Co-existing mental and somatic conditions in Swedish children with the avoidant restrictive food intake disorder phenotype.

Background: Avoidant restrictive food intake disorder (ARFID) is a feeding and eating disorder, characterized by limited variety and/or quantity of food intake impacting physical health and psychosocial functioning. Children with ARFID often present with a range of psychiatric and somatic symptoms, and therefore consult various pediatric subspecialties; large-scale studies mapping comorbidities are however lacking. To characterize health care needs of people with ARFID, we systematically investigated ARFID-related mental and somatic conditions in 616 children with ARFID and >30,000 children without ARFID. Methods: In a Swedish twin cohort, we identified the ARFID phenotype in 6-12-year-old children based on parent-reports and register data. From >1,000 diagnostic ICD-codes, we specified mental and somatic conditions within/across ICD-chapters, number of distinct per-person diagnoses, and inpatient treatment days between birth and 18th birthday (90 outcomes). Hazard ratios (HR) and incidence rate ratios (IRR) were calculated. Findings: Relative risks of neurodevelopmental, gastrointestinal, endocrine/metabolic, respiratory, neurological, and allergic disorders were substantially increased in ARFID (e.g., autism HR[CI95%]=9.7[7.5-12.5], intellectual disability 10.3[7.6-13.9], gastroesophageal reflux disease 6.7[4.6-9.9], pituitary conditions 5.6[2.7-11.3], chronic lower respiratory diseases 4.9[2.4-10.1], epilepsy 5.8[4.1-8.2]). ARFID was not associated with elevated risks of autoimmune illnesses and obsessive-compulsive disorder. Children with ARFID had a significantly higher number of distinct mental diagnoses (IRR[CI95%]=4.7[4.0-5.4]) and longer duration of hospitalizations (IRR[CI95%]=5.5[1.7-17.6]) compared with children without ARFID. Children with ARFID were diagnosed earlier with a mental condition than children without ARFID. No sex-specific differences emerged. Interpretation: This study yields the broadest and most detailed evidence of co-existing mental and somatic conditions in the largest sample of children with ARFID to date. Findings suggest a complex pattern of health needs in youth with ARFID, underscoring the critical importance of attention to the illness across all pediatric specialties. Funding: Fredrik and Ingrid Thurings Foundation, Mental Health Foundation.

Proposal for increasing diagnostic clarity in research and clinical practice by renaming and reframing atypical anorexia nervosa as "Restrictive Eating Disorder" (RED).

Atypical anorexia nervosa (AAN) in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5), is characterized by meeting all criteria for anorexia nervosa (AN) except for weight being within or above the "normal" range despite significant weight loss. The current definition is plagued by several problems, resulting in widely heterogeneous operationalizations in research and clinical practice. As such, the poorly defined diagnosis of AAN negatively impacts affected individuals and frustrates research attempts to better understand the syndrome. We consider conceptual flaws in the AAN description and contend that the undefined weight range and nature of weight loss renders these two factors functionally inapplicable in research and practice. They also represent a departure from the originally intended use of the AAN category, i.e., arresting a negative weight trajectory likely to result in AN, making the target population, and the application of the label, unclear. We propose revised criteria and a new name, restrictive eating disorder (RED), intended to reduce stigma and encompass a wide but better-defined range of presentations. The RED criteria focus on clinically significant restrictive behavior that disrupts normal living (i.e., impairment), and cognitive symptoms of overevaluation, disturbed experience, and lack of recognition of illness seriousness. We believe that RED may enable more appropriate clinical application, but also inspire coordinated research toward a more valid psychiatric nosology in the eating disorders field.

Self-reported expertise and confidence in diagnosing and treating avoidant restrictive food intake disorder among Swedish clinicians.

OBJECTIVE: To assess self-reported knowledge and confidence regarding avoidant restrictive food intake disorder (ARFID) diagnosis and treatment in Swedish clinicians from various disciplines. METHOD: The study included 489 clinicians who attended educational lectures about ARFID. Participants responded to 20 ARFID-related questions and statements using the online audience engagement platform Mentimeter. Items assessed ARFID-related knowledge, education, and experience, as well as treatment methods offered to ARFID patients at clinicians' healthcare units. RESULTS: We found predominantly correct responses to three basic knowledge-based items about ARFID. However, most participants (64.0%) reported never having received education about ARFID, and few participants reported feeling confident in their ability to diagnose (13.4%) and treat (10.7%) ARFID. Nearly half the sample reported either not knowing which ARFID treatments their unit offered (22.3%) or that no treatment was offered (21.3%). CONCLUSION: Experience and confidence in diagnosing and treating ARFID are generally low in Swedish clinicians, and many individuals with ARFID do not receive treatment. We identify a pressing need for resources, clearer organisation, and structure, and for additional education and training opportunities for clinicians meeting individuals with ARFID.

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.

First-Gen Lens: Assessing Mental Health of First-Generation Students across Their First Year at College Using Mobile Sensing.

The transition from high school to college is a taxing time for young adults. New students arriving on campus navigate a myriad of challenges centered around adapting to new living situations, financial needs, academic pressures and social demands. First-year students need to gain new skills and strategies to cope with these new demands in order to make good decisions, ease their transition to independent living and ultimately succeed. In general, first-generation students are less prepared when they enter college in comparison to non-first-generation students. This presents additional challenges for first-generation students to overcome and be successful during their college years. We study first-year students through the lens of mobile phone sensing across their first year at college, including all academic terms and breaks. We collect longitudinal mobile sensing data for N=180 first-year college students, where 27 of the students are first-generation, representing 15% of the study cohort and representative of the number of first-generation students admitted each year at the study institution, Dartmouth College. We discuss risk factors, behavioral patterns and mental health of first-generation and non-first-generation students. We propose a deep learning model that accurately predicts the mental health of first-generation students by taking into account important distinguishing behavioral factors of first-generation students. Our study, which uses the StudentLife app, offers data-informed insights that could be used to identify struggling students and provide new forms of phone-based interventions with the goal of keeping students on track.

Nurses' Experiences of Caring for Patients With Suspected or Confirmed COVID-19 in the Initial Stage of the Pandemic.

Introduction: Nursing staff have faced various challenges during the global pandemic of COVID-19 such as nursing shortages. The great number of COVID-19 patients requiring hospitalization placed heavy demands on healthcare staff to maintain patient safety and to work according to constantly changing guidelines to prevent the spread of infection. Objective: The objective was to describe nurses' experiences of caring for patients with suspected or confirmed COVID-19 in the initial phase of the pandemic. Methods: The study has a qualitative design. Semi-structured interviews were conducted with seven nurses in primary care and hospital care during the initial stage of the pandemic. Qualitative content analysis with an inductive approach was used. Results: The nurses expressed that the working routines changed very quickly at the onset of the pandemic. A triage system was implemented to care for patients with symptoms of COVID-19 to prevent transmission between patients. A major change was the constant use of personal protective equipment in patient care. The nurses also experienced a sense of inadequacy regarding the care of the patients and became emotionally affected and exhausted. Conclusion: The nurses experienced that many patients worsened clinically, leading to exhausting and difficult nursing care situations. They also experienced increasing responsibility since new protective equipment and procedures needed to be quickly implemented according to frequently changing recommendations, causing the nurses to feel uncertain about how to maintain patient safety. Support from colleagues was crucial to cope throughout the initial stage of the pandemic.

Validity of eating disorder diagnoses in the Swedish national patient register.

The Swedish National Patient Register (NPR) includes population-level longitudinal data, and determining the validity of NPR diagnoses is critical to undergirding the research and policy recommendations they inform. Sweden also has the integrated "Riksät" and "Stepwise" National Quality Registers (QR), with data from specialized eating disorder (ED) treatment based on structured, valid assessment methods. To validate NPR ED diagnoses, we compared ICD-10-based anorexia nervosa (AN), bulimia nervosa (BN), and unspecified ED in NPR to DSM-IV-based AN, BN, and ED not otherwise specified category (EDNOS) in QR. Patients' first diagnoses registered in QR between February 2008 and August 2013 were compared with NPR diagnoses entered within ±1 month (N = 2074). QR registration includes the semi-structured DSM-IV-based Structured ED Interview. Each ED diagnosis was analyzed separately for degree of match using several indices: overall agreement, sensitivity, positive predictive value, specificity, negative predictive value, area under the curve, and Cohen's kappa. Results showed moderate to excellent agreement depending on estimate (e.g. positive predictive values AN: 0.747; BN:.836; EDNOS: 0.761), except for a somewhat low sensitivity for BN, and EDNOS agreement was overall the lowest. Case prevalence in the NPR and QR was highly similar for AN, and within five percentage points for BN and EDNOS. Generalizability is hampered by limited age range and diagnostic resolution as well as few males. Available data precluded study of presence/absence of ED, and complementary approaches are considered for future research. We conclude that NPR ED diagnoses have acceptable validity and are appropriate for use in research.

Mental Health and Behavior of College Students During the COVID-19 Pandemic: Longitudinal Mobile Smartphone and Ecological Momentary Assessment Study, Part II.

BACKGROUND: Since late 2019, the lives of people across the globe have been disrupted by COVID-19. Millions of people have become infected with the disease, while billions of people have been continually asked or required by local and national governments to change their behavioral patterns. Previous research on the COVID-19 pandemic suggests that it is associated with large-scale behavioral and mental health changes; however, few studies have been able to track these changes with frequent, near real-time sampling or compare these changes to previous years of data for the same individuals. OBJECTIVE: By combining mobile phone sensing and self-reported mental health data in a cohort of college-aged students enrolled in a longitudinal study, we seek to understand the behavioral and mental health impacts associated with the COVID-19 pandemic, measured by interest across the United States in the search terms coronavirus and COVID fatigue. METHODS: Behaviors such as the number of locations visited, distance traveled, duration of phone use, number of phone unlocks, sleep duration, and sedentary time were measured using the StudentLife mobile smartphone sensing app. Depression and anxiety were assessed using weekly self-reported ecological momentary assessments, including the Patient Health Questionnaire-4. The participants were 217 undergraduate students. Differences in behaviors and self-reported mental health collected during the Spring 2020 term, as compared to previous terms in the same cohort, were modeled using mixed linear models. RESULTS: Linear mixed models demonstrated differences in phone use, sleep, sedentary time and number of locations visited associated with the COVID-19 pandemic. In further models, these behaviors were strongly associated with increased interest in COVID fatigue. When mental health metrics (eg, depression and anxiety) were added to the previous measures (week of term, number of locations visited, phone use, sedentary time), both anxiety and depression (P<.001) were significantly associated with interest in COVID fatigue. Notably, these behavioral and mental health changes are consistent with those observed around the initial implementation of COVID-19 lockdowns in the spring of 2020. CONCLUSIONS: In the initial lockdown phase of the COVID-19 pandemic, people spent more time on their phones, were more sedentary, visited fewer locations, and exhibited increased symptoms of anxiety and depression. As the pandemic persisted through the spring, people continued to exhibit very similar changes in both mental health and behaviors. Although these large-scale shifts in mental health and behaviors are unsurprising, understanding them is critical in disrupting the negative consequences to mental health during the ongoing pandemic.

On the Transition of Social Interaction from In-Person to Online: Predicting Changes in Social Media Usage of College Students during the COVID-19 Pandemic based on Pre-COVID-19 On-Campus Colocation.

Pandemics significantly impact human daily life. People throughout the world adhere to safety protocols (e.g., social distancing and self-quarantining). As a result, they willingly keep distance from workplace, friends and even family. In such circumstances, in-person social interactions may be substituted with virtual ones via online channels, such as, Instagram and Snapchat. To get insights into this phenomenon, we study a group of undergraduate students before and after the start of COVID-19 pandemic. Specifically, we track N=102 undergraduate students on a small college campus prior to the pandemic using mobile sensing from phones and assign semantic labels to each location they visit on campus where they study, socialize and live. By leveraging their colocation network at these various semantically labeled places on campus, we find that colocations at certain places that possibly proxy higher in-person social interactions (e.g., dormitories, gyms and Greek houses) show significant predictive capability in identifying the individuals' change in social media usage during the pandemic period. We show that we can predict student's change in social media usage during COVID-19 with an F1 score of 0.73 purely from the in-person colocation data generated prior to the pandemic.

Mental Health and Behavior of College Students During the Early Phases of the COVID-19 Pandemic: Longitudinal Smartphone and Ecological Momentary Assessment Study.

BACKGROUND: The vast majority of people worldwide have been impacted by coronavirus disease (COVID-19). In addition to the millions of individuals who have been infected with the disease, billions of individuals have been asked or required by local and national governments to change their behavioral patterns. Previous research on epidemics or traumatic events suggests that this can lead to profound behavioral and mental health changes; however, researchers are rarely able to track these changes with frequent, near-real-time sampling or compare their findings to previous years of data for the same individuals. OBJECTIVE: By combining mobile phone sensing and self-reported mental health data among college students who have been participating in a longitudinal study for the past 2 years, we sought to answer two overarching questions. First, have the behaviors and mental health of the participants changed in response to the COVID-19 pandemic compared to previous time periods? Second, are these behavior and mental health changes associated with the relative news coverage of COVID-19 in the US media? METHODS: Behaviors such as the number of locations visited, distance traveled, duration of phone usage, number of phone unlocks, sleep duration, and sedentary time were measured using the StudentLife smartphone sensing app. Depression and anxiety were assessed using weekly self-reported ecological momentary assessments of the Patient Health Questionnaire-4. The participants were 217 undergraduate students, with 178 (82.0%) students providing data during the Winter 2020 term. Differences in behaviors and self-reported mental health collected during the Winter 2020 term compared to previous terms in the same cohort were modeled using mixed linear models. RESULTS: During the first academic term impacted by COVID-19 (Winter 2020), individuals were more sedentary and reported increased anxiety and depression symptoms (P<.001) relative to previous academic terms and subsequent academic breaks. Interactions between the Winter 2020 term and the week of the academic term (linear and quadratic) were significant. In a mixed linear model, phone usage, number of locations visited, and week of the term were strongly associated with increased amount of COVID-19-related news. When mental health metrics (eg, depression and anxiety) were added to the previous measures (week of term, number of locations visited, and phone usage), both anxiety (P<.001) and depression (P=.03) were significantly associated with COVID-19-related news. CONCLUSIONS: Compared with prior academic terms, individuals in the Winter 2020 term were more sedentary, anxious, and depressed. A wide variety of behaviors, including increased phone usage, decreased physical activity, and fewer locations visited, were associated with fluctuations in COVID-19 news reporting. While this large-scale shift in mental health and behavior is unsurprising, its characterization is particularly important to help guide the development of methods to reduce the impact of future catastrophic events on the mental health of the population.

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.

Predicting Brain Functional Connectivity Using Mobile Sensing.

Brain circuit functioning and connectivity between specific regions allow us to learn, remember, recognize and think as humans. In this paper, we ask the question if mobile sensing from phones can predict brain functional connectivity. We study the brain resting-state functional connectivity (RSFC) between the ventromedial prefrontal cortex (vmPFC) and the amygdala, which has been shown by neuroscientists to be associated with mental illness such as anxiety and depression. We discuss initial results and insights from the NeuroSence study, an exploratory study of 105 first year college students using neuroimaging and mobile sensing across one semester. We observe correlations between several behavioral features from students' mobile phones and connectivity between vmPFC and amygdala, including conversation duration (r=0.365, p<0.001), sleep onset time (r=0.299, p<0.001) and the number of phone unlocks (r=0.253, p=0.029). We use a support vector classifier and 10-fold cross validation and show that we can classify whether students have higher (i.e., stronger) or lower (i.e., weaker) vmPFC-amygdala RSFC purely based on mobile sensing data with an F1 score of 0.793. To the best of our knowledge, this is the first paper to report that resting-state brain functional connectivity can be predicted using passive sensing data from mobile phones.

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.