Health technologies tools provide support for behavioral goals but largely assume that people live a stable life routine and continuously engage with their goal. Despite barriers to behavior being discussed in literature, they are largely not at the center of design, and researchers lack a systematic understanding of the prevalence and burdens of disruptions. To characterize individuals’ disruptions to engaging in wellbeing goals, we surveyed 149 US adults. We identified eight types of disruptions, such as emotional/cognitive, physical/medical, financial and four resulting burdens (emotional, physical, logistical, and financial). The majority of participants experienced multiple disruptions, with over 40% of experiencing daily disruptions. Over half of participants experienced disruptions lasting over a month. We discuss how health and wellbeing technologies can support people’s goals through adaptation based on disruptions’ burden, temporality, relevance and scale of disruptions.

Peer Reviewed

HCI research on goals and behavior change has significantly increased over the past decade.However, while emerging work has synthesized personal informatics goals, fewer efforts have focused on also integrating HCI research on behavior change to chart future research directions.We conducted a systematic review of 180 papers focused on goals and behavior change from over 10 years of SIGCHI journals and conference proceedings.We further analyzed 37 papers from the data set that included evaluations of interventions' effectiveness in-the-wild.We also reported on the effectiveness of 76 of such technology-based interventions and the meta-analysis of 28 of these interventions.We find that most research has focused on goals in the health and wellbeing domains, centered on the individual, low intrinsic goals, and partial use of theoretical constructs in technology-based interventions.We highlight opportunities for supporting multiple-domain, social, high intrinsic, and qualitative goals in HCI research for behavior change, and for more effective technology-based interventions with stronger theoretical underpinning, supporting users' awareness of deep motives for qualitative goals.

Pregnancy brings physical, emotional, and economic challenges for expectant parent(s), close relatives, and friends. Existing technology support, including tracking technology, largely targets pregnant people and ignores other stakeholders. We therefore lack an understanding of how to approach designing collaborative pregnancy tracking technology. To understand how people collaborate around pregnancy tracking and wish to do so, we interviewed 13 pregnant people and 11 non-pregnant stakeholders in the U.S., including partners, friends, and grandparents-to-be. We find that people collaborate for goals like social bonding and jointly managing various pregnancy data. Stakeholders collaborated by either dividing up data types or collectively monitoring the same information. We also identify tensions and challenges, such as pregnant people’s privacy concerns and stakeholders’ varied levels of interest in tracking. In light of socio-cultural norms and stakeholders’ distinctive roles around pregnancy, we point to opportunities for designing collaborative technology that aligns with as well as challenges socio-cultural practices around pregnancy tracking.

Mental health activities conducted by patients between therapy sessions (or "therapy homework") are a component of addressing anxiety and depression. However, to be effective, therapy homework must be tailored to the client's needs to address the numerous barriers they encounter in everyday life. In this study, we analyze how therapists and clients tailor therapy homework to their client's needs. We interviewed 13 therapists and 14 clients about their experiences tailoring and engaging in therapy homework. We identify criteria for tailoring homework, such as client skills, discomfort, and external barriers. We present how homework gets adapted, such as through changes in difficulty or by identifying alternatives. We discuss how technologies can better use client information for personalizing mental health interventions, such as adapting to client barriers, adjusting homework to these barriers, and creating a safer environment to support discomfort.

Pregnancy is a significant but stressful life transition, requiring effort from multiple stakeholders including expectant parents, family members, and friends to navigate. Existing work has primarily focused on understanding and supporting the technology use of pregnant people, neglecting other stakeholders' needs and participation. We therefore consider how pregnancy tracking apps both improve and interfere with the reconfiguration of social relationships caused by pregnancy, drawing on insights from family sociology to examine how these relationships evolve over pregnancy and the transition to parenthood. We reviewed the features of 20 pregnancy tracking apps, and analyzed 4,709 public reviews of them, finding that stakeholders used apps to bond with one another around the excitement of pregnancy, build a prenatal relationship with the fetus, and co-manage pregnancy-related logistical tasks. We find that not accounting for fetal demographics and users' identities, along with socio-cultural norms around gender and parenting roles, often inhibit these collaborative practices. We therefore suggest designing collaborative pregnancy tracking technology that considers both inclusiveness and specificity regarding stakeholders' different roles and relationships to pregnancy.

Psychosocial therapies play a crucial role in effectively treating anxiety and depression. An integral aspect of these therapies involves setting goals that clients engage in outside therapy, known as therapy homework or between-session goals. Yet, clients overwhelmingly do not complete between-session goals. This study explores mental health therapists' and clients' challenges in collaborating to set and manage engagement with between-session goals and discusses how technology could better support them. We interviewed 13 therapists and 14 clients about their experiences with between-session goals. We identified therapists' needs for information to support their clients, challenges in collaboration, and how technology can support client-therapist collaboration. Therapists need in-the-moment information about clients' engagement with goals to inform their decision-making. Clients may feel reluctant to share information due to a lack of trust, embarrassment, or not knowing what to share. Clients could use technology to asynchronously communicate about sensitive topics with their therapists. Technologies could facilitate gathering in-the-moment data that supports client-therapist collaboration on goals.

Goal setting is critical to achieving desired changes in life. Many technologies support defining and tracking progress toward goals, but these are just some parts of the process of setting and achieving goals. People want to set goals that are more complex than the ones supported through technology. Additionally, people use goal-setting technologies longitudinally, yet the understanding of how people's goals evolve is still limited. We study the collaborative practices of mental health therapists and clients for longitudinally setting and working toward goals through semi-structured interviews with 11 clients and 7 therapists who practiced goal setting in their therapy sessions. Based on the results, we create the Longitudinal Goal Setting Model in mental health, a three-stage model. The model describes how clients and therapists select among multiple complex problems, simplify complex problems to specific goals, and adjust goals to help people address complex issues. Our findings show collaboration between clients and therapists can support transformative reflection practices that are difficult to achieve without the therapist, such as seeing problems through new perspectives, questioning and changing practices, or addressing avoided issues.

Human-centered computing research has been increasingly applied to address important challenges in the health domain. Conducting research in cross-disciplinary teams can come with a lot of challenges in integrating knowledge across fields. Yet, we do not know what challenges HCI researchers encounter in building collaborations with health researchers, and how these researchers negotiate challenges while balancing their professional goals. We interviewed 17 early- and mid-career HCI faculty working in the United States who conducted research in collaboration with health researchers. Drawing from a Team Science framework, we share participants' lived experiences and identify major challenges that HCI researchers encounter when finding, collaborating with, and negotiating with health collaborators when building technologies. We propose ways to better support research collaboration aimed at designing technologies using human-centered computing approaches. This includes strategies to support HCI researchers at individual, institutional, research community, and funding agencies levels through tools to translate disciplinary approaches. We suggest institutional policies to support HCI researchers through training, networking, and promotion.

Exercise plans help people implement behavior change. Crowd workers can help create exercise plans for clients, but their work may result in lower quality plans than produced by experts. We built CrowdFit, a tool that provides feedback about compliance with exercise guidelines and leverages strengths of crowdsourcing to create plans made by non-experts. We evaluated CrowdFit in a comparative study with 46 clients using exercise plans for two weeks. Clients received plans from crowd planners using CrowdFit, crowd planners without CrowdFit, or from expert planners. Compared to crowd planners not using CrowdFit, crowd planners using CrowdFit created plans that are more actionable and more aligned with exercise guidelines. Compared to experts, crowd planners created more actionable plans, and plans that are not significantly different with respect to tailoring, strength and aerobic principles. They struggled, however, to satisfy exercise requirements of amount of exercise. We discuss opportunities for designing technology supporting physical activity planning by non-experts.

Many people appropriate social media and online communities in their pursuit of personal health goals, such as healthy eating or increased physical activity. However, people struggle with impression management, and with reaching the right audiences when they share health information on these platforms. Instagram, a popular photo-based social media platform, has attracted many people who post and share their food photos. We aim to inform the design of tools to support healthy behaviors by understanding how people appropriate Instagram to track and share food data, the benefits they obtain from doing so, and the challenges they encounter. We interviewed 16 women who consistently record and share what they eat on Instagram. Participants tracked to support themselves and others in their pursuit of healthy eating goals. They sought social support for their own tracking and healthy behaviors and strove to provide that support for others. People adapted their personal tracking practices to better receive and give this support. Applying these results to the design of health tracking tools has the potential to help people better access social support.

We consider why and how women track their menstrual cycles, examining their experiences to uncover design opportunities and extend the field's understanding of personal informatics tools. To understand menstrual cycle tracking practices, we collected and analyzed data from three sources: 2,000 reviews of popular menstrual tracking apps, a survey of 687 people, and follow-up interviews with 12 survey respondents. We find that women track their menstrual cycle for varied reasons that include remembering and predicting their period as well as informing conversations with healthcare providers. Participants described six methods of tracking their menstrual cycles, including use of technology, awareness of their premenstrual physiological states, and simply remembering. Although women find apps and calendars helpful, these methods are ineffective when predictions of future menstrual cycles are inaccurate. Designs can create feelings of exclusion for gender and sexual minorities. Existing apps also generally fail to consider life stages that women experience, including young adulthood, pregnancy, and menopause. Our findings encourage expanding the field's conceptions of personal informatics.

The negative effect of lapses during a behavior-change program has been shown to increase the risk of repeated lapses and, ultimately, program abandonment. In this paper, we examine the potential of system-driven lapse management -- supporting users through lapses as part of a behavior-change tool. We first review lessons from domains such as dieting and addiction research and discuss the design space of lapse management. We then explore the value of one approach to lapse management -- the use of "cheat points" -- as a way to encourage sustained participation. In an online study, we first examine interpretations of progress that was reached through using cheat points. We then present findings from a deployment of lapse management in a two-week field study with 30 participants. Our results demonstrate the potential of this approach to motivate and change users' behavior. We discuss important open questions for the design of future technology-mediated behavior change programs.

Specific, achievable plans can increase people's commitment to behavior change and increase their likelihood of success. However, many people struggle to create such plans, and available plans often do not fit their individual constraints. We conducted a study with 22 participants exploring the creation of personalized plans by strangers and friends to support three kinds of behavior change: diet, physical activity, and financial. In semi-structured interviews and analyses of the generated plans, we found that friends and strangers can help create behavior change plans that are actionable and help improve behavior. Participants perceived plans more positively when they were personalized to their goals, routines and preferences, or when they could foresee executing the plans with friends - often the friend who created the plan. Participants felt more comfortable sharing information with strangers and they received more diverse recommendations from strangers than friends.

While crowd work typically involves tasks that performed at any time and anywhere, some tasks inherently require the physical presence of workers at a specific time and location. This paper presents a case study of a hybrid crowdsourcing process that involves the collaborative production of event reports using a combination of local and remote workers. The process extends human computation into the physical world by using local workers to collect information in person at events and remote workers to curate the collected information and generate event reports. We deployed the process at 11 events, employing 84 workers, and identified the challenges local workers face as constraints in mobility, time available to perform tasks, unpredictability of events, and interaction with others. We discuss issues related to collaboration with remote workers and bias in field reporting, and conduct a qualitative analysis to make design recommendations for extending human computation into the physical environment.

Although longer queries can produce better results for information seeking tasks, people tend to type short queries. We created an interface designed to encourage people to type longer queries, and evaluated it in two Mechanical Turk experiments. Results suggest that our interface manipulation may be effective for eliciting longer queries.

Exploratory search is a complex, iterative information seeking activity that involves running multiple queries and finding and examining many documents. We designed a query preview control that visualizes the distribution of newly-retrieved and re-retrieved documents prior to running the query. When evaluating the preview control with a control condition, we found effects on both people's information seeking behavior and improved retrieval performance. People spent more time formulating a query and were more likely to explore search results more deeply, retrieved a more diverse set of documents, and found more different relevant documents when using the preview.