Course and predictors of eating disorder symptoms, anxiety symptoms, and pandemic-related eating disorder concerns among adults with eating disorders during the first year of the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic and public health mitigation measures have negatively impacted individuals with eating disorders (ED). We evaluated changes in and predictors of ED symptoms, pandemic-related ED concerns, and anxiety symptoms across the first 12 months of the COVID-19 pandemic among individuals with self-reported EDs in the United States (US), Sweden (SE), and the Netherlands (NL). METHOD: Participants in the US (N = 510), SE (N = 982), and NL (N = 510) completed an online survey assessing ED symptoms (binge eating, restriction, compensatory behaviors, and anxiety about being unable to exercise), general anxiety symptoms, and pandemic-related ED concerns about accessing food, lack of structure and social support, being in a triggering environment, and food and treatment costs. In the US and NL, respondents completed surveys beginning April 2020 and continuing monthly for a year. In SE, respondents completed baseline surveys in May 2020, a six-month follow-up around December 2020, and a 12-month follow-up in May 2021. RESULTS: Three patterns emerged: (1) a curvilinear course with the highest level of symptoms at baseline, declining through November 2020, and increasing through the rest of the year; (2) a linear declining course over time; and (3) a stable course with no changes. Worries about COVID-19 infection, lockdown, concerns about lack of structure and social support, and concerns about accessing food consistent with one's recovery meal plan predicted increases in ED symptoms. DISCUSSION: ED symptoms tracked with pandemic-related concerns in people with EDs. Conceptualizing predictors of symptoms may inform therapy and public health resources that reduce the impact of pandemics on mental health. PUBLIC SIGNIFICANCE: Our findings suggest that the COVID-19 pandemic had negative impacts on people with eating disorders, including amplification of mental health symptoms and stressors around peak periods of infection and COVID-19 restrictions. These findings inform medical providers, policy-makers, and community-based supports about the information and resource needs of this group to ensure efficient dissemination in future public health emergencies and during the ongoing COVID-19 pandemic.

Causal Factors of Anxiety and Depression in College Students: Longitudinal Ecological Momentary Assessment and Causal Analysis Using Peter and Clark Momentary Conditional Independence.

BACKGROUND: Across college campuses, the prevalence of clinically relevant depression or anxiety is affecting more than 27% of the college population at some point between entry to college and graduation. Stress and self-esteem have both been hypothesized to contribute to depression and anxiety levels. Although contemporaneous relationships between these variables have been well-defined, the causal relationship between these mental health factors is not well understood, as frequent sampling can be invasive, and many of the current causal techniques are not well suited to investigate correlated variables. OBJECTIVE: This study aims to characterize the causal and contemporaneous networks between these critical mental health factors in a cohort of first-year college students and then determine if observed results replicate in a second, distinct cohort. METHODS: Ecological momentary assessments of depression, anxiety, stress, and self-esteem were obtained weekly from two cohorts of first-year college students for 40 weeks (1 academic year). We used the Peter and Clark Momentary Conditional Independence algorithm to identify the contemporaneous (t) and causal (t-1) network structures between these mental health metrics. RESULTS: All reported results are significant at P<.001 unless otherwise stated. Depression was causally influenced by self-esteem (t-1 rp, cohort 1 [C1]=-0.082, cohort 2 [C2]=-0.095) and itself (t-1 rp, C1=0.388, C2=0.382) in both cohorts. Anxiety was causally influenced by stress (t-1 rp, C1=0.095, C2=0.104), self-esteem (t-1 rp, C1=-0.067, C2=-0.064, P=.002), and itself (t-1 rp, of C1=0.293, C2=0.339) in both cohorts. A causal link between anxiety and depression was observed in the first cohort (t-1 rp, C1=0.109) and only observed in the second cohort with a more liberal threshold (t-1 rp, C2=0.044, P=.03). Self-esteem was only causally influenced by itself (t-1 rp, C1=0.389, C2=0.393). Stress was only causally influenced by itself (t-1 rp, C1=0.248, C2=0.273). Anxiety had positive contemporaneous links to depression (t rp, C1=0.462, C2=0.444) and stress (t rp, C1=0.354, C2=0.358). Self-esteem had negative contemporaneous links to each of the other three mental health metrics, with the strongest negative relationship being stress (t rp, C1=-0.334, C2=-0.340), followed by depression (t rp, C1=-0.302, C2=-0.274) and anxiety (t rp, C1=-0.256, C2=-0.208). Depression had positive contemporaneous links to anxiety (previously mentioned) and stress (t rp, C1=0.250, C2=0.231). CONCLUSIONS: This paper is an initial attempt to describe the contemporaneous and causal relationships among these four mental health metrics in college students. We replicated previous research identifying concurrent relationships between these variables and extended them by identifying causal links among these metrics. These results provide support for the vulnerability model of depression and anxiety. Understanding how causal factors impact the evolution of these mental states over time may provide key information for targeted treatment or, perhaps more importantly, preventative interventions for individuals at risk for depression and anxiety.

Fusing Mobile Phone Sensing and Brain Imaging to Assess Depression in College Students.

As smartphone usage has become increasingly prevalent in our society, so have rates of depression, particularly among young adults. Individual differences in smartphone usage patterns have been shown to reflect individual differences in underlying affective processes such as depression (Wang et al., 2018). In the current study, a positive relationship was identified between smartphone screen time (e.g., phone unlock duration) and resting-state functional connectivity (RSFC) between the subgenual cingulate cortex (sgCC), a brain region implicated in depression and antidepressant treatment response, and regions of the ventromedial/orbitofrontal cortex (OFC), such that increased phone usage was related to stronger connectivity between these regions. This cluster was subsequently used to constrain subsequent analyses looking at individual differences in depressive symptoms in the same cohort and observed partial replication in a separate cohort. Similar analyses were subsequently performed on metrics of circadian rhythm consistency showing a negative relationship between connectivity of the sgCC and OFC. The data and analyses presented here provide relatively simplistic preliminary analyses which replicate and provide an initial step in combining functional brain activity and smartphone usage patterns to better understand issues related to mental health. Smartphones are a prevalent part of modern life and the usage of mobile sensing data from smartphones promises to be an important tool for mental health diagnostics and neuroscience research.