Daniel R. Strunk

Objective One barrier to treatment seeking, uptake, and engagement is the belief that nothing can be done to reduce symptoms. Given the widespread use of social media to disseminate information about important issues, including psychological health, we sought to understand how the influence of social media communication regarding mental health impacts viewers' beliefs about psychopathology recovery. Method Undergraduate participants from a large Midwestern university ( N = 322) were randomized to view a series of Tweets characterizing psychopathology from a fixed mindset perspective, a growth mindset perspective, or, in the control condition, Tweets unrelated to psychopathology. Afterward, they completed a series of questionnaires designed to assess beliefs about recovery from depression and anxiety. Results Participants in the growth mindset condition endorsed less pessimistic beliefs about their ability (i.e., self‐efficacy) to alleviate symptoms of depression and anxiety, and they believed these symptoms to be less stable and innate relative to those in the fixed mindset condition. Conclusion Social media communication that characterizes psychopathology from a growth mindset perspective may be a viable intervention for improving beliefs around mental health self‐efficacy and the malleable nature of mental illness, particularly depression and anxiety. Clinicians may be able to use social media platforms to promote functional beliefs around mental illness.

Background Although the importance of sleep difficulties in emotional disorders has long been acknowledged, the nature of the potential reciprocal relationship between sleep and depressive symptoms is not yet well understood. The coronavirus disease 19 pandemic provided a unique opportunity to study the interrelation of these symptoms over a period marked by increases in sleep and psychological difficulties. Methods Using online data collection, we followed 1200 adults (59% male) through 1 year of the pandemic. Measures of sleep disturbance and depressive symptoms were assessed at eight time points. Factor analysis of the items from these two measures suggested separate insomnia and depressive symptom factors. A random intercept cross‐lagged panel model was used to assess within‐person relationships between factor analysis‐informed subscales of insomnia and depressive symptoms. Results Depressive symptoms predicted subsequent changes in insomnia symptoms; however, insomnia did not predict changes in depressive symptoms. Conclusions Our findings suggest the impact of depressive symptoms on insomnia is evident, but the reverse is not. Implications of this finding along with the need for research addressing depressive symptoms and insomnia as treatment targets are discussed.