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Over the last decades, ambulatory psychosocial interventions aimed at treating child externalized behavior problems have been developed and tested. In recent years, however, it has become clear that the reported effects of psychotherapies have been considerably overestimated due to publication bias. In addition, previous meta-analyses of psychosocial interventions aimed at treating child disruptive behaviors have not accounted for potential interaction effects among moderators. The purpose of this meta-analysis was to examine the effects of interventions while accounting for publication bias and dependencies among moderators. We searched electronic databases to identify randomized controlled trials targeting child externalized behavior problems treated in ambulatory settings. A total of 111 randomized controlled trials with 11,623 participating children were analyzed. Interventions targeting children with symptom severity below the clinical range demonstrated a non-significant effect (adjusted g = 0.12), while interventions targeting children with symptom severity within the clinical range demonstrated a small to moderate effect size (adjusted g = 0.38) that was sustained at follow-up (adjusted g = 0.27). We found the highest pooled effect size for individually administered treatments involving both the parent and the child (g = 1.11; no indication of publication bias). No other differences were found between delivery formats, including assisted self-help interventions. Publication bias was relatively smaller in high-quality studies. These findings suggest that the most effective treatment regime involves both the parent and the child, however, only when they are treated in an individual setting. Our results highlight the importance of accounting for interaction effects, publication bias and trial quality in future meta-analyses.

BACKGROUND Digital health interventions (DHIs) are efficacious for several mental disorders in youth; however, integrated, evidence-based knowledge about the mechanisms of change in these interventions is lacking. OBJECTIVE This systematic review aims to comprehensively evaluate studies on mediators and mechanisms of change in different DHIs for common mental disorders in children and adolescents. METHODS A systematic literature search of the electronic databases Cochrane Central Register of Controlled Trials, Embase, MEDLINE, and PsycINFO was conducted, complemented by backward and forward searches. Two independent reviewers selected studies for inclusion, extracted the data, and rated the methodological quality of eligible studies (ie, risk of bias and 8 quality criteria for process research). RESULTS A total of 25 studies that have evaluated 39 potential mediators were included in this review. Cognitive mediators were the largest group of examined intervening variables, followed by a broad range of emotional and affective, interpersonal, parenting behavior, and other mediators. The mediator categories with the highest percentages of significant intervening variables were the groups of affective mediators (4/4, 100%) and combined cognitive mediators (13/19, 68%). Although more than three-quarters of the eligible studies met 5 or more quality criteria, causal conclusions have been widely precluded. CONCLUSIONS The findings of this review might guide the empirically informed advancement of DHIs, contributing to improved intervention outcomes, and the discussion of methodological recommendations for process research might facilitate mediation studies with more pertinent designs, allowing for conclusions with higher causal certainty in the future.

While the efficacy of Internet- and mobile-based interventions (IMIs) for treating anxiety disorders is well established, there is no comprehensive overview about the underlying therapeutic processes so far. Thus, this systematic review and meta-analysis evaluated research on mediators and mechanisms of change in IMIs for adult anxiety disorders (PROSPERO: CRD42020185545). A systematic literature search was performed in five databases (i.e., CENTRAL, Embase, MEDLINE, PsycINFO and ClinicalTrials.gov). Two reviewers independently screened studies for inclusion, assessed the risk of bias and adherence to quality criteria for process research. Overall, 26 studies (N=6042) investigating 64 mediators were included. Samples consisted predominantly of participants with clinically relevant symptoms of generalized anxiety disorder and severe health anxiety, as well as of participants with non-clinically relevant anxiety symptoms. The largest group of examined mediators (45%) were cognitive variables, evincing also the second highest proportion of significance (19/29); followed in numbers by skills (examined: 22%; significant: 10/14) and a wide range of other (19%; 7/12), emotional/affective (11%; 2/7) and behavioral mediators (3%; 1/2). Meta-analytical synthesis of mediators, limited by a small number of eligible studies, was conducted by deploying a two-stage structural equation modeling approach, resulting in a significant indirect effect for negative thinking (k=3 studies) and non-significant indirect effects for combined cognitive variables, both in clinical (k=5) and non-clinical samples (k=3). The findings of this review might further the understanding on presumed change mechanisms in IMIs for anxiety, informing intervention development and the concurrent optimization of outcomes. Furthermore, by reviewing eligible mediation studies, we discuss methodological implications and recommendations for future process research, striving for causally robust findings. Future studies should investigate a broader range of variables as potential mediators, as well as to develop and apply original (digital) process and engagement measures to gather qualitative and high-resolution data on therapeutic processes. Copyright © 2021 Elsevier Ltd. All rights reserved.

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The classic Marshmallow Test, where children were offered a choice between one small but immediate reward (eg, one marshmallow) or a larger reward (eg, two marshmallows) if they waited for a period of time, instigated a wealth of research on the relationships among impulsive responding, self-regulation, and clinical and life outcomes. Impulsivity is a hallmark feature of self-regulation failures that lead to poor health decisions and outcomes, making understanding and treating impulsivity one of the most important constructs to tackle in building a culture of health. Despite a large literature base, impulsivity measurement remains difficult due to the multidimensional nature of the construct and limited methods of assessment in daily life. Mobile devices and the rise of mobile health (mHealth) have changed our ability to assess and intervene with individuals remotely, providing an avenue for ambulatory diagnostic testing and interventions. Longitudinal studies with mobile devices can further help to understand impulsive behaviors and variation in state impulsivity in daily life.The aim of this study was to develop and validate an impulsivity mHealth diagnostics and monitoring app called Digital Marshmallow Test (DMT) using both the Apple and Android platforms for widespread dissemination to researchers, clinicians, and the general public.The DMT app was developed using Apple's ResearchKit (iOS) and Android's ResearchStack open source frameworks for developing health research study apps. The DMT app consists of three main modules: self-report, ecological momentary assessment, and active behavioral and cognitive tasks. We conducted a study with a 21-day assessment period (N=116 participants) to validate the novel measures of the DMT app.We used a semantic differential scale to develop self-report trait and momentary state measures of impulsivity as part of the DMT app. We identified three state factors (inefficient, thrill seeking, and intentional) that correlated highly with established measures of impulsivity. We further leveraged momentary semantic differential questions to examine intraindividual variability, the effect of daily life, and the contextual effect of mood on state impulsivity and daily impulsive behaviors. Our results indicated validation of the self-report sematic differential and related results, and of the mobile behavioral tasks, including the Balloon Analogue Risk Task and Go-No-Go task, with relatively low validity of the mobile Delay Discounting task. We discuss the design implications of these results to mHealth research.This study demonstrates the potential for assessing different facets of trait and state impulsivity during everyday life and in clinical settings using the DMT mobile app. The DMT app can be further used to enhance our understanding of the individual facets that underlie impulsive behaviors, as well as providing a promising avenue for digital interventions.ClinicalTrials.gov NCT03006653; https://www.clinicaltrials.gov/ct2/show/NCT03006653.

BACKGROUND The classic Marshmallow Test, where children were offered a choice between one small but immediate reward (eg, one marshmallow) or a larger reward (eg, two marshmallows) if they waited for a period of time, instigated a wealth of research on the relationships among impulsive responding, self-regulation, and clinical and life outcomes. Impulsivity is a hallmark feature of self-regulation failures that lead to poor health decisions and outcomes, making understanding and treating impulsivity one of the most important constructs to tackle in building a culture of health. Despite a large literature base, impulsivity measurement remains difficult due to the multidimensional nature of the construct and limited methods of assessment in daily life. Mobile devices and the rise of mobile health (mHealth) have changed our ability to assess and intervene with individuals remotely, providing an avenue for ambulatory diagnostic testing and interventions. Longitudinal studies with mobile devices can further help to understand impulsive behaviors and variation in state impulsivity in daily life. OBJECTIVE The aim of this study was to develop and validate an impulsivity mHealth diagnostics and monitoring app called Digital Marshmallow Test (DMT) using both the Apple and Android platforms for widespread dissemination to researchers, clinicians, and the general public. METHODS The DMT app was developed using Apple’s ResearchKit (iOS) and Android’s ResearchStack open source frameworks for developing health research study apps. The DMT app consists of three main modules: self-report, ecological momentary assessment, and active behavioral and cognitive tasks. We conducted a study with a 21-day assessment period (N=116 participants) to validate the novel measures of the DMT app. RESULTS We used a semantic differential scale to develop self-report trait and momentary state measures of impulsivity as part of the DMT app. We identified three state factors (inefficient, thrill seeking, and intentional) that correlated highly with established measures of impulsivity. We further leveraged momentary semantic differential questions to examine intraindividual variability, the effect of daily life, and the contextual effect of mood on state impulsivity and daily impulsive behaviors. Our results indicated validation of the self-report sematic differential and related results, and of the mobile behavioral tasks, including the Balloon Analogue Risk Task and Go-No-Go task, with relatively low validity of the mobile Delay Discounting task. We discuss the design implications of these results to mHealth research. CONCLUSIONS This study demonstrates the potential for assessing different facets of trait and state impulsivity during everyday life and in clinical settings using the DMT mobile app. The DMT app can be further used to enhance our understanding of the individual facets that underlie impulsive behaviors, as well as providing a promising avenue for digital interventions. CLINICALTRIAL ClinicalTrials.gov NCT03006653; https://www.clinicaltrials.gov/ct2/show/NCT03006653

UNSTRUCTURED The majority of digital health interventions lean on the promise of bringing health and self-care into people’s homes and hands. However, these interventions are delivered while people are in their triggering environments, which places competing demands on their attention. Individuals struggling to change or learn a new behavior have to work hard to achieve even a minor change because of the automatic forces propelling them back to their habitual behaviors. We posit that effort and burden should be explored at the outset and throughout the digital intervention development process as a core therapeutic mechanism, beyond the context of design or user experience testing. In effort-focused conceptualization, it is assumed that, even though goals are rational and people want to achieve them, they are overtaken by competing cognitive, emotional, and environmental processes. We offer the term effort-optimized intervention to describe interventions that focus on user engagement in the face of competing demands. We describe design components based on a 3-step process for planning an effort-optimized intervention: (1) nurturing effortless cognitive and environmental salience to help people keep effort-related goals prominent despite competition; (2) making it as effortless as possible to complete therapeutic activities to avoid ego depletion and self-efficacy reduction; and (3) turning the necessary effortful activities into sustainable assets. We conclude by presenting an example of designing a digital health intervention based on the effort-optimized intervention model.

Although many people access publicly available digital behavioral and mental health interventions, most do not invest as much effort in these interventions as hoped or intended by intervention developers, and ongoing engagement is often low. Thus, the impact of such interventions is minimized by a misalignment between intervention design and user behavior. Digital micro interventions are highly focused interventions delivered in the context of a person’s daily life with little burden on the individual. We propose that these interventions have the potential to disruptively expand the reach of beneficial therapeutics by lowering the bar for entry to an intervention and the effort needed for purposeful engagement. This paper provides a conceptualization of digital micro interventions, their component parts, and principles guiding their use as building blocks of a larger therapeutic process (ie, digital micro intervention care). The model represented provides a structure that could improve the design, delivery, and research on digital micro interventions and ultimately improve behavioral and mental health care and care delivery.

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UNSTRUCTURED Although many people access publicly available digital behavioral and mental health interventions, most do not invest as much effort in these interventions as hoped or intended by intervention developers, and ongoing engagement is often low. Thus, the impact of such interventions is minimized by a misalignment between intervention design and user behavior. Digital micro interventions are highly focused interventions delivered in the context of a person’s daily life with little burden on the individual. We propose that these interventions have the potential to disruptively expand the reach of beneficial therapeutics by lowering the bar for entry to an intervention and the effort needed for purposeful engagement. This paper provides a conceptualization of digital micro interventions, their component parts, and principles guiding their use as building blocks of a larger therapeutic process (ie, digital micro intervention care). The model represented provides a structure that could improve the design, delivery, and research on digital micro interventions and ultimately improve behavioral and mental health care and care delivery.

Background Recent studies have utilized available online data to examine the impact of depression- and anxiety-related apps that incorporate evidence-based techniques; however, the impact of apps incorporating non-evidence-based techniques is unknown. Understanding this impact is important in order to assess the potential benefits or harm from their use. Methods We systematically reviewed apps incorporating relevant techniques aimed at depression- and anxiety-related conditions, found through Google Play search. We conducted quantitative and qualitative analyses of user reviews, and analyzed app usage utilizing an independent user panel. Results Compared to apps incorporating evidence-based techniques (n = 14), user ratings of apps classified as non-evidence-based (n = 27) were lower (4.0 versus 4.5, p=.001, η2=0.24) and a smaller percentage of users found these apps to be beneficial for mental health (76.2% versus 100%, p=.003, η2=0.23). Users found apps incorporating non-evidence-based techniques to be mostly helpful in providing in-the-moment relief; however, some users described these apps as containing content that could be harmful for a person in such a mental state. Limitations The data do not enable the differentiation of user experiences based on user groups (e.g. according to the severity of symptoms), which should be examined in future studies. Conclusions This study indicates that depression and anxiety apps incorporating non-evidence-based techniques are viewed less favorably and have more potential to cause harm. However, many users found them helpful mostly in providing in-the-moment relief. Examining user experiences with these apps is an important way to learn about unmet user needs and potential benefits or harm.

Triple P Online (i.e., TPOL; www2.tripleponline.net ) is an online self-help parent training program aimed at reducing child behavior problems through “positive parenting practices”—available at time of review for $79.95. TPOL is comprised of 8 video-based modules that also incorporate in-session activities and homework. Randomized control trials have shown that TPOL effectively reduces child behavior problems. The program’s main strengths include very high-quality content with an abundance of relevant and easily locatable resources, an easy-to-use interface, and a professional look and feel. The program’s main weakness lies in its lack of monitoring and adaptation to the user’s state (e.g., child’s and parent’s behaviors), and real-time reminders for desired actions. Altogether, TPOL is an extremely valuable and important resource for families seeking evidence-based treatment for child behavior problems.

Existing frameworks have identified a range of intervention design features that may facilitate adherence to eHealth interventions; however, empirical data are lacking on whether intervention design features can predict user adherence in the real world-where the public access available tools-and whether some design aspects of behavioral eHealth interventions are more important than others in predicting adherence. This study examined whether intervention design qualities predict user adherence to behavioral eHealth interventions in real-world use and which qualities matter the most. We correlated the online activities of users of 30 web-based behavioral interventions-collected from a proprietary data set of anonymized logs from consenting users of Microsoft Internet Explorer add-on-with interventions' quality ratings obtained by trained raters prior to empirical examination. The quality ratings included: Usability, Visual Design, User Engagement, Content, Therapeutic Persuasiveness (i.e., persuasive design and incorporation of behavior change techniques), and Therapeutic Alliance. We found Therapeutic Persuasiveness (i.e., the incorporation of persuasive design/behavior change principles) to be the most robust predictor of adherence (i.e., duration of use, number of unique sessions; 40 ≤ rs ≤ .58, ps ≤ .005), explaining 42% of the variance in user adherence in our regression model. Results indicated up to six times difference in the percentage of users utilizing the interventions for more than a minimum amount of time and sessions based on Therapeutic Persuasiveness. Findings suggest the importance of persuasive design and behavior change techniques incorporation during the design and evaluation of digital behavioral interventions.

Background Digital health interventions (DHIs) are efficacious for several mental disorders in youth; however, integrated, evidence-based knowledge about the mechanisms of change in these interventions is lacking. Objective This systematic review aims to comprehensively evaluate studies on mediators and mechanisms of change in different DHIs for common mental disorders in children and adolescents. Methods A systematic literature search of the electronic databases Cochrane Central Register of Controlled Trials, Embase, MEDLINE, and PsycINFO was conducted, complemented by backward and forward searches. Two independent reviewers selected studies for inclusion, extracted the data, and rated the methodological quality of eligible studies (ie, risk of bias and 8 quality criteria for process research). Results A total of 25 studies that have evaluated 39 potential mediators were included in this review. Cognitive mediators were the largest group of examined intervening variables, followed by a broad range of emotional and affective, interpersonal, parenting behavior, and other mediators. The mediator categories with the highest percentages of significant intervening variables were the groups of affective mediators (4/4, 100%) and combined cognitive mediators (13/19, 68%). Although more than three-quarters of the eligible studies met 5 or more quality criteria, causal conclusions have been widely precluded. Conclusions The findings of this review might guide the empirically informed advancement of DHIs, contributing to improved intervention outcomes, and the discussion of methodological recommendations for process research might facilitate mediation studies with more pertinent designs, allowing for conclusions with higher causal certainty in the future.

Over the years, evidence-based treatments for children with disruptive behavior disorders (DBDs; e.g., conduct disorder, oppositional defiant disorder) have been developed, however, there is not much information about the treatment children receive in usual mental healthcare settings. This study examined the common treatment provided in US ambulatory mental health clinics to children aged 3 to 9 years who are diagnosed with DBDs. An online survey was filled by appropriate respondents from 145 ambulatory mental health centers across 33 states within the US. The most common treatment provided for childhood DBDs was a combination of child therapy (CT) and parent training (PT) (n = 81, 56%), followed by family therapy (n = 42, 29%), CT (n = 17, 12%), and PT (n = 5, 3%). Behavioral and cognitive principles were reported as the most common treatment orientations across all types of treatment (n = 116/145, 80%). The mean number of sessions administered was 31.38 ± 22.72, and PT as a standalone treatment required approximately a third of sessions (10.6 ± 1.34). In treatments combining CT and PT, the utilization of specific parenting programs was associated with fewer administered sessions. Results suggest that the importance of parental involvement in treating DBDs is acknowledged in routine practice. However, more studies are needed to determine why certain types and orientations of treatments are favored over others.

OBJECTIVE To systematically review digitally assisted parent training programs (DPTs) targeting the treatment of children and adolescents with disruptive behaviors. DATA SOURCES A search was conducted using PubMed, PsycINFO, and EMBASE databases for peer-reviewed studies published between January 1, 2000, and March 1, 2016. Reference lists of included and review articles were searched manually for additional references. STUDY SELECTION Broad search terms in varying combinations for parent, training, technologies, and disruptive behavior problems were used. We included English-language articles reporting on the effectiveness of DPTs targeting child or adolescent disruptive behaviors (eg, conduct disorder, oppositional defiant disorder). DPTs designed to use digital media or software programs not to be primarily used within a therapy setting (eg, group, face-to-face) were included. DATA EXTRACTION Study design, recruitment and sample characteristics, theoretical background, digital program features, user's engagement, and measures of child behavior were extracted. RESULTS Fourteen intervention studies (n = 2,427, 58% male, 1,500 in DPT conditions, 12 randomized trials) examining 10 programs met inclusion criteria. Interventions included self-directed noninteractive (eg, podcasts; 3 studies) and interactive (eg, online software; 4 studies) DPTs, remotely administered DPTs combined with professional phone-based coaching (2 studies), and a smartphone enhancement of standard treatment. Interventions were delivered over a mean ± SD period of 8.7 ± 4.2 weeks, most (11/14; 78.6%) were remotely administered, and all recruitment procedures included an outreach for parents outside of mental health-care settings. For programs with > 5 sessions, the mean ± SD completion rate of available sessions was 68.6% ± 13.1%. In comparison to no treatment control, self-directed programs yielded significant improvements in child behavior for children (age < 9 years, Cohen d = 0.47-0.80, 4 studies) and adolescents (d = 0.17, 0.20, 2 studies). Overall, reduced professional support combined with DPT was not inferior to full-contact conditions and showed small improvement in comparison to usual care (d = 0.34). Preliminary indicators also suggested that technology enhancements may increase engagement and outcomes of standard treatment. CONCLUSIONS The current review indicates the efficacy of DPT across a range of therapy formats applied in real-world settings demonstrating the potential for increased accessibility of evidence-based treatment for youth with disruptive behaviors. Additional studies are needed to extend these findings and to determine moderating effects of different designs.

This study investigated attachment styles as contributors to dispositional envy and to the negative emotions being elicited when an individual confronts a deficiency-context situation. A total of 124 undergraduates completed self-report assessments of their attachment orientation, self-esteem, tendency towards social comparison and dispositional envy. Participants also underwent a procedure of contextual deficiency priming in which negative feelings towards the self and the other were measured. Results pointed to the contribution of attachment dimensions over and above the contribution of social comparison and self-esteem in explaining the variance of dispositional envy, negative feelings towards the self and the other. The study’s results suggest how to approach insecurely attached clients who harbour envy.

Trial settings that include proactive recruitment, human contact, and assessment procedures may substantially impact the way users engage with unguided e-mental health programs and the generalizability of reported findings. This study examined the impact of trial setting on user behavior by directly comparing reported user engagement in trial-based research and objective measures of real-world usage of the same unguided mental health programs. The authors conducted a systematic search for papers reporting user engagement with off-the-shelf unguided e-mental health programs. Real-world usage was obtained from a panel that presents aggregated nonpersonal information on user engagement with digital programs across the world. A total of 13 papers yielding 14 comparable usage metrics met all inclusion criteria. In three papers reporting the use of programs by lay users without any proactive trial procedures, the ratios calculated by dividing the usage reported in the paper by the usage documented within the objective dataset were 0.84, 1.05, and 1.27—suggesting a sufficient criterion validity for our examination. In studies that proactively recruited users and included pre- to post-assessment procedures (11 comparisons), the median program usage rate reported was 4.06 times higher (IQR = 4.49) than the real-world usage of the same program. Severity of clinical symptoms, in-person versus remote assessment procedures, study design, and program cost had no impact on these differences. The results suggest that trial settings have a large impact on user engagement with unguided interventions and, therefore, on the generalizability of the findings to the real world.

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 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.

At a time, in which people are more and more suffering from lifestyle-related diseases such as cardiovascular diseases, diabetes, or obesity, changing health behavior and preserving a healthy lifestyle are salient factors of any public health effort. Hence, research on predictors and pathways of health behavior change is increasingly important. Following this, new ways of implementing behavior change interventions become possible based on internet technologies, allowing for technological approaches fostering behavior change. Such union of media informatics and psychology is denoted as persuasive design and refers to all technological intervention components, which help people to take, regularly use and re-take (after relapses into unwanted behavior) interventions. Along this trend, the present chapter introduces (1) theories of health behavior change and summarizes (2) present persuasive design approaches, thereby ending with (3) future directions in the field.

The majority of digital health interventions lean on the promise of bringing health and self-care into people’s homes and hands. However, these interventions are delivered while people are in their triggering environments, which places competing demands on their attention. Individuals struggling to change or learn a new behavior have to work hard to achieve even a minor change because of the automatic forces propelling them back to their habitual behaviors. We posit that effort and burden should be explored at the outset and throughout the digital intervention development process as a core therapeutic mechanism, beyond the context of design or user experience testing. In effort-focused conceptualization, it is assumed that, even though goals are rational and people want to achieve them, they are overtaken by competing cognitive, emotional, and environmental processes. We offer the term effort-optimized intervention to describe interventions that focus on user engagement in the face of competing demands. We describe design components based on a 3-step process for planning an effort-optimized intervention: (1) nurturing effortless cognitive and environmental salience to help people keep effort-related goals prominent despite competition; (2) making it as effortless as possible to complete therapeutic activities to avoid ego depletion and self-efficacy reduction; and (3) turning the necessary effortful activities into sustainable assets. We conclude by presenting an example of designing a digital health intervention based on the effort-optimized intervention model.

Background The classic Marshmallow Test, where children were offered a choice between one small but immediate reward (eg, one marshmallow) or a larger reward (eg, two marshmallows) if they waited for a period of time, instigated a wealth of research on the relationships among impulsive responding, self-regulation, and clinical and life outcomes. Impulsivity is a hallmark feature of self-regulation failures that lead to poor health decisions and outcomes, making understanding and treating impulsivity one of the most important constructs to tackle in building a culture of health. Despite a large literature base, impulsivity measurement remains difficult due to the multidimensional nature of the construct and limited methods of assessment in daily life. Mobile devices and the rise of mobile health (mHealth) have changed our ability to assess and intervene with individuals remotely, providing an avenue for ambulatory diagnostic testing and interventions. Longitudinal studies with mobile devices can further help to understand impulsive behaviors and variation in state impulsivity in daily life. Objective The aim of this study was to develop and validate an impulsivity mHealth diagnostics and monitoring app called Digital Marshmallow Test (DMT) using both the Apple and Android platforms for widespread dissemination to researchers, clinicians, and the general public. Methods The DMT app was developed using Apple’s ResearchKit (iOS) and Android’s ResearchStack open source frameworks for developing health research study apps. The DMT app consists of three main modules: self-report, ecological momentary assessment, and active behavioral and cognitive tasks. We conducted a study with a 21-day assessment period (N=116 participants) to validate the novel measures of the DMT app. Results We used a semantic differential scale to develop self-report trait and momentary state measures of impulsivity as part of the DMT app. We identified three state factors (inefficient, thrill seeking, and intentional) that correlated highly with established measures of impulsivity. We further leveraged momentary semantic differential questions to examine intraindividual variability, the effect of daily life, and the contextual effect of mood on state impulsivity and daily impulsive behaviors. Our results indicated validation of the self-report sematic differential and related results, and of the mobile behavioral tasks, including the Balloon Analogue Risk Task and Go-No-Go task, with relatively low validity of the mobile Delay Discounting task. We discuss the design implications of these results to mHealth research. Conclusions This study demonstrates the potential for assessing different facets of trait and state impulsivity during everyday life and in clinical settings using the DMT mobile app. The DMT app can be further used to enhance our understanding of the individual facets that underlie impulsive behaviors, as well as providing a promising avenue for digital interventions. Trial Registration ClinicalTrials.gov NCT03006653; https://www.clinicaltrials.gov/ct2/show/NCT03006653

Digital-based parent training (DPT) programs for parents of children with disruptive behaviors have been developed and tested in randomized trials. The aim of this study was to quantitatively assess the efficacy of these programs versus a control condition.We conducted a systematic review and random effects meta-analysis of peer-reviewed randomized studies comparing DPT targeting children with disruptive behaviors versus a control group (wait list or no treatment).Altogether, seven studies (n = 718) were meta-analyzed. Compared to the control groups, DPT resulted in significantly greater improvement in child behavior (effect size [ES] = 0.44, 95% confidence interval [CI] = 0.21-0.66, studies = 7), parent behavior (ES = 0.41, 95% CI = 0.25-0.57, studies = 6), and parental confidence (ES = 0.36, 95% CI = 0.12-0.59, studies = 4). The improvement in child behavior was moderated by age group and severity of clinical presentation, which overlapped 100%. While DPT was superior to control conditions in studies of young children (mean age7 years) with a clinical range of disruptive behaviors (ES = 0.61, 95% CI = 0.40-0.82, studies = 4), results were nonsignificant in studies of older children (mean age11 years) with a nonclinical range of symptoms (ES = 0.21, 95% CI = -0.01 to 0.42, studies = 3). Analyses yielded similar results of higher ESs favoring studies of young children with clinical range disruptive behaviors for parent behavior and parental confidence, but the differences were not significant. Results further suggested that in studies of younger children, interactive programs (e.g., computerized programs) were more effective in improving child behavior compared to noninteractive programs (e.g., watching video clips) (p 0.05).Although additional studies are needed, DPT holds promise as a potentially scalable evidence-based treatment of children with disruptive behaviors that can save human resources.

BACKGROUND The literature suggests that the product design of self-guided electronic health (eHealth) interventions impacts user engagement. Traditional trial settings, however, do not enable the examination of these relationships in real-world use. OBJECTIVE This study aimed to examine whether the qualities of product design, research evidence, and publicly available data predict real-world user engagement with mobile and Web-based self-guided eHealth interventions. METHODS This analysis included self-guided mobile and Web-based eHealth interventions available to the public-with their qualities assessed using the Enlight suite of scales. Scales included Usability, Visual Design, User Engagement, Content, Therapeutic Persuasiveness, Therapeutic Alliance, Credibility, and Research Evidence. Behavioral data on real-world usage were obtained from a panel that provides aggregated nonpersonal information on user engagement with websites and mobile apps, based on a time window of 18 months that was set between November 1, 2016 and April 30, 2018. Real-world user engagement variables included average usage time (for both mobile apps and websites) and mobile app user retention 30 days after download. RESULTS The analysis included 52 mobile apps (downloads median 38,600; interquartile range [IQR] 116,000) and 32 websites (monthly unique visitors median 5689; IQR 30,038). Results point to moderate correlations between Therapeutic Persuasiveness, Therapeutic Alliance, and the 3 user engagement variables (.31≤rs≤.51; Ps≤.03). Visual Design, User Engagement, and Content demonstrated similar degrees of correlation with mobile app engagement variables (.25≤rs≤.49; Ps≤.04) but not with average usage time of Web-based interventions. Positive correlations were also found between the number of reviews on Google Play and average app usage time (r=.58; P

BACKGROUND The literature suggests that the product design of self-guided electronic health (eHealth) interventions impacts user engagement. Traditional trial settings, however, do not enable the examination of these relationships in real-world use. OBJECTIVE This study aimed to examine whether the qualities of product design, research evidence, and publicly available data predict real-world user engagement with mobile and Web-based self-guided eHealth interventions. METHODS This analysis included self-guided mobile and Web-based eHealth interventions available to the public—with their qualities assessed using the Enlight suite of scales. Scales included Usability, Visual Design, User Engagement, Content, Therapeutic Persuasiveness, Therapeutic Alliance, Credibility, and Research Evidence. Behavioral data on real-world usage were obtained from a panel that provides aggregated nonpersonal information on user engagement with websites and mobile apps, based on a time window of 18 months that was set between November 1, 2016 and April 30, 2018. Real-world user engagement variables included average usage time (for both mobile apps and websites) and mobile app user retention 30 days after download. RESULTS The analysis included 52 mobile apps (downloads median 38,600; interquartile range [IQR] 116,000) and 32 websites (monthly unique visitors median 5689; IQR 30,038). Results point to moderate correlations between Therapeutic Persuasiveness, Therapeutic Alliance, and the 3 user engagement variables (.31≤rs≤.51; Ps≤.03). Visual Design, User Engagement, and Content demonstrated similar degrees of correlation with mobile app engagement variables (.25≤rs≤.49; Ps≤.04) but not with average usage time of Web-based interventions. Positive correlations were also found between the number of reviews on Google Play and average app usage time (r=.58; P CONCLUSIONS Results indicate that the qualities of product design predict real-world user engagement with eHealth interventions. The use of real-world behavioral datasets is a novel way to learn about user behaviors, creating new avenues for eHealth intervention research.

Technology provides an unparalleled opportunity to remove barriers to earlier identification and engagement in services for mental and addictive disorders by reaching people earlier in the course of illness and providing links to just-in-time, cost-effective interventions. Achieving this opportunity, however, requires stakeholders to challenge underlying assumptions about traditional pathways to mental health care. In this Open Forum, the authors highlight key issues discussed in the Technology for Early Awareness of Addiction and Mental Illness (TEAAM-I) meeting-held October 13-14, 2016, in New York City-that are related to three identified areas in which technology provides important and unique opportunities to advance early identification, increase service engagement, and decrease the duration of untreated mental and addictive disorders.

The current study addresses the link between attachment styles and manifestations of malicious envy. One hundred twenty-four Israeli undergraduate students completed measures of attachment styles, self-esteem, social comparison, and participated in a subject manipulation tapping malicious envy using tools developed for the present study. These measures were developed to examine envy in a direct way while controlling confounding variables such as the general tendency to see others in negative ways. Our findings revealed that dismissive avoidants exhibited higher levels of malicious envy manifestations in comparison to fearful avoidants. Theoretical implications of the findings were discussed by the authors.

The purpose of this review was to identify and classify key criteria concepts related to the evaluation of user-facing eHealth programs. In line with the PRISMA statement methodology, computer searches of relevant databases were conducted for studies published between January 1, 2000 and March 1, 2016 that contained explicit quality criteria related to mHealth and eHealth products. Reference lists of included articles, review articles, and grey literature (e.g., books, websites) were searched for additional sources. A team of nine experts led by the first author was gathered to support the classification of these criteria. Identified criteria were extracted, grouped and organized using an inductive thematic analysis. Eighty-four sources - emanating from 26 different courtiers - were included in this review. The team extracted 454 criteria that were grouped into 11 quality domains, 58 criteria concepts and 134 concepts' sub-groups. Quality domains were: Usability, Visual Design, User Engagement, Content, Behavior Change/Persuasive Design, Influence of Social Presence, Therapeutic Alliance, Classification, Credibility/Accountability, and Privacy/Security. Findings suggest that authors around the globe agree on key criteria concepts when evaluating user-facing eHealth products. The high proportion of new published criteria in the second half of this review time-frame (2008-2016), and more specifically, the high proportion of criteria relating to persuasive design, therapeutic alliance and privacy/security within this time-frame, points to the advancements made in recent years within this field.

This manuscript assesses the use of the Child Attachment Interview (CAI) in a sample of Israeli Jewish children in middle childhood in order to add to empirical data on this measure.Forty-one children between the ages of 7 and 13 were consecutively recruited to the study. The clinical sample included 29 children diagnosed with anxiety disorder, major depression or ADHD. The Father Focused Referral (FFR) sample included 12 children whose father was unavailable to them. Participants were administered the CAI and coded by certified personnel.81.4% concordance was found between maternal and paternal secure-insecure attachment classifications in the clinical sample; 100% of the children in the FFR group were classified as insecurely attached to their fathers suggesting convergent validity for the classification of father attachment; 45.4% of the children in the FFR sample were also classified as insecurely attached to their mothers, pointing to the difference that can be found between the two parental attachment classifications in relevant cases, and therefore to sufficient discriminant validity between the two classifications.The clinical sample concordance rate, which was lower than in previous studies, indicates that parental concordance rates should be further investigated using different samples and countries. The study's findings regarding the difference that can be found between parental attachment classifications show the instrument's relevance in cases which the parental representations may differ. In these cases, using an instrument that does not examine the attachment toward both parents might not suffice. Study limitations and further implications are discussed.

Digital triggers such as text messages, emails, and push alerts are designed to focus an individual on a desired goal by prompting an internal or external reaction at the appropriate time. Triggers therefore have an essential role in engaging individuals with digital interventions delivered outside of traditional health care settings, where other events in daily lives and fluctuating motivation to engage in effortful behavior exist. There is an emerging body of literature examining the use of digital triggers for short-term action and longer-term behavior change. However, little attention has been given to understanding the components of digital triggers. Using tailoring as an overarching framework, we separated digital triggers into 5 primary components: (1) who (sender), (2) how (stimulus type, delivery medium, heterogeneity), (3) when (delivered), (4) how much (frequency, intensity), and (5) what (trigger’s target, trigger’s structure, trigger’s narrative). We highlighted key considerations when tailoring each component and the pitfalls of ignoring common mistakes, such as alert fatigue and habituation. As evidenced throughout the paper, there is a broad literature base from which to draw when tailoring triggers to curate behavior change in health interventions. More research is needed, however, to examine differences in efficacy based on component tailoring, to best use triggers to facilitate behavior change over time, and to keep individuals engaged in physical and mental health behavior change efforts. Dismantling digital triggers into their component parts and reassembling them according to the gestalt of one’s change goals is the first step in this development work. [J Med Internet Res 2017;19(5):e147]

It is often difficult for health providers to evaluate available e-mental health products because of the need to balance between obtaining reliable evidence of efficacy and the burdens associated with standard empirical evaluation. This paper makes the case for using a feasible method to investigate available e-mental health programs in order to promote knowledge and increase the uptake of e-mental health products.

The authors examined patients' acceptance of the Health Technology Program (HTP), an integrative approach to relapse prevention after hospitalization of adults with schizophrenia or related disorders. The program combines use of digital tools with support from a mental health technology coach (MHTC).Patients with schizophrenia spectrum disorders received six months of treatment that began within 60 days of a psychiatric hospitalization and included the development of a personalized relapse prevention plan, three digital tools, and contacts with MHTCs.A total of 200 patients (mean±SD age=34.6±10.6 years) had 28.2±2.0 contacts with the MHTC that lasted 38.3±14.2 minutes. The most discussed topic was case management (52%), and digital tools were discussed in 45% of meetings. Altogether, 87% of patients used at least one of the digital tools, with 96% of patients rating the HTP as satisfying to at least some extent.These data suggest very high acceptance of the HTP, a program that integrates available human support with digital tools.

BackgroundPeer support is considered to be an important framework of support for mothers experiencing postpartum depression (PPD); however, some barriers exist that may limit its use including peer availability and mothers’ lack of time due to child care. ObjectiveThis non-randomized study was designed to examine the feasibility, acceptance, and preliminary clinical outcomes of using 7 Cups of Tea (7Cups), a digital platform that delivers self-help tools and 24/7 emotional support delivered by trained volunteers, as an adjunct treatment for mothers diagnosed with PPD. MethodsMothers with PPD were referred during intake to the study coach who provided guidance about 7Cups. 7Cups features included self-help tools and chats with trained volunteers who had experienced a perinatal mood disorder in their past. Acceptability was measured by examining self-reports and user engagement with the program. The primary outcome was the Edinburgh Postnatal Depression Scale (EPDS) change score between pre- and postintervention at 2 months, as collected in usual care by clinicians blinded to the study questions. Using a propensity score matching to control for potential confounders, we compared women receiving 7Cups to women receiving treatment as usual (TAU). ResultsParticipants (n=19) proactively logged into 7Cups for a median of 12 times and 175 minutes. Program use was mostly through the mobile app (median of mobile use 94%) and between 18:00 and 08:00 when clinicians are unavailable (68% of total program use time). Participants chatted with volunteers for a total of 3064 minutes and have indicated in their responses 0 instances in which they felt unsafe. Intent-to-treat analysis revealed that 7Cups recipients experienced significant decreases in EPDS scores (P

Background: Studies of criteria-based assessment tools have demonstrated the feasibility of objectively evaluating eHealth interventions independent of empirical testing. However, current tools have not included some quality constructs associated with intervention outcome, such as persuasive design, behavior change, or therapeutic alliance. In addition, the generalizability of such tools has not been explicitly examined. Objective: The aim is to introduce the development and further analysis of the Enlight suite of measures, developed to incorporate the aforementioned concepts and address generalizability aspects. Methods: As a first step, a comprehensive systematic review was performed to identify relevant quality rating criteria in line with the PRISMA statement. These criteria were then categorized to create Enlight. The second step involved testing Enlight on 42 mobile apps and 42 Web-based programs (delivery mediums) targeting modifiable behaviors related to medical illness or mental health (clinical aims). Results: A total of 476 criteria from 99 identified sources were used to build Enlight. The rating measures were divided into two sections: quality assessments and checklists. Quality assessments included usability, visual design, user engagement, content, therapeutic persuasiveness, therapeutic alliance, and general subjective evaluation. The checklists included credibility, privacy explanation, basic security, and evidence-based program ranking. The quality constructs exhibited excellent interrater reliability (intraclass correlations=.77-.98, median .91) and internal consistency (Cronbach alphas=.83-.90, median .88), with similar results when separated into delivery mediums or clinical aims. Conditional probability analysis revealed that 100% of the programs that received a score of fair or above (≥3.0) in therapeutic persuasiveness or therapeutic alliance received the same range of scores in user engagement and content—a pattern that did not appear in the opposite direction. Preliminary concurrent validity analysis pointed to positive correlations of combined quality scores with selected variables. The combined score that did not include therapeutic persuasiveness and therapeutic alliance descriptively underperformed the other combined scores. Conclusions: This paper provides empirical evidence supporting the importance of persuasive design and therapeutic alliance within the context of a program’s evaluation. Reliability metrics and preliminary concurrent validity analysis indicate the potential of Enlight in examining eHealth programs regardless of delivery mediums and clinical aims. [J Med Internet Res 2017;19(3):e82]

Introduction Recent evidence suggests that text messaging may help to reduce problem drinking as an extension to in-person services, but very little is known about the effectiveness of remote messaging on problem drinking as a stand-alone intervention, or how different types of messages may improve drinking outcomes in those seeking to moderate their alcohol consumption. Methods We conducted an exploratory, single-blind randomized controlled pilot study comparing four different types of alcohol reduction-themed text messages sent daily to weekly drink self-tracking texts in order to determine their impact on drinking outcomes over a 12-week period in 152 participants (≈ 30 per group) seeking to reduce their drinking on the internet. Messaging interventions included: weekly drink self-tracking mobile assessment texts (MA), loss-framed texts (LF), gain-framed texts (GF), static tailored texts (ST), and adaptive tailored texts (TA). Poisson and least squares regressions were used to compare differences between each active messaging group and the MA control. Results When adjusting for baseline drinking, participants in all messaging groups except GF significantly reduced the number of drinks consumed per week and the number of heavy drinking days compared to MA. Only the TA and GF groups were significantly different from MA in reducing the number of drinking days. While the TA group yielded the largest effect sizes on all outcome measures, there were no significant differences between active messaging groups on any outcome measure. 79.6% of individuals enrolled in the study wanted to continue receiving messages for an additional 12 weeks at the end of the study. Discussion Results of this pilot study indicate that remote automated text messages delivered daily can help adult problem drinkers reduce drinking frequency and quantity significantly more than once-a-week self-tracking messages only, and that tailored adaptive texts yield the largest effect sizes across outcomes compared to MA. Larger samples are needed to understand differences between messaging interventions and to target their mechanisms of efficacy.

Background Perinatal depression and anxiety are common and debilitating conditions. Novel, cost effective services could improve the uptake and the impact of mental health resources among women who suffer from these conditions. E-mental health products are one example of such services. Many publically available e-mental health products exist, but these products lack validation and are not designed to be integrated into existing health care settings. Objective The objective of the study was to present a program to use 7 Cups of Tea (7Cups), an available technological platform that provides online peer (ie, listener) based emotional support, to supplement treatment for women experiencing perinatal depression or anxiety and to summarize patient’s feedback on the resultant program. Methods This study consisted of two stages. First, five clinicians specializing in the treatment of perinatal mood disorders received an overview of 7Cups. They provided feedback on the 7Cups platform and ways it could complement the existing treatment efforts to inform further adjustments. In the second stage, nine women with perinatal depression or anxiety used the platform for a single session and provided feedback. Results In response to clinicians’ feedback, guidelines for referring patients to use 7Cups as a supplement for treatment were created, and a training program for listeners was developed. Patients found the platform usable and useful and their attitudes toward the trained listeners were positive. Overall, patients noted a need for support outside the scheduled therapy time and believed that freely available online emotional support could help meet this need. Most patients were interested in receiving support from first time mothers and those who suffered in the past from perinatal mood disorders. Conclusions The study results highlight the use of 7Cups as a tool to introduce accessible and available support into existing treatment for women who suffer from perinatal mood disorders. Further research should focus on the benefits accrued from such a service. However, this article highlights how a publicly available eHealth product can be leveraged to create new services in a health care setting.

In recent years, the number of available eHealth interventions aimed at treating behavioral and mental health challenges has been growing. From the perspective of health care providers, there is a need for eHealth interventions to be evaluated prior to clinical trials and for the limited resources allocated to empirical research to be invested in the most promising products. Following a literature review, a gap was found in the availability of eHealth interventions evaluation principles related to the patient experience of the therapeutic process. This paper introduces principles and concepts for the evaluation of eHealth interventions developed as a first step in a process to outline general evaluation guidelines that relate to the clinical context from health care providers’ perspective. Our approach was to conduct a review of literature that relates to the examination of eHealth interventions. We identified the literature that was most relevant to our study and used it to define guidelines that relate to the clinical context. We then compiled a list of heuristics we found to be useful for the evaluation of eHealth intervention products’ suitability for empirical examination. Four heuristics were identified with respect to the therapeutic process: (1) the product’s ease of use (ie, usability), (2) the eHealth intervention’s compatibility with the clinical setting, (3) the presence of tools that make it easier for the user to engage in therapeutic activities, and (4) the provision of a feasible therapeutic pathway to growth. We then used this set of heuristics to conduct a detailed examination of MyFitnessPal. This line of work could help to set the bar higher for product developers and to inform health care providers about preferred eHealth intervention designs.

The behavior of concerned significant others (CSOs) can have a measurable impact on the health and wellness of individuals attempting to meet behavioral and health goals, and research is needed to better understand the attributes of text-based CSO language when encouraging target significant others (TSOs) to achieve those goals. In an effort to inform the development of interventions for CSOs, this study examined the language content of brief text-based messages generated by CSOs to motivate TSOs to achieve a behavioral goal. CSOs generated brief text-based messages for TSOs for three scenarios: (1) to help TSOs achieve the goal, (2) in the event that the TSO is struggling to meet the goal, and (3) in the event that the TSO has given up on meeting the goal. Results indicate that there was a significant relationship between the tone and compassion of messages generated by CSOs, the CSOs’ perceptions of TSO motivation, and their expectation of a grateful or annoyed reaction by the TSO to their feedback or support. Results underscore the importance of attending to patterns in language when CSOs communicate with TSOs about goal achievement or failure, and how certain variables in the CSOs’ perceptions of their TSOs affect these characteristics.