Using Mobile Apps to Support the Implementation of Coping-relevant Behaviour Change Techniques for Self-management of Stress

Mobile apps have shown potential in early stress self-management interventions, yet they remain less beneficial than face-to-face therapies. One of the most effective ways people can cope with stress is to identify what their stressors are and take action in managing them. Coping-relevant behaviour change techniques (BCTs), such as self-monitoring, goal setting, and action planning, have the potential to support this process. Nevertheless, there is little guidance on how to incorporate such techniques into stress management apps. Drawing on mixed methods research, this thesis provides two contributions. First, it improves our understanding of how existing stress management apps support coping-relevant BCTs and suggests areas for improvements. An app functionality review and follow-up 3-week intervention using Welltory stress monitoring and Coach.me goal setting apps revealed that existing apps do not support users’ efforts with coping-relevant BCTs. Participants reported that Welltory did not yield sufficient data to gain insights into the factors affecting their stress. Relatedly, the way in which these apps implemented coping-relevant BCTs diminished peoples’ sense of autonomy and competence. Drawing on peoples’ experiences with existing apps and principles of positive computing, the second contribution of this thesis is the design and evaluation of Reffy - a chatbot prototype that integrates coping-relevant BCTs in a way that meets people’s stress management needs. Based on findings from a field evaluation study, we identify specific benefits and challenges of using a stress self-management chatbot. We find that chatbot-based reflective questioning helps people identify how factors impact their stress during early stages of self-tracking. Likewise, adding features that promote users’ sense of autonomy and competence improves Welltory’s ability to support coping strategies. This thesis advances our understanding of how behaviour change and stress coping techniques can be incorporated into mobile apps to effectively support stress self-management

Theory-driven Visual Design to Support Reflective Dietary Practice via mHealth: A Design Science Approach

Design for reflection in human-computer interaction (HCI) has evolved from focusing on an abstract and outcome-driven design subject towards exposing procedural or structural reflection characteristics. Although HCI research has recognized that an individual\u27s reflection is a long-lasting, multi-layered process that can be supported by meaningful design, researchers have made few efforts to derive insights from a theoretical perspective about appropriate translation into end-user visual means. Therefore, we synthesize theoretical knowledge from reflective practice and learning and argue for a differentiation between time contexts of reflection that design needs to address differently. In an interdisciplinary design-science-research project in the mHealth nutrition promotion context, we developed theory-driven guidelines for “reflection-in-action” and “reflection-on-action”. Our final design guidelines emerged from prior demonstrations and a final utility evaluation with mockup artifacts in a laboratory experiment with 64 users. Our iterative design and the resulting design guidelines offer assistance for addressing reflection design by answering reflective practice’s respective contextual requirements. Based on our user study, we show that reflection in terms of “reflection- in-action” benefits from offering actionable choice criteria in an instant timeframe, while “reflection-on-action” profits from the structured classification of behavior-related criteria from a longer, still memorable timeframe

Representation Effects and Loss Aversion in Analytical Behaviour: An Experimental Study into Decision Making Facilitated by Visual Analytics

This paper presents the results of an experiment into the relationship between the representation of data and decision-making. Three hundred participants online, were asked to choose between a series of financial investment opportunities using data presented in line charts. A single dependent variable of investment choice was examined over four levels of varying display conditions and randomised data. Three variations to line chart visualisations provided a controlled factor between subjects divided into three groups; -˜standard’ line charts, -˜tall’ line charts, and one dual-series line chart. The final results revealed a consistent main effect and two other interactions between certain display conditions and decision-making. The findings of this paper are significant to the study visualisation and to the field of visual analytics. This experiment was devised as part of a study into Analytical Behaviour, defined as decision-making facilitated by visual analytics - a new topic that encompasses existing research and real-world applications

Comparing and Improving the Design of Physical Activity Data Visualizations

Heart disease is a leading cause of death in the United States, and older adults are at highest risk of being diagnosed with heart disease. Consistent physical exercise is an effective means of deterring onset of heart disease, and physical activity tracking devices can inspire greater activity in older adults. However, physical activity tracking device abandonment is quite common due to limitations on what can be learned from the activity data that is collected. Better data visualization of physical data presents an opportunity to surpass these limitations. In this thesis, a task-based human subject study was performed with three different data visualizations to gain insight into how the format of physical activity data visualizations impact older adults’ abilities to infer meaning from physical activity data. Participants (n = 30) interacted with a prototype data visualization as well as two data visualizations from popular fitness tracking applications (Fitbit and Strava) and used these visualizations to complete 11 tasks. Results from these tasks show each visualization was able to facilitate users answer some task questions effectively, though no visualizations exhibited strong performance across all tasks. From the successes and shortcomings of each visualization, three key design recommendations for the design of data visualizations for physical activity data were made: 1) make exact values available, 2) summarize data at multiple timescales, and 3) ensure accessibility for the entire population of users

HEURISTIC THINKING ON DATA VISUALIZATION BASED ON DASHBOARD CASE STUDIES AT NATIONAL HOSPITAL SURABAYA

Dashboard-based data visualization has various information is an option for presenting data is expected to support decision making. The ease of the dashboard isn't perfect, but it also has weakness. The nature of heuristic thinking makes users behave inconsistent with the rational decision-making process tobe an important issue. This study was conducted to explain the heuristic thinking behavior phenomenon from dashboard-based data visualization in the decision-making process. A qualitative approach is used with procedures and data collection based on interview techniques, observation and literature study. Data were observed from the National Hospital, Surabaya. The result is there is a bias in seeing data in a visual form, someone will tend to simplify the decision-making process. The contribution of this study is heuristic thinking on dashboard-based data visualization which can lead users to make irrational decisions

Supporting Diabetes Self-Management with Ubiquitous Computing Technologies: A User-Centered Inquiry

Ubiquitous computing technologies offer opportunities to improve treatments for chronic health conditions. Type 1 diabetes is a compelling use-case for such approaches, given its severity, and need for individuals to make frequent care decisions, informed by complex data. However, current apps, typically based on effortful reflection on collected data, generally show poor adoption, lack vital cognitive and emotional support, and are poorly tailored to users’ actual diabetes decision making processes. This thesis investigates how diabetes apps can be improved from a user-centered perspective. An initial questionnaire-based study investigated how well existing diabetes apps meet user needs. Perceived benefits, limitations, and reasons for low adoption rates were identified. A talk-aloud study of detailed user interactions with diabetes logging apps was conducted to characterize the benefits and limitations of diverse UI elements for T1 diabetes management, and to more precisely identify wider problems with current interaction designs. This led to positing a refined version of Mamykina et al.’s model for diabetes self-management, to account for observed practices, whereby the previously accepted habitual and sensemaking cognitive states are augmented by a posited ‘fluid contextual reasoning’ (FCR) mode, which allows multiple contextual factors to be balanced for dynamic course correction when navigating complex situations, using previously learned knowledge. To investigate user perceptions of the levels and kinds of monitoring anticipated in next generation diabetes decision support systems, a 4-week technology probe, in which participants used multiple networked devices and external data aggregation, was used to frame requirements for user-centered development of such future systems. Integrating all of the above work, an iterative design process was undertaken to create DUETS, a card-based system to facilitate reflection by designers, users, and other stakeholders on diabetes support management systems. The resulting tool and method were then implemented and evaluated through structured sessions with stakeholder focus groups