Development and testing of a digitally assisted risk reduction platform for youth at high risk for suicide

摘要

ABSTRACT Despite efforts to prevent suicide, US rates are climbing, and suicide is the second leading cause of death amongst youth. Although promising approaches are available for preventative interventions with youth at-risk for suicide, they demonstrate modest benefit, and recent reviews have concluded that new developments are required that facilitate not only greater effectiveness, but also enhance treatment engagement, adherence, and continuity of care amongst these young people. Digital tools, especially personal smartphones, are promising avenues to address these issues and can be used to provide a unique understanding of proximal risk factors, including psychological distress, anhedonia and behavioral withdrawal, and sleep disturbance amongst high- risk individuals. Furthermore, digital methods can provide ongoing supportive patient contact to support the reduction of suicide risk. The overall aim of this Fast-track SBIR proposal is to enhance the effectiveness of selective and indicated prevention for youth who are received outpatient mental health care by developing and testing a comprehensive digital platform that allows practitioners to integrate objective mobile sensing and HIPAA compliant client communication tools into their management of these young people. We have developed an initial MVP version of these products, and in Phase I will utilize user-centered design principles to enhance the product fit with typical service delivery systems found in healthcare organizations working with high-risk individuals (i.e., intensive outpatient services). The aim of Phase II is to further optimize these products and conduct a pragmatic clinical trial of the effectiveness, feasibility, and acceptability of the products in a real world intensive outpatient clinical service. We will utilize the data generated by this trial to improve adoption, implementation fidelity, and sustained use of these tools, guided by an implementation science framework.