The Center for Accelerating Practices to End Suicide through Technology Translation (CAPES) addresses the gap in translating evidence-based technologies for suicide prevention into clinical practice. Leveraging a transdisciplinary team with extensive expertise, CAPES will innovate by integrating implementation science, person-centered design, and technology transfer to maximize public health impact. Supported by UMass, Worcester Polytechnic Institute, and other partners, CAPES aims to advance suicide prevention through scalable solutions aligned with the Zero Suicide framework, targeting diverse settings and populations for transformative outcomes. NIH Project Link

The Probation/Parole And Reentry Coach Application (PARCA) platform aims to improve engagement in substance use treatment for justice-involved persons (JIPs) under community supervision, addressing their elevated rates of opioid use. PARCA integrates a mobile app for JIPs with a Justice Team (JT) Dashboard to enhance goal-setting, connect users with local resources, and improve communication with probation and parole officers (PPOs). In a Phase I/II STTR study, PARCA will be refined and tested in Dallas and Hidalgo Counties to assess its feasibility, acceptability, and efficacy in supporting treatment engagement and reducing criminal behavior, using a user-centered design approach and stepped wedge effectiveness design. NIH Project Link

Perinatal depression affects 1 in 7 pregnant and postpartum individuals, contributing to adverse outcomes for mothers and infants. To address barriers in accessing preventive interventions, the Text4Moms program will develop a text messaging intervention (TMI) that screens for major depressive episode (MDE) risk and delivers tailored, evidence-based content rooted in cognitive behavioral therapy (CBT) and interpersonal therapy (IPT). Combining proactive text messages, video resources, and peer navigator support via secure chat, Text4Moms aims to enhance self-efficacy and reduce depressive symptoms. A pilot randomized trial will evaluate its feasibility, acceptability, and preliminary effectiveness in improving mental health outcomes for perinatal individuals. NIH Project Link

This project aims to develop a smartphone-based wound infection risk screener that uses deep learning to analyze photographs and thermal images, enabling non-expert caregivers to detect infections at the point of care (POC) without debridement. The system will provide evidence-based care recommendations and referral guidance, improving infection detection and reducing unnecessary referrals. Validated on diverse wound types, this innovation seeks to enhance care efficiency, minimize treatment delays, and lower the risk of amputations for chronic wound patients. NIH Project Link

This project seeks to improve decision-making for surrogate decision-makers of patients with severe acute brain injury (SABI) in intensive care units (ICUs). By developing a digital decision aid and communication (DA+C) tool, the intervention aims to enhance clinician-family communication, provide balanced and accessible information on prognosis and treatment options, and support decisions aligned with patient values. A pilot study will assess the tool's feasibility and impact on decision-making quality, laying the groundwork for a multicenter trial to improve outcomes for patients, families, and healthcare systems. NIH Project Link