Mobile Data Collection
Our lab regulatory uses ambulatory assessment methods to study relationship processes. We are currently developing, testing, and validating mobile data collection software systems to capture multimodal data streams in families’ everyday lives. Such systems can collect data on electrodermal activity, skin temperature, heart rate, movement, sleep, self-report, audio, video, and GPS data, among many others. The development of these data collection systems could help us gain new insights about family functioning and will inform our understanding of how small-scale events impact long-term health.
Interdisciplinary Collaboration
Our research is interdisciplinary and integrates concepts across clinical, engineering, statistical, and technology domains. We find there is a close, reciprocal link between the questions that interest us, the analytic methods that help us to investigate those questions, and the technological innovations that make those visions a reality. Merging knowledge across fields is a central component of making advancements in science. Our ultimate goal is to develop and employ advanced methods in combination with emerging technological platforms to support child development.
Just-in-Time Adaptive Interventions
Current interventions aiming to improve relationship functioning largely rely on self-reports and therapists’ observations. Additionally, traditional therapy methods cannot provide in-the-moment feedback when problems actually occur in people’s day-to-day lives. Using wearable technologies, we aim to monitor people outside the laboratory and intervene in problems as they naturalistically unfold. We are currently collaborating with engineers to develop phone-based smart interventions capable of providing personalized 24-hour feedback and support delivered in daily life in moments of critical need.
Digital Assessment and Real-World Measurement
Understanding mental health and human behavior requires studying people in the contexts in which their lives naturally unfold. Our lab uses mobile technologies, wearable sensors, and intensive longitudinal assessment to capture emotional, behavioral, interpersonal, and physiological processes in everyday life. These approaches allow us to move beyond traditional snapshots of psychological functioning to understand how experiences fluctuate, interact, and change over time.
Our research integrates ecological momentary assessment, passive sensing, and multimodal data collection, including physiological signals, movement, sleep, and naturalistic audio recordings. We are particularly interested in how these technologies can reveal dynamic patterns of psychological functioning, identify emerging risks and opportunities for intervention, and illuminate how everyday experiences accumulate to shape longer-term mental health and development.
AI-Enabled Mental Health Interventions
Digital technologies offer new opportunities to expand access to evidence-based mental health care and provide support within the contexts of everyday life. Advances in artificial intelligence make it increasingly possible to deliver interventions that are interactive, personalized, and responsive to individuals’ needs, extending therapeutic support beyond traditional clinical settings.
Our lab develops and evaluates innovative digital mental health interventions that integrate psychological science, mobile technologies, and artificial intelligence. Our work includes AI-supported parenting interventions that provide individualized guidance, feedback, and skill-building opportunities during everyday parent-child interactions. Through randomized controlled trials and intensive longitudinal research, we investigate the effectiveness of these approaches, the mechanisms through which they influence psychological and relational functioning, and their potential to improve access to scalable, evidence-based mental health support.
Precision Mental Health and Adaptive Interventions
Traditional mental health interventions often rely on standardized approaches that do not fully account for differences in individuals’ needs, circumstances, or responses to treatment. Yet psychological functioning is dynamic, and the types of support people need may vary considerably across individuals, contexts, and time. Precision mental health seeks to understand this variability and use it to develop interventions that are more personalized, responsive, and effective.
Our research investigates when, how, and for whom different intervention strategies are most effective, with the goal of identifying mechanisms of change and optimizing intervention delivery. We use microrandomized trials, intensive longitudinal assessment, and adaptive intervention designs to examine how therapeutic strategies can be tailored to individuals’ evolving needs and circumstances. Our work also addresses engagement as a critical determinant of intervention effectiveness, investigating how personalized support can improve participation, sustain therapeutic involvement, and maximize clinical benefit. Ultimately, we aim to develop intelligent, adaptive interventions that deliver the right support, to the right person, at the right time, improving mental health outcomes and expanding the reach and impact of evidence-based care.