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Health and fitness apps have grown exponentially during covid-19 lockdowns. Using a sample of 331 European fitness apps users, this study investigated the psychological drivers of users' intention on fitness apps. This study draws upon the Technology Acceptance Model (TAM) and innovation diffusion theory. Its findings reveal that subjective knowledge and personal innovativeness predict perceived Usefulness, health consciousness, and ease of use. The strongest predictor of intention to use an app is perceived Usefulness, which mediates the influence of subjective knowledge and innovativeness on intention to use. Health consciousness predicts ease of use;however, the latter does not predict behavioural intention. This is one of the first studies on European users of fitness apps and investigating the psychological antecedents of TAM, i.e., innovativeness, subjective knowledge, and consciousness.
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Background: Anticipating the correlation between SARS-CoV-2 infection and ‘triplenegative breast cancer (TNBC)' remains challenging. It has been reported that people currently diagnosed with cancer have a higher risk of severe complications if they are affected by the viral infection. Cancer treatments, including chemotherapy, targeted therapies, and immunotherapy, may weaken the immune system and possibly cause critical lung damage and breathing problems. Special attention must be paid to the ‘comorbidity condition' while estimating the risk of severe SARSCoV- 2 infection in TNBC patients. Hence the work aims to study the correlation between triplenegative breast cancer (TNBC) and SARS-CoV-2 using biomolecular networking.Methods: The genes associated with SARS CoV-2 have been collected from curated data in Bio- GRID. TNBC-related genes have been collected from expression profiles. Molecular networking has generated a Protein-Protein Interaction (PPI) network and a Protein-Drug Interaction (PDI) network. The network results were further evaluated through molecular docking studies followed by molecular dynamic simulation.Results: The genetic correlation of TNBC and SARS-Cov-2 has been observed from the combined PPI of their proteins. The drugs interacting with the disease's closely associated genes have been identified. The docking and simulation study showed that anti-TNBC and anti-viral drugs interact with these associated targets, suggesting their influence in inhibiting both the disease mutations.Conclusion: The study suggests a slight influence of SARS-CoV-2 viral infection on Triple Negative Breast Cancer. Few anticancer drugs such as Lapatinib, Docetaxel and Paclitaxel are found to inhibit both TNBC and viral mutations. The computational studies suggest these molecules are also useful for TNBC patients to control SARS-CoV-2 infection.
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PurposeThis study aims to reveal the topic structure and evolutionary trends of health informatics research in library and information science.Design/methodology/approachUsing publications in Web of Science core collection, this study combines informetrics and content analysis to reveal the topic structure and evolutionary trends of health informatics research in library and information science. The analyses are conducted by Pajek, VOSviewer and Gephi.FindingsThe health informatics research in library and information science can be divided into five subcommunities: health information needs and seeking behavior, application of bibliometrics in medicine, health information literacy, health information in social media and electronic health records. Research on health information literacy and health information in social media is the core of research. Most topics had a clear and continuous evolutionary venation. In the future, health information literacy and health information in social media will tend to be the mainstream. There is room for systematic development of research on health information needs and seeking behavior.Originality/valueTo the best of the authors' knowledge, this is the first study to analyze the topic structure and evolutionary trends of health informatics research based on the perspective of library and information science. This study helps identify the concerns and contributions of library and information science to health informatics research and provides compelling evidence for researchers to understand the current state of research.
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We examine the risk minimization utility of Islamic stock and Sukuk (bond) indices by studying their linkages against traditional global counterparts. We first employ an asymmetric power ARCH-based ADCC model on an extended dataset employed by Kenourgios et al. (2016). Our sample ranges from July 2007 to June 2021 covering the Global Financial Crisis (GFC), the European Sovereign Debt Crisis (ESDC), and the COVID-19 pandemic. Econometric tests suggest strong evidence of coupling in the bulk of Islamic equity indices. A handful of emerging market indices constitute exceptions. Qualitatively similar results emerge from time–frequency analysis via wavelet tools, revealing pervasive coupling in both returns and volatility series. The linkages are scale-dependent in only a few pairs. In contrast, Sukuk indices are uncoupled from their global fixed income counterparts and relevant risky debt portfolios. In sum, the risk-return characteristics of Islamic equities (especially in developed economies) remain coupled to major global benchmarks and therefore are unlikely to appeal as safe haven candidates. The converse applies to Sukuk, which promises potential portfolio diversification benefits and safe haven status in ‘normal' and crisis periods.
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PurposeAs of December 2021, WeChat had more than 1.2 billion active users worldwide, making it the most active online social media in mainland China. The term social commerce is used to describe new online sales through a mix of social networks and/or peer-to-peer communication or marketing strategies in terms of allowing consumers to satisfy their shopping behaviour through online social media. Thus, given the numerous active users, the development of online social media and social commerce on WeChat is a critical issue of internet research.Design/methodology/approachThis empirical study takes WeChat as the online social media research object. Questionnaires for WeChat users in China were designed and distributed. All items are designed as nominal and ordinal scales (not Likert scale). The obtained data was put into a relational database (N = 2,342), and different meaningful patterns and rules were examined through data mining analytics, including clustering analysis and association rules, to explore the role of WeChat in the development of online social media and social commerce.FindingsPractical implications are presented according to the research findings of meaningful patterns and rules. In addition, alternatives to WeChat in terms of further development are also proposed according to the investigation findings of WeChat users' behaviour and preferences in China.Originality/valueThis study concludes that online social media, such as WeChat, will be able to transcend the current development pattern of most online social media and make good use of investigating users' behaviour and preferences, not only to stimulate the interaction of users in the social network, but also to create social commerce value in social sciences.