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This study aims to investigate the user’s behavior and intention to continue using e-health services by analyzing the factors influencing their decision. The stimuli–organism–behavior–consequence (SOBC) framework was used to assess how the risks and benefits of e-health influence both behavioral intention (BI) and continued use.

The hypotheses proposed for this study were tested with partial least square-based structural equation modeling. This study relied on the primary data collected from 572 respondents using convenient sampling.

This study examined the SOBC model’s four phases’ with the help of eight constructs. The conceptual model allowed the authors to examine 10 relationships to measure e-health adoption behavior in emerging nations like India. This study found that convenience, perceived risk and facilitating conditions are positively related to the effort and performance expectancy (PE) associated with e-health consultation. Only social influence is unrelated. This study also found a positive and substantial relationship between BI, effort and PE.

The study uses the unified theory of acceptance and use of technology and the SOBC paradigm to determine the factors influencing users’ intentions to use e-health. In addition to bringing new aspects to the existing literature on technology adoption and e-health consultation, the results of this study will aid e-health service providers in formulating strategies to promote the usage of e-health in emerging economies like India.

This study aims to investigate the role of information normalization in online healthcare consultation, a typical complex human-to-human communication requiring both effectiveness and efficiency. The globalization and digitization trend calls for high-quality information, and normalization is considered an effective method for improving information quality. Meanwhile, some researchers argued that excessive normalization (standardized answers) may be perceived as impersonal, repetitive, and cold. Thus, it is not appreciated for human-to-human communication, for instance, when patients are anxious about their health condition (e.g. with high-risk disease) in online healthcare consultation. Therefore, the role of information normalization in human communication is worthy to be explored.

Data were collected from one of the largest online healthcare consultation platforms (Dxy.com). This study expanded the existing information quality model by introducing information normalization as a new dimension. Information normalization was assessed using medical templates, extracted through natural language processing methods such as Bidirectional Encoder Representations from Transformers (BERT) and Latent Dirichlet Allocation (LDA). Patient decision-making behaviors, namely, consultant selection and satisfaction, were chosen to evaluate communication performance.

The results confirmed the positive impact of information normalization on communication performance. Additionally, a negative moderating effect of disease risk on the relationship between information normalization and patient decision-making was identified. Furthermore, the study demonstrated that information normalization can be enhanced through experiential learning.

These findings highlighted the significance of information normalization in online healthcare communication and extended the existing information quality model. It also facilitated patient decision-making on online healthcare platforms by providing a comprehensive information quality measurement. In addition, the moderating effects indicated the contradiction between informational support and emotional support, enriching the social support theory.

This paper reports on a workshop discussing the views of the augmentative and alternative communication (AAC) community on the opportunities and risks posed by the integration of artificial intelligence (AI) into voice output communication aid systems. The views of the community on whether a Code of Practice was needed for the use of this new technology were also sought.

This was an explorative, qualitative study in which members of the AAC community attending a session at a UK national conference were invited to discuss the topic, responding to structured questions from the research team. The use of AI for both novel language generation and rate enhancement was discussed within the session.

Many potential opportunities and benefits of AI to AAC users were discussed by the group. Risks associated with new and existing biases in AI language models were raised, as was the need to ensure that outputs generated by AI were authentically authored by users. Whilst there was broad support for the idea of a Code of Practice, questions were posed about how it would be designed and what it should contain.

This study presents a unique insight into the views of the AAC community on the benefits and risks of incorporating AI into AAC systems. The views of the community on the need for a Code of Practice may support how the field moves forward with this complex technology.

In the digital age, the spread of online behavior and real-world information leads to social contagion. This study aims to investigate the contagion phenomenon of online physician choice and then discuss its potential influence on the sub-specialization process in the healthcare service industry. In specific, this study aims to propose the basic mechanism of infection and immunity as follows – exposure to antigen may lead to an immune response, and the success of the immune response may depend on the provision of appropriate immune signaling.

Data collected from haodf.com including 4 disease types and 247 physicians from 2008 to 2015 were used to test the proposed hypotheses. Panel vector autoregression method was utilized to analyze the panel data.

The obtained result shows that social contagion of physician choice over disease type is salient on e-consultation platforms, indicating that physicians associated with/on haodf.com are concentrating on an even narrower type of disease. Disclosing more simple signals (physician history orders) results in more disease concentration for that physician in the future. In contrast, disclosing more detailed signals (physician-contributed knowledge or physician reviews) leads to less disease concentration.

This finding implies that physician-contributed knowledge and physician reviews may act as immune signal which will tend to trigger a success immune response. This study not only suggests managers should be careful about the double-edged sword effect of online physician choice contagion but also provides the useful approaches to promote or restrain such a contagion in a flexible way.

This paper aims to describe several artificial intelligence (AI)-based applications that librarians can use to serve and design virtual library instruction, so it will be more effective and efficient.

The approach involves a comprehensive review of AI-based applications that bring benefits to librarian to enhance the virtual instructional services (AI). This study explores the existing papers to reveal the potential use of AI for research consultation, designing the instructional services and conducting evaluation of the program.

There are some AI-based applications that are available for free that will help instructional librarian jobs. Librarians use the AI to increase effectiveness of the services. The AI-based applications that can be used to support instructional services on research inquiries include virtual assistance, knowledge mapping and note making, and to support designing virtual instruction, librarians can use design apps, image generators, voice generator, grammar checker and paraphrasing.

There are many studies on AI at the library; however, it’s still rare a paper studied AI-based application that potentially will bring benefit for virtual instructional services. This paper will give overview of AI application that will help instructional librarian on transactions with users and help librarians to create innovative instructional media.

Technology-enabled healthcare focuses on providing better information flow and coordination in healthcare operations. Technology-enabled health services enable hospitals to manage their resources effectively, maintain continuous patient engagement and provide seamless services without compromising their perceived quality.

This study investigates the role of technology-enabled health services in improving perceived healthcare quality among patients. Data are collected from the users (n = 418) of health platforms offered in multi-specialty hospitals. Multiple learners are employed to accurately represent the users' perceived quality regarding the perceived usefulness of the features provided via these digital health platforms.

The best-fitted model using a decision tree classifier (accuracy = 0.86) derives the accurate significance of features offered in the digital health platform in fostering perceived healthcare quality. Diet and lifestyle recommendations (30%) and chatting with health professionals (11%) are the top features offered in digital health platforms that primarily influence the perceived quality of healthcare among users.

The predictability of perceived quality with the individual features existing in the digital health platform, the significance of the features on the perceived healthcare quality and the prediction rules showing the combined effect of features on healthcare quality can help healthcare managers accelerate digital transformation in hospitals by improving their digital health platform, designing and offering new health packages while strengthening their e-infrastructure.

The study represents perceived healthcare quality with the features offered in digital health platforms using machine learners based on users' post-pandemic experience. By advancing digital platforms with more patient-centric features using emerging technologies, this model can further foresee its impact on the perceived quality of healthcare, offering valuable directions to healthcare service providers. The study is limited to focusing on digital health platforms that can deal with people's general healthcare needs.

Establishing and developing digital science and education evaluation platforms (DSEEPs) have several practical implications for the development of China's science, technology and education. Identifying and analyzing the key factors influencing DSEEP user experience (UX) can improve the users' willingness to use the platform and effectively promote its sustainable development.

First, a literature survey, a five-element model of UX and semi-structured interviews were used in this study to develop a DSEEP UX-influencing factor model, which included five dimensions and 22 influencing factors. Second, the model validity was verified using questionnaire data. Finally, the key influencing factors were identified and analyzed using a fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) method.

Fourteen influencing factors, including diverse information forms and comprehensive information content, are crucial for the DSEEP UX. Its optimization path is “‘Function Services’ → ‘Information Resources’ → ‘Interaction Design’ → ‘Interface Design’ and ‘Visual Design’.” In this regard, platform managers can take the following measures to optimize UX: strengthening functional services, improving information resources, enhancing the interactive experience and considering interface effects.

This study uses a combination of qualitative and quantitative research methods to determine the key influencing factors and optimization path of DSEEP UX. Optimization suggestions for UX are proposed from the perspective of platform managers, who provide an effective theoretical reference for innovating and developing a DSEEP.

This exploratory study illustrated an integrated academic library supply chain (IALSC) model to design the strategic planning management tool of the academic library. The supply chain (SC) model has been widely used in manufacturing industries and has also been applied in many service industries with the same objectives. However, very few studies for academic libraries, particularly the implementation of the integrated SC model, are being executed, although it has been proven that SC management in practice can enhance stakeholder satisfaction, increase revenues and decrease total costs. The academic library also needs to be successful in providing quality products, services and information to fulfil the library users’ needs within the library budget. This research aims to develop a verified model of the integrated SC for the academic library.

This research used both qualitative and quantitative approaches to achieve its objectives. The proposed conceptual SC model, named as IALSC, for the academic library has been developed using the system thinking method; eventually, it has been validated through the fuzzy Delphi method, an expert judgement technique.

The research findings could contribute to academic library management in planning and formulating a roadmap for the library to increase its quality services for all stakeholders.

The conceptual model would have a high potential to be proposed as the strategic decision-making tool for an academic library, i.e. the flow of funds through the operations of the library, the library stakeholders’ satisfaction measurement, the decision process currently made by the library management team on the purchase of new library resources, the library resource suppliers, etc.

Designing digital artifacts is not a linear, straightforward process. This is particularly true when applying a user-centered design approach, or co-design, with users who are unable to participate in the design process. Although the reduced participation of a particular user group may harm the end result, the literature on solving this issue is sparse. In this article, proxy design is outlined as a method for involving a user group as proxy users to speak on behalf of a group that is difficult to reach. The article investigates the following research question: How can roleplaying be embedded in co-design to engage users as proxies on behalf of those who are unable to represent themselves?

The article presents a design ethnography spanning three years at a cancer rehabilitation clinic, where digital artifacts were designed to be used collaboratively by nurses and patients. The empirical data were analyzed using content analysis and consisted of 20 observation days at the clinic, six proxy design workshops, 21 telephone consultations between patients and nurses, and log data from the digital artifact.

The article shows that simulated consultations, with nurses roleplaying as proxies for patients ignited and initiated the design process and enabled an efficient in-depth understanding of patients. Moreover, the article reveals how proxy design as a method further expanded the design. The study findings illustrate: (1) proxy design as a method for initiating design, (2) proxy design as an embedded element in co-design and (3) six design guidelines that should be considered when engaging in proxy design.

The main contribution is the conceptualization of proxy design as a method that can ignite and initiate the co-design process when important users are unreachable, vulnerable or unable to represent themselves in the co-design process. More specifically, based on the empirical findings from a design ethnography that involved nurses as proxy users speaking on behalf of patients, the article shows that roleplaying in proxy design is a fitting way of initiating the design process, outlining proxy design as an embedded element of co-design.

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.