Reducing Risk: A Comprehensive mHealth Sleep Health Intervention for Adolescents at Risk for Depression and Anxiety Disorders

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Project Summary This application for a Mentored Patient-Oriented Career Development Award (K23) aims to support additional training and research that will enable the candidate to achieve her career goal of becoming an independent clinical scientist conducting research aimed at preventing mental illness among adolescents. Adolescence is a critical period characterized by dramatic increases in rates of depression and anxiety disorders, hereafter referred to as internalizing disorders (IDs). Problems with sleep health are ubiquitous and modifiable targets that precede and predict the development of IDs. This project uses an experimental design to (a) improve sleep health (through a sleep focused treatment), (b) determine whether a sleep focused treatment improves ID symptoms, and a known biological marker of risk for IDs, cortisol reactivity and recovery in response to a stress exposure, and (c) elucidate target mechanisms underlying the effect of poor sleep health on ID symptoms, and cortisol measures. The present study will test an innovative adaptation of Transdiagnostic Sleep and Circadian Intervention (TranS-C), a sleep health treatment that improves sleep and mental health and effectively treats the most common sleep health deficits among adolescents, each of which was previously shown to be independently associated with increased risk for IDs. To overcome the challenge of low availability of qualified providers as a barrier to treatment access, we adapted TranS-C for mobile device delivery (referred to as mTranS-C), thereby leveraging the high rates of mobile phone use among adolescents. To further increase access, we will test mTranS-C within primary care services, a proven strategy for improving access to behavioral health care. The application builds on the candidates’ prior work in transdiagnostic mechanisms of mental illness, identifying targets for intervention and the prevention of IDs, and evidence based interventions for sleep problems. The proposed training plan emphasizes the following training areas for the candidate: (1) develop expertise in mHealth technology/science, (2) the biology and objective measurement of cortisol, and (3) statistical methods for analyzing longitudinal data sets. An inter-disciplinary team of mentors and consultants consisting of international leaders in the areas of sleep interventions, mHealth technology/science, developmental psychopathology, cortisol measurement, and statistical methods, collectively will provide the expertise to help the candidate meet her training objectives.