilson and Lankton (53) used TAM as a conceptual framework to study the patients’ acceptance of e-Health and revealed that the TAM provides a means to understand which variables influence the adoption and future use of e-Health. A recent study revealed that the perceived ability, Internet efficacy, and PU influence the attitudes and use of online health information (54). Another recent study used the TAM to identify factors that affect patients’ acceptance of a web-based interactive self-management technology (55). This study showed that PEU, PU, and health care knowledge predict patients’ acceptance and use of web-based self-management technology. Hu et al. (56) suggested that PEU and PU influence the intention of physicians to use telemedicine. These researchers also confirmed the relationship between intention to use and actual use of telemedicine technology. Wu et al. (57) indicated that PEU, PU, subjective norm, and trust have significant effects on a health care professional’s intention to use an adverse event reporting system in e-Health. Based on the above-described literature, the following hypotheses were proposed for the current study: H1: H2: H3: H4:

Perceived usefulness (PU) positively influences the intention to use e-Health. Perceived ease of use (PEU) positively influences the intention to use e-Health. Perceived ease of use (PEU) positively influences perceived usefulness of e-Health. Intention to use positively influences the actual use of e-Health.

Although the basic TAM comprising PEU and PU constructs presents a rigorous explanation for predicting a user’s acceptance of technology, including e-Health, some studies suggest that additional explanatory variables beyond PEU and PU may be needed depending on the specific technology context (58–63). Davis (41) himself argued that future acceptance research needs to address how other variables affect PEU, PU, and user acceptance. Bagozzi (64) mentioned that TAM does not focus on group, social, cultural, and privacy variables that have an important influence on the adoption of technology. Tung (65) implemented an extended TAM for the adoption of an electronic logistics information system in health information systems in the medical industry. These researchers confirmed the influence of additional variables, namely trust and compatibility, influence the use of health information systems. Ortega and Gonzalez (66) explored the physician’s acceptance of Electronic Health Care Records (EHCR) systems. In their study, trust was identified as an additional variable that affects the physicians’ attitude toward the use of EHCR systems. These researchers found that trust, PU, and PEU have a direct effect on physicians’ decision to use EHCR systems. The above-presented review demonstrates that factors contributing to the acceptance and use of a new technology are likely to vary depending on the targeted users and context. e-Health itself is an emerging new ICT, particularly in Bangladesh. Among other issues, privacy and trust have been identified as major concerns that influence an individual’s decision to use e-Health. Therefore, this study extends the TAM (shown in Figure 1) by the inclusion of two additional salient variables, namely privacy and trust, to increase the number of users in Bangladesh. Gender is also addressed as a moderating variable in the proposed extended model, as will be discussed in the following subsection, titled “Moderating Role of Gender.”

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Perceived Usefulness (PU)

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Perceived Ease of Use (PEU)

Intention to Use

Actual Use

Privacy

Trust Gender Figure 1. Research model.

Privacy and trust Privacy in the health care sector is an issue of increasing importance. Patients need to share information with their physicians for diagnosis and treatment purposes (67). However, patients are reluctant to disclose health-related information, such as HIV, psychiatric behaviour, genetic information, and sexual preference, because they feel it may lead to societal disgrace and discrimination (68). It has also been indicated that the patient’s perception of privacy concerns has increased with an increase in the level of use of health technology (69). Sankar (70) found that most patients agreed to share information with physicians but not with a third party, such as employers and even with family members. Westin (71) revealed that patients have a serious concern regarding the privacy of their personal health information and worry regarding the distribution of this information without their consent. Therefore, the following hypothesis was proposed: H5: Privacy positively influences the intention to use e-Health. Similar to privacy, many researchers have confirmed a relationship between trust and technology acceptance. Moorman et al. (72) defined trust as “a willingness to rely on an exchange partner in whom one has confidence.” Trust plays a significant role in users’ willingness to disclose their status and medical information in health systems (73). Zwaan (74) found a strong relationship between diagnostic errors due to a patient’s failure to report health information and increased patient risk and harm. Sillence (75) argued that trust is one of the most significant factors influencing a patients’ decision to use e-Health websites. Briggs (76) conducted a study on over 2500 people who sought health advice online and found that people are more willing to trust a site if the perceived risk is low. Smith and Manna (77) claimed that the success of e-medicine systems depends on trust and loyalty. Surveys of Internet users suggest that trust is a vital issue in the health domain (78). Trust has also

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been identified by Luo and Najdawi (79), Stefan (80), and McGraw (81) as the most significant issue in the adoption of e-Health. Accordingly, the following hypothesis was proposed: H6: Trust positively influences the intention to use e-Health.

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Moderating role of gender Males and females behave differently and play different roles in society (82). Females are relatively more passive than males in terms of adventure, exploring new things and the use of technology (83). Venkatesh (84) introduced gender as a moderator variable into the unified theory of acceptance and use of technology model (UTAUT). Recently, Zhang (85) addressed gender as a moderator in m-Health adoption and revealed that men have a higher level of adoption intention than women. Bao (86) investigated the influence of gender as a moderating variable in mobile learning adoption and found that gender has significant impacts on PEU and the intention to use but no significant impact on PU. Previous research shows that males are strongly influenced by PU in their decision to adopt technology, whereas females are more strongly influenced by PEU (87). Gender differences have been confirmed in different TAM studies from different points of views: males have a higher level of computer self-efficacy than females (88), process information differently (84), are more inclined to use the Internet than females (89), and are comparatively more active in using technology than females (90). The above-described discussion indicates that gender has a significant influence on a user’s intention to use and use of technology (91). However, few studies have investigated such a relationship in e-Health technology usage, particularly in the context of developing nations, such as Bangladesh (92). Therefore, this study addressed the impact of gender on e-Health adoption (Figure 1) in the context of Bangladesh, and the following hypotheses were formulated: H7: Gender has a significant moderating role in the relationship between PU and the intention to use e-Health. H8: Gender has a significant moderating role in the relationship between PEU and the intention to use e-Health. H9: Gender has a significant moderating role in the relationship between privacy and the intention to use e-Health. H10: Gender has a significant moderating role in the relationship between trust and the intention to use e-Health.

Research design and methods Research setting Due to the limited previous research in the adoption of e-Health, particularly in the context of Bangladesh, an exploratory research study was most justifiable (93). A positivist approach was appropriate for investigating the intention and acceptance of e-Health in this study (94). To test our theoretical model and hypothesis, a survey of patients at different private and public hospitals in Dhaka, Bangladesh, was conducted. Most of the private and public hospitals in Dhaka offer e-Health services and Internet penetration. Internet penetration is one of the prerequisites for e-Health and is high in Dhaka (95), indicating that the targeted sampling area is appropriate for data collection. A convenience sampling method, which is cost-effective and widely applied in information systems research, was used as the survey instrument in this study (96). The purpose of the study was explained in detail to the prospective participants, and informed consent was sought from the subjects prior to commencement of the survey.

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Measures All of the measures for latent constructs within the proposed model were developed from prior studies and modified according to the e-Health context in Bangladesh. The items for PU, PEU, intention to use, and actual use were adapted from Davis (41), Chau and Hu (97), Venkatesh and Davis (50), Taylor and Todd (98), and Venkatesh (80). Measures for privacy were obtained from Featherman and Pavlou (99), Chellappa (100), Chellappa and Pavlou (101), and Korgonkar and Wolin (102). The items for trust were adopted from Gefen (103) Yoon (104), and Tung (65).

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Questionnaire design and data collection The structured questionnaire survey method was used to collect the relevant data for measuring the latent constructs in the research hypotheses. The questionnaire was divided into Part A and Part B. Part A contains the demographic information, which was sought to establish the descriptive characteristics of the sample. Respondents were asked to provide information regarding their gender, age, marital status, educational qualifications, and IT usage experience. Part B includes questions regarding the different constructs in the research model that could be answered using a 5-point Likert scale ranging from (1) “strongly disagree” to (5) “strongly agree.” The questions for each construct are listed in Appendix A. A pilot study was conducted, and the feedback was used to design and test the effectiveness of the final questionnaire. A face-to-face, personally administered, active recruitment strategy was applied to recruit potential participants to this study. The study distributed 350 questionnaires, and 326 were returned, resulting in a 93% response rate. Eight incomplete questionnaires were excluded from the analysis. Thus, 318 questionnaires were subjected to further analysis. The partial least-squares (PLS) method, a statistical analysis technique based on structural equation modeling (SEM), was used to test and validate the proposed extended TAM and the relationships among the hypothesized constructs.

Data analysis and results Demographic information There were no significant differences between the male and female response rates (Appendix B). The majority of participants were over 30 years of age. In addition, 58% of the participants were married, and 31% were unmarried. Moreover, 56% of the participants had a graduate level of education, and 67% had more than 4 years of experience using information technology. Measurement model The measurement model was assessed by examining the internal reliability, convergent validity, and discriminant validity (105). The internal reliability was evaluated by examining Cronbach’s alpha and composite reliability, and a level of 0.70 was considered an indicator of acceptable internal consistency (106). The constructs with an average variance extracted (AVE) of at least 0.50 can be assumed to present convergent validity, and a similar assumption can be made if the item loading is well above 0.50 (107). Table 1 shows the loadings, composite reliability, Cronbach’s alpha, and AVE obtained in this study. The calculated Cronbach’s alpha (α) values ranged from 0.81 to 0.93. Values greater than 0.70 support a strong internal reliability. Table 1 also shows that the estimated loading range (0.80 to 0.97) and AVE range (0.67 to 0.87) are greater than the recommended levels. Therefore, the conditions for convergent validity are satisfied in this study. The discriminant validity was assessed by the square root of the AVE and cross-loading matrix. For satisfactory discriminant validity, the square root of the AVE of a construct should be greater than its correlation with other constructs (108). The calculated square root of AVE, which is shown

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Table 1. Measurement model. Constructs Actual use Intention to use Perceived ease of use

Privacy

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Perceived usefulness

Trust

Items ACT1 ACT2 ACT3 INT1 INT2 INT3 PEU1 PEU2 PEU3 PEU4 PRI1 PRI2 PRI3 PU1 PU2 PU3 PU4 TRU1 TRU2 TRU3

Loadings 0.84 0.92 0.92 0.81 0.85 0.90 0.89 0.87 0.81 0.88 0.96 0.90 0.92 0.82 0.80 0.81 0.83 0.96 0.86 0.97

CR 0.92

Cronbach’s alpha 0.87

AVE 0.80

0.89

0.81

0.73

0.92

0.88

0.74

0.95

0.93

0.87

0.89

0.84

0.67

0.95

0.93

0.87

AVE = average variance extracted; CR = composite reliability.

Table 2. Correlation matrix and square root of the AVE. ACT INT PEU PRI PU TRU

ACT 0.89 0.83 0.74 –0.04 0.65 0.06

INT

PEU

PRI

PU

TRU

0.86 0.74 –0.10 0.59 0.12

0.86 –0.12 0.51 0.07

0.93 0.21 –0.87

0.82 –0.19

0.94

Note: ACT = actual use; INT = intention to use; PEU = perceived ease of use; PRI = privacy; PU = perceived usefulness; TRU = trust.

Table 3. Structural model. Path INT -> ACT PEU -> INT PEU -> PU PRI -> INT PU -> INT TRU -> INT

Coefficient 0.828 0.576 0.511 0.120 0.321 0.250

t-statistics 55.155 11.820 10.880 1.168 6.387 2.565

Comments Supported Supported Supported Not supported Supported Supported

R2 for INT = 0.636; R2 for ACT = 0.686; Significant at p < 0.05.

in Table 2, was greater than the corresponding correlation, confirming the discriminant validity of the data.

Structural model A structural model was developed to identify the relationships among the constructs in the research model. The bootstrap method was used to test the hypotheses at a level of significance of 0.05 (p < 0.05) (109). In the first stage, the study tested the relationship between dependent and independent variables by path coefficient (β) and t-statistics. In the second stage, the study discovered the role of gender as a moderating variable. Table 3 shows the path coefficient (β) and t-statistics. The results show that PU (t = 6.387, β = 0.321, p < 0.05), PEU (t = 11.820, β = 0.576, p < 0.05), and trust (t = 2.565, β = 0.250, p < 0.05) have significant effects on the intention to use e-Health and that PEU is positively associated with PU

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(t = 10.880, β = 0.511, p < 0.05). Thus, H1, H2, H3, and H6 are supported by the results. However, surprisingly, privacy (t = 1.168, β = 0.120, p > 0.05) had no significant effect on the intention to use e-Health. Thus, H5 was not supported. As indicated in these studies, PEU is a more important determinant than PU (β = 0.576 versus β = 0.321, p < 0.05) with regard to e-Health adoption in Bangladesh. Finally, the single linear regression results confirmed that intention to use is positively associated with actual use (t = 55.155, β = 0.828, p < 0.05), supporting H4. The model explains 63.6% of the variance in the intention to use e-Health (=0.636) and 68.6% of the variance in the actual use of e-Health (=0.686).

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Moderating effect of gender Table 4 shows the moderating effect of gender. In terms of PEU (0.667 versus 0.133, t = 4.970, p < 0.05), privacy (0.639 versus 0.010, t = 4.437, p < 0.05), and trust (0.893 versus 0.106, t = 7.810, p < 0.05), males had a higher level of intention to use e-Health than females. Thus, Hypotheses 7–9 were all supported. Therefore, the results support the assertion that males find it easier to adopt e-Health technologies and services than females. Table 4 also shows that females had a higher level of PU with regard to e-Health adoption (0.031 versus 0.637, t = 9.045, p < 0.05) than males. According to Table 4, it can, therefore, be concluded that gender has a significant impact on the decision to use e-Health in Bangladesh.

Discussion This study applied an extended TAM model to determine users’ (patients’) behavioral intention to adopt e-Health in the Bangladesh context. Overall, the study provides empirical support for the hypotheses proposed in the research. Our findings are in agreement with the results of previous studies on the application of TAM in e-Health adoption (32,63). PU was found to be a significant predictor of the intention to use e-Health. Therefore, users are likely to use e-Health if the technology appears to be useful. Lim (110) also found that PU positively predicts the intention of Singaporean women to accept and use mobile phones for health information. Our results support the hypothesis that PEU has a significant influence on the intention to use e-Health. PEU also predicts the PU and was found to be a stronger predictor of intention to use e-Health. These findings are consistent with the results of past studies, indicating that PEU is more important than PU for technology acceptance, including e-Health adoption (111). In addition to the basic TAM variables, privacy and trust were identified and investigated in this study. It is generally argued that trust is an important prerequisite for users’ acceptance of electronic services, such as e-Health, e-commerce, and e-governance (112). Our results confirm the positive impact of trust on the patients’ intention to use e-Health in Bangladesh, which is consistent with the results of some previous studies (65,113). In this study, no significant relationship was found between privacy and the acceptance and use of e-Health in Bangladesh. This finding is apparently surprising, given that many studies confirm a direct relationship between privacy and technology adoption. For example, Wilkowska and Ziefle (114) Table 4. Moderating effect of gender. Female Path INT -> ACT PEU -> INT PEU -> PU PRI -> INT PU -> INT TRU-> INT Significant at p < 0.05.

Coefficient 0.805 0.133 0.643 0.010 0.637 –0.106

Male t-statistics 29.391 1.876 11.991 0.095 10.552 1.097

Coefficient 0.905 0.667 0.367 0.639 –0.031 0.893

Comparison t-statistics 76.616 8.126 4.723 7.383 1.061 12.331

t-statistics 3.062 4.970 2.902 4.437 9.045 7.810

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found a strong correlation between privacy and acceptance and usage of medical assistive technologies. Our findings may be reflective of the fact that people in Bangladesh are not highly concerned with privacy and with disclosing information to third parties, which is due to a number of reasons, such as Bangladesh’s collectivist culture, the low bargaining power of the patients, and the almost-complete absence of a Privacy Act or regulation to support the protection of patient data or user rights in Bangladesh. Male doctors, male nurses, and other male personnel in government hospitals even conduct the medical examinations of rape victims (115). These arguments may suggest that privacy does not play a significant role in e-Health adoption in the current situation in Bangladesh. This study also investigated the effect of gender on the adoption of e-Health in Bangladesh. Our findings show that gender significantly influences the intention to use e-Health in the local context. The findings show that males and females express their views about PU, PEU, privacy, and trust in e-Health adoption differently. It has been found that PEU has a stronger influence on the adoption of e-Health for males. This finding may be reflective of the socioeconomic condition in Bangladesh, where males has more access to technology than females. Most females in Bangladesh are housewives with less opportunity to access and use technology, resulting in unfamiliarity with technology. The results also show that gender has a significant impact on trust in technology. Males trust the use of technology more strongly than females. This finding is consistent with the results of some previous studies. For example, Siegrist (116) found that females have less trust in and exhibit a lower rate of acceptance of technology than males. Awad and Ragowsky (117) also found that the effect of trust on online shopping is stronger for males than females. The findings of our study also show that females have PU to a greater extent than males do when making a decision regarding e-Health adoption. This finding is also consistent with some previous observations (118).

Implications This research study has important theoretical and practical implications in the area of e-Health adoption in developing countries, specifically Bangladesh. TAM is a widely used model in the study of users’ acceptance of technologies. However, few previous studies have tested the validity of TAM constructs in e-Health, and the current works have been limited to the context of developed nations. This study justifies the validity of TAM constructs by extending the base model to include additional variables, i.e., trust and privacy, in the context of a developing country, such as Bangladesh. Furthermore, we delineated how gender differences affect trust and influence behavior and revealed that the effects of PU and PEU on behavioral intention are moderated by gender. Our empirical findings may provide information regarding the development of practical guidelines for the successful implementation of e-Health services in Bangladesh. This study revealed that PU and PEU have a strong influence on patients’ intention to use e-Health. This finding suggests that user-friendly interfaces are particularly sensitive to gender (119) and that the usefulness and efficiency of e-Health services and technologies are critically important to achieving a wider adoption of these technologies (120–121). Online health information and services must satisfy the condition of users’ continued trust to ensure the success of e-Health applications (122). The study found an insignificant co-relationship between privacy and the acceptance of e-Health. As elaborated in the previous section, this finding may be unexpected but could be reflective of the current socioeconomic context of Bangladesh. This finding is significant to the Bangladesh Government and policymakers because the privacy of personal information, including health records, should be considered a citizen’s basic right. In fact, the finding suggests that inadequate privacy policies and legislations result in a lack of understanding of health information privacy issues.

Study limitations and future research directions This study was conducted on a sample population selected from hospitals located only in Dhaka, the capital of Bangladesh. Hence, the results may not provide a true reflection of the attitudes toward the

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intention to use e-Health of the entire population of Bangladesh because approximately 76% of the Bangladesh population live in rural areas with unbalanced socioeconomic infrastructures and privileges, including access to technology, education, and health (123). A potential future research study, therefore, could focus on a wider scope, including rural areas, to identify and include other potential factors, such as socioeconomic status and culture, in order to develop a model that is more widely applicable. Furthermore, based on the generic nature of the approach, the acceptance model developed in this study can be applied to other developing countries with a less advanced e-Health infrastructure than expected. The model proposed in this study can also be applied to the adoption of other types of e-Health services, such as mobile health (mHealth) and Electronic Health Record (EHR), in the context of Bangladesh.

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Conclusions E-Health, while promising, remains a challenge in developing countries, such as Bangladesh. The successful adoption of e-Health depends on the engagement of end users, i.e., both physicians and patients. However, based on the published work, it is clear that few studies have attempted to reveal patients’ attitudes toward the acceptance and use of e-Health, particularly in Bangladesh. This study has revealed some attitudinal determinants to the adoption of e-Health in developing countries from the patients’ perspective and has confirmed a hypothesized correlational model using the TAM as a framework for predicting patients’ attitudes toward the acceptance and use of e-Health technologies in the context of e-Health in Bangladesh. The basic TAM was extended to include the impact of privacy, trust, and gender in the context of e-Health in Bangladesh. This study confirmed that PU, PEU, and trust are vital for the adoption of e-Health in Bangladesh. In developed countries, privacy is noted as one of the most significant factors to the adoption and use of e-Health technology. However, interestingly, this study identified privacy as a less significant factor in Bangladesh. The findings of this study contribute to the development of strategies and policies to enhance e-Health services in Bangladesh. In addition, the developed model can easily be adapted for investigating the adoption of e-Health in other developing countries.

Conflict of interest There are no conflicts of interest associated with the submission of this manuscript.

Ethical approval Ethical approval for the study was granted by the Center for Modern Information Management, School of Management, Huazhong University of Science and Technology, P. R. China.

Funding This research was supported by the MOE (Ministry of Education in China) Project of Humanities and Social Science (Project No. 13YJA630002) and a grant from the Modern Information Management Research Center at Huazhong University of Science and Technology (Project No. 2014AA043).

Notes on contributors Md. Rakibul Hoque contributed to the conceptualization and design of the study, the collection and analysis of the required information, and the drafting of the original and final versions of the manuscript. Yukun Bao led the study in the development of the research model and troubleshooting the issues arising from the data analysis and draft writing/revision.

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Golam Sorwar assisted in the collection and analysis of the required information and the drafting of the initial and final versions of the manuscript.

ORCID Yukun Bao

http://orcid.org/0000-0001-5418-8799

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Appendix A Table A1. Measurement items. Construct Measurement items Perceived usefulness (PU) PU1: Using the e-Health services will improve my life quality PU2: Using the e-Health services will make my life more convenient PU3: Using the e-Health services will make me more effective in my life PU4: Overall, I find the e-Health services to be useful in my life Perceived ease of use PEU1: Learning to operate the e-Health services will be easy for me (PEU) PEU2: I can easily become skillful at using the e-Health services PEU3: I can get the e-Health services to do what I want it to do PEU4: Overall, the e-Health services are easy to use Privacy (PRI) PRI1: I believe privacy of e-Health participants is protected PRI2: I believe personal information stored in e-Health system is safe PRI3: I believe e-Health systems to keep participants information secure Trust (TRU) TRU1: Based on my experience with the e-Health in the past, I know it is trustworthy TRU2: Based on my experience with the e-Health in the past, I know that it is not opportunistic TRU3: Based on my experience with e-Health in the past, I know that it keeps its promises to its patient Intention to use (INT) INT1: I have high intention to use the e-Health service INT2: I intend to learn about using e-Health services INT3: I plan to use e-Health services to manage my health Actual use (ACT) ACT1: e-Health service is a pleasant experience ACT2: I use e-Health service currently ACT3: I spend a lot of time on e-Health service

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Appendix B Table B1. Demographics of respondents. Descriptions Gender Marital status

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Educational qualification

Age

IT usage experience

Male Female Married Unmarried Widow Separated Others Illiterate Secondary Bachelor’s Master’s Others Less than 20 20–30 30–40 40–50 50–60 More than 60 Less than 1 years 1–3 years 4–6 years 7–9 years More than 10 years

Frequency 181 137 186 97 15 12 8 7 54 178 71 8 14 58 161 47 27 11 34 73 152 47 12

Percentage 57% 43% 58% 31% 5% 4% 2% 2% 17% 56% 22% 3% 4% 18% 51% 15% 9% 3% 10% 23% 48% 15% 4%

Investigating factors influencing the adoption of e-Health in developing countries: A patient's perspective.

The aim of the study was to investigate factors that influence the adoption and use of e-Health applications in Bangladesh from citizens' (patients') ...
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