6 research outputs found
Health Capability Maturity Model: Person-centered Approach in Personal Health Record system
Personal health record (PHR) system is considered an important component in implementing continuity of care and evidence based treatment in modern healthcare. However, the adoption rates for PHR system by general public still remained low due to lack of interest and low health literacy level. In this paper, we propose a health capability maturity model (HCMM) and corresponding improvement paths to improve an individualâs capability to manage oneâs health systematically by using PHRs. The HCMM allows an individual to collect, monitor, and control oneâs health information. To this end, we attempt to integrate some of the key processes and concepts from Capability Maturity Model Integration (CMMI) and Trans-theoretical Model (TTM) into HCMM that assesses an individualâs capability and awareness on managing health and well-being and suggests customized improvement goals
Eye Movements as Deception Indicators in Online Video Chatting
Online video chat is emerging as one of the common forms of computer-mediated communication (CMC). It can also be easily exploited by deceiver for persuasive conversation. Research on deception cues in CMC is gaining increasing attention in recent years but has largely ignored this new medium. This study aims to investigate the effect of eye movement behavior in the detection of deception in online video chatting. A laboratory experiment is conducted to test pupil dilation and blinking rate as possible cues to online deception. During the study, the eye movement behavior of participants was captured using an eye tracking system. The preliminary results confirmed the effect of pupil dilation but did not yield any significant effect for blinking rate
Eye Gazing Behaviors in Online Deception
Psychophysiological behaviors of deceivers have been used as an effective leakage channel of face-to-face deception. Among various psychophysiological behaviors, eye movement has been identified as one of the most reliable sources of deception behavior in face-to-face communication. However, empirical studies of eye movement behavior in online deception remain scarce. In this research, we investigated eye gazing behaviors of deceivers in online video chatting. Based on the findings of previous deception studies and the unique characteristics of online video chatting, we hypothesized that online deception has an impact on eye gazing behaviors. In addition, we innovatively operationalized eye gazing behaviors in terms of areas of interest. We conducted a lab-based experiment to test the hypotheses. The results supported the effect of deception on eye gazing behaviors. The findings of this study provide insights on how to improve the performance of online deception detection and how to apply eye tracking technologies to understand emerging human behaviors in online communication
Health Improvement Path: Ontological Approach to Self-management Support in Personal Health Management Systems
Ontologies have been used for knowledge modeling and reasoning in healthcare domain (e.g., homecare, hospital clinical procedure, mHealth, etc.), but few in a context of self-management in healthcare with no sufficient reasoning rules to specify a systematic health management plan for an individual. In response to such needs, we aim to provide a generic ontology model for organizing the broad range of multidisciplinary knowledge required in personal health management by applying the ontology design patterns as well as for being extensible to more specific activity ontologies (e.g., physical exercises, diet, medication intake, etc.). The scope of a proposed ontology is to classify core concepts and relations in health self-management process and to build axioms for health improvement plans to meet an individualâs needs and health capability/maturity level. The proposed ontology is developed based on our previous work, health capability maturity model (HCMM) and can be integrated with existing health-related ontologies for further specification in health management processes
Detecting Deception in Computer Mediated Communication: A Social Structural Perspective
Despite the widespread use of Computer-Mediated Communication (CMC) for effective collaboration and interaction, CMC has become a growing hotbed for deception due to its provision of ubiquity, anonymity and open environment. Deception is an increasing threat to our society and to the daily communication of both individuals and groups. This dissertation aims to provide a new venue for understanding deception and for detecting deception through the identification, extraction, and application of social structural behaviors of deceptive communication. To this end, the dissertation consists of three major studies. The first study conceptualizes deception in terms of social structure by drawing on interpersonal deception theory and social network theories and proposes a research model of structural properties of deceptive communication: centrality, cohesion and similarity. Viewed from the social structural perspective, structural behaviors are denoted as the relationships between different individuals (entities) or as relatively stable patterns of relationships. The second study examines the impact of time on structural behaviors of deception based on interactional adaption theory and characteristics of temporal networks. The third study addresses the problem of automatic deception detection by extracting the structural features of deceptive communication and by combining the structural features with linguistic features. In addition, it evaluates the generality of the structural features identified from synchronous CMC to asynchronous CMC. The findings of this dissertation extend existing theories and research on explaining the effect of deception intent on structural behaviors of communication in multi-fold aspects. First, this dissertation extends the context of deception theories from interpersonal interaction to social interaction by addressing the interactional dynamics in group communication that is composed of one deceiver and multiple receivers. Second, the dissertation operationalizes the structural behaviors of deceptive CMC and extracts them from two different types of networks: static and temporal, and empirically validates the behaviors with real-world data. Third, the dissertation improves the performance of automated deception detection by incorporating the structural behaviors of deception
Detecting Deception in Computer Mediated Communication: A Social Structural Perspective
Despite the widespread use of Computer-Mediated Communication (CMC) for effective collaboration and interaction, CMC has become a growing hotbed for deception due to its provision of ubiquity, anonymity and open environment. Deception is an increasing threat to our society and to the daily communication of both individuals and groups. This dissertation aims to provide a new venue for understanding deception and for detecting deception through the identification, extraction, and application of social structural behaviors of deceptive communication. To this end, the dissertation consists of three major studies. The first study conceptualizes deception in terms of social structure by drawing on interpersonal deception theory and social network theories and proposes a research model of structural properties of deceptive communication: centrality, cohesion and similarity. Viewed from the social structural perspective, structural behaviors are denoted as the relationships between different individuals (entities) or as relatively stable patterns of relationships. The second study examines the impact of time on structural behaviors of deception based on interactional adaption theory and characteristics of temporal networks. The third study addresses the problem of automatic deception detection by extracting the structural features of deceptive communication and by combining the structural features with linguistic features. In addition, it evaluates the generality of the structural features identified from synchronous CMC to asynchronous CMC. The findings of this dissertation extend existing theories and research on explaining the effect of deception intent on structural behaviors of communication in multi-fold aspects. First, this dissertation extends the context of deception theories from interpersonal interaction to social interaction by addressing the interactional dynamics in group communication that is composed of one deceiver and multiple receivers. Second, the dissertation operationalizes the structural behaviors of deceptive CMC and extracts them from two different types of networks: static and temporal, and empirically validates the behaviors with real-world data. Third, the dissertation improves the performance of automated deception detection by incorporating the structural behaviors of deception