Design guidelines for behavioral feedback visualizations to support health behavior change
A variety of self-monitoring technologies (e.g., wristbands, mobile applications) enable users to monitor personal health behaviors (e.g., daily steps, medication taking) and visualize the behavioral data as feedback via interactive or ambient displays to support health behavior change. The visualization tools could promote a robust understanding and engage individuals in reflective analysis of health behaviors by providing them with visualizations about past recorded information and the context. The visualizations have the potential to help them change health behaviors by increasing self-reflection, changing attitude, enhancing motivation, boosting self-efficacy, and implementation intentions. However, to the best of my knowledge, there is no study to identify the mechanism of action of visual feedback, and no systematic and comprehensive review and analysis to integrate the literature and identify potential gaps of feedback visualizations for health behavior change. In addition, most self-monitoring technologies are designed to provide visual feedback for health behaviors, such as physical activity, for younger populations. Little attention has been paid to designing visual feedback in medication monitoring technology for older adults to support the behavior of medication taking and it is unknown how to design understandable, reflective, and actionable visual feedback for older adults for medication adherence. The primary objective of the research was to identify beneficial approaches for providing behavioral feedback visualizations to optimize comprehension and reflection of personal health data information and action on health behavior change. Specifically, the goals were to: 1) identify feedback components and visualization types of feedback visualizations for health behavior change; 2) identify potential mechanisms of action of visual feedback; 3) provide a road map for feedback visualization development and assessment for health behavior change; 4) develop and assess feedback visualizations to support medication adherence for older adults; and 5) provide guidance for designing comprehensible and actionable feedback visualizations to support older adults medication adherence. To achieve these goals, I first conducted a systematic review study to identify effective feedback components and design requirements of behavioral feedback visualizations for health behavior change. In this study, I developed an organizational framework representing visualization types, feedback components, and potential mechanisms of action of visual feedback, guided by behavior change theories; organized empirical evidence for the framework from existing research; developed design guidelines of behavioral feedback visualizations based on the theories as well as the empirical evidence. The guidelines from the systematic review informed the design of feedback visualizations for hypertensive medication adherence for older adults in the second study-a use case study. In the use case study, I worked with MEDSReM team to design visual prototypes for medication adherence for older adults and I interviewed both healthcare providers and older adults to evaluate perceived effectiveness of feedback visualizations for medication adherence and identified factors that might influence their perception of the effectiveness. The insights from the use case study allowed me to develop design guidelines for medication feedback visualizations for older adults. This research showed the value of feedback visualizations for improving comprehension of personal behavioral health data and feasibility for health behavior change. The dissertation research was the first study that proposed a framework of feedback visualization-action process, which provided a clearer picture of what we consider feedback visualizations and what are the potential mechanisms of action. It also provided a wealth of data about the specific feedback components that influence the mechanisms of behavior change and directions for future feedback visualization design and research. In addition, guidelines were generated to help researchers and designers in human factors, information visualization, computer science, and others to develop understandable and actionable feedback visualizations for medication adherence for older adults, which has the potential to generalize to other health behaviors and a larger population.
Visual feedback, Health behavior change, Self-monitoring technology, Personal informatics, Medication adherence
University of Illinois - Urbana-Champaign
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