Search results

With the advent of the Digital 2.0 era, online doctor–patient (D–P) interaction has become increasingly popular. However, due to the fact that doctors use their fragmented time to serve patients, online D–P interaction inevitably has some problems, such as the lack of pertinence in the reply content and doctors' relative unfamiliarity with their individual patients. Therefore, the purpose of this study is to excavate whether potential D–P social ties and D–P knowledge ties accentuate or attenuate the influence of patient selection (online and offline selection).

The authors used the methods of text mining and empirical analysis on the structured and unstructured data of an online consultation platform in China to examine the research hypotheses.

The findings illustrate that the potential D–P social ties increase the influence on patient selection, as do the potential D–P knowledge ties. Specifically, the effect of social ties on patient selection is positively moderated by patient health literacy. Conversely, health literacy weakens the link between knowledge ties and patient selection. In addition, the doctor's title weakens the influence of social ties on patient selection, in contrast to knowledge ties (partially).

This study provides guidance for doctors and patients on how to communicate effectively and alleviate tension within D–P relationships. The study’s findings have both theoretical and practical implications for both doctors' and online platforms' decision-making.

Active interaction and knowledge contribution are vital yet challenging elements of the sustainable development of online health communities (OHCs). To investigate the cognitive mechanisms underlying these behaviours in doctors' and patients' use of OHCs, this study develops a theoretical model to examine the relationships among cognitive modes, patterns of interaction, perceived usefulness, and contribution behaviour and the impact of user identity on these relationships.

To test the research hypotheses, structural equation modelling and multiple-group analysis were used to analyse survey data from 207 doctors and 213 patients.

The results indicate that dual processes and perceived usefulness are the key cognitive antecedents of interaction and knowledge contribution, respectively. However, the correlation of the rational mode and instrumental interaction is significantly stronger in the doctors' group than in the patients' group, while a stronger correlation between the experiential mode and instrumental interaction is observed in the patients' group.

These findings support the development of information and system strategies to support the operation of dual processes underlying doctors' and patients' instrumental and affective interactions, facilitate evaluation and sense-making of interaction activities, and motivate knowledge contribution.

This study uncovers the invariance and variability in the relationships between salient cognitive activities and behavioural responses in doctors' and patients' use of OHCs and the impact of user identity on variability.

Despite the prevalent use of professional status and service feedback in online healthcare markets, the potential interaction relationship between two types of information is still unknown. This study used the signaling theory to examine the substitute relationship between professional status and service feedback in patients' doctor choice, as well as the moderating effect of illness severity.

To test the paper's hypotheses, we constructed a panel data model using 418 doctors' data collected over a period of six months from an online healthcare market in China. Then, according to the results of the Hausman test, we estimated a fixed-effects model of patients' choice in online healthcare markets.

The empirical results showed that the effect of a doctor's professional status and service feedback on a patient's doctor choice was substitutable. Moreover, patients' illness severity played a moderating role, in that the influence of professional status on a patient with high-severity illness was higher than that on a patient with low-severity illness, whereas the influence of service feedback on a patient with low-severity illness was higher than that of a patient with high-severity illness. In addition, we found that illness severity negatively moderated the substitute relationship between professional status and service feedback on a patient's choice.

These findings not only contribute to signaling theory and research on online healthcare markets, but also help us understand the importance of professional status and service feedback on a patient's choice when seeking a doctor online.

The purpose of this paper is to investigate factors that influence the patients’ intentions to visit doctors face-to-face for consultations from the perspective of online doctor–patient interaction. Justice theory, SERVQUAL and the halo effect are integrated to develop a research model based on the performance-evaluation-outcome framework. The authors hypothesize that perceived justice and service quality are the significant factors in reflecting the performance of online doctor–patient interaction, which influences patient satisfaction evaluation and online and offline behavioral intentions.

The study conducted an online survey to collect data. Patients on a healthcare consulting website were invited to participate in the survey. The research model and hypotheses were tested with 254 collected data from patients and analyzed using the partial least squares method.

The results show that perceived justice and service quality have a positive effect on patient satisfaction, and satisfaction and the intention of online consultation have a positive effect on the intention of face-to-face consultation.

This study offers suggestions on how doctors interact with patients and build their brand image. The findings also offer effective insights into improving doctors’ online services to retain patients and even encourage patients to go to clinics.

Online health consultation is one of the most popular online health services and is growing quickly. After patients consult online doctors, they are able to visit their doctors in person for further diagnosis and treatment if they have the need. This study investigates how patients’ online interactive experience influences their offline behavioral intentions, which are different from most of the past literature on eHealth.

Considering both online and offline service scenarios, this study aims to explore the factors affecting doctors' intention to offer consulting services in eHealth and compare the factors between the free- and paid-service doctors. The theory of reasoned action and social exchange theory are integrated to develop the research model that conceptualizes the role of extrinsic motivations, intrinsic motivations, costs, and attitudes in doctors' behavioral intentions.

Partial least square structural equation modeling (PLS-SEM) was leveraged to analyze 326 valid sample data. To provide robust results, three non-parametric multigroup analysis (MGA) methods, including the PLS-MGA, confidence set, and permutation test approaches, were applied to detect the potential heterogeneity between the free- and paid-service doctors.

The results with overall samples reveal that anticipated rewards, anticipated associations, anticipated contribution, and perceived fee are all positively related to attitude, which in turn positively influences behavioral intention, and that perceived fee positively moderates the relationship between attitude and behavioral intention. Attitude's full mediation is also confirmed. However, results vary between the two groups of doctors. The three MGA approaches return relatively convergent results, indicating that the effects of anticipated associations and perceived fee on attitude are significantly larger for the paid-service doctors, while that of anticipated rewards is found to be significantly larger for the free-service doctors.

eHealth, as a potential contactless alternative to face-to-face diagnoses, has recently attracted widespread attention, especially during the continued spread of COVID-19. Most existing studies have neglected the underlying heterogeneity between free- and paid-service doctors regarding their motivations to engage in online healthcare activities. This study advances the understanding of doctors' participation in eHealth by emphasizing their motivations derived from both online and offline service scenarios and comparing the differences between free- and paid-service doctors. Besides, horizontally comparing the results by applying diverse MGA approaches enriches empirical evidence for the selection of MGA approaches in PLS-SEM.

Research on the impact of the engagement of online medical teams (OMTs) on patient evaluation, for example, satisfaction, remains insufficient. This study attempts to recognize the underlying mechanism of how OMTs’ engagement influences patient satisfaction by adopting social support as the mediator. This study also scrutinizes the moderating effects of the transactive memory system (TMS) on the link between OMTs’ engagement and social support.

We utilized a linear model that had fixed effects controlled at the team level for analysis. A bootstrapping approach using 5,000 samples was employed to test the mediation effect.

Our results reveal that OMTs’ engagement improves informational and emotional support, thereby promoting patient satisfaction. Specialization and credibility strengthen the impact of OMTs’ engagement on informational and emotional support. Simultaneously, coordination has an insignificant influence on the link between OMTs’ engagement and social support.

This study contributes to the literature on OMTs, social support, and TMS, providing insights into patients’ perceptions of OMTs’ engagement during online team consultation. This study also generates several implications for the practice of online health communities and OMTs.

This study aims to investigate the external and internal stimuli, which affect the organismic experiences of the users and thereby influence their response in terms of behavioral intention toward the use of online doctor consultation platforms.

The study operationalized the stimulus–organism–response framework for the research model and surveyed 357 users in India who had experienced online doctor consultation platforms. The analysis has been done using the structural equation modeling approach.

The authors’ main results indicate the following key points. One, perceived usefulness, social influence, health anxiety, offline consultation habit and perceived technology usage risk are significant predictors of perceived value. In contrast, perceived ubiquity is identified to be an insignificant predictor of perceived value. Second, social influence and perceived technology usage risk have significant influence on trust. However, perceived usefulness is not a significant predictor of trust.

This study contributes to the theory by integrating technology-oriented factors with behavioral attributes for determining the behavioral intention of users toward the online doctor consultation platforms.

The managerial contributions of this study involve highlighting those technology-oriented and behavioral elements, which can be targeted to attract more users toward these platforms.

This is an original study that has looked beyond the role of technology-oriented factors in influencing the perceived value and trust elements while investigating the behavioral intention among the users toward the online doctor consultation platforms.

This study examines how service feedback and physician popularity affect physician demand in the context of virtual healthcare environment. Based on the signaling theory, the critical factor of environment uncertainty (i.e. disease risk) and its impact on physician demand is also investigated. Further, the research on the endogeneity of online reviews in healthcare is also examined in the current study.

A secondary data econometric analysis using 3-wave data sets of 823 physicians obtained from two PRWs (Healthgrades and Vitals) was conducted. The analysis was run using the difference-in-difference method to consider physician and website-specific effects.

The study's findings indicate that physician popularity has a stronger positive effect on physician demand compared with service feedback. Improving popularity leads to a relative increase in the number of appointments, which in turn enhance physician demand. Further, the impact of physician popularity on physician demand is positively mitigated by the disease risk.

The authors' research contributes to a better understanding of the signaling transmission mechanism in the online healthcare environment. Further, the findings provide practical implications for key stakeholders into how an efficient feedback and popularity mechanism can be built to enhance physician service outcomes in order to maximize the financial efficiency of physicians.

This study aims to study the mechanisms and conditions of users' intention to continue to use online health platforms from an information technology (IT) affordance perspective.

b This research proposes that a critical affordance effect on an online health platform, users' intention to continue the use of the platform, is affected by five platform affordances via two actualized affordances (i.e. perceived benefits (PBs) and online engagement (OE)). Perceived health threat moderates the effect generated by affordance actualization. A dataset involving 409 users from the “Ping An Health” platform was collected through an online survey and analyzed to validate the research hypotheses.

The data analysis results confirm that the proposed online health platform affordances affect users' PBs and OE, which influence users' intentions to continue using the platform. Perceived threats (perceived vulnerability (PVU) and perceived severity (PSE)) moderate the relationship between PBs and continuance intention (CI) and between OE and CI.

The research provides important recommendations for online health platform designers to develop IT affordances that can support users' needs for healthcare services.

Limited studies investigated why users continue participating in online diagnosis and treatment. This study provides a new perspective to expand the affordance framework by combining technology features and user health behavior. The study also emphasizes the importance of perceived threats in IT use.

Continuous knowledge contribution behaviors (CKCB) are critical for the healthy development of online medical communities (OMCs). However, it is unclear that if and how contributors' prior actions and the responses they received from the community influence the nature of their future contributions. Drawing upon the Information Systems Continuance theory and Service Feedback theory, the purpose of the study is to examine the impact of knowledge contribution performance (KCP) on doctors' CKCB. Evaluation of social motivation, financial incentive and the moderating influence of expertise level (EL) provided further insight into the pathways that motivate various forms of CKCB.

In order to better understand the CKCB of physicians in OMCs, the authors divided it into two categories: A_CKCB (active CKCB) and P_CKCB (passive CKCB). Information Systems Continuance theory and Service Feedback theory are adapted and integrated with empirical findings from previous research on OMCs to develop a model of CKCB. This study used ordinary least squares (OLS) regression to test hypotheses in the preexisting research model based on data collected from a Chinese OMC platform.

The results show that KCP helps develop several facets of CKCB. According to the findings, doctors' CKCB improved dramatically after receiving feedback from A_CKCB and P_CKCB, but feedback from peers did not promote CKCB. This study found that financial rewards only have a significant positive effect on P_CKCB, and that the level of expertise has a negative effect on the effect. The findings also demonstrated that doctors' level of expertise moderates the relationship between fA_CKCB (a comprehensive evaluation of doctors' A_CKCB) and A_CKCB.

Future studies should look at the role of self-efficacy as a mediator and attitudes as a moderator in the link between KCP and various forms of CKCB. This will help authors figure out how important KCP is for physicians' CKCB. And future research should use more than one way to gather data to prove the above roles.

This study makes a significant contribution to understanding the association between CKCB and KCP by highlighting the significance of distinguishing between the various forms of CKCB and their underlying causes.

This research has advanced both the theory and practice of OMCs' user management by illuminating the central role of KCP in this context.