Abstract
Sensors and wearables measure physiological and behavioral data in real time for behavioral health, using a variety of methods, interventions, and outcomes. A six-stage scoping review of 10 literature databases focused on keywords in four concept areas: (1) mobile technologies; (2) sensors, wearables, and remote monitoring; (3) mood and anxiety disorders, as well as stress; and (4) behavioral health care. Two authors independently screened results based on titles and abstracts, reviewed the full-text articles, and used inclusion/exclusion criteria to find research that studied self-report or management of symptoms and interventions. Out of a total of 5468 potential references, 76 papers were selected and an additional 16 studies were discovered in references. Of the 92 studies, 54 (58.7%) focused on mood (depressive, N = 28; bipolar, N = 26), 18 (19.6%) on anxiety disorders, and 20 (21.7%) on psychological stress/stress disorders. There were 7 (7.6%) randomized controlled trials, and 31 (33.7%) comparison studies. Research is shifting toward standardized methods, interventions, and evaluation measures, with longitudinal correlation, prediction, and/or biomarking/digital phenotyping of patients’ outcomes. These technologies pose several challenges for users, clinicians (e.g., selection, training, skills), healthcare systems (e.g., technology, integration into workflow, privacy), and organizations (e.g., training, creating a professional e-culture, change). Future research is needed on clinical health outcomes; human–computer interaction; medico-legal, professional, and privacy policy issues; models of service delivery; and effectiveness at a population level, across cultures, and related to economic costs. Clinician and institutional competencies could ensure quality of care, integration of missions, and institutional change.