Psychotherapy delivery relies on a negotiation between patient self-reports and clinical intuition. Growing evidence for technological support of psychotherapy suggests opportunities to aid the mediation of this tension. To explore this prospect, we designed a prototype of a clinical decision support system (CDSS) for treating veterans with post-traumatic stress disorder in a Prolonged Exposure (PE) therapy intensive outpatient program. We conducted a two-phase interview study to collect perspectives from practicing PE clinicians and former PE patients who are United States veterans. Our analysis distills opportunities for a CDSS (e.g., offering homework review at a glance, aiding patient conceptualization) and larger challenges related to context and deployment (e.g., navigating Veterans Affairs). By reframing our findings through three human-centered perspectives (distributed cognition, situated learning, infrastructural inversion), we highlight the complexities of designing a CDSS for psychotherapists in this context and offer theory-aligned design considerations.

The mental health crisis in the United States spotlights the need for more scalable training for mental health workers. While present-day AI systems have sparked hope for addressing this problem, we must not be too quick to incorporate or solely focus on technological advancements. We must ask empirical questions about how to ethically collaborate with and integrate autonomous AI into the clinical workplace. For these Human-Autonomy Teams (HATs), poised to make the leap into the mental health domain, special consideration around the construct of trust is in order. A reflexive look toward the multidisciplinary nature of such HAT projects illuminates the need for a deeper dive into varied stakeholder considerations of ethics and trust. In this paper, we investigate the impact of domain---and the ranges of expertise within domains---on ethics- and trust-related considerations for HATs in mental health. We outline our engagement of 23 participants in two speculative activities: design fiction and factorial survey vignettes. Grounded by a video storyboard prototype, AI- and Psychotherapy-domain experts and novices alike imagined TEAMMAIT, a prospective AI system for psychotherapy training. From our inductive analysis emerged 10 themes surrounding ethics, trust, and collaboration. Three can be seen as substantial barriers to trust and collaboration, where participants imagined they would not work with an AI teammate that didn't meet these ethical standards. Another five of the themes can be seen as interrelated, context-dependent, and variable factors of trust that impact collaboration with an AI teammate. The final two themes represent more explicit engagement with the prospective role of an AI teammate in psychotherapy training practices. We conclude by evaluating our findings through the lens of Mayer et al.'s Integrative Model of Organizational Trust to discuss the risks of HATs and adapt models of ability-, benevolence-, and integrity-based trust. These updates motivate implications for the design and integration of HATs in mental health work.

Informal caregivers perform an important role in taking care of family members with chronic disease. Informal caregivers' mental health can be negatively impacted by life-changing events (e.g., patients' diagnosis, care transitioning, etc.). This leads the caregiver to suffer from interpersonal and intrapersonal conflicts, causing a sense of disorientation and escalating malaise. In this study, we investigated informal caregivers' experiences of facing conflicts and life-changing events by qualitatively analyzing the data from online health communities. We categorized conflicts using a psychodynamic framework. We further looked at the interplay of life-changing events and conflicts and how this leads to caregivers' sense-making and decisions to mediate conflicts. We also found that online health communities provide support by helping caregivers interpret and navigate conflicts and raising awareness of the temporal resolution of life-changing events. We conclude this study by discussing designing online health communities to better support such practice.

Many people do not get enough physical activity. Establishing routines to incorporate physical activity into people’s daily lives is known to be effective, but many people struggle to establish and maintain routines when facing disruptions. In this paper, we build on prior self-experimentation work to assist people in establishing or improving physical activity routines using a framework we call “reflective iteration.” This framework encourages individuals to articulate, reflect upon, and iterate on high-level “strategies” that inform their day-to-day physical activity plans. We designed and deployed a mobile application, Planneregy, that implements this framework. Sixteen U.S. college students used the Planneregy app for 42 days to reflectively iterate on their weekly physical exercise routines. Based on an analysis of usage data and interviews, we found that the reflective iteration approach has the potential to help people find and maintain effective physical activity routines, even in the face of life changes and temporary disruptions.

Today, clinicians have limited visibility into the quality of homework exercises that occur outside of the clinical context; however, understanding patient performance in these exercises is essential for guiding patient-centered care. To address this, we present the Clinician Homework Review (CHR), a unique measure and interface that displays similarity ratings calculated using sensor-captured patient-generated data (sPGD; i.e. heart rate, phone usage, ambient noise, and physical activity) for therapeutic exercises outside of the clinical setting within the post-traumatic stress disorder (PTSD) treatment context. Through concept testing sessions with 10 clinicians, we examine how sPGD can be leveraged to measure and investigate what contributes to patient performance in a therapeutic exercise. We also share in-depth information regarding clinician interpretation and planned use of data displayed by CHR in clinical sessions with patients. We frame our results in the context of situated objectivity and propose the notion of "perceived reference weight," which describes the significance attributed to contextualized data. In doing so, we support clinical decision-making in PTSD therapy.

Clinical decision support tools have typically focused on one-time support for diagnosis or prognosis, but have the ability to support providers in longitudinal planning of patient care regimens amidst infrastructural challenges. We explore an opportunity for technology support for discontinuing antidepressants, where clinical guidelines increasingly recommend gradual discontinuation over abruptly stopping to avoid withdrawal symptoms, but providers have varying levels of experience and diverse strategies for supporting patients through discontinuation. We conducted two studies with 12 providers, identifying providers' needs in developing discontinuation plans and deriving design guidelines. We then iteratively designed and implemented AT Planner, instantiating the guidelines by projecting taper schedules and providing flexibility for adjustment. Provider feedback on AT Planner highlighted that discontinuation plans required balancing interpersonal and infrastructural constraints and surfaced the need for different technological support based on clinical experience. We discuss the benefits and challenges of incorporating flexibility and advice into clinical planning tools.

Many parents of young children find it challenging to deal with their children's eating problems, and parent--child mealtime interaction is fundamental in forming children's healthy eating habits. In this paper, we present the results of a three-week study through which we deployed a mealtime assistant application, MAMAS, for monitoring parent--child mealtime conversation and food intake with 15 parent--child pairs. Our findings indicate that the use of MAMAS helped 1) increase children's autonomy during mealtime, 2) enhance parents' self-awareness of their words and behaviors, 3) promote the parent--child relationship, and 4) positively influence the mealtime experiences of the entire family. The study also revealed some challenges in eating behavior interventions due to the complex dynamics of childhood eating problems. Based on the findings, we discuss how a mealtime assistant application can be better designed for parents and children with challenging eating behaviors.

Adolescence is a challenging period for individuals with autism because they undergo radical physical, emotional, and social transitions. We describe our setup to support the self-management of adolescents with autism for assisting adaptive transitions. We propose COSMA, an interactive mobile application that allows both individuals with autism and their caregivers to cooperatively manage, plan, reflect on, and improve behavior. COSMA is a self- management tool for adolescents with autism, including behavioral goal setting by means of the co-contract process, self-reporting while performing everyday tasks, and cooperative reflection to support their smooth transition to adulthood.