Antifragile Behavior Change Through Digital Health Behavior Change Interventions

Digital health behavior change interventions (DHBCIs) offer users accessible support, yet their promise to improve health behaviors at scale has not been met. One reason for this unmet potential may be a failure to offer users support that is tailored to their personal characteristics and goals. We apply the concept of antifragility to propose how DHBCIs could be better designed to support diverse users’ behavior change journeys. We first define antifragility as a feature of an individual’s relationship to a particular challenge such that if one is antifragile to a challenge, one is well positioned to benefit from facing that challenge. Second, we introduce antifragile behavior change to describe behavior change processes that leverage person-specific antifragilities to maximize benefits and minimize risk in the behavior change process. While most existing behavior change models focus on improving one’s motivation and ability to face challenges, antifragile behavior change complements these models by helping to select challenges that are most likely to produce desired outcomes. Next, we propose three principles by which DHBCIs can help users to develop antifragile behavior change strategies: providing personalized guidance, embracing variance and exploration in choosing behaviors, and prioritizing user agency. Finally, we offer an example of how a DHBCI could be designed to support antifragile behavior change.

Social Interactivity in Live Video Experiences Reduces Loneliness

Background

Loneliness, especially when chronic, can substantially reduce one's quality of life. However, positive social experiences might help to break cycles of loneliness by promoting more prosocial cognitions and behaviors. Internet-mediated live video communication platforms (eg Zoom and Twitch) may offer an engaging and accessible medium to deliver such social experiences to people at scale. Despite these platforms' widespread use, there is a lack of research into how their socially interactive elements affect users' feelings of loneliness and connection.

Objective

We aimed to experimentally evaluate whether socially interactivity in live video experience improves loneliness-related outcomes.

Materials and Methods

We recruited participants from an online survey recruitment platform and assigned half to participate in a socially interactive live video experience with 6–12 strangers and the other half to a non-interactive control experience that was designed to be identical in every way but not socially interactive. Participants completed several baseline self-report measures of psychosocial wellbeing, participated in the hour-long video experience (an entertaining astronomy lesson), and then completed some baseline measures again. Four weeks later, we followed up with participants to evaluate their change in trait loneliness since baseline. We Pre-registered our hypotheses and analysis plan and provide our data, analysis code, and study materials online.

Results

Two hundred and forty-nine participants completed the initial study and met inclusion criteria, 199 of whom also completed the 4-week follow-up. Consistent with our predictions, we found that directly after the more socially interactive experience, participants' feelings of connectedness increased more (p < 0.001), positive affect increased more (p = 0.002), feelings of loneliness decreased more (p < 0.001), social threat decreased more (p = 0.006), and negative affect decreased more (p = 0.003) than they did after the less interactive experience. However, change in trait loneliness between baseline and 4 weeks later did not differ between conditions (p = 0.953).

Conclusions

Including socially interactive components in live video experiences can improve loneliness-related psychosocial outcomes for a short time. Future work should explore leveraging these benefits toward longer-term prosociality. Future work can also identify if the effects we observed generalize across different populations and kinds of online experiences.

Irrelevant insights make worldviews ring true

Our basic beliefs about reality can be impossible to prove and yet we can feel a strong intuitive conviction about them, as exemplified by insights that imbue an idea with immediate certainty. Here we presented participants with worldview beliefs such as "people's core qualities are fixed" and simultaneously elicited an aha moment. In the first experiment (N = 3000, which included a direct replication), participants rated worldview beliefs as truer when they solved anagrams and also experienced aha moments. A second experiment (N = 1564) showed that the worldview statement and the aha moment must be perceived simultaneously for this 'insight misattribution' effect to occur. These results demonstrate that artificially induced aha moments can make worldview beliefs seem truer, possibly because humans partially rely on feelings of insight to appraise an idea's veracity. Feelings of insight are therefore not epiphenomenal and should be investigated for their effects on decisions, beliefs, and delusions.

User Experience, Engagement, and Popularity in Mental Health Apps: Secondary Analysis of App Analytics and Expert App Reviews

Background

User experience and engagement are critical elements of mental health apps’ abilities to support users. However, work examining the relationships among user experience, engagement, and popularity has been limited. Understanding how user experience relates to engagement with and popularity of mental health apps can demonstrate the relationship between subjective and objective measures of app use. In turn, this may inform efforts to develop more effective and appealing mental health apps and ensure that they reach wide audiences.

Objective

We aimed to examine the relationship among subjective measures of user experience, objective measures of popularity, and engagement in mental health apps.

Methods

We conducted a preregistered secondary data analysis in a sample of 56 mental health apps. To measure user experience, we used expert ratings on the Mobile App Rating Scale (MARS) and consumer ratings from the Apple App Store and Google Play. To measure engagement, we acquired estimates of monthly active users (MAU) and user retention. To measure app popularity, we used download count, total app revenue, and MAU again.

Results

MARS total score was moderately positively correlated with app-level revenue (Kendall rank [T]=0.30, P=.002), MAU (T=0.39, P<.001), and downloads (T=0.41, P<.001). However, the MARS total score and each of its subscales (Engagement, Functionality, Aesthetics, and Information) showed extremely small correlations with user retention 1, 7, and 30 days after downloading. Furthermore, the total MARS score only correlated with app store rating at T=0.12, which, at P=.20, did not meet our threshold for significance.

Conclusions

More popular mental health apps receive better ratings of user experience than less popular ones. However, user experience does not predict sustained engagement with mental health apps. Thus, mental health app developers and evaluators need to better understand user experience and engagement, as well as to define sustained engagement, what leads to it, and how to create products that achieve it. This understanding might be supported by better collaboration between industry and academic teams to advance a science of engagement.