Mental Health Self-Tracking Preferences of Young Adults With Depression and Anxiety Not Engaged in Treatment: Qualitative Analysis.

BACKGROUND: Despite the high prevalence of anxiety and depression among young adults, many do not seek formal treatment. Some may turn to digital mental health tools for support instead, including to self-track moods, behaviors, and other variables related to mental health. Researchers have sought to understand processes and motivations involved in self-tracking, but few have considered the specific needs and preferences of young adults who are not engaged in treatment and who seek to use self-tracking to support mental health. OBJECTIVE: This study seeks to assess the types of experiences young adults not engaged in treatment have had with digital self-tracking for mood and other mental health data and to assess how young adults not seeking treatment want to engage in self-tracking to support their mental health. METHODS: We conducted 2 online asynchronous discussion groups with 50 young adults aged 18 years to 25 years who were not engaged in treatment. Participants were recruited after indicating moderate to severe symptoms of depression or anxiety on screening surveys hosted on the website of Mental Health America. Participants who enrolled in the study responded anonymously to discussion prompts on a message board, as well as to each other's responses, and 3 coders performed a thematic analysis of their responses. RESULTS: Participants had mixed experiences with self-tracking in the past, including disliking when tracking highlighted unwanted behaviors and discontinuing tracking for a variety of reasons. They had more positive past experiences tracking behaviors and tasks they wanted to increase, using open-ended journaling, and with gamified elements to increase motivation. Participants highlighted several design considerations they wanted self-tracking tools to address, including building self-understanding; organization, reminders, and structure; and simplifying the self-tracking experience. Participants wanted self-tracking to help them identify their feelings and how their feelings related to other variables like sleep, exercise, and events in their lives. Participants also highlighted self-tracking as useful for motivating and supporting basic activities and tasks of daily living during periods of feeling overwhelmed or low mood and providing a sense of accomplishment and stability. Although self-tracking can be burdensome, participants were interested and provided suggestions for simplifying the process. CONCLUSIONS: These young adults not engaged in treatment reported interest in using self-tracking to build self-understanding as a goal in and of itself or as a first step in contemplating and preparing for behavior change or treatment-seeking. Alexithymia, amotivation, and feeling overwhelmed may serve both as barriers to self-tracking and opportunities for self-tracking to help.

From formative design to service-ready therapeutic: A pragmatic approach to designing digital mental health interventions across domains.

As digital mental health interventions (DMHIs) proliferate, there is a growing need to understand the complexities of moving these tools from concept and design to service-ready products. We highlight five case studies from a center that specializes in the design and evaluation of digital mental health interventions to illustrate pragmatic approaches to the development of digital mental health interventions, and to make transparent some of the key decision points researchers encounter along the design-to-product pipeline. Case studies cover different key points in the design process and focus on partnership building, understanding the problem or opportunity, prototyping the product or service, and testing the product or service. We illustrate lessons learned and offer a series of questions researchers can use to navigate key decision points in the digital mental health intervention (DMHI) development process.

Changes in Learning From Social Feedback After Web-Based Interpretation Bias Modification: Secondary Analysis of a Digital Mental Health Intervention Among Individuals With High Social Anxiety Symptoms.

BACKGROUND: Biases in social reinforcement learning, or the process of learning to predict and optimize behavior based on rewards and punishments in the social environment, may underlie and maintain some negative cognitive biases that are characteristic of social anxiety. However, little is known about how cognitive and behavioral interventions may change social reinforcement learning in individuals who are anxious. OBJECTIVE: This study assessed whether a scalable, web-based cognitive bias modification for interpretations (CBM-I) intervention changed social reinforcement learning biases in participants with high social anxiety symptoms. This study focused on 2 types of social reinforcement learning relevant to social anxiety: learning about other people and learning about one's own social performance. METHODS: Participants (N=106) completed 2 laboratory sessions, separated by 5 weeks of ecological momentary assessment tracking emotion regulation strategy use and affect. Approximately half (n=51, 48.1%) of the participants completed up to 6 brief daily sessions of CBM-I in week 3. Participants completed a task that assessed social reinforcement learning about other people in both laboratory sessions and a task that assessed social reinforcement learning about one's own social performance in the second session. Behavioral data from these tasks were computationally modeled using Q-learning and analyzed using mixed effects models. RESULTS: After the CBM-I intervention, participants updated their beliefs about others more slowly (P=.04; Cohen d=-0.29) but used what they learned to make more accurate decisions (P=.005; Cohen d=0.20), choosing rewarding faces more frequently. These effects were not observed among participants who did not complete the CBM-I intervention. Participants who completed the CBM-I intervention also showed less-biased updating about their social performance than participants who did not complete the CBM-I intervention, learning similarly from positive and negative feedback and from feedback on items related to poor versus good social performance. Regardless of the intervention condition, participants at session 2 versus session 1 updated their expectancies about others more from rewarding (P=.003; Cohen d=0.43) and less from punishing outcomes (P=.001; Cohen d=-0.47), and they became more accurate at learning to avoid punishing faces (P=.001; Cohen d=0.20). CONCLUSIONS: Taken together, our results provide initial evidence that there may be some beneficial effects of both the CBM-I intervention and self-tracking of emotion regulation on social reinforcement learning in individuals who are socially anxious, although replication will be important.

Examining social reinforcement learning in social anxiety.

BACKGROUND AND OBJECTIVES: Reinforcement learning biases have been empirically linked to anhedonia in depression and theoretically linked to social anhedonia in social anxiety disorder, but little work has directly assessed how socially anxious individuals learn from social reward and punishment. METHODS: N = 157 individuals high and low in social anxiety symptoms completed a social probabilistic selection task that involved selecting between pairs of neutral faces with varying probabilities of changing to a happy or angry face. Computational modeling was performed to estimate learning rates. Accuracy in choosing the more rewarding face was also analyzed. RESULTS: No significant group differences were found for learning rates. Contrary to hypotheses, participants high in social anxiety showed impaired punishment learning accuracy; they were more accurate at choosing the most rewarding face than they were at avoiding the most punishing face, and their punishment learning accuracy was lower than that of participants low in social anxiety. Secondary analyses found that high (vs. low) social anxiety participants were less accurate at selecting the more rewarding face on more (vs. less) punishing face pairs. LIMITATIONS: Stimuli were static, White, facial images, which lack important social cues (e.g., movement, sound) and diversity, and participants were largely non-Hispanic, White undergraduates, whose social reinforcement learning may differ from individuals at different developmental stages and those holding more marginalized identities. CONCLUSIONS: Socially anxious individuals may be less accurate at learning to avoid social punishment, which may maintain negative beliefs through an interpersonal stress generation process.

Effects of Mass Shootings on Mental Illness Stigma in the United States.

Although the vast majority of people with mental illness (PWMI) are not violent, Americans tend to think they are more dangerous than the general population. Because negative media portrayals may contribute to stigma, we used time-series analyses to examine changes in the public's perceived dangerousness of PWMI around six mass shootings whose perpetrators were reported to have a mental illness. From 2011 to 2019, 38,094 U.S. participants completed an online study assessing implicit and explicit perceived dangerousness of PWMI. There were large, upward spikes in perceived dangerousness the week of the Sandy Hook mass shooting that were relatively short-lived. However, there was not a consistent pattern of effects for other events analyzed, and any other spikes observed were smaller. Effects tended to be larger for explicit versus implicit perceived dangerousness. Sandy Hook seemed to temporarily worsen perceived dangerousness of PWMI, but this pattern was not observed for other mass shootings.

Building an emotion regulation recommender algorithm for socially anxious individuals using contextual bandits.

OBJECTIVES: Poor emotion regulation (ER) has been implicated in many mental illnesses, including social anxiety disorder. To work towards a scalable, low-cost intervention for improving ER, we developed a novel contextual recommender algorithm for ER strategies. DESIGN: N = 114 socially anxious participants were prompted via a mobile app up to six times daily for five weeks to report their emotional state, use of 19 different ER strategies (or no strategy), physical location, and social context. Information from passive sensors was also collected. METHODS: Given the large number of ER strategies, we used two different approaches for variable reduction: (1) grouping ER strategies into categories based on a prior meta-analysis, and (2) considering only the ten most frequently used strategies. For each approach, an algorithm that recommends strategies based on one's current context was compared with an algorithm that recommends ER strategies randomly, an algorithm that always recommends cognitive reappraisal, and the person's observed ER strategy use. Contextual bandits were used to predict the effectiveness of the strategies recommended by each policy. RESULTS: When strategies were grouped into categories, the contextual algorithm was not the best performing policy. However, when the top ten strategies were considered individually, the contextual algorithm outperformed all other policies. CONCLUSIONS: Grouping strategies into categories may obscure differences in their contextual effectiveness. Further, using strategies tailored to context is more effective than using cognitive reappraisal indiscriminately across all contexts. Future directions include deploying the contextual recommender algorithm as part of a just-in-time intervention to assess real-world efficacy. PRACTITIONER POINTS: Emotion regulation strategies vary in their effectiveness across different contexts. An algorithm that recommends emotion regulation strategies based on a person's current context may one day be used as an adjunct to treatment to help dysregulated individuals optimize their in-the-moment emotion regulation. Recommending flexible use of emotion regulation strategies across different contexts may be more effective than recommending cognitive reappraisal indiscriminately across all contexts.

Emotion Malleability Beliefs and Emotion Experience and Regulation in the Daily Lives of People with High Trait Social Anxiety.

BACKGROUND: The extent to which a person believes they can change or control their own emotions is associated with trait-level symptoms of mood and anxiety-related psychopathology. Method: The present study examined how this belief relates to momentary and daily self-reports of affect, emotion regulation tendencies, and perceived effectiveness of emotion regulation attempts throughout a five-week experience sampling study conducted in N = 113 high socially anxious people (https://osf.io/eprwt/). RESULTS: Results suggest that people with relatively stronger beliefs that their emotions are malleable experienced more momentary and daily positive affect (relative to negative affect), even after controlling for social anxiety symptom severity (although only daily positive affect, and not momentary positive affect, remained significant after correcting for false discovery rate). However, emotion malleability beliefs were not uniquely associated with other emotion regulation-related outcomes in daily life, despite theory suggesting malleability beliefs influence motivation to engage in emotion regulation. CONCLUSION: The paucity of significant associations observed between trait malleability beliefs and momentary and daily self-reports of emotion regulation (despite consistent findings of such relationships at trait levels) calls for additional research to better understand the complex dynamics of emotion beliefs in daily life.

Social anxiety and dynamic social reinforcement learning in a volatile environment.

Adaptive social behavior requires learning probabilities of social reward and punishment, and updating these probabilities when they change. Given prior research on aberrant reinforcement learning in affective disorders, this study examines how social anxiety affects probabilistic social reinforcement learning and dynamic updating of learned probabilities in a volatile environment. N=222 online participants completed questionnaires and a computerized ball-catching game with changing probabilities of reward and punishment. Dynamic learning rates were estimated to assess the relative importance ascribed to new information in response to volatility. Mixed-effects regression was used to analyze throw patterns as a function of social anxiety symptoms. Higher social anxiety predicted fewer throws to the previously punishing avatar and different learning rates after certain role changes, suggesting that social anxiety may be characterized by difficulty updating learned social probabilities. Socially anxious individuals may miss the chance to learn that a once-punishing situation no longer poses a threat.

Impaired reward prediction error encoding and striatal-midbrain connectivity in depression.

Anhedonia (hyposensitivity to rewards) and negative bias (hypersensitivity to punishments) are core features of major depressive disorder (MDD), which could stem from abnormal reinforcement learning. Emerging evidence highlights blunted reward learning and reward prediction error (RPE) signaling in the striatum in MDD, although inconsistencies exist. Preclinical studies have clarified that ventral tegmental area (VTA) neurons encode RPE and habenular neurons encode punishment prediction error (PPE), which are then transmitted to the striatum and cortex to guide goal-directed behavior. However, few studies have probed striatal activation, and functional connectivity between VTA-striatum and VTA-habenula during reward and punishment learning respectively, in unmedicated MDD. To fill this gap, we acquired fMRI data from 25 unmedicated MDD and 26 healthy individuals during a monetary instrumental learning task and utilized a computational modeling approach to characterize underlying neural correlates of RPE and PPE. Relative to controls, MDD individuals showed impaired reward learning, blunted RPE signal in the striatum and overall reduced VTA-striatal connectivity to feedback. Critically, striatal RPE signal was increasingly blunted with more major depressive episodes (MDEs). No group differences emerged in PPE signals in the habenula and VTA or in connectivity between these regions. However, PPE signals in the habenula correlated positively with number of MDEs. These results highlight impaired reward learning, disrupted RPE signaling in the striatum (particularly among individuals with more lifetime MDEs) as well as reduced VTA-striatal connectivity in MDD. Collectively, these findings highlight reward-related learning deficits in MDD and their underlying pathophysiology.

Moderators of age effects on attention bias toward threat and its association with anxiety.

OBJECTIVE: The current study used a research domain criteria (RDoC) approach to assess age differences in multiple indicators of attention bias and its ties to anxiety, examining stimulus domain and cognitive control as moderators of older adults' oft-cited positivity effect (bias towards positive and away from negative stimuli, when compared to younger adults). METHOD: 38 Younger adults and 38 older adults were administered a battery of cognitive control and trait and state anxiety measures, and completed a dot-probe task to assess attention bias, during which reaction time and fixation duration (using eye-tracking) were recorded for negative and neutral social (a salient threat domain for younger adults) and physical (a salient threat domain for older adults) stimuli. RESULTS: Mixed-effects models demonstrated that older adults were faster to react to dot-probe trials when the probe appeared in the place of negative (vs. neutral) physical stimuli, but displayed no difference in reaction time for social stimuli. Also, older (vs. younger) adults with lower levels of cognitive control were less negatively biased in their visual fixation to social stimuli. A negative reaction time attention bias on the dot-probe task predicted greater trait anxiety among participants with low levels of cognitive control, with a more complex pattern predicting state anxiety. CONCLUSION: Older adults do attend to social and physical stimuli differently. When stimuli concern a social threat, older adults do not preferentially attend to either neutral or negative stimuli. However, when stimuli concern physical threat, older adults preferentially attend to negative stimuli. Threat biases are associated with anxiety at all ages for those with low cognitive control.

Rethinking butterflies: the affective, physiological, and performance effects of reappraising arousal during social evaluation.

This study examined the effects of reappraising stress arousal on affective displays, physiological responses, and social performance during an evaluative situation. Participants were sampled from across the social anxiety spectrum and instructed to reappraise arousal as beneficial or received no instructions. Independent raters coded affective displays, nonverbal signaling, and speech performance. Saliva samples collected at baseline and after evaluation were assayed for salivary alpha-amylase (sAA), a protein that indexes sympathetic activation. Arousal reappraisal participants exhibited less shame and anxiety, less avoidant nonverbal signaling, and performed marginally better than no instruction controls. Reappraisal participants also exhibited increased levels of sAA and increased appraisals of coping resources compared with controls. Furthermore, stress appraisals mediated relationships between reappraisal and affective displays. This research indicates that reframing stress arousal can improve behavioral displays of affect during evaluative situations via altering cognitive appraisals.