Background: In an oversaturated market of publicly available mobile apps for psychosocial self-care and stress management, health care providers, patients, and consumers interested in mental health–related apps may wonder which, if any, are efficacious. Readily available metrics for consumers include user popularity and media buzz rather than scientific evidence.Objective: This systematic review aimed to (1) examine the breadth of therapeutic contents and features of psychosocial wellness and stress management apps available to self-help seekers for public download and (2) determine which of these apps have original research support.Methods: First, we conducted a systematic review of publicly available apps on the iPhone App Store (Apple Inc) and Android Google Play (Google LLC) platforms using conventional self-help-seeking search terms related to wellness and stress. The results were limited to English-language apps available for free download. In total, 2 reviewers independently evaluated all apps and discussed the findings to reach 100% consensus regarding inclusion. Second, a literature review was conducted on the included apps to identify supporting studies with original data collection.Results: We screened 3287 apps and found 1009 psychosocial wellness and stress management apps. Content varied widely. The most common evidence-based strategy was mindfulness-meditation, followed by positive psychology and goal setting. Most apps were intended to be used as self-help interventions, with only 1.09% (11/1009) involving an electronic therapist and 1.88% (19/1009) designed as a supplement to in-person psychotherapy. Only 4.66% (47/1009) of apps targeted individuals with psychological disorders, and less than 1% of apps (6/1009, 0.59%) targeted individuals with other chronic illnesses. Approximately 2% (21/1009, 2.08%) were supported by original research publications, with a total of 25 efficacy studies and 10 feasibility studies. The Headspace mindfulness app had the most evidence, including 8 efficacy studies. Most other scientifically backed apps were supported by a single feasibility or efficacy study.Conclusions: Only 2.08% (21/1009) of publicly available psychosocial wellness and stress management mobile apps discoverable to self-help seekers have published, peer-reviewed evidence of feasibility and/or efficacy. Clinicians and investigators may use these findings to help patients and families navigate the volume of emerging digital health interventions for stress management and wellness.

Background: Although there are thousands of mental health apps, 2 apps, Headspace and Calm, claim a large percentage of the marketplace. These two mindfulness and meditation apps have reached tens of millions of active users. To guide consumers, clinicians, and researchers, we performed a systematic review of randomized controlled trials (RCTs) of Headspace and Calm. Objective: Our study aimed to evaluate intervention efficacy, risk of bias, and conflicts of interest (COIs) in the evidence base for Headspace and Calm, the two most popular mental health apps at the time of our search. Methods: To identify studies, we searched academic databases (Google Scholar, MEDLINE, and PsycINFO) and the websites of Headspace and Calm in May 2021 for RCTs of Headspace and Calm testing efficacy via original data collection, published in English in peer-reviewed journals. For each study, we coded (1) study characteristics (eg, participants, sample size, and outcome measures), (2) intervention characteristics (eg, free vs paid version of the app and intended frequency of app usage), (3) all study outcomes, (4) Cochrane risk of bias variables, and (5) COI variables (eg, presence or absence of a preregistration and the presence or absence of a COI statement involving the company). Results: We identified 14 RCTs of Headspace and 1 RCT of Calm. Overall, 93% (13/14) of RCTs of Headspace and 100% (1/1) of RCTs of Calm recruited participants from a nonclinical population. Studies commonly measured mindfulness, well-being, stress, depressive symptoms, and anxiety symptoms. Headspace use improved depression in 75% of studies that evaluated it as an outcome. Findings were mixed for mindfulness, well-being, stress, and anxiety, but at least 40% of studies showed improvement for each of these outcomes. Studies were generally underpowered to detect “small” or “medium” effect sizes. Furthermore, 50% (7/14) of RCTs of Headspace and 0% (0/1) of RCTs of Calm reported a COI that involved Headspace or Calm (the companies). The most common COI was the app company providing premium app access for free for participants, and notably, 14% (2/14) of RCTs of Headspace reported Headspace employee involvement in study design, execution, and data analysis. Only 36% (5/14) of RCTs of Headspace were preregistered, and the 1 RCT of Calm was not preregistered. Conclusions: The empirical research on Headspace appears promising, whereas there is an absence of randomized trials on Calm. Limitations of this study include an inability to compare Headspace and Calm owing to the dearth of RCTs studying Calm and the reliance on author reports to evaluate COIs. When determining whether or not mental health apps are of high quality, identification of high-quality apps and evaluation of their effectiveness and investigators’ COIs should be ensured.

Background: An estimated 12.8% of children and adolescents experience chronic health conditions that lead to poor quality of life, adjustment and coping issues, and concurrent mental health problems. Digital health deployment of psychosocial interventions to support youth with chronic illness has become increasingly popular with the advent of the technological advances in the digital age.Objective: Our objectives were to systematically review published efficacy studies of eHealth and mHealth (mobile health) psychosocial interventions for youths with chronic illnesses and review intervention theory and treatment components.Methods: PubMed, Embase, Web of Science, PsycInfo, and Cochrane Database of Systematic Reviews were searched for studies published from 2008 to 2019 of eHealth and mHealth psychosocial interventions designed for children and adolescents with chronic illnesses in which efficacy outcomes were reported. We excluded studies of interventions for caregivers, healthy youth, disease and medication management, and telehealth interventions that function solely as a platform to connect patients to providers via phone, text, or videoconference.Results: We screened 2551 articles and 133 relevant full-text articles. Sixteen efficacy studies with psychosocial and health outcomes representing 12 unique interventions met the inclusion criteria. Of the included studies, 12 were randomized controlled trials and 4 were prospective cohort studies with no comparison group. Most interventions were based in cognitive behavioral theory and designed as eHealth interventions; only 2 were designed as mHealth interventions. All but 2 interventions provided access to support staff via text, phone, email, or discussion forums. The significant heterogeneity in intervention content, intervention structure, medical diagnoses, and outcomes precluded meta-analysis. For example, measurement time points ranged from immediately postcompletion of the mHealth program to 18 months later, and we identified 39 unique outcomes of interest. The majority of included studies (11/16, 69%) reported significant changes in measured health and/or psychosocial posttreatment outcomes, with small to large effect sizes.Conclusions: Although the available literature on the efficacy of eHealth and mHealth psychosocial interventions for youth with chronic illnesses is limited, preliminary research suggests some evidence of positive treatment responses. Future studies should continue to evaluate whether digital health platforms may be a viable alternative model of delivery to traditional face-to-face approaches.

Background: TikTok is a social media mobile application that is widely used by adolescents, and has the potential to serve as a revolutionary platform for public and mental health discourse, education, and intervention. Objective: Our study aimed to describe the content and engagement metrics of the hashtag #teenmentalhealth on TikTok. Methods: In this study, we: (a) conducted a directed content analysis of the Top 100 TikTok videos tagged with #teenmentalhealth, and (b) collected data on video engagements (views, likes, saves, and shares) and computed view-based engagement rates. Results: The videos collectively garnered 144,320,591 views; 28,289,655 likes; 219,780 comments; 1,971,492 saves; and 478,696 shares. Most of the generated content were from teens and therapists. Engagement metrics revealed strong user engagement rates across user types. The most prevalent content categories represented across videos were personal experience, coping techniques or treatment, humor, interpersonal relationships, and health campaign. The content categories with the highest engagement rates were relatable media representation, health campaign, social isolation, and humor. Only a single video incorporated evidence-based treatment content. Conclusion: TikTok facilitates communication and information dissemination on teen mental health. Future research should focus on improving the quality and credibility of digital content while maintaining engagement through creativity, self-expression, and relatability. Use of popular social media platforms and community-engaged research to disseminate evidence-based content may help bridge the translational research gap.

Background: There is a robust market for mobile health (mHealth) apps focused on self-guided interventions to address a high prevalence of mental health disorders and behavioral health needs in the general population. Disseminating mental health interventions via mHealth technologies may help overcome barriers in access to care and has broad consumer appeal. However, development and testing of mental health apps in formal research settings are limited and far outpaced by everyday consumer use. In addition to prioritizing efficacy and effectiveness testing, researchers should examine and test app design elements that impact the user experience, increase engagement, and lead to sustained use over time. Objective: The aim of this study was to evaluate the objective and subjective quality of apps that are successful across both research and consumer sectors, and the relationships between objective app quality, subjective user ratings, and evidence-based behavior change techniques. This will help inform user-centered design considerations for mHealth researchers to maximize design elements and features associated with consumer appeal, engagement, and sustainability. Methods: We conducted a user-centered design analysis of popular consumer apps with scientific backing utilizing the well-validated Mobile Application Rating Scale (MARS). Popular consumer apps with research support were identified via a systematic search of the App Store iOS (Apple Inc) and Google Play (Google LLC) and literature review. We evaluated the quality metrics of 19 mental health apps along 4 MARS subscales, namely, Engagement, Functionality, Aesthetics, and Information Quality. MARS total and subscale scores range from 1 to 5, with higher scores representing better quality. We then extracted user ratings from app download platforms and coded apps for evidence-based treatment components. We calculated Pearson correlation coefficients to identify associations between MARS scores, App Store iOS/Google Play consumer ratings, and number of evidence-based treatment components. Results: The mean MARS score was 3.52 (SD 0.71), consumer rating was 4.22 (SD 0.54), and number of evidence-based treatment components was 2.32 (SD 1.42). Consumer ratings were significantly correlated with the MARS Functionality subscale (r=0.74, P<.001), Aesthetics subscale (r=0.70, P<.01), and total score (r=0.58, P=.01). Number of evidence-based intervention components was not associated with MARS scores (r=0.085, P=.73) or consumer ratings (r=–0.329, P=.16). Conclusions: In our analysis of popular research-supported consumer apps, objective app quality and subjective consumer ratings were generally high. App functionality and aesthetics were highly consistent with consumer appeal, whereas evidence-based components were not. In addition to designing treatments that work, we recommend that researchers prioritize aspects of app design that impact the user experience for engagement and sustainability (eg, ease of use, navigation, visual appeal). This will help translate evidence-based interventions to the competitive consumer app market, thus bridging the gap between research development and real-world implementation.