We explore the Examined Life, informing the design of reflective systems to promote emotional well-being, a critical health issue. People now have increasingly rich, digital records of highly personal data about what they said, did, and felt in the past. But social science research shows that people have difficulty in tracking and regulating their emotions. New reflective technologies that promote constructive analysis of rich personal data potentially offer transformative ways that individuals might better understand themselves and improve well-being. However, there are important system design challenges in supporting effective reflection about personal data. We explore fidelity in recording and representing past personal mood data, and forecasting future actions, feelings, and thoughts. Much prior personal informatics work has been dedicated to past-centric tools for recording and capture. In contrast, forecasting examines how we might use such past data to inform and motivate our future selves, providing recommendations about remedial actions to improve future well-being. Fidelity addresses both how and what reflective systems should show people about their pasts, in particular whether we should filter negative past experiences. To inform reflective system design, we examine forecasting and fidelity in controlled field trial interventions that explore two novel system designs for presenting and reflecting on mood data. We detail findings from 165 participants, 4,693 participant logfiles, 65 surveys, and 15 user interviews. Our novel forecasting system, EmotiCal, uses past mood data to model and visualize future user moods with the goal of encouraging participants to adopt remedial new behaviors to regulate negative moods before they occur. Such forecasting both improved mood and subsequent emotional self-awareness compared with controls who simply monitored their past. Consistent with system goals, interview responses also indicated that participants generated important insights into behaviors that affect their moods. Our second intervention examined filtering; it assessed the impact on well-being of recording and revisiting past experiences containing negative emotions. We compared participants who were encouraged to record and reflect on positive versus negative experiences. Long-term measures of happiness and ruminative behaviors improved by recording and reflecting on positive but not negative experiences, although this depended on the intensity of the negative experience. We discuss general design and theory implications for future systems that support monitoring, reflection, and forecasting to facilitate productive examination of our emotional lives.

Maintaining work focus when on a computer is a major challenge, and people often feel that they use their time ineffectively. To improve focus we designed meTime, a real-time awareness application that shows users how they allocate their time across applications. In two real-world deployments involving 118 participants, we examined whether greater awareness of time use improves focus. In our first deployment, we provided awareness information using meTime, to both office workers and students. Exposure to meTime reduced use of social media, email, browsing and total time online. However increased awareness didn't affect time spent in productivity applications. A second educational deployment largely replicated these results and showed that meTime also reduced users' perceptions of their ability to focus effectively. Changed perceptions were associated with higher class grades. We discuss practical and theoretical implications as well as design principles for use of time applications.

Preventable behaviors contribute to many life threatening health problems. Behavior-change technologies have been deployed to modify these, but such systems typically draw on traditional behavioral theories that overlook affect. We examine the importance of emotion tracking for behavior change. First, we conducted interviews to explore how emotions influence unwanted behaviors. Next, we deployed a system intervention, in which 35 participants logged information for a self-selected, unwanted behavior (e.g., smoking or overeating) over 21 days. 16 participants engaged in standard behavior tracking using a Fact-Focused system to record objective information about goals. 19 participants used an Emotion-Focused system to record emotional consequences of behaviors. Emotion-Focused logging promoted more successful behavior change and analysis of logfiles revealed mechanisms for success: greater engagement of negative affect for unsuccessful days and increased insight were key to motivating change. We present design implications to improve behavior-change technologies with emotion tracking.

As people document more of their lives online, some recent systems are encouraging people to later revisit those recordings, a practice we're calling technology-mediated reflection (TMR). Since we know that unmediated reflection benefits psychological well-being, we explored whether and how TMR affects well-being. We built Echo, a smartphone application for recording everyday experiences and reflecting on them later. We conducted three system deployments with 44 users who generated over 12,000 recordings and reflections. We found that TMR improves well-being as assessed by four psychological metrics. By analyzing the content of these entries we discovered two mechanisms that explain this improvement. We also report benefits of very long-term TMR.