With the massive expansion in live streaming, enhancing the sustained engagement of users has become a key issue in ensuring its success. This study examines the relationship between real-time interaction, user perceptions, user intention to keep using live streaming, and whether this relationship differs between a live and a virtual live streaming environment. Using partial least squares (PLS) structural equation modelling (SEM), this paper analyses 240 valid questionnaire responses and finds that there is a link between real-time interactions, visual stimuli, and users’ sustained engagement. This shows that users’ active interactions while watching live streaming videos significantly affect their perceptions of social presence and trust, which in turn, affect their sustained engagement behaviour. These effects were found to vary with differences in the live streaming environment. The findings of this paper will play a positive role in understanding the differences between various live streaming environments, in optimizing the design of live streaming content and in improving the perceptions of emotional warmth by live streaming users.

Micro-expression recognition (MER) has attracted the attention of many researchers in the past decade. However, occlusion occurs for MER in real-world scenarios. In this paper, a challenging issue in MER that is interesting but unexplored, i.e., occlusion MER, is deeply investigated. First, to research MER under real-world occlusion conditions, synthetic occluded microexpression databases are created by using various community masks. Second, to suppress the influence of occlusion, a Region-inspired Relation Reasoning Network (RRRN) is proposed to model the relations between various facial regions. The RRRN consists of a backbone network, a region-inspired (RI) module and a relation reasoning (RR) module. More specifically, the backbone network aims to extract feature representations from different facial regions, the RI module is designed to compute the adaptive weight from the facial region itself based on the unobstructedness and importance of the region for suppressing the influence of occlusion using an attention mechanism, and the RR module exploits the progressive interactions among these regions by performing graph convolutions. Experiments are conducted on two tasks of MEGC 2018: the holdout-database evaluation task and the composite database evaluation task. Experimental results show that RRRN can be utilized to significantly explore the importance of facial regions and capture the cooperative complementary relationship of facial regions for MER. The results also demonstrate that RRRN outperforms the state-of-the-art approaches, especially with respect to occlusion, where RRRN is more robust.

With the recent development of internet healthcare, many hospitals have laid out their online platforms. However, there have been some poor service levels and low quality. The frequency of such problems has led to a decline in patient satisfaction. Therefore, it is vital to explore how hospitals can improve user satisfaction and willingness to visit them offline by setting up an online presence. Most studies conducted so far have remained limited to the single dimension of online or offline healthcare, with few studies exploring the relationship between them. While a few studies have explored the impact of online service quality on willingness to seek offline care, they also face the problem of a single perspective of analysis. Therefore, this study constructs a multidimensional model of the factors influencing online healthcare users’ willingness to seek offline care by integrating the value-based adoption model and the stimulus–organism–response model. Through a partial least squares-structural equation modelling analysis of 283 valid samples, this study found that online doctor–patient interactions and service quality positively impact user perception. This paper explores the development path of online healthcare from a new theoretical perspective. In addition, the findings provide new guidelines for hospitals to achieve economic and social benefits.

Social media provide users with multi-directional dialogue for creating and sharing health information that can effectively promote the self-management of health. In regard to the ‘greying’ trend in social media, most researchers have studied the health-related social media (HRSM) acceptance status and use behavior of middle-aged and elderly people, and have explored the role of HRSM in this group. However, the continuous participation of users is the key to the successful operation of HRSM, and is an essential prerequisite for the subsequent HRSM behavior habits of middle-aged and elderly people. Therefore, we aimed to explore what motivations drive the first use of HRSM among middle-aged and older adults, and the impact of their perception of HRSM, after personal use, on their intention to use it continually. In the study, we used the partial least squares structural equation model (PLS-SEM) to analyze data collected from online questionnaires. The results showed that a self-protection motivation and a social motivation promoted the initial participation of middle-aged and elderly individuals. In addition, these people experienced deeper levels of perceived usefulness and perceived entertainment after their initial participation. The results also revealed that these two perceptions could positively influence middle-aged and elderly individuals’ intention to continue with their participation. Our findings should help service platforms to better understand the needs of middle-aged and elderly users. This would help researchers and practitioners to gain a more complete understanding of the motivation of middle-aged and elderly people for participating in HRSM, and the related impacts this may have.