Social media platforms are popular venues for sharing personal experiences, seeking information, and offering peer-to-peer support among individuals living with mental illness. With significant shortfalls in the availability, quality, and reach of evidence-based mental health services across the United States and globally, social media platforms may afford new opportunities to bridge this gap. However, caution is warranted, as numerous studies highlight risks of social media use for mental health. In this commentary, we consider the role of social media as a potentially viable intervention platform for offering support to persons with mental disorders, promoting engagement and retention in care, and enhancing existing mental health services. Specifically, we summarize current research on the use of social media among mental health service users, and early efforts using social media for the delivery of evidence-based programs. We also review the risks, potential harms, and necessary safety precautions with using social media for mental health. To conclude, we explore opportunities using data science and machine learning, for example by leveraging social media for detecting mental disorders and developing predictive models aimed at characterizing the aetiology and progression of mental disorders. These various efforts using social media, as summarized in this commentary, hold promise for improving the lives of individuals living with mental disorders.

Background: Peer support is recognized globally as an essential recovery service for people with mental health conditions. With the influx of digital mental health services changing the way mental health care is delivered, peer supporters are increasingly using technology to deliver peer support. In light of these technological advances, there is a need to review and synthesize the emergent evidence for peer-supported digital health interventions for adults with mental health conditions. Objective: The aim of this study was to identify and review the evidence of digital peer support interventions for people with a lived experience of a serious mental illness. Methods: This systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedures. The PubMed, Embase, Web of Science, Cochrane Central, CINAHL, and PsycINFO databases were searched for peer-reviewed articles published between 1946 and December 2018 that examined digital peer support interventions for people with a lived experience of a serious mental illness. Additional articles were found by searching the reference lists from the 27 articles that met the inclusion criteria and a Google Scholar search in June 2019. Participants, interventions, comparisons, outcomes, and study design (PICOS) criteria were used to assess study eligibility. Two authors independently screened titles and abstracts, and reviewed all full-text articles meeting the inclusion criteria. Discrepancies were discussed and resolved. All included studies were assessed for methodological quality using the Methodological Quality Rating Scale. Results: Thirty studies (11 randomized controlled trials, 2 quasiexperimental, 15 pre-post designs, and 2 qualitative studies) were included that reported on 24 interventions. Most of the studies demonstrated feasibility, acceptability, and preliminary effectiveness of peer-to-peer networks, peer-delivered interventions supported with technology, and asynchronous and synchronous technologies. Conclusions: Digital peer support interventions appear to be feasible and acceptable, with strong potential for clinical effectiveness. However, the field is in the early stages of development and requires well-powered efficacy and clinical effectiveness trials. Trial Registration: PROSPERO CRD42020139037; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID= 139037

Workforce shortages pose major obstacles to delivering adequate mental health care and scaling up services to address the global treatment gap. Mounting evidence demonstrates the clinical effectiveness of having nonspecialist health workers, such as community health workers, lay health workers, midwives, or nurses, deliver brief psychosocial treatments for common mental disorders in primary care settings. With rapidly increasing access to, and use of, digital technology worldwide, new opportunities are available to leverage these emerging digital technologies to support nonspecialist health workers and increase mental health workforce capacity. This Perspectives article considers the potential that digital technology holds for supporting nonspecialist health workers in delivering evidence-based mental health care. Specifically, from our search of the academic literature, we identified seven promising examples from primary care settings in different low- and middle-income countries (India, Pakistan, Zimbabwe, Peru, China, and Nigeria) where digital platforms are being used to support delivery of mental health care from a variety of nonspecialist providers by offering training, providing digital tools for diagnosis, guiding treatment, facilitating supervision, and integrating services. We summarize these examples and discuss future opportunities to use digital technology for supporting the development of a trained, effective, and sustainable mental health workforce. We also consider the potential to leverage these technologies for integrating mental health care into existing health systems in low-resource settings.

Obesity prevalence is nearly double among individuals with serious mental illness (SMI), including schizophrenia spectrum disorders, bipolar disorder, or major depressive disorder, compared with the general population. Emerging mobile health (m-health) technologies are increasingly available and offer the potential to support lifestyle interventions targeting weight loss, yet the practical feasibility of using these technologies in this high-risk group has not been established. We evaluated the feasibility and acceptability of popular m-health technologies for activity tracking among overweight and obese individuals with SMI. We provided wearable activity monitoring devices (FitBit [San Francisco, CA] Zip™ or Nike Inc. [Beaverton, OR] FuelBand) and smartphones (Apple [Cupertino, CA] iPhone ^® 4S) for accessing the smartphone application for each device to participants with SMI enrolled in a weight loss program. Feasibility of these devices was measured by the frequency of use over time. Acceptability was measured through qualitative follow-up interviews with participants. Ten participants with SMI wore the devices for a mean of 89% (standard deviation=13%) of the days in the study. Five participants wore the devices 100% of the time. Participants reported high satisfaction, stating the devices were easy to use, helpful for setting goals, motivational, and useful for self-monitoring. Several participants liked the social connectivity feature of the devices where they could see each other's progress on the smartphone application, noting that “friendly” competition increased motivation to be more physically active. This study supports using popular m-health technologies for activity tracking among individuals with SMI. These findings can inform the design of weight loss interventions targeting this vulnerable patient population.

Research shows that people with serious mental illness are increasingly using mobile devices. Less is known about how these individuals use their mobile devices or whether they access social media. We surveyed individuals with serious mental illness to explore their use of these technologies. Individuals with serious mental illness engaged in lifestyle interventions through community mental health centers completed a survey about their use of mobile and online technologies. Responses were compared with data from the general population. Among respondents (n = 70), 93% owned cellphones, 78% used text messaging, 50% owned smartphones, and 71% used social media such as Facebook. Most respondents reported daily use of text messaging, mobile apps, and social media. Technology use was comparable to the general population, though smartphone ownership was lower. These findings can inform future interventions that fully leverage this group's use of popular digital technologies. (PsycINFO Database Record