Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: College students are increasingly reporting common mental health problems, such as depression and anxiety, and frequently encounter barriers to seeking traditional mental health treatments. Digital mental health interventions, such as those delivered via the web and apps, offer the potential to improve access to mental health treatment. Objective: This study reviews the literature on digital mental health interventions focused on depression, anxiety, and enhancement of psychological well-being among samples of college students to identify the effectiveness, uptake, and adoption of such programs. Methods: We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, and the search strategy was conducted by a medical research librarian in the following databases: MEDLINE (Ovid), EMBASE (Elsevier), PsycINFO (EbscoHost), the Cochrane Library (Wiley), and Web of Science (Thomson Reuters) databases (from the date of inception to December 2017). Data were synthesized using a systematic narrative synthesis framework and formal quality assessments were conducted to address risk of bias. Results: A total of 65 studies met inclusion criteria. The majority of interventions (n = 51) were delivered via website, and the most common intervention was internet-based cognitive behavioral therapy (iCBT; n = 15). Many programs (n = 27) featured human support in the form of coaching. The majority of studies (n = 35) did not present any usability or acceptability outcomes, and few studies examined broad implementation of digital mental health interventions on college campuses (n = 3). Conclusions: Results suggest that digital mental health interventions can be effective for improving depression, anxiety, and psychological well-being among college students, but more rigorous studies are needed to ascertain the effective elements of these interventions. Continued research on improving the user experience of, and thus user engagement with, these programs appears vital for the sustainable implementation of digital mental health on college campuses.

U.S. health care systems are tasked with alleviating the burden of mental health, but are frequently underprepared and lack workforce and resource capacity to deliver services to all in need. Digital mental health interventions (DMHIs) can increase access to evidence-based mental health care. However, DMHIs commonly do not fit into the day-to-day activities of the people who engage with them, resulting in a research-to-practice gap for DMHI implementation. For health care settings, differences between digital and traditional mental health services make alignment and integration challenging. Specialized attention is needed to improve the implementation of DMHIs in health care settings so that these services yield high uptake, engagement, and sustainment. The purpose of this article is to enhance efforts to integrate DMHIs in health care settings by proposing implementation strategies, selected and operationalized based on the discrete strategies established in the Expert Recommendations for Implementing Change project, that align to DMHI-specific barriers in these settings. Guidance is offered in how these strategies can be applied to DMHI implementation across four phases commonly distinguished in implementation science using the Exploration, Preparation, Implementation, Sustainment Framework. Next steps to advance research in this area and improve the research-to-practice gap for implementing DMHIs are recommended. Applying implementation strategies to DMHI implementation will enable psychologists to systematically evaluate this process, which can yield an enhanced understanding of the factors that facilitate implementation success and improve the translation of DMHIs from controlled trials to real-world settings. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The unprecedented COVID‐19 crisis presents an imperative for mental health care systems to make digital mental health interventions a routine part of care. Already because of COVID‐19, many therapists have rapidly moved to using telehealth in place of in‐person contact. In response to this shift, Waller and colleagues compiled a series of expert recommendations to help clinicians pivot to delivering teletherapy to address eating disorders during COVID‐19. However, numerous barriers still impede widespread adoption and implementation of digital interventions. In this commentary, we aim to extend the recommendations for clinicians offered by Waller and colleagues by presenting a roadmap of the systems‐ and policy‐level requirements that are needed. We advocate for addressing barriers associated with training, licensing, safety, privacy, payment, and evaluation, as these factors have greatly limited use of these promising interventions. We also indicate that longer‐term goals should include introducing truly innovative digital mental health practices, such as stepped‐care models and simultaneously providing preventive and self‐management services in addition to clinical services, into the health care system. Now is the time to catalyze change and comprehensively address the barriers that have prevented widespread delivery of these efficacious digital services to the millions of people who would benefit.

Background: User engagement is key to the effectiveness of digital mental health interventions. Considerable research has examined the clinical outcomes of overall engagement with mental health apps (eg, frequency and duration of app use). However, few studies have examined how specific app use behaviors can drive change in outcomes. Understanding the clinical outcomes of more nuanced app use could inform the design of mental health apps that are more clinically effective to users. Objective: This study aimed to classify user behaviors in a suite of mental health apps and examine how different types of app use are related to depression and anxiety outcomes. We also compare the clinical outcomes of specific types of app use with those of generic app use (ie, intensity and duration of app use) to understand what aspects of app use may drive symptom improvement. Methods: We conducted a secondary analysis of system use data from an 8-week randomized trial of a suite of 13 mental health apps. We categorized app use behaviors through a mixed methods analysis combining qualitative content analysis and principal component analysis. Regression analyses were used to assess the association between app use and levels of depression and anxiety at the end of treatment. Results: A total of 3 distinct clusters of app use behaviors were identified: learning, goal setting, and self-tracking. Each specific behavior had varied effects on outcomes. Participants who engaged in self-tracking experienced reduced depression symptoms, and those who engaged with learning and goal setting at a moderate level (ie, not too much or not too little) also had an improvement in depression. Notably, the combination of these 3 types of behaviors, what we termed “clinically meaningful use,” accounted for roughly the same amount of variance as explained by the overall intensity of app use (ie, total number of app use sessions). This suggests that our categorization of app use behaviors succeeded in capturing app use associated with better outcomes. However, anxiety outcomes were neither associated with specific behaviors nor generic app use. Conclusions: This study presents the first granular examination of user interactions with mental health apps and their effects on mental health outcomes. It has important implications for the design of mobile health interventions that aim to achieve greater user engagement and improved clinical efficacy.

This Viewpoint discusses the integration of user-centered design methods to improve engagement with digital mental health services and adaptation of the Nationa