Background Understanding patterns of real-world usage of mental health apps is key to maximizing their potential to increase public self-management of care. Although developer-led studies have published results on the use of mental health apps in real-world settings, no study yet has systematically examined usage patterns of a large sample of mental health apps relying on independently collected data. Objective Our aim is to present real-world objective data on user engagement with popular mental health apps. Methods A systematic engine search was conducted using Google Play to identify Android apps with 10,000 installs or more targeting anxiety, depression, or emotional well-being. Coding of apps included primary incorporated techniques and mental health focus. Behavioral data on real-world usage were obtained from a panel that provides aggregated nonpersonal information on user engagement with mobile apps. Results In total, 93 apps met the inclusion criteria (installs: median 100,000, IQR 90,000). The median percentage of daily active users (open rate) was 4.0% (IQR 4.7%) with a difference between trackers (median 6.3%, IQR 10.2%) and peer-support apps (median 17.0%) versus breathing exercise apps (median 1.6%, IQR 1.6%; all z≥3.42, all P<.001). Among active users, daily minutes of use were significantly higher for mindfulness/meditation (median 21.47, IQR 15.00) and peer support (median 35.08, n=2) apps than for apps incorporating other techniques (tracker, breathing exercise, psychoeducation: medians range 3.53-8.32; all z≥2.11, all P<.05). The medians of app 15-day and 30-day retention rates were 3.9% (IQR 10.3%) and 3.3% (IQR 6.2%), respectively. On day 30, peer support (median 8.9%, n=2), mindfulness/meditation (median 4.7%, IQR 6.2%), and tracker apps (median 6.1%, IQR 20.4%) had significantly higher retention rates than breathing exercise apps (median 0.0%, IQR 0.0%; all z≥2.18, all P≤.04). The pattern of daily use presented a descriptive peak toward the evening for apps incorporating most techniques (tracker, psychoeducation, and peer support) except mindfulness/meditation, which exhibited two peaks (morning and night). Conclusions Although the number of app installs and daily active minutes of use may seem high, only a small portion of users actually used the apps for a long period of time. More studies using different datasets are needed to understand this phenomenon and the ways in which users self-manage their condition in real-world settings.

Recent studies have found a significant association between PTSD and low heart rate variability (HRV), a biomarker of autonomic dysregulation. Research indicates that respiratory sinus arrhythmia (RSA) biofeedback increases HRV while reducing related pathological symptoms. This controlled pilot study compared RSA biofeedback to progressive muscle relaxation (PMR) as adjunctive interventions for 38 persons with PTSD symptoms in a residential treatment facility for a substance use disorder. Both groups were assessed at pre-intervention and 4-week post-intervention. Group x time interactions revealed significantly greater reductions in depressive symptoms and increases in HRV indices for the RSA group. Both groups significantly reduced PTSD and insomnia symptoms and a statistical trend was observed for reduced substance craving for the RSA group. Increases in HRV were significantly associated with PTSD symptom reduction. Overall, these results provide preliminary support for the efficacy of RSA biofeedback in improving physiological and psychological health for individuals with PTSD.

This study tested the efficacy of behavioral treatments for alcohol use disorders (AUD) among men who have sex with men (MSM) and who are at risk for HIV transmission. HIV-negative MSM with current AUD (N = 198) were recruited, offered treatment focused on reducing drinking and HIV risk, and followed during treatment and 12 months posttreatment. Participants (n = 89) accepted treatment and were randomized to either 4 sessions of motivational interviewing (MI) or 12 sessions of combined MI and coping skills training (MI + CBT). Other participants (n = 109) declined treatment but were followed, forming a non-help-seeking group (NHS). MI yielded significantly better drinking outcomes during the 12-week treatment period than MI + CBT, but posttreatment outcomes were equivalent. NHS participants significantly reduced their drinking as well. Service delivery and treatment research implications are discussed.

While numbers and proportions of older adults with behavioral health issues are expected to substantially increase, there is also a widening gap in available services for older adults. Mobile health interventions (mhealth) are a way to address existing barriers to treatment, provide frontline assessment and increase access to services for older adults. Due to perpetuated stereotypes, many assume that older adults do not utilize mobile technology nor will they accept a mHealth intervention. The purpose of this paper is to synthesize contemporary literature from information technology and healthcare regarding: (1) current mobile technology utilization by older adults, particularly in regards to health; (2) factors affecting older adult motivation to engage with mobile technology; and (3) older adult preferences for interacting with mobile technology. Findings reveal that significant proportions of older adults: already utilize mobile technology; are willing to engage in existing mobile interventions for health reasons; and have positive attitudes overall towards mobile technology. Finally, recommendations for optimizing mobile interventions to better suit older adults with behavioral health problems are reviewed.

At the moment, although anxiety apps have the potential to enhance access to mental health care, there is a marked discrepancy between the wealth of commercially available apps, and the paucity of data regarding their efficacy and effectiveness. Although the great promise of apps is their ability to increasing access to evidence-based mental health, the field is not quite there yet and the full potential of apps for treating anxiety has yet to be exploited.