<p>Chronic pain is a prevalent condition where fear of movement and pain interferes with everyday functioning. Yet, there is no open body movement dataset for people with chronic pain in everyday settings. Our EmoPain@Home dataset addresses this with capture from people with and without chronic pain in their homes, while they performed their routine activities. The data includes labels for pain, worry, and movement confidence continuously recorded for activity instances for the people with chronic pain. We explored two-level pain detection based on this dataset and obtained 0.62 mean F1 score. However, extension of the dataset led to deterioration in performance confirming high variability in pain expressions for real world settings. We investigated activity recognition for this setting as a first step in exploring the use of the activity label as contextual information for improving pain level classification performance. We obtained mean F1 score of 0.43 for 9 activity types, highlighting its feasibility. Further exploration, however, showed that data from healthy people cannot be easily leveraged for improving performance because worry and low confidence alter activity strategies for people with chronic pain. Our dataset and findings lay critical groundwork for automatic assessment of pain experience and behaviour in the wild. </p>

Though some work has looked at the implementation of personal informatics tools with youth and in schools, the approach has been prescriptive; students are pushed toward behaviour change intervention or otherwise use the data for prescribed learning in a particular curriculum area. This has left a gap around how young people may themselves choose to use personal informatics tools in ways relevant to their own concerns. We gave workshops on personal informatics to 13 adolescents at two secondary schools in London, UK. We asked them to use a commercial personal informatics app to track something they chose that they thought might impact their learning. Our participants proved competent and versatile users of personal informatics tools. They tracked their feelings, tech activity, physical activity, and sleep with many using the process as a system for understanding and validating aspects of their own lives, rather than changing them.

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Schools are increasingly focusing on ways to increase adolescents’ self-efficacy in areas of their life from relationships to sleep. Commercially available apps such as mood and sleep trackers may be able to sup-port this process. This paper draws on Rubtsova’s explication of “role experimentation” and on Vygotsky’s reading of Freud to delineate dynamics within adolescent personality development. This theoretical back-ground is utilized in a study of seven 12—13 year-olds in a secondary school in London. Participants used an app designed by other students to track their sleep for two weeks. Their data mediated dramatic situations while discussing their experiences with their peers in the study. This process supported self-reflection and helped participants develop concepts for talking about their everyday life in subsequent one-on-one interviews. In negotiating peer and student roles, participants experimented with scientific and everyday concepts, allowing them to see their own data and the experiences it signified from a new angle.

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