Effects of a Digital Mental Health Intervention on Perceived Stress and Rumination in Adolescents Aged 13 to 17 Years: Randomized Controlled Trial.

BACKGROUND: Although adolescents report high levels of stress, they report engaging in few stress management techniques. Consequently, developing effective and targeted programs to help address this transdiagnostic risk factor in adolescence is particularly important. Most stress management programs for adolescents are delivered within schools, and the evidence for these programs is mixed, suggesting a need for alternative options for stress management among adolescents. OBJECTIVE: The aim of the study is to test the short-term effects of a self-guided digital mental health intervention (DMHI) designed for adolescents on perceived stress and rumination (ie, brooding). METHODS: This was a 12-week, 2-arm decentralized randomized controlled trial of adolescents aged 13 to 17 years who presented with elevated levels of perceived stress and brooding. Participants were randomly assigned to engage with a self-guided DMHI (Happify for Teens) or to a waitlist control. Participants assigned to the intervention group were given access to the program for 12 weeks. Happify for Teens consists of various evidence-based activities drawn from therapeutic modalities such as cognitive behavioral therapy, positive psychology, and mindfulness, which are then organized into several programs targeting specific areas of concern (eg, Stress Buster 101). Participants in the waitlist control received access to this product for 12 weeks upon completing the study. Participants in both groups completed measures of perceived stress, brooding, optimism, sleep disturbance, and loneliness at baseline, 4 weeks, 8 weeks, and 12 weeks. Changes in outcomes between the intervention and waitlist control groups were assessed using repeated-measures multilevel models. RESULTS: Of the 303 participants included in data analyses, 132 were assigned to the intervention and 171 to the waitlist. There were significantly greater improvements in the intervention condition for perceived stress (intervention: B=-1.50; 95% CI -1.82 to -1.19; P<.001 and control: B=-0.09; 95% CI -0.44 to 0.26; P=.61), brooding (intervention: B=-0.84; 95% CI -1.00 to -0.68; P<.001 and control: B=-0.30; 95% CI -0.47 to -0.12; P=.001), and loneliness (intervention: B=-0.96; 95% CI -1.2 to -0.73; P<.001 and control: B=-0.38; 95% CI: -0.64 to -0.12; P=.005) over the 12-week study period. Changes in optimism and sleep disturbance were not significantly different across groups (Ps≥.096). CONCLUSIONS: Happify for Teens was effective at reducing perceived stress, rumination, and loneliness among adolescents over 12 weeks when compared to a waitlist control group. Our data reveal the potential benefits of DMHIs for adolescents, which may present a more scalable, destigmatized, and cost-effective alternative to school-based programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04567888; https://clinicaltrials.gov/ct2/show/NCT04567888. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/25545.

Engagement in Digital Mental Health Interventions: Can Monetary Incentives Help?

Digital mental health interventions (DMHI) are scalable and cost-effective strategies for increasing access to mental health care; however, dropout rates associated with digital interventions are high, particularly for open-access digital interventions. While some studies have focused on predictors of dropout from digital mental health programs, few studies have focused on engagement features that might improve engagement. In this perspective article, we discuss whether monetary incentives (MI) are one avenue to increasing user engagement in DMHI. We begin by reviewing the literature on the effects of MI for behavior change in health domains (e.g., dietary behaviors, substance use, and medication adherence). Then, drawing on a pilot study we conducted to test the effects of different levels of MI on usage and improvement in subjective well-being among users of a DMHI (Happify), we discuss the potential applications of MI for DMHI, the potential drawbacks of financial incentives in this context, and open questions for future research.

Artificially intelligent chatbots in digital mental health interventions: a review.

INTRODUCTION: Increasing demand for mental health services and the expanding capabilities of artificial intelligence (AI) in recent years has driven the development of digital mental health interventions (DMHIs). To date, AI-based chatbots have been integrated into DMHIs to support diagnostics and screening, symptom management and behavior change, and content delivery. AREAS COVERED: We summarize the current landscape of DMHIs, with a focus on AI-based chatbots. Happify Health's AI chatbot, Anna, serves as a case study for discussion of potential challenges and how these might be addressed, and demonstrates the promise of chatbots as effective, usable, and adoptable within DMHIs. Finally, we discuss ways in which future research can advance the field, addressing topics including perceptions of AI, the impact of individual differences, and implications for privacy and ethics. EXPERT OPINION: Our discussion concludes with a speculative viewpoint on the future of AI in DMHIs, including the use of chatbots, the evolution of AI, dynamic mental health systems, hyper-personalization, and human-like intervention delivery.

The Effects of a Digital Mental Health Intervention in Adults With Cardiovascular Disease Risk Factors: Analysis of Real-World User Data.

BACKGROUND: The American Heart Association has identified poor mental health as a key barrier to healthy behavior change for those with cardiovascular disease (CVD) risk factors such as high blood pressure, high cholesterol, and diabetes. Digital mental health interventions, like those delivered via the internet to computers or smartphones, may provide a scalable solution to improving the mental and physical health of this population. Happify is one such intervention and has demonstrated evidence of efficacy for improving aspects of mental health in both the general population and in users with chronic conditions. OBJECTIVE: The objectives of this analysis of real-world data from Happify users with self-reported CVD risk factors, including high blood pressure and cholesterol, diabetes, and heart disease, were to examine whether these users would report improvements in subjective well-being and anxiety over time (H1) and use of Happify as recommended would be associated with significantly greater improvement in subjective well-being and anxiety over time compared to less-than-recommended usage (H2). METHODS: Data were obtained from existing Happify users who reported the aforementioned CVD risk factors. The sample included 1803 users receiving at least 6 weeks' exposure to Happify (ranging from 42 days to 182 days) who completed at least one activity and two assessments within the app during that time. Subjective well-being was assessed with the Happify Scale, a 9-item measure of positive emotionality and life satisfaction, and anxiety was assessed with the Generalized Anxiety Disorder 2 (GAD-2). To evaluate H1, changes over time in both outcomes were assessed using mixed effects linear regression models, controlling for demographics and usage. For H2, an interaction term was added to the models to assess whether usage as recommended was associated with greater improvement over time. RESULTS: Both hypotheses were supported. For both the Happify scale and GAD-2, the initial multivariable model without an interaction demonstrated an effect for time from baseline, and the addition of the interaction term between time and recommended use was significant as well. CONCLUSIONS: This analysis of real-world data provides preliminary evidence that Happify users with self-reported CVD risk factors including high blood pressure or cholesterol, diabetes, and heart disease experienced improved well-being and anxiety over time and that those who used Happify as recommended experienced greater improvements in these aspects of mental health than those who completed fewer activities. These findings extend previous research, which demonstrated that engagement with Happify as recommended was associated with improved well-being among physically healthy users and in those with chronic conditions, to a new population for whom mental health is especially critical: those at risk of developing CVD.

Effects of a Digital Mental Health Program on Perceived Stress in Adolescents Aged 13-17 Years: Protocol for a Randomized Controlled Trial.

BACKGROUND: Stress is an important transdiagnostic risk factor in adolescence and predicts a host of physical and psychological problems in adolescence and adulthood. Adolescence is also a developmental stage in which people may be more sensitive or reactive to stress. Indeed, research has shown that adolescents report high levels of stress, particularly when enrolled in school. However, adolescents report engaging in few, if any, stress management techniques. Consequently, the development of effective programs to help address adolescent stress is particularly important. To date, most stress management programs for adolescents are delivered within schools, and the evidence for such programs is mixed. Furthermore, most of these programs rely on traditional stress management techniques rather than incorporating methods to address the underlying negative cognitive processes, such as rumination, that may contribute to or exacerbate the effects of perceived stress. OBJECTIVE: The aim of this study is to test the short-term effects of a digital mental health program designed for adolescents aged 13-17 years on perceived stress and rumination. METHODS: This is a randomized controlled trial in which adolescents between the ages of 13 and 17 years, with elevated levels of perceived stress and brooding, will be randomly assigned to complete 8 weeks of a digital mental health program (Happify for Teens) or to a corresponding wait-list control group. The study will take place over 3 months, including the 8-week intervention period and 1-month postintervention follow-up. The primary outcome, perceived stress, along with secondary and exploratory outcomes (ie, brooding, optimism, sleep disturbance, and loneliness) will be assessed via self-report at baseline, 4 weeks, 8 weeks, and 12 weeks to compare changes in these outcomes across conditions. RESULTS: Recruitment is expected to begin in the second quarter of 2021, with a target sample size of 800 participants (400 per condition). Participants will begin the study as they are recruited and will finish in waves, with the first wave of data expected 8 weeks after recruitment begins and the final wave of data expected by the end of the third quarter of 2021. CONCLUSIONS: Although school-based stress management programs for adolescents are common, research suggests that they may be limited in their reach and more effective for school-based stress than other types of stress. This trial will be one of the first attempts to examine the potential benefits of a digital mental health program on adolescents to address stress along with negative cognitive processes such as rumination. If successful, this would help introduce a more scalable alternative to school-based programs that offers adolescents greater privacy while also providing insight into novel ways to target adolescent mental health more generally. TRIAL REGISTRATION: ClinicalTrials.gov NCT04567888; https://clinicaltrials.gov/ct2/show/NCT04567888. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/25545.

The Impact of a Digital Intervention (Happify) on Loneliness During COVID-19: Qualitative Focus Group.

BACKGROUND: Loneliness is a growing area of concern, attracting attention as a public health concern due to its association with a variety of psychological and physical health problems. However, interventions targeting loneliness are less common than interventions for other mental health problems, such as depression and anxiety, and existing interventions focus primarily on building social skills and increasing opportunities for social interaction despite research suggesting these techniques are not the most effective. Furthermore, although there is an increasing need for scalable and convenient interventions, digital interventions for loneliness are even less common. OBJECTIVE: Using a qualitative approach, we explore how adults (18-64 years of age) who express wanting to be more connected to others experience loneliness and react to a digital mental health intervention targeting loneliness. METHODS: A total of 11 participants were recruited from a pilot randomized controlled trial exploring the impact of a digital mental health intervention, Happify Health, on loneliness among adults aged 18-64 years who indicated wanting to feel more connected to others when signing up for the platform. Participants were invited to participate in a 3-day asynchronous focus group about their experiences with loneliness, with Happify Health, and with social distancing during the COVID-19 pandemic. All 11 participants completed the focus group in May 2020. RESULTS: Participants' responses were coded using thematic analysis, which led to identifying five themes, each with separate subthemes, that could be applied across the 3-day focus group: loneliness, relationships, social distancing, skill acquisition, and coping. Overall, we observed variability across participants in terms of the source of their loneliness, their perceptions of their social connections, and their motivation to reduce feelings of loneliness; however, participants commonly referred to negative self-perceptions as a cause or consequence of loneliness. Participants also varied in the extent to which they felt social distancing increased or decreased feelings of loneliness. In regard to the intervention, participants showed evidence of adopting skills they used to address their loneliness, particularly mindfulness and gratitude, and then using these skills to shift toward more active coping strategies following the intervention, including during the COVID-19 pandemic. CONCLUSIONS: The heterogeneity in participants' experiences with loneliness described during this focus group emphasizes the subjective and complex nature of loneliness. This highlights the importance of developing loneliness interventions that use a variety of strategies, including both direct and indirect strategies for reducing loneliness. However, based on our data, a key component to loneliness interventions is incorporating strategies for addressing underlying negative self-perceptions that stem from, but also contribute to, loneliness. This data also provides preliminary evidence that digital platforms may be an effective tool for disseminating loneliness interventions while providing the added benefit of offering a productive distraction when feeling lonely.

The Effects of a Digital Well-Being Intervention on Patients With Chronic Conditions: Observational Study.

BACKGROUND: Chronic conditions account for 75% of health care costs, and the impact of chronic illness is expected to grow over time. Although subjective well-being predicts better health outcomes, people with chronic conditions tend to report lower well-being. Improving well-being might mitigate costs associated with chronic illness; however, existing interventions can be difficult to access and draw from a single theoretical approach. Happify, a digital well-being intervention program drawing from multiple theoretical traditions to target well-being, has already been established as an efficacious means of improving well-being in both distressed and nondistressed users. OBJECTIVE: This study aimed to compare change in well-being over time after using Happify for users with and without a chronic condition. METHODS: Data were obtained from Happify users, a publicly available digital well-being program accessible via website or mobile phone app. Users work on tracks addressing a specific issue (eg, conquering negative thoughts) composed of games and activities based on positive psychology, cognitive behavioral therapy, and mindfulness principles. The sample included 821 users receiving at least 6 weeks' exposure to Happify (ranging from 42 to 179 days) who met other inclusion criteria. As part of a baseline questionnaire, respondents reported demographic information (age and gender) and whether they had any of the prespecified chronic conditions: arthritis, diabetes, insomnia, multiple sclerosis, chronic pain, psoriasis, eczema, or some other condition (450 reported a chronic condition, whereas 371 did not). Subjective well-being was assessed with the Happify Scale, a 9-item measure of positive emotionality and life satisfaction. To evaluate changes in well-being over time, a mixed effects linear regression model was fit for subjective well-being, controlling for demographics and platform usage. RESULTS: At baseline, users with a chronic condition had significantly lower subjective well-being (mean 38.34, SD 17.40) than users without a chronic condition (mean 43.65, SD 19.13). However, change trajectories for users with or without a chronic condition were not significantly different; both groups experienced equivalent improvements in well-being. We also found an effect for time from baseline (b=0.071; SE=0.010; P<.01) and number of activities completed (b=0.03; SE=0.009; P<.01), and a 2-way interaction between number of activities completed and time from baseline (b=0.0002; SE=0.00006; P<.01), such that completing more activities and doing so over increasingly longer periods produced improved well-being scores. CONCLUSIONS: Data from this study support the conclusion that users with a chronic condition experienced significant improvement over time. Despite reporting lower subjective well-being on the whole, their change trajectory while using Happify was equivalent to those without a chronic condition. Consistent with past research, users who completed more activities over a longer period showed the most improvement. In short, the presence of a chronic condition did not prevent users from showing improved well-being when using Happify.

Interpersonal sensitivity, status, and stereotype accuracy.

A classic question in social and organizational psychology is whether low-status persons are more accurate in the perception of their high-status partners than the latter are in their perception of their subordinates. In a series of studies, Snodgrass (1985, 1992) tested this idea. She found that subordinates were more accurate at judging how their bosses viewed them than bosses were at judging how their subordinates viewed them, but that bosses were more accurate at judging how subordinates viewed themselves than subordinates were at judging how bosses viewed themselves. We believe, however, that these results were obscured by stereotype accuracy. Using previously collected data, we found that stereotype accuracy does lead to the pattern previously observed by Snodgrass. We also discovered that when we controlled for stereotype accuracy, subordinates' perceptions were generally more accurate than those of their bosses, which supports Snodgrass's original hypothesis.

A context-informed approach to the study of negative-feedback seeking in depression.

The purpose of the current study was to examine the link between negative-feedback seeking (NFS) and depression using a behavioural task that addressed many of the limitations of existing measures of NFS, to use a remitted-depressive design to determine whether NFS is a temporary or stable feature of depression, and to examine the role of personality and contextual variables (e.g., marital quality, spousal characteristics) in NFS. Using a sample of 59 couples (12 wife currently depressed, 20 wife remitted-depressed, and 27 wife never-depressed), we designed a task that correlated with an established measure of NFS and was able to distinguish between non-depressed and currently depressed wives. Using this behavioural task, we found that NFS is stably associated with depression and that relationship and partner characteristics may protect depressed individuals from engaging in destructive interpersonal patterns.