Exploring the inhibitors of online health service use intention: A status quo bias perspective

Increasing the use of telemedicine: A field experiment

Patients are reluctant to use telemedicine health services, compared to its substitute in-person visits. One reason is that telemedicine can be accurately evaluated and compared to its substitute only after the product has been adopted and experienced. As such, an intervention that increases the probability of a first experience can have lasting effects. This article reports the results of a randomized field experiment conducted in collaboration with a health insurance company. During the intervention, half of the households out of 3,469 in the sample received periodic e-mails with information about the available services. It effectively increased the take-up and demand for telemedicine. Within the first 8 months of the experiment, patients assigned to the treatment group were 6 percentage points more likely to have used the service at least once (and had about five times the odds of using telemedicine compared to those in the control group). Eight months after the start of the intervention, the number of virtual consultations by the treatment group was six times larger than that of the control group. These results, even if limited by the sample and context in which the intervention took place, provide additional evidence about how information interventions can increase technological take-up within the health sector and could serve as the stepping stone for evaluating the impact of telemedicine on health outcomes causally.

Online Physician-Patient Interaction and Patient Satisfaction: Empirical Study of the Internet Hospital Service

BACKGROUND

In China, a form of online health service called the internet hospital became a prominent means of patient care when face-to-face visits were not possible during the COVID-19 pandemic to minimize transmission of the SARS-CoV-2 virus. Patients' internet hospital experiences largely depend on online physician-patient interaction. Yet, little is known about how physicians can improve patient satisfaction by using specific communication strategies online.

OBJECTIVE

This study aimed to identify specific communication strategies to help physicians deliver better quality internet hospital services. We also outline recommendations for hospitals to operate internet hospital platforms more effectively.

METHODS

A longitudinal data set was collected from an internet hospital platform operated by a top hospital in China. By extracting communication patterns from approximately 20,000 records of online health care services and by controlling the features of service requests, we tested the impacts of response load, more detailed style, and emotional comfort on patient satisfaction. We further explored the effects of these communication patterns in different service contexts.

RESULTS

Physicians with a low response load, a more detailed style, and expressions of emotional comfort received more positive patient feedback. Response load did not affect patient satisfaction with free online health service, whereas a more detailed style and emotional comfort enhanced satisfaction with free service. Response load significantly reduced patient satisfaction with paid online health service, while a more detailed style had no effect. Compared with free service, emotional comfort more strongly promoted patient satisfaction with paid service.

CONCLUSIONS

The communication strategies identified can help physicians provide patients with a better internet hospital experience. These strategies require hospitals to schedule each physician's online service period more appropriately. In addition, tailoring the strategies to service situations can facilitate more targeted and effective internet hospital service for patients.

Switching from offline to online health consultation in the post-pandemic era: the role of perceived pandemic risk

Introduction

Due to its effectiveness and various benefits, the use of online health consultation (OHC) has dramatically increased in recent years, especially since the outbreak of the COVID-19 pandemic. However, underlying mechanism whereby the pandemic impacted OHC usage is still unclear.

Methods

Via an online survey (N=318), the present paper measures the users' perceptions towards both offline and online services, their intention to switch to OHC, and the perceived pandemic risks. The relationships among these factors are conceptualized by the push-pull-mooring framework, and tested via structural equation modelling.

Results

Dissatisfaction with offline service (process inefficiency and consultation anxiety), the attractiveness of OHC (perceived benefits and perceived ease of use), and users' behavioral inertia (switching cost and habit) jointly influence the intention to switching to OHC. The significant role of the perceived pandemic risk of going to medical facilities is particularly addressed. On the one hand, the perceived pandemic risk is found with an indirect impact on the switching intention by enlarging the dissatisfaction with offline service and the attractiveness of OHC. On the other hand, a high perceived pandemic risk induces more actual switching behavior and also amplifies the transition from switching intention to behavior.

Discussion

The study provides novel insights into the understanding of OHC usage in the post-pandemic era, and also informs medical facilities, OHC platforms, and policymakers on managing and balancing the online and offline healthcare provision.

The Roles of Trust and Its Antecedent Variables in Healthcare Consumers' Acceptance of Online Medical Consultation during the COVID-19 Pandemic in China

Online medical consultation (OMC) is generating considerable interest among researchers and practitioners due to the mandatory quarantine measures implemented during the COVID-19 pandemic in China. However, the acceptance rate of OMC has declined over time. This paper aims to empirically investigate OMC acceptance using a proposed research model by integrating the technology acceptance model (TAM) with trust and its antecedent variables. A quantitative self-administered cross-sectional survey was conducted to collect data from 260 healthcare consumers. A partial least squares structural equation modeling method was used to examine the data. Results revealed that healthcare consumers' behavioral intention was influenced by attitudes, while perceived usefulness and trust significantly influenced behavioral intention through attitude as a mediator. In addition, perceived risk, perceived privacy protection, network externalities, cognitive reputation, and interactivity directly influenced trust. Overall, the research model explained 50% of the variance in attitude and 71% of the variance in behavioral intention. The study's findings should provide useful insights into making effective design, development, and implementation decisions for OMC services.

Determinants Influencing the Adoption of Internet Health Care Technology Among Chinese Health Care Professionals: Extension of the Value-Based Adoption Model With Burnout Theory

BACKGROUND

The global COVID-19 pandemic has been widely regarded as a catalyst for adopting internet health care technology (IHT) in China. IHT consists of new health care technologies that are shaping health services and medical consultations. Health care professionals play a substantial role in the adoption of any IHT, but the consequences of doing so can often be challenging, particularly when employee burnout is prevalent. Few studies have explored whether employee burnout influences the adoption intention of IHT in health care professionals.

OBJECTIVE

This study aims to explain the determinants influencing the adoption of IHT from the perspective of health care professionals. To do so, the study extends the value-based adoption model (VAM) with consideration for employee burnout as a determining factor.

METHODS

A cross-sectional web-based survey using a sample of 12,031 health care professionals selected through multistage cluster sampling from 3 provinces in mainland China was conducted. The hypotheses of our research model were developed based on the VAM and employee burnout theory. Structural equation modeling was then used to test the research hypotheses.

RESULTS

The results indicate that perceived usefulness, perceived enjoyment, and perceived complexity positively correlate with perceived value (β=.131, P=.01; β=.638, P<.001; β=.198, P<.001, respectively). Perceived value had a positive direct effect on adoption intention (β=.725, P<.001), perceived risk negatively correlated with perceived value (β=-.083, P<.001), and perceived value negatively correlated with employee burnout (β=-.308, P<.001). In addition, employee burnout was negatively related to adoption intention (β=-.170, P<.001) and mediated the relationship between perceived value and adoption intention (β=.052, P<.001).

CONCLUSIONS

Perceived value, perceived enjoyment, and employee burnout were the most important determinants of IHT adoption intention by health care professionals. In addition, while employee burnout was negatively related to adoption intention, perceived value inhibited employee burnout. Therefore, this study finds that it is necessary to develop strategies to improve the perceived value and reduce employee burnout, which will benefit the promotion of the adoption intention of IHT in health care professionals. This study supports the use of the VAM and employee burnout in explaining health care professionals' adoption intention regarding IHT.

Fighting rumors to fight COVID-19: Investigating rumor belief and sharing on social media during the pandemic

The outbreak of the coronavirus disease (COVID-19) pandemic, a significant health threat, influenced information-related behaviors and induced increased rumor-sharing behaviors on social media. Fighting COVID-19 thus entails the need to fight the rumors as well, providing a strong motivation to explore rumor-related behavior during this extraordinary period. From the perspective of information acquisition, we predicted that information acquisition from social and traditional media would interactively influence rumor-related decisions (i.e., rumor belief and sharing) and that critical thinking would shape this relationship. Through a survey of 2424 individuals who used social media during the pandemic, we found that information acquisition from social media was negatively related to rumor sharing and that rumor belief mediated this relationship. Meanwhile, information acquisition from traditional media weakened the negative effect of information acquisition from social media on rumor belief, and critical thinking alleviated the positive effect of rumor belief on rumor sharing. This study contributes to the literature by explaining the diffusion of COVID-19 rumors on social media from an information perspective and revealing how different information sources and thinking styles come into conflict in rumor decisions.

Influences of governance mechanisms on patients' usage intention: A study on web-based consultation platforms

The study object is the doctor-patient online community, an online health service model with the greatest growth potential during the global COVID-19 pandemic. In the web-based medical market, patients are in a weak position, relying on web-based medical platform operators to ensure medical service quality. Following social exchange theory, this empirical study divides governance mechanisms into three-supervision, reputation, and communication-to determine their influence on online patients willingness to use web-based medical platforms. It also explores the moderating effect of perceived uncertainty on the influence of social exchange and transaction cost theory. A questionnaire survey was conducted to determine online patients' attitudes toward medical service providers including physicians and medical websites. Hierarchical linear regression analysis showed the significant positive effect of the supervision, reputation, and communication mechanisms on online patients' usage willingness. Perceived uncertainty of doctors' behavior has a significant moderating effect on the relationship between the three mechanisms and online patients' usage willingness. Website-perceived uncertainty moderates the relationship between the supervision and reputation mechanisms and online patients' usage willingness. This study provides a reference for improving online patients' usage willingness through the platform governance of Internet medical treatment.

Exploring the effects of health information seeking on e-satisfaction in online health communities: an empirical investigation

BACKGROUND

Online health communities (OHCs) are becoming effective platforms for people to seek health information. Existing studies divide health information into general and specific information in OHCs. However, few studies discuss the effects of different types of information seeking in OHCs on users' electronic satisfaction (e-satisfaction).

OBJECTIVE

This study explores the effects of general and specific information seeking on users' e-satisfaction with OHCs through the mediating roles of perceived benefits and costs drawing on the social information processing theory and the social exchange theory.

METHODS

This study conducted an online survey to collected data from individuals who used OHCs to seek information. The structural equation model was used to analyze the collect data and the research model. Specifically, this study examined the common method bias and conducted a robustness check.

RESULTS

Results show that general and specific information seeking affect e-satisfaction through the mediating roles of perceived benefits and costs. An interesting result is that general information seeking has a stronger effect on e-satisfaction than specific information seeking.

CONCLUSIONS

This study suggests that e-satisfaction should be further enhanced by information seeking as online healthcare practices evolve and change. Managers of OHCs should focus on increasing users' perceived benefits, thereby increasing their e-satisfaction. Besides, this study discusses implications, limitations, and future research directions.

Motive perception pathways to the release of personal information to healthcare organizations

BACKGROUND

The goal of the study is to assess the downstream effects of who requests personal information from individuals for artificial intelligence-(AI) based healthcare research purposes-be it a pharmaceutical company (as an example of a for-profit organization) or a university hospital (as an example of a not-for-profit organization)-as well as their boundary conditions on individuals' likelihood to release personal information about their health. For the latter, the study considers two dimensions: the tendency to self-disclose (which is aimed to be high so that AI applications can reach their full potential) and the tendency to falsify (which is aimed to be low so that AI applications are based on both valid and reliable data).

METHODS

Across three experimental studies with Amazon Mechanical Turk workers from the U.S. (n = 204, n = 330, and n = 328, respectively), Covid-19 was used as the healthcare research context.

RESULTS

University hospitals (vs. pharmaceutical companies) score higher on altruism and lower on egoism. Individuals were more willing to disclose data if they perceived that the requesting organization acts based on altruistic motives (i.e., the motives function as gate openers). Individuals were more likely to protect their data by intending to provide false information when they perceived egoistic motives to be the main driver for the organization requesting their data (i.e., the motives function as a privacy protection tool). Two moderators, namely message appeal (Study 2) and message endorser credibility (Study 3) influence the two indirect pathways of the release of personal information.

CONCLUSION

The findings add to Communication Privacy Management Theory as well as Attribution Theory by suggesting motive-based pathways to the release of correct personal health data. Compared to not-for-profit organizations, for-profit organizations are particularly recommended to match their message appeal with the organizations' purposes (to provide personal benefit) and to use high-credibility endorsers in order to reduce inherent disadvantages in motive perceptions.

On the demand for telemedicine: Evidence from the COVID-19 pandemic

Telemedicine can expand access to health care at relatively low cost. Historically, however, demand for telemedicine has remained low. Using administrative records and a difference-in-differences methodology, we estimate the change in demand for telemedicine experienced after the onset of the COVID-19 epidemic and the imposition of mobility restrictions. We find that the number of telemedicine calls made during the pandemic increased by 230 percent compared to the pre-pandemic period. The effects were mostly driven by older individuals with preexisting conditions who used the service for internal medicine consultations. The demand for telemedicine remained relatively high even after mobility restrictions were relaxed, which is consistent with telemedicine being an "experience good." These results are a proof of concept for policy makers to use such relatively low-cost medical consultations, made possible by new technologies, to provide needed expansion of access to health care.

A Holistic Perspective Model of Plenary Online Consumer Behaviors for Sustainable Guidelines of the Electronic Business Platforms

The holistic perspective model is a concept of three stages that considers the whole of online consumer behavior. It is based on dynamic aspects and overview measurement to demonstrate the preliminary of three stages, including “Pre-purchase”, “Purchase” and “Post-purchase”. There is a shared purpose for all the positive, negative, and hesitation factors that inhibit or encourage online shopping decisions. This model can capture the dynamic and fast-changing elements in online shopping platforms. Most online buying-selling platforms are gaining popularity and growing rapidly. Thus, they should maintain good levels of online customers’ satisfaction. This research presents a balanced investigation model of online consumer purchasing behaviors under uncertainty through the integration of Push-Pull Mooring (PPM) theory and the three stages of online consumer behaviors. In this study, questionnaires were collected from 525 online applications from experienced users of electronic business platforms. The outcome reveals that PPM affects three stages of online consumer behaviors. This means that PPM factors influence online customers during and after online shopping. This research can be used to develop attractive online shopping applications for prospective customers while retaining existing customers, which is the challenge faced by online shopping platforms.

The Effects of Online Text Comments on Patients' Choices: The Mediating Roles of Comment Sentiment and Comment Content

As an increasingly important application of mobile social media usage, online healthcare platforms provide a new avenue for patients to obtain and exchange information, referring not only to online doctor's advice but also to the patients' comments on a doctor. Extant literature has studied the patients' comments facilitated with the direct numeric information gathered in the web pages including the frequencies of "thanks letter," "flowers," and "recommendation scores." Adopting the text analysis method, we analyzed patients' comments on the healthcare platform, focusing on the comments from two aspects, namely, comment contents and content sentiment. Based on the analysis of the data collected from one of the most popular healthcare apps named "Haodaifu" in China, the results show that the vast majority of the comments are positive, which basically follows the L-shaped distribution. Meanwhile, comment sentiment covering sentiment tendency and proportion of positive comments demonstrates significant effects on recent 2-week consultation by a doctor. One of the comment contents "patience explanation" has significant effects both on the total consultation and recent 2-week consultation by a doctor. The research findings indicate that the online preferences for and evaluations on doctors provide strong support and guidance for improving doctor-patient relationships and offer implications for medical practices and healthcare platforms improvement.

The Effects of Service Characteristics on Intention to Use Mobile Health Services: The Moderating Role of Innovativeness and Privacy Concern

Objectives: In this study, we explored how service characteristics (service relevance and service accuracy) interact to influence individuals' use intention of mHealth services. We also investigated the moderating roles of innovativeness and privacy concerns. Methods: To meet these objectives, we developed 6 hypotheses that were subsequently empirically validated using a survey to test the effects of service characteristics and personal traits on intention to use mHealth. Results: We confirm that service relevance and service accuracy positively and directly influence individuals' intention to use mHealth services. In addition, innovativeness positively affects the relationship between service relevance and use intention. Privacy concern negatively influences the relationship between service relevance and use intention, but positively influences the relationship between service accuracy and use intention. Conclusions: The present study provides new insights into the influencing factors of individuals' usage behavior toward mHealth services. Such insight could provide further understanding of how individuals adopt new information services or technologies, which contribute to both information system and healthcare research areas in a promising way.

A mixed-method approach to assess users' intention to use mobile health (mHealth) using PLS-SEM and fsQCA

Purpose

Despite the enormous potential of mobile health (mHealth), identifying the asymmetric relationship among the predictors towards intention to use (ITU) of mHealth tends to remain unresolved. This study aims to investigate the predictors and their asymmetric effects on ITU of mHealth through patients and healthcare professionals.

Design/methodology/approach

An integrated information systems (IS) model with four additional constructs has been developed to analyze symmetric and asymmetric effects on ITU of mHealth. An exploratory survey on 452 mHealth users with prior experience was conducted to evaluate the model using a mixed-method approach including partial least squares-based structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) technique.

Findings

The findings show that facilitating conditions, personal awareness building, perceived enjoyment, effort expectancy and perceived usefulness have predictive power for ITU of mHealth. In contrast, fsQCA reveals four more alternative solutions, including the main drivers explored by PLS-SEM. The results indicate that various conditions that were not crucial in PLS-SEM analysis are shown to be sufficient conditions in fsQCA.

Research limitations/implications

This study contributes to theory by integrating self-actualization factors (i.e. personal awareness building, patients as decision support unit) into the IS model. And practically, this study makes an essential contribution to users' ITU of mHealth, enabling relevant stakeholders to build strategies to implement mHealth successfully.

Originality/value

While mHealth has revolutionized healthcare and the prior literature only showed linear relationships, this empirical study revealed asymmetrical relationships among the determinants of ITU of mHealth. Thus, this study extends to the growing body of literature on the use of mHealth technology in the least developing nation.

Does employees' perception towards mobile human resource management application quality affect usage intention? A moderated-mediation analysis

Purpose

Mobile human resource management application (mHRM app) has emerged as an innovative solution to manage human resources. However, the performance of the application is questionable, and hence, it is crucial to know employees' perception towards it. This study aims to explore employees' perceived service quality towards mHRM app using the moderated-mediation framework.

Design/methodology/approach

Data were collected from 265 Indian HR professionals using online questionnaire. The proposed hypotheses were examined using structural equation modelling and PROCESS Macro.

Findings

Results indicate that navigation and contact significantly affect employees' mHRM usage behaviour. Results also indicate that perceived values significantly mediates the association between perceived service quality and mHRM usage behaviour.

Practical implications

The findings of the study will help organisations in enhancing their employees' perceived service quality towards mHRM app.

Originality/value

This study contributes to the literature on human resource management, total quality management and cognitive-motivational-relational (CMR) theory.

Factors Affecting User Intention to Pay via Online Medical Service Platform

With regard to platform performance and trust, we study the influencing factors of users’ intention to pay on an online medical service platform. Results of this paper will provide a new perspective for online medical service platform research in the context of the Internet.A questionnaire survey is administered to collect 312 effective sample data, and the data are analyzed by partial least squares structural equation modeling. Results showed that the information quality, system quality, and convenience of the platform significantly affect the perceived benefit (PB) of users. Users’ perceived reliability of the platform significantly positively affects doctor reliability (DR). Users’ PB significantly positively affects their ITP and DR, and DR significantly positively affects the users’ ITP. The misdiagnosis risk positively regulates the relationship between the users’ trust tendency and DR. The timeliness of the response of the platform positively adjusts the relationship between DR and users’ ITP.

Disambiguating Between Privacy and Security in the Context of Health Care: New Insights on the Determinants of Health Technologies Use

Health care providers are increasingly providing technologies for patient care; however, patients are still loath to use such technologies consistently. This research examines the impediments to patients' use of e-health portals. Our analysis of 836 data records showed that while privacy and security concerns have a negative impact on attitudes toward e-health portals, increasing the awareness of privacy and security controls alleviates such concerns. Our findings also suggest that individuals worry more about who possesses the right to access their health data (i.e., who, what, when, and why) than the mechanisms used to safeguard data from unauthorized access. We found that perceived benefits and support (i.e., emotional and technical support) positively influenced the determinants of use intentions. The implications of these findings for health care providers and policy makers are discussed.

Health-tech startups in healthcare service delivery: A scoping review

BACKGROUND

An efficient and affordable healthcare service delivery to everyone is a prerogative of the national governments. Such delivery is quite exacting, and gaps remain. In this regard, startups are trying to disrupt the market with innovative solutions and reach the underserved market. Though anecdotal evidence remains, a rigorous literature review is missing. This paper attempts to understand the status of health-tech startups in healthcare service delivery.

METHODS

We scanned a total of 110 journals - Financial Times top 50, top ten information systems journals listed by the Australian Business Dean Council, and the top 50 Scopus indexed journals in health informatics and health information management. We followed a systematic process for this scoping review - reading of titles, abstracts, and then full papers for final analysis based on inclusion and exclusion criteria.

RESULTS

A total of 76 articles met the inclusion criteria. Only five studies portrayed the status of health-tech startups in healthcare service delivery. To capture the overall startup ecosystem, we continued with a scoping review of all the 76 articles.

DISCUSSIONS

The identified five themes are Technology adoption, Electronic health services, Business planning and framework, Psychographics, and Regulations. There is evidence of technology adoption in service delivery and its nature in the businesses undertaken by startups. Very few studies represented the patterns of the existing business model. The acceptance of the services is dependent on service effectiveness and affordability. The challenges are licensing, policies, data privacy and security, and inadequate technology access among healthcare seekers.

CONCLUSIONS

Albeit the feasibility potential, research concerning the impact of health tech startups in healthcare service delivery is emerging but incipient. The review indicates that research on startups is inadequate, especially related to entrepreneurship, business frameworks, and regulations. Future research should explore the same.

Influence of Online Social Support on the Public's Belief in Overcoming COVID-19

The sudden outbreak of coronavirus disease 2019 (COVID-19) in early 2020 has dramatically changed people's lives. Some countries have taken mass home quarantine to control the virus. However, the side effects of quarantine have rarely been interrogated by current COVID-19 research. This study thus investigates the effects of online social support on the public's beliefs in overcoming COVID-19 by embracing their cognition and emotion during the epidemic. First, by crawling and content analysis of the messages posted on "Baidu COVID-19 bar", this study identified 5 types of online social support given or received by the public during COVID-19. On this basis, a model explaining the public's beliefs was developed from the perspectives of online social support, cognition and emotion. 334 valid online questionnaires were collected to examine the proposed model and hypotheses. The results show that cognition has a direct effect on the belief, while emotion affects the belief via a full mediating effect of cognition. Tangible support and esteem support can directly affect the public's beliefs, and educational level significantly moderates these effects. In addition, the public's cognition is influenced by informational support, however, emotion is not influenced by social support but by other factors (e.g., information disclosure, material supplies and frustration caused by the epidemic). These research results provide a deep insight into how to reduce the negative effects of quarantine, consolidate the theoretical basis of the public's beliefs, and have important practical implications for individuals and the government in dealing with such emergencies.

A two-factor theoretical model of social media discontinuance: role of regret, inertia, and their antecedents

Purpose

Although materializing the benefits of social media substantially depends on sustained user participation, social media service providers are experiencing a decline in the number of users. Despite the relevance of studying and managing discontinuance behaviors, a systematic empirical investigation remains lacking. The present study draws on the idea of a two-factor model and aims to examine the enabler, inhibitor and their antecedents in the context of social media discontinuance.

Design/methodology/approach

The proposed theoretical model was empirically validated through an online survey study of 238 social media users in China.

Findings

Findings indicated that two negative outcomes of social media use (i.e. social overload and invasion of privacy) induce regret experience and ultimately foster discontinuance intentions. The development of discontinuance intentions was undermined by the level of inertia, which is rooted in social media habit, sunk costs and affective commitment.

Originality/value

This study draws attention to the fundamental difference between continuance and discontinuance behaviors, advances the existing understanding of postadoption behaviors by focusing on discontinuance inhibitors (e.g. inertia) and develops the first two-factor model for social media discontinuance by integrating the regret and status quo bias literature.

Patients' Willingness to Share Information in Online Patient Communities: Questionnaire Study

Background

Online patient communities provide new channels for users to access and share medical information. In-depth study of users’ willingness to share information in online patient communities is of great significance for improving the level of information sharing among the patient community and the long-term development of communities.

Objective

The aim of this study was to build a model of factors affecting patients’ willingness to share medical information from the perspective of both positive and negative utilities. Specifically, we aimed to determine the influence of online information support and privacy concerns, as well as the moderating effect of disease severity and information sensitivity of different patients on their willingness to share.

Methods

Data from 490 users with experience in online patient communities were collected through a questionnaire survey, and structural equations were applied to empirically verify the model hypotheses.

Results

Privacy concerns negatively affected the patients’ willingness to share information (P<.001), whereas online information support positively affected patients’ willingness to share information (P<.001), and information sensitivity negatively moderated the impact of online information support on sharing willingness (P=.01). Disease severity positively moderated the impact of privacy concerns on sharing willingness (P=.05). However, the hypotheses that information sensitivity is a negative moderator and disease severity is a positive moderator of the impact of privacy concerns on sharing willingness could not be supported.

Conclusions

To improve the level of user information sharing, the online patient community should design a safe user registration process, ensure the confidentiality of information, reduce the privacy concerns of users, and accurately identify the information needs of patients to provide personalized support services.

Understanding continuance usage intention of mHealth in a developing country

Purpose

This study aims to understand the factors affecting the continuance usage intention (CUI) of mHealth among the rural elderly.

Design/methodology/approach

An integrated model was proposed with the constructs derived from multiple models such as the unified theory of acceptance and use of technology, information system success model and expectation confirmation model. Data were collected from 400 participants who had prior experiences with mHealth services in Bangladesh. The research model was tested using the partial least squares method based upon structural equation modelling.

Findings

The findings indicated that system quality, performance expectancy, facilitating conditions and social influence were significant to the degree of confirmation and ultimately affect satisfaction and CUI. Surprisingly, service quality and information quality were insignificant.

Research limitations/implications

This study has added in the field of knowledge by contributing some new thoughts and interpretations of continuance usage modelling for mHealth services. The findings may become beneficial for the government agencies, policymakers, mHealth systems developers and service providers.

Originality/value

As limited research was found on CUI of mHealth in the integrated view of rural elderly’s value, this research contributes to the extant literature by categorizing key factors that might support to proliferate the continuance usage of this service. Moreover, the contextualization of the related variables and integration of the existing model is theoretically original. Furthermore, because of a generic approach, the findings could be easily modified to assist other developing countries in the planning and up-take of mHealth.

An Integrated Structural Equation Model of eHealth Behavioral Intention

eHealth offers promising tools and services to manage and improve the quality of health as well as the potential to provide accessible health information all over the world. The relatively low adoption rates among eHealth users motivates us to develop an integrated model to explain the learning process and provide essential antecedents of eHealth behavioral intention. The integrated model is empirically tested by using different structural equation modeling (SEM) methods, including partial least squares SEM (PLS-SEM), PLSc, and covariance-based SEM (CB-SEM). The model successfully explains the learning process and provides essential antecedents of eHealth behavioral intention. The findings support the interplay of social, cognitive, and personal factors that impact 18-30-year-old users' learning process related to eHealth behavioral intention. The results empirically show that these three types of SEM techniques provide consistent results with respect to path coefficients and coefficients of determination. The findings indicate that CB-SEM and PLS-SEM provide adverse consequences of interaction-term path coefficients.

Factors Influencing the Adoption of Online Health Consultation Services: The Role of Subjective Norm, Trust, Perceived Benefit, and Offline Habit

The cyberspace plays an important role in improving the quality, equity, and efficiency of health services. Studying people's adoption of online health services, such as online health consultation services (OHCS) can benefit both industry and policy in the health service sector. This paper investigates influencing factors and paths of people's intention of adopting OHCS by employing the extended valence framework, with our new contribution of integrating subjective norm and offline habit into the model. Five hundred forty-three university students participated in the survey. Structural equation models and Sobel-Goodman tests were applied to test the models. The results show that subjective norm (β = 0.077, p = 0.041), trust in providers (β = 0.194, p = 0.002) and perceived benefit (β = 0.463, p < 0.001) positively affect the intention to adopt OHCS, while offline habit (β = -0.111, p = 0.026) has a negative effect. However, the association of perceived risk (β = -0.062, p = 0.315) and adoption is not supported. Moreover, trust in providers plays a mediating role between subjective norm and the intention of adopting, while perceived benefit mediates the relationship between trust in providers and the intention of adopting. This study highlights the importance of trust, subjective norm, perceived benefit, and persisting habits in promoting the adoption of OHCS.

How Resource Scarcity and Accessibility Affect Patients' Usage of Mobile Health in China: Resource Competition Perspective

BACKGROUND

The last decade has witnessed many achievements in China's health care industry, but the industry still faces major challenges among which the uneven distribution of medical resources and the imbalance between supply and demand are the most pressing problems. Although mobile health (mHealth) services play a significant role in mitigating problems associated with health care delivery, their adoption rates have been low.

OBJECTIVE

The objective of this study was to explore the impact of resource scarcity and resource accessibility on the adoption of mHealth from the perspective of resource competition, to examine the concerning factors, and to provide a theoretical basis for promoting mHealth in China.

METHODS

We used 229,516 original registration records of outpatients to conduct an empirical analysis to examine the adoption of mHealth services from the perspective of resource competition.

RESULTS

The adoption rate of mobile services for outpatients was low, accounting for only 31.5% (N=71,707). The empirical results indicated that resource scarcity (beta=.435, P=.01) and accessibility (beta=-.134, P=.02) have a significant impact on the adoption of mHealth. In addition, gender (beta=.073, P=.01) and age (beta=-.009, P<.001) are significantly related to adoption of mHealth. Experience with mHealth has a moderating role in the relationship between resource scarcity (beta=-.129, P=.02), accessibility (beta=.138, P=.04), and adoption of mHealth.

CONCLUSIONS

In this study we demonstrate that the external environment (resource scarcity and resource accessibility) has a significant impact on the adoption of mHealth. This study also demonstrates that experience with mHealth has a moderating role in the relationship between the elements of the external environment. Finally, we confirm that mHealth is a key factor in the delivery and allocation of medical resources and provide a theoretical basis for government agencies to develop policies on mHealth.

Disease risk and its moderating effect on the e-consultation market offline and online signals

Purpose

The purpose of this paper is to investigate the moderating effect of disease risk in terms of the major signals (i.e. status, reputation and self-representation) on the e-consultation platforms.

Design/methodology/approach

In this study, the proposed research hypotheses are tested using the transaction data collected from xywy.com (in Need of Therapy). In fact, xywy.com is one the leading e-consultation service websites in China that provides a platform for the interactions between the physicians and patients (Yu et al., 2016; Peng et al., 2015). Generally speaking, it has all the needed design elements and in other words, a standard e-consultation website should have such items/components as physician homepage, physician review, free consultation, paid consultation and recommendation systems.

Findings

The obtained results reveal that all attributes including status, reputation and self-representation have a positive impact on physician’s online order volume. Moreover, there is a positive moderating effect of disease risk onto the online reputation, indicating a higher effect exists for the diseases with high risk. However, the effect of offline status and online self-representation is not moderated by the disease risk, indicating market signals (online reputation) may have a stronger predictive power than seller signals (offline status and online self- representation), and therefore market signals are more effective when/if the disease risk is high.

Originality/value

E-consultation has gradually become a significant trend to provide the healthcare services, in the emerging economy such as China because of shortage of medical resources but having an adequate access in internet usage. The impacts of signals on the health care market have been validated by previous studies. However, the research focusing on the moderating effect of signaling environment in the health care industry is still lacking. As a result, the value of this research helps to bridge the aforementioned research gap.

Investigating the Effect of Paid and Free Feedback About Physicians' Telemedicine Services on Patients' and Physicians' Behaviors: Panel Data Analysis

Background

In recent years, paid online patient-physician interaction has been incorporated into the telemedicine markets. With the development of telemedicine and telemedicine services, online feedback has been widely applied, helping other patients to identify quality services. Recently, in China, a new type of service feedback has been applied to the telemedicine markets, namely, paid feedback. Patients who are satisfied with a physician’s online service can buy a virtual gift or give a tip to the physicians. This paid feedback can improve the reliability of service feedback and reduce the proportion of false information because it increases the cost for feedback providers. Paid online feedback can benefit the physicians, such as by providing them with monetary incentives; however, research on the impacts and value of such paid feedback from the physician perspective in the telemedicine markets is scant. To fill this research gap, this study was designed to understand the role of paid feedback by developing a research model based on the theories of signaling and self-determination.

Objective

This study aimed to explore the effects of free and paid feedback on patients’ choice and physicians’ behaviors as well as to investigate the substitute relationship between these 2 types of feedback in the telemedicine markets.

Methods

A JAVA software program was used to collect online patient-doctor interaction data over a 6-month period from a popular telemedicine market in China (Good Physician Online). This study drew on a 2-equation panel model to test the hypotheses. Both fixed and random effect models were used to estimate the combined effects of paid feedback and free feedback on patients’ choice and physicians’ contribution. Finally, the Hausman test was adopted to investigate which model is better to explain our empirical results.

Results

The results of this study show that paid feedback has a stronger effect on patients’ choice (a₅=0.566; t₂₁₉₂=9.160; P<.001) and physicians’ contribution (β₄=1.332; t₂₁₉₃=11.067; P<.001) in telemedicine markets than free feedback. Moreover, our research also proves that paid feedback and free feedback have a substitute relationship in determining patients’ and physicians’ behaviors (a₆=−0.304; t₂₁₉₁=−5.805; P<.001 and β₅=−0.823; t₂₁₉₂=−8.136; P<.001).

Conclusions

Our findings contribute to the extant literature on service feedback in the telemedicine markets and provide insight for relevant stakeholders into how to design an effective feedback mechanism to improve patients’ service experience and physicians’ engagement.