Massive open online interventions (MOOIs) have the potential to increase the reach, scalability, and affordability of psychological interventions. This article reports on an extension of a proof-of-concept participant-preference smoking-cessation trial conducted in the form of a MOOI. This resource was available in Spanish and English for 30 months, and a total of 292,978 individuals from 168 countries visited the site. This report presents data on the last 18 months of recruitment during which 27,163 participants were screened for eligibility, 8,881 signed consent, and 7,407 completed the baseline survey. Observed quit rates were 39.2%, 43.5%, 45.7%, and 50.3%, respectively, at 1, 3, 6, and 12 months; at the same time intervals, the missing=smoking quit rates were 7.6%, 5.7%, 4.8%, and 5.5%. Results suggest that MOOIs have the potential to provide people worldwide with evidence-based behavioral interventions. The authors conclude that MOOIs should become an integral part of global health efforts.

Subthreshold depression has been found to be associated with considerable impairment and an increased risk of developing major depression. Although several randomized trials have examined the effects of psychological interventions for subthreshold depression in children and adolescents, no meta-analysis has integrated the results of these trials. We searched 4 bibliographic databases and included randomized trials comparing psychological interventions with control conditions in children and adolescents scoring above a cut-off of a depression questionnaire but not meeting diagnostic criteria for major depression (or persistent depressive disorder) according to a diagnostic interview. Effect sizes and incidence rates of major depression were pooled with random effects meta-analyses. A total of 12 trials with 1,576 children and adolescents met inclusion criteria. The overall effect size indicating the difference between treatment and control at post-test was g = 0.38 (95% CI = 0.14-0.63), which corresponds to a number-needed-to-treat (NNT) of 8.4. Heterogeneity was moderate to high (I² = 61; 95% CI = 28-79), and there was significant risk of publication bias (p < .04). The 2 studies in children less than 12 years of age showed nonsignificant effects (g = 0.01; 95% CI = -1.16 to 1.18). We found no significant effect on the incidence of major depression at follow-up (relative risk = 0.52; 95% CI = 0.25-1.08), although this may be related to low statistical power. Interventions for subthreshold depression may have positive acute effects in adolescents. There is currently insufficient evidence, however, that these interventions are effective in children less than 12 years of age, or that they prevent the onset of major depression at follow-up.

Evidence-based psychological interventions are growing in number but are not within reach of many individuals who could benefit from them. The recent revolution in digital technologies now makes it possible to reach people around the globe with digital interventions in the form of web sites, mobile applications, wearable devices, and so on. Although a plethora of digital interventions are available online few are evidence-based and individuals have little guidance to decide among the multitude of options. We propose the development of “digital apothecaries,” that is, online repositories of evidence-based digital interventions. As portals to effective interventions, digital apothecaries would be useful to individuals who could access evidence-based interventions directly, to health care providers, who could identify specific digital tools to suggest to or use with their patients, and to researchers, who could study a range of tools with large samples, enabling comparative tests and evaluation of moderators of effects. We present a taxonomy of types of in-person and digital interventions ranging from traditional therapy without the use of digital tools to totally automated self-help interventions. This taxonomy highlights the potential of blending digital tools into health care systems to expand their reach. Digital apothecaries would provide access to evidence-based digital interventions (both free and paid versions), provide data on effectiveness (including effectiveness for diverse populations), and encourage the development and testing of more such tools. Other issues discussed include: criteria for inclusion of interventions into digital apothecaries; how digital tools could enhance health care for diverse populations; and cautionary notes regarding potential negative unintended consequences of the adoption of digital interventions into the health care system. In particular, we warn about the potential misuse of evidence-based digital interventions to justify reducing access to live providers. Digital apothecaries bring with them the promise of reducing health disparities by reaching large numbers of individuals across the world who need health interventions but are not currently receiving them. The health care field is encouraged to mindfully develop this promise, while being alert not to cause inadvertent harm.

Most individuals at risk for or already experiencing mental disorders have no access to mental health care. Digital mental health interventions (DMHIs) can be effective in preventing and treating mental disorders. A taxonomy of digital interventions was previously proposed to organize the different types of digital tools being developed to expand mental health service delivery. This article updates that framework and presents illustrations for four types of digital interventions specific to mental health and revises their definitions. The illustrations primarily focus on studies that include populations underrepresented in the literature to highlight the potential of DMHIs to reduce health disparities. Provider administered DMHIs (Type 1) and provider administered DMHIs with blended digital adjuncts (Type 2) are offered within a healthcare system. Self-help human supported/guided DMHIs with therapeutic or technical guidance (Type 3) are offered outside a healthcare system. And self-help fully automated DMHIs (Type 4) are interventions similar to self-help books, do not involve human support and are also offered outside a healthcare system. Type 1, 2, and 3 interventions are consumable, they require human time to administer and are limited by the number of hours a health care provider or guide (to promote adherence) is available. Type 4 interventions are non-consumable because these can be used an unlimited number of times anytime anywhere in the world without human interaction. Identifying DMHIs as belonging to one of these categories can promote the development of each category, guide future reviews and help disseminate those DMHIs to as many people as possible.

Most users of unsupported Internet interventions visit that site only once, therefore there is a need to create interventions that can be offered as a single brief interaction with the user. The main goal of this study was to compare the effect of a one-session unsupported Internet intervention on participants' clinical symptoms (depressive and anxiety symptoms) and related variables (mood, confidence and motivation). A total of 765 adults residing in the United States took part in a randomized controlled trial. Participants were randomly assigned to one of five brief plain text interventions lasting 5-10 min. The interventions designed to address depressive symptoms were: thoughts (increasing helpful thoughts), activities (increasing activity level), sleep hygiene, assertiveness (increasing assertiveness awareness), Own Methods (utilizing methods that were previously successful). They were followed-up one week after consenting. A main effect of time was observed for both depression (F(1, 563) = 234.70, p < 0.001) and anxiety (F(1, 551) = 170.27, p < 0.001). In all cases, regardless of assigned condition and Major Depressive Episode status, mean scores on both positive outcomes (mood, confidence and motivation) and negative outcome scores (depression and anxiety) improved over time. Brief unsupported Internet interventions can improve depressive symptoms at one-week follow-up. Further outcome data and research implications will be discussed.