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The advent of online live streaming platforms (OLSPs) and online health communities (OHCs) has expedited the integration of traditional medical services with Internet new media technology. Since the practice of physicians conducting live streaming is a relatively new phenomenon, the potential cross-platform effects of such physicians’ live streaming have not received adequate attention.

This study collected data from 616 physicians specializing in cardiology, obstetrics and gynecology and neurology between April and November 2022 on Live.Baidu.com and WeDoctor.com. It constructed a panel data set comprising a total of 4,928 observations over an 8-month period and validated the model using empirical analysis with the fixed-effects method.

We find evidence of cross-platform influence in online healthcare. Physicians’ live streaming behavior (whether live or not and the heat of their streams) on OLSPs positively impacts both their consultation and reputation on OHCs. Additionally, physicians’ ability positively moderates the relationships between live streaming heat and their performance (in terms of consultation volume and reputation) on OHCs. However, ability does not moderate the relationship between physicians’ live streaming status (live or not) and their performance (in terms of consultation and reputation) on OHCs. Furthermore, the attractive appearance of the physicians also significantly moderates the impact in a positive way.

This is one of the pioneering studies on physicians’ live streaming. The study offers vital guidance for physicians and patients utilizing dual platforms and holds significant reference value for platform operators (such as OLSPs and OHCs) aiming to optimize platform operations and for the government in policy formulation and industry regulation.

Social media facilitates the communication and the relationship between healthcare professionals and patients. However, limited research has examined the role of social media in a physicians' online return. This study, therefore, investigates physicians' online economic and social capital return in relation to physicians' use of social media and consumer engagement.

Using ordinary least squares (OLS) regression with fixed effects (FE) and panel data collected from Sina Weibo and Sina Health, this study analyzes the impact of physicians' social media use and consumer engagement on physicians' online return and the moderation effect of professional seniority.

The results reveal that physicians' use of social media and consumer sharing behavior positively affect physicians' online economic return. In contrast, consumer engagement positively impacts physicians' online social capital return. While professional seniority enhances the effect of physicians' social media use on online economic return, professional seniority only enhances the relationship between consumers' sharing behavior to the posts and physicians' online social capital return when professional seniority comes to consumer engagement.

This study reveals the different roles of social media use and consumer engagement in physicians' online return. The results also extend and examine the social media affordances theory in online healthcare communities and social media platforms.

The purpose of this study is to explore the sustainability of innovations introduced during the coronavirus disease 2019 (Covid-19) pandemic in remote and rural primary care advanced clinical practice.

The methodology includes an exploratory qualitative study of eight key stakeholders from Scottish remote and rural primary care advanced practice (three policymakers and five advanced practitioners). Data were collected using semi-structured interviews during 2022 and analysed thematically.

Advanced practice in remote and rural primary care is characterised by a shortage of doctors, close-knit communities and a broad scope of practice. Covid-19 catalysed changes in the delivery of healthcare. Innovations which participants wanted to sustain include hybrid working, triage, online training and development, and increased inter-professional support networks.

Findings provide valuable insights into how best to support remote and rural advanced practice which may have implications for retaining healthcare professionals. They also identified useful innovations which could benefit from further investment.

Given current healthcare workforce pressures, identifying and sustaining innovations which will support and retain staff are imperative. Hybrid consultations and online access to training, development and support should be sustained to support the remote and rural advanced practice workforce. Further research should explore the sustainability of innovations introduced during the Covid-19 pandemic in other care contexts.

This paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.

An adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.

The results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.

The findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.

This study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.

Almost four years after the COVID-19 pandemic, the changes in the labour market and legislation, but also in people's lives, do not stop. At the same time, employees' perceptions regarding the change in the legislative and contractual framework, as well as in the working conditions and the use of telework, also change. Therefore, the aim of the paper is to identify the perceptions of employees regarding the use of telework in the post-pandemic period.

The research was based on a survey carried out on 128 teleworkers in the post-pandemic period. The statistical hypotheses were tested using Kolmogorov–Smirnov and Kruskal–Wallis tests, multiple linear regression and pairwise comparison analysis.

The results of the study demonstrate that the modification of the legislative and contractual framework and of the working conditions, as well as of the way of using information and communication technology in the post-pandemic era, generates a positive and significant impact on the use of telework by employees. Some of the main advantages valued by teleworkers included the possibility of benefitting from a flexible work schedule and the possibility of reducing transport costs.

The study highlights the need to continuously develop and update labour policies and strategies in line with current and future labour market requirements, considering the implications of telework on the perceptions of employees, so that government organisations and managers who want to protect the rights and interests of teleworkers, aspects of their lives and organise an appropriate work environment manage to do so in order to achieve the expected results.

Effectively engaging patients is critical for the sustainable development of online health communities (OHCs). Although physicians’ general knowledge-sharing, which is free to the public, represents essential resources of OHCs that have been shown to promote patient engagement, little is known about whether such knowledge-sharing can backfire when superfluous knowledge-sharing is perceived as overwhelming and anxiety-provoking. Thus, this study aims to gain a comprehensive understanding of the role of general knowledge-sharing in OHCs by exploring the spillover effects of the depth and breadth of general knowledge-sharing on patient engagement.

The research model is established based on a knowledge-based view and the literature on knowledge-sharing in OHCs. Then the authors test the research model and associated hypotheses with objective data from a leading OHC.

Although counterintuitive, the findings revealed an inverted U-shape relationship between general knowledge-sharing (depth and breadth of knowledge-sharing) and patient engagement that is positively associated with physicians’ number of patients. Specifically, the positive effects of depth and breadth of general knowledge-sharing increase and then decrease as the quantity of general knowledge-sharing grows. In addition, physicians’ offline and online professional status negatively moderated these curvilinear relationships.

This study further enriches the literature on knowledge-sharing and the operations of OHCs from a novel perspective while also offering significant specific implications for OHCs practitioners.

Knowledge sharing in online health communities (OHCs) disrupts consumers' health information-seeking behavior patterns such as seeking health information and consulting. Based on social exchange theory, this study explores how the two dimensions of experts' free knowledge sharing (general and specific) affect customer transactional and nontransactional engagement behavior and how the quality of experts' free knowledge sharing moderates the above relationships.

We adopted negative binomial regression models using homepage data of 2,982 experts crawled from Haodf.com using Python.

The results show that experts' free general knowledge sharing and free specific knowledge sharing positively facilitate both transactional and nontransactional engagement of consumers. The results also demonstrate that experts' efforts in knowledge-sharing quality weaken the positive effect of their knowledge-sharing quantity on customer engagement.

This study provides new insights into the importance of experts' free knowledge sharing in OHCs. This study also revealed a “trade-off” between experts' knowledge-sharing quality and quantity. These findings could help OHCs managers optimize knowledge-sharing recommendation mechanisms to encourage experts to share more health knowledge voluntarily and improve the efficiency of healthcare information dissemination to promote customer engagement.

The advancement of technologies has made it possible for health-care organizations to provide convenient online services that enable people to manage their health conditions. Although many studies have investigated the adoption and benefits of e-health services, there has been little focus on health-oriented behaviors after adoption, particularly in relation to service quality and user satisfaction.

This paper is based on the SOR model and service quality theories to investigate behavioral responses, including word-of-mouth, intention to use and intention to act. The authors use a partial least squares structural equation modeling analysis with 194 participants and the diabetes risk test survey in Finland.

The results show that people are willing to engage in health self-management behaviors if they intend to use the e-health service and are satisfied with it. User satisfaction can be enhanced by improving the visual appeal of the website presentation, the quality of the presented information, as well as the usability of the website, all as components of e-health services.

The authors contribute by creating a construct “intention to act,” referring to health-oriented behaviors resulting from e-health service use. In addition, this study is among the first to apply the SOR model to investigate how user satisfaction leads to intention to use, intention to act and word-of-mouth.