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      The Application of User Event Log Data for Mental Health and Wellbeing Analysis

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      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

      Human Computer Interaction Conference

      4 - 6 July 2018

      User event log, log analytics, machine learning, data mining, mental health, digital interaction technology, m-Health, e-Health

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          Many digital interaction technologies, including web-based interventions, smartphone applications, and telephone helplines, can provide a basis for capturing real time data of interactions between the user and the system. Such data is recorded in the form of log files, which records user events that range from simple keystrokes on a computer, user activated sensor data or duration/frequency of phone calls. These interactions can provide rich datasets amenable to user data analytics using machine learning and other analytics techniques. This data analysis can highlight usage patterns and user behaviours based on their interaction with the technology. User log data analysis can be descriptive statistics (what users have done), predictive analytics (what events will happen) and prescriptive (what action to take given a predicted event or outcome). This can also be thought of as spanning across different levels of user analytics from hindsight, insight and foresight. Predictive analytics are used with log data to provide predictions on future user behaviour based on early usage behaviours. Event logs are objective regarding usage, but usage may not correlate with the level of the system’s user experience. Hence, ecological momentary assessment (EMA) of the user experience can be used augment user log data. Nevertheless, with the emergence of health applications and other app-based health services, we consider how user event logs can be specifically used within the mental health domain. This can provide beneficial insights into how users interact with mental health e-services, which can provide an indication of their current and future mental state.

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                Author and article information

                July 2018
                July 2018
                : 1-14
                Ulster University Jordanstown Shore Road, Newtownabbey Northern Ireland
                © Turkington et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit

                Proceedings of the 32nd International BCS Human Computer Interaction Conference
                Belfast, UK
                4 - 6 July 2018
                Electronic Workshops in Computing (eWiC)
                Human Computer Interaction Conference
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page):
                Electronic Workshops in Computing


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