Digital Terror: Its Striking Impact on Public Mental Health.

Digital terror refers to the use of digital technology to disseminate graphic images of acts of violence to frighten the public. On October 7, 2023, militants of the Palestinian organization Hamas launched a brutal attack on Israel and used digital terror to magnify their acts. Although the purposeful spreading of terror via digital means is not new, the Hamas attack was significant for the scope, immediacy, and widespread dissemination of its digital content. This column aims to describe and analyze the psychological significance of this new form of terror, the public mental health challenges raised, and the interventions needed to assist those exposed to digital terror.

Blended care in psychosis - A systematic review.

Blended-care, a psychosocial intervention combining traditional, face-to-face therapy with digital mental health tools, has shown potential for improving therapeutic processes, fostering patient engagement, and augmenting clinical outcomes. This systematic review aimed to evaluate the development and effectiveness of blended-care interventions tailored for adults diagnosed with schizophrenia-spectrum disorders or other conditions with psychotic features. Our search strategy spanned three electronic databases (PsycINFO, Web of Science, and PubMed) in accordance with the reporting guidelines outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. We identified 11 papers, each examining the use of one of eight distinct blended-care interventions. Significantly, the majority of these papers (10/11, 91 %) examined these interventions exclusively within controlled research environments, demonstrating both acceptability and favourable impacts on symptomatology and recovery (e.g., 0.22 ≤ Cohen's ds ≤ 1.00). Only one intervention was examined in research settings and real-world conditions, and the shift resulted in low real-world uptake (e.g., only 50 % of practitioners were able to engage at least one of their clients with the intervention) and an inability to reproduce positive changes in clinical outcomes. Additional research is needed to determine the viability of successfully developing and implementing blended-care interventions for psychosis in real-world conditions. An exploration of the developmental processes that could facilitate the transition from research settings to routine clinical practice is vital.

Examining the Effectiveness of a Digital Media Campaign at Reducing the Duration of Untreated Psychosis in New York State: Results From a Stepped-wedge Randomized Controlled Trial.

BACKGROUND AND HYPOTHESIS: Longer duration of untreated psychosis (DUP) predicts worse outcomes in First Episode Psychosis (FEP). Searching online represents one of the first proactive step toward treatment initiation for many, yet few studies have informed how best to support FEP youth as they engage in early online help-seeking steps to care. STUDY DESIGN: Using a stepped-wedge randomized design, this project evaluated the effectiveness of a digital marketing campaign at reducing DUP and raising rates of referrals to FEP services by proactively targeting and engaging prospective patients and their adult allies online. STUDY RESULTS: Throughout the 18-month campaign, 41 372 individuals visited our website, and 371 advanced to remote clinical assessment (median age = 24.4), including 53 allies and 318 youth. Among those assessed (n = 371), 53 individuals (14.3%) reported symptoms consistent with psychotic spectrum disorders (62.2% female, mean age 20.7 years) including 39 (10.5%) reporting symptoms consistent with either Clinical High Risk (ie, attenuated psychotic symptoms; n = 26) or FEP (n = 13). Among those with either suspected CHR or FEP (n = 39), 20 (51.3%) successfully connected with care. The campaign did not result in significant differences in DUP. CONCLUSION: This study highlights the potential to leverage digital media to help identify and engage youth with early psychosis online. However, despite its potential, online education and professional support alone are not yet sufficient to expedite treatment initiation and reduce DUP.

Automated, tailored adaptive mobile messaging to reduce alcohol consumption in help-seeking adults: A randomized controlled trial.

AIMS: To test differential outcomes between three 6-month text-messaging interventions to reduce at-risk drinking in help-seeking adults. DESIGN: A three-arm single-blind randomized controlled trial with 1-, 3-, 6- and 12-month follow-ups. SETTING: United States. A fully remote trial without human contact, with participants recruited primarily via social media outlets. PARTICIPANTS: Seven hundred and twenty-three adults (mean = 39.9 years, standard deviation = 10.0; 62.5% female) seeking to reduce their drinking were allocated to 6 months of baseline 'tailored statically' messaging (TS; n = 240), 'tailored adaptive' messaging (TA; n = 239) or 'drink tracking' messaging (DT; n = 244). INTERVENTIONS: TS consisted of daily text messages to reduce harmful drinking that were tailored to demographics and alcohol use. TA consisted of daily, tailored text messages that were also adapted based on goal achievement and proactive prompts. DT consisted of a weekly assessment for self-reported drinking over the past 7 days. MEASUREMENTS: The primary outcome measure was weekly sum of standard drinks (SSD) at 6-month follow-up. Secondary outcome measures included drinks per drinking day (DDD), number of drinking days (NDD) per week and heavy drinking days (HDD) at 1-, 3-, 6- and 12-month follow-ups. FINDINGS: At 6 months, compared with DT, TA resulted in significant SSD reductions of 16.2 (from 28.7 to 12.5) drinks [adjusted risk ratio (aRR) = 0.80, 95% confidence interval (CI) = 0.71, 0.91] using intent-to-treat analysis. TA also resulted in significant improvements in DDD (aRR = 0.84; 95% CI = 0.77-0.92) and drinking days per week (b = -0.39; 95% CI = -0.67, -0.10), but not HDD compared with DT at 6 months. TA was not significantly different from TS at any time-point, except DDD at 6 months. All groups made improvements in SSD at 12-month follow-up compared with baseline with an average reduction of 12.9 drinks per week across groups. CONCLUSIONS: Automated tailored mobile messaging interventions are scalable solutions that can reduce weekly alcohol consumption in remote help-seeking drinkers over time.

The impact of therapeutic persuasiveness on engagement and outcomes in unguided interventions: A randomized pilot trial of a digital parent training program for child behavior problems.

Understanding how to design engaging unguided digital health interventions is key in our ability to utilize digital tools to improve access to care. Therapeutic persuasiveness (TP) is a design concept that relates to how the digital intervention features as a whole should be designed to encourage users to make positive changes in their lives, while reducing the experienced effort required from them to engage in these activities. In our previous work, we examined the user traffic of publicly available programs, finding programs' TP quality to be a reliable, robust, and stable predictor of real-world usage; however, these findings have not been subject to experimental manipulation in a controlled trial. The current study examined the impact of TP quality in digital parent training programs (DPTs) aimed at treating child's behavior problems. We conducted a pilot randomized controlled trial comparing two interventions that utilize the same evidence-based content of established DPTs, but that differ in terms of the quality of TP (standard: DPT-STD; enhanced: DPT-TP). Altogether, parents from 88 families who have a child with behavior problems were enrolled in the study. Compared to DPT-STD (n = 43), participants allocated to DPT-TP (n = 45) used the program significantly more (ps < 0.001; Cohen's ds = 0.91-2.22). In terms of program completion, 68.9 % of DPT-TP participants completed it compared to 27.9 % of DPT-STD participants. Significant differences between the interventions were also found in reported improvements in child behavior problems favoring DPT-TP (ps < 0.05; Cohen's ds = 0.43-0.54). The results point to the importance of adequate product design and the utilization of conceptual frameworks in order to improve user engagement challenges.

Digital Tools in the Service of Peer and Social Support for Perinatal Mental Health.

PURPOSE OF REVIEW: This study is critically evaluating the current status of digital tools for perinatal mental health, specifically focusing on how these tools can enhance peer and social support. RECENT FINDINGS: Digital tools could be used to: (1) identify individuals in need and guide them towards appropriate human-supportive care; (2) autonomously train and allocate peers to aid women experiencing perinatal mental health challenges; and (3) amplify support from their natural social network. Despite clear evidence supporting the significance of social support for perinatal mental health, there is a dearth of studies on digital tools aimed at boosting such support, leaving a gap in the evidence. Findings underscore the necessity of developing digital initiatives that explicitly aim to augment social support as an active ingredient of therapeutic change for women's perinatal mental health. To establish clear evidence of digital tools' value in providing digital peer-support, further development and research are indispensable.

Suicide Prevention Outreach on Social Media Delivered by Trained Volunteers.

Background: There is a need to develop new ways to reach and engage people at risk for suicidal behavior. Suicide prevention outreach on social media (SPOSM) represents a promising strategy, and trained volunteers could potentially provide the needed human resources. Aims: We aimed to investigate users' perception of SPOSM delivered by volunteers of the Israeli Sahar organization and its potential to promote help-seeking behavior. Methods: Outreach messages written by Sahar volunteers between July 2015 and June 2020 in response to suicidal posts on a social media site were screened. User responses were analyzed using inductive thematic analysis. Results: One hundred sixteen user responses were analyzed. Positive impact themes were identified in 69.8% of responses, while 16.4% of responses mentioned barriers to care and 10.3% were negative. Limitations: As the study is based on real-life data, the data are limited to users who chose to respond to outreach. Conclusion: The findings suggest that volunteer-based SPOSM is viewed positively by many users and may foster help-seeking behavior. The findings also outline challenges such as emotional barriers to care and privacy concerns.

Digital Strategies to Accelerate Help-Seeking in Youth With Psychiatric Concerns in New York State.

Background: Mental illness in transition age youth is common and treatment initiation is often delayed. Youth overwhelmingly report utilizing the Internet to gather information while psychiatric symptoms emerge, however, most are not yet ready to receive a referral to care, forestalling the established benefit of early intervention. Methods: A digital outreach campaign and interactive online care navigation platform was developed and deployed in New York State on October 22, 2020. The campaign offers live connection to a peer or counselor, a self-assessment mental health quiz, and educational material all designed to promote help-seeking in youth and their allies. Results: Between October 22, 2020 and July 31, 2021, the campaign resulted in 581,981 ad impressions, 16,665 (2.9%) clicks, and 13,717 (2.4%) unique website visitors. A third (4,562, 33.2%) completed the quiz and 793 (0.1%) left contact information. Of those, 173 (21.8%) completed a virtual assessment and 155 (19.5%) resulted in a referral to care. The median age of those referred was 21 years (IQR = 11) and 40% were considered to be from low-income areas. Among quiz completers, youth endorsing symptoms of depression or anxiety were more likely to leave contact information (OR = 2.18, 95% CI [1.39, 3.41] and OR = 1.69, 95% CI [1.31, 2.19], respectively) compared to those not reporting symptoms of depression or anxiety. Youth endorsing symptoms of psychosis were less likely to report a desire to receive a referral to care (OR = 0.58, 95% CI [0.43, 0.80]) compared to those who did not endorse symptoms of psychosis. Conclusion: Self-reported symptomatology impact trajectories to care, even at the earliest stages of help-seeking, while youth and their allies are searching for information online. An online care navigation team could serve as an important resource for individuals with emerging behavioral health concerns and help to guide the transition between online information seeking at baseline to care.

Mechanisms of Change in Digital Health Interventions for Mental Disorders in Youth: Systematic Review.

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.

Therapeutic processes in digital interventions for anxiety: A systematic review and meta-analytic structural equation modeling of randomized controlled trials.

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.

Effort-Optimized Intervention Model: Framework for Building and Analyzing Digital Interventions That Require Minimal Effort for Health-Related Gains.

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.

Correction: The Digital Marshmallow Test (DMT) Diagnostic and Monitoring Mobile Health App for Impulsive Behavior: Development and Validation Study.

[This corrects the article DOI: 10.2196/25018.].

The Digital Marshmallow Test (DMT) Diagnostic and Monitoring Mobile Health App for Impulsive Behavior: Development and Validation Study.

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 Micro Interventions for Behavioral and Mental Health Gains: Core Components and Conceptualization of Digital Micro Intervention Care.

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.

There is a non-evidence-based app for that: A systematic review and mixed methods analysis of depression- and anxiety-related apps that incorporate unrecognized techniques.

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.

Is there a trial bias impacting user engagement with unguided e-mental health interventions? A systematic comparison of published reports and real-world usage of the same programs.

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.

Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis.

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.

Examining Predictors of Real-World User Engagement with Self-Guided eHealth Interventions: Analysis of Mobile Apps and Websites Using a Novel Dataset.

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<.001) and user retention after 30 days (r=.23; P=.049). Although several product quality ratings were positively correlated with research evidence, the latter was not significantly correlated with real-world user engagement. Hierarchical stepwise regression analysis revealed that either Therapeutic Persuasiveness or Therapeutic Alliance explained 15% to 26% of user engagement variance. Data on Google Play (number of reviews) explained 15% of the variance of mobile app usage time above Enlight ratings; however, publicly available data did not significantly contribute to explaining the variance of the other 2 user-engagement variables. 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.

Digital Peer-Support Platform (7Cups) as an Adjunct Treatment for Women With Postpartum Depression: Feasibility, Acceptability, and Preliminary Efficacy Study.

BACKGROUND: Peer 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. OBJECTIVE: This 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. METHODS: Mothers 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). RESULTS: Participants (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<.001, Cohen d=1.17). No significant difference in EPDS decrease over time was found between 7Cups and TAU, yet the effect size was medium favoring 7Cups (P=.05, Cohen d=0.58). CONCLUSIONS: This study supports using a computerized method to train lay people, without any in-person guidance or screening, and engage them with patients diagnosed with mental illness as part of usual care. The medium effect size (d=0.58) favoring the 7Cups group relative to TAU suggests that 7Cups might enhance treatment outcomes. A fully powered trial has to be conducted to examine this effect.

Predicting user adherence to behavioral eHealth interventions in the real world: examining which aspects of intervention design matter most.

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.