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The purpose of the current study is to examine a social network site (SNS) users' overall satisfaction with SNS use in conjunction with their fan page visiting activities. We examined overall satisfaction with SNS usage from the lens of people's perceptions acquired from the use of sub-components of SNS.

The current study employed uncertainty reduction theory (URT) and general systems theory (GST) to examine antecedents affecting overall satisfaction with SNS use. Five constructs were adopted: interactive and passive uncertainty reduction strategies, perceived usefulness and continuance visiting behavior, satisfaction, and perceived functional benefits. Using a web-based survey, we analyzed 200 SNS users who follow at least one company's fan page, utilizing seemingly unrelated regression models to test hypotheses empirically.

Research findings reveal that uncertainty reduction strategies supported by URT are significantly associated with the perceived usefulness of a company's fan page. In turn, we found that perceived usefulness becomes a strong motivator to continuance visits to the fan page. The frequency of return visiting behaviors eventually accounts for overall satisfaction with SNS. Perceived functional benefits moderates the relationship between perceived usefulness and visiting behaviors significantly.

The current study contributes to information systems (IS), electronic communication, and their adjacent academic disciplines in providing evidence, including (1) the impact of uncertainty reduction strategies on continuance visiting behaviors in the SNS context, (2) SNS functionalities influencing the relationship between people's belief and behavior, and (3) theoretical significant perceptional link between a sub-component and a whole.

An increasing aging population and an increasing number of people suffering from musculoskeletal disorders have increased the demand for wearable robots. Comfortable, wearable robots that can be worn like clothing are currently being investigated. However, the embedded components may be displaced owing to the flexibility of the fabrics, which can lower the sensing accuracy and limit natural body movements. This study aims to develop clothing-type wearable platforms to minimize the displacement of embedded components such as sensors and actuators while maintaining comfort.

Four designs were developed using materials with different seam lines, that can serve as anchoring details, and flatlock stitches considering body movements and musculoskeletal structures. The wear evaluation experiment was filmed using a speed camera and analyzed using the TimeViewer software and SPSS 26.0. Based on these results, four clothing-type wearable platform designs were developed.

The variation in the location of a point in the armhole among the designs was marginal. Participants were satisfied with the functionality, practicality, wearability, efficiency and ease of use of the developed designs. A final clothing-type wearable platform was developed by applying a design with the least change in location, a suitable design for each area and wear comfort.

The results of this study contribute to the development of wearable robots by establishing clothing design data to minimize changes in sensor and actuator movements.

This study aims to conduct text mining and semantic network analysis of muscle-supportive and posture-corrective wearable robots for the elderly to understand key terms related to the topic and to identify considerations for developing these types of clothing.

The authors searched and identified the key terms wearable robot, muscle-supportive, posture correction and elderly using the text-mining software Textom to extract terms as well as the network analysis software UCINET 6 to process and visualize the relationships among the terms. The authors compared and analyzed the term frequency (TF), the TF-inverse document frequency and the degree centrality of the terms, and the authors visualized and summarized the terms using NetDraw.

The key terms and their relationships in 3–4 groups were identified: wearable robot, muscle-supportive, posture correction and elderly. The authors identified the aspects of designing muscle-supportive and posture-corrective wearable robots for the elderly.

This study contributes to the field of muscle-supportive clothing and wearable robotics by deriving insights into what people are discussing and interested in, and by offering recommendations when developing these types of clothing for the elderly.

The objective of this study was to develop wearable suit platforms with various anchoring structure designs with the intention of improving wearability and enhancing user satisfaction.

This study selected fabrics and materials for the suit platform through material performance tests. Two anchoring structure designs, 11-type and X-type are compared with regular clothing under control conditions. To evaluate the comfort level of the wearable suit platform, a satisfaction survey and electroencephalogram (EEG) measurements are conducted to triangulate the findings.

The 11-type exhibited higher values in comfort indicators such as α, θ, α/High-β and lower values in concentration or stress indicators such as β, ϒ, sensorimotor rhythm (SMR)+Mid-β/θ, and a spectral edge frequency of 95% compared to the X-type while walking. The 11-type offers greater comfort and satisfaction compared to the X-type when lifting based on the EEG measurements and the participants survey.

It is recommended to implement the 11-type when designing wearable suit platforms. These findings offer essential data on wearability, which can guide the development of soft wearable robots.