Big data architecture for pervasive healthcare: a literature review

Pervasive healthcare aims to deliver deinstitutionalised healthcare services to patients anytime and anywhere. Pervasive healthcare involves remote data collection through mobile devices and sensor network which the data is usually in large volume, varied formats and high frequency. The nature of big data such as volume, variety, velocity and veracity, together with its analytical capabilities com-plements the delivery of pervasive healthcare. However, there is limited research in intertwining these two domains. Most research focus mainly on the technical context of big data application in the healthcare sector. Little attention has been paid to a strategic role of big data which impacts the quality of healthcare services provision at the organisational level. Therefore, this paper delivers a conceptual view of big data architecture for pervasive healthcare via an intensive literature review to address the aforementioned research problems. This paper provides three major contributions: 1) identifies the research themes of big data and pervasive healthcare, 2) establishes the relationship between research themes, which later composes the big data architecture for pervasive healthcare, and 3) sheds a light on future research, such as semiosis and sense-making, and enables practitioners to implement big data in the pervasive healthcare through the proposed architecture.

Clinical implications of cognitive bias modification for interpretative biases in social anxiety: an integrative literature review

Cognitive theories of social anxiety indicate that negative cognitive biases play a key role in causing and maintaining social anxiety. On the basis of these cognitive theories, laboratory-based research has shown that individuals with social anxiety exhibit negative interpretation biases of ambiguous social situations. Cognitive Bias Modification for interpretative biases (CBM-I) has emerged from this basic science research to modify negative interpretative biases in social anxiety and reduce emotional vulnerability and social anxiety symptoms. However, it is not yet clear if modifying interpretation biases via CBM will have any enduring effect on social anxiety symptoms or improve social functioning. The aim of this paper is to review the relevant literature on interpretation biases in social anxiety and discuss important implications of CBM-I method for clinical practice and research.