Although impressive progress has been made toward developing empirically-supported psychological treatments, the reality remains that a significant proportion of people with mental health problems do not receive these treatments. Finding ways to reduce this treatment gap is crucial. Since app-supported smartphone interventions are touted as a possible solution, access to up-to-date guidance around the evidence base and clinical utility of these interventions is needed. We conducted a meta-analysis of 66 randomized controlled trials of app-supported smartphone interventions for mental health problems. Smartphone interventions significantly outperformed control conditions in improving depressive (g=0.28, n=54) and generalized anxiety (g=0.30, n=39) symptoms, stress levels (g=0.35, n=27), quality of life (g=0.35, n=43), general psychiatric distress (g=0.40, n=12), social anxiety symptoms (g=0.58, n=6), and positive affect (g=0.44, n=6), with most effects being robust even after adjusting for various possible biasing factors (type of control condition, risk of bias rating). Smartphone interventions conferred no significant benefit over control conditions on panic symptoms (g=-0.05, n=3), post-traumatic stress symptoms (g=0.18, n=4), and negative affect (g=-0.08, n=5). Studies that delivered a cognitive behavior therapy (CBT)-based app and offered professional guidance and reminders to engage produced larger effects on multiple outcomes. Smartphone interventions did not differ significantly from active interventions (face-to-face, computerized treatment), although the number of studies was low (n≤13). The efficacy of app-supported smartphone interventions for common mental health problems was thus confirmed. Although mental health apps are not intended to replace professional clinical services, the present findings highlight the potential of apps to serve as a cost-effective, easily accessible, and low intensity intervention for those who cannot receive standard psychological treatment.

Objective Research investigating the effects of COVID‐19 on eating disorders is growing rapidly. A comprehensive evaluation of this literature is needed to identify key findings and evidence gaps to better inform policy decisions related to the management of eating disorders during and after this crisis. We conducted a systematic scoping review synthesizing and appraising this literature. Method Empirical research on COVID‐19 impacts on eating disorder severity, prevalence, and demand for treatment was searched. No sample restrictions were applied. Findings ( n = 70 studies) were synthesized across six themes: (a) suspected eating disorder cases during COVID‐19; (b) perceived pandemic impacts on symptoms; (c) symptom severity pre versus during the pandemic; (d) pandemic‐related correlates of symptom severity; (e) impacts on carers/parents; and (f) treatment experiences during COVID‐19. Results Pandemic impacts on rates of probable eating disorders, symptom deterioration, and general mental health varied substantially. Symptom escalation and mental health worsening during―and due to―the pandemic were commonly reported, and those most susceptible included confirmed eating disorder cases, at‐risk populations (young women, athletes, parent/carers), and individuals highly anxious or fearful of COVID‐19. Evidence emerged for increased demand for specialist eating disorder services during the pandemic. The forced transition to online treatment was challenging for many, yet telehealth alternatives seemed feasible and effective. Discussion Evidence for COVID‐19 effects is mostly limited to participant self‐report or retrospective recall, cross‐sectional and descriptive studies, and samples of convenience. Several novel pathways for future research that aim to better understand, monitor, and support those negatively affected by the pandemic are formulated.

Objectives: E-mental health (digital) interventions can help overcome existing barriers that stand in the way of people receiving help for an eating disorder (ED). Although e-mental health interventions for treating and preventing EDs have been met with enthusiasm, earlier reviews brought attention to poor quality of evidence, and offered solutions to enhance their evidence base. To assess developments in the field, we conducted an updated meta-analysis on the efficacy of e-mental health interventions for treating and preventing EDs, paying attention to whether trial quality and outcomes have improved in recent trials. We also assessed whether user-centered design principles have been implemented in existing digital interventions. Method: Four databases were searched for RCTs of digital interventions for treating and preventing EDs. Thirty-six RCTs (28 prevention- and 8 treatment-focused) were included. Results: Some evidence that study quality improved in recent prevention-focused trials was found. Few trials involved the end-user in the design or development stage of the intervention. Issues with intervention engagement were noted, and 1 in 4 participants dropped out from prevention- and treatment-focused trials. Digital interventions were more effective than control conditions in reducing established risk factors and symptoms in prevention- (g’s = 0.19 to 0.43) and treatment-focused trials (g’s = 0.29 to 0.69), respectively. Effect sizes have not increased in recent trials. Few trials compared a digital intervention with a face-to-face intervention. Whether digital interventions can prevent ED onset is unclear. Conclusion: Digital interventions are a promising approach to ED treatment and prevention, but improvements are still needed. Three key recommendations are provided.

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Objective The efficacy of cognitive‐behavioral therapy (CBT) for eating disorders is well‐established. The extent to which CBT tested in controlled research settings generalizes to real‐world circumstances is unknown. We conducted a meta‐analysis of nonrandomized studies of CBT for eating disorders, with three aims: (a) to estimate the prevalence of patients who achieve binge‐purge abstinence after CBT in routine practice; (b) to compare these estimates with those derived from two recent meta‐analyses of randomized controlled trials (RCTs) of CBT for bulimia nervosa (BN) and binge‐eating disorder (BED); (c) to examine whether the degree of clinical representativeness of studies was associated with effect sizes. Method Twenty‐seven studies, mainly involving BN, were included. Pooled event rates were calculated using random effects models. Results The percentage of treatment completers who achieved abstinence at post‐treatment was 42.1% (95% CI = 34.7–50.0). The intention‐to‐treat (ITT) estimate was lower (34.6% [95% CI = 29.3–40.4]). However, abstinence rates varied across diagnoses, such that the completer and ITT analysis abstinence estimates were larger for BED samples (completer = 50.2%, 95% CI = 29.4–70.9; ITT = 47.2%, 95% CI = 29.8–65.2) than for BN (completer = 37.4%, 95% CI = 29.1–46.5; ITT = 29.8%, 95% CI = 24.9–35.3) and atypical eating disorder samples (completer = 37.8%, 95% CI = 20.2–59.3; ITT = 28.8%, 95% CI = 18.2–42.4). No relationship between the degree of clinical representativeness and the effect size was observed, and our estimates were highly comparable to those observed in recent meta‐analyses of RCTs. Discussion Findings suggest that CBT for eating disorder can be effectively delivered in real‐world settings. This study provides evidence for the generalizability of CBT from controlled research settings to routine clinical services.