Search

Several studies report incidence of psychiatric symptoms and disorders among patients who recovered from COVID-19; however, little is known about the emotional impact of acute COVID-19 illness and recovery on these survivors. Qualitative methods are ideal for understanding the psychological impact of a novel illness.To describe the emotional experience of acute COVID-19 illness and recovery in patients who contracted the virus during the early months of the pandemic.Semi-structured interviews conducted by consultation-liaison (C-L) psychiatrists were used to elicit participant responses about the emotional impact of the acute and recovery phases of COVID-19 illness. Participants recruited from the Maryland, District of Columbia, and Virginia area were interviewed and audio recorded between June 2020 and December 2020. The research team extracted qualitative themes from the recordings using the principles of thematic analysis.One hundred and one COVID-19 survivors (54 women; mean [SD] age, 50 [14.7] years) were interviewed a mean of 5.16 months after their acute illness, and their responses were audio recorded. Most participants were White (77%), non-Hispanic/Latino (86.1%), and not hospitalized for COVID-19 (87.1%). Coders identified 26 themes from participant responses. The most frequently coded themes included Anxiety/Worry (49), Uncertainty (37), Supportfrom Others (35), Alone/Isolation (32), Positive Reframe/Positive Emotions (32).Survivors who contracted SARS-CoV-2 during the early months of the pandemic described both negative and positive valence emotions. They experienced emotional distress and psychosocial stressors associated with acute illness and recovery but also drew upon personal resiliency to cope. This report highlights the utility of qualitative research methods in identifying emotional responses to a novel illness that may otherwise go unnoted. C-L psychiatrists may be uniquely positioned to work in collaboration with medical colleagues in developing a multidimensional approach to evaluating an emerging illness.

The NIMH Healthy Research Volunteer Dataset is a collection of phenotypic data characterizing healthy research volunteers using clinical assessments such as assays of blood and urine, mental health assessments, diagnostic and dimensional measures of mental health, cognitive and neuropsychological functioning, structural and functional magnetic resonance imaging (MRI), along with diffusion tensor imaging (DTI), and a comprehensive magnetoencephalography battery (MEG). In addition, blood samples of healthy volunteers are banked for future analyses. All data collected in this protocol are broadly shared in the OpenNeuro repository, in the Brain Imaging Data Structure (BIDS) format. In addition, task paradigms and basic pre-processing scripts are shared on GitHub. There are currently few open access MEG datasets, and multimodal neuroimaging datasets are even more rare. Due to its depth of characterization of a healthy population in terms of brain health, this dataset may contribute to a wide array of secondary investigations of non-clinical and clinical research questions.

BACKGROUND The COVID-19 pandemic and its associated restrictions have been a major stressor that has exacerbated mental health worldwide. Qualitative data play a unique role in documenting mental states through both language features and content. Text analysis methods can provide insights into the associations between language use and mental health and reveal relevant themes that emerge organically in open-ended responses. OBJECTIVE The aim of this web-based longitudinal study on mental health during the early COVID-19 pandemic was to use text analysis methods to analyze free responses to the question, “Is there anything else you would like to tell us that might be important that we did not ask about?” Our goals were to determine whether individuals who responded to the item differed from nonresponders, to determine whether there were associations between language use and psychological status, and to characterize the content of responses and how responses changed over time. METHODS A total of 3655 individuals enrolled in the study were asked to complete self-reported measures of mental health and COVID-19 pandemic–related questions every 2 weeks for 6 months. Of these 3655 participants, 2497 (68.32%) provided at least 1 free response (9741 total responses). We used various text analysis methods to measure the links between language use and mental health and to characterize response themes over the first year of the pandemic. RESULTS Response likelihood was influenced by demographic factors and health status: those who were male, Asian, Black, or Hispanic were less likely to respond, and the odds of responding increased with age and education as well as with a history of physical health conditions. Although mental health treatment history did not influence the overall likelihood of responding, it was associated with more negative sentiment, negative word use, and higher use of first-person singular pronouns. Responses were dynamically influenced by psychological status such that distress and loneliness were positively associated with an individual’s likelihood to respond at a given time point and were associated with more negativity. Finally, the responses were negative in valence overall and exhibited fluctuations linked with external events. The responses covered a variety of topics, with the most common being mental health and emotion, social or physical distancing, and policy and government. CONCLUSIONS Our results identify trends in language use during the first year of the pandemic and suggest that both the content of responses and overall sentiments are linked to mental health.

Somatic symptom and related disorders (SSRD) and functional gastrointestinal disorders (FGID) are common causes of morbidity in children and adults. They are associated with impaired functioning in multiple domains and increasing health care utilization and costs. Their complex nature with medical and psychiatric comorbidities, diverse symptomatology, and often waxing and waning course can make them difficult to study and treat. However, there is some literature in this area regarding pharmacologic and behavioral treatment approaches. This review aims to examine the existing evidence for pharmacological treatments of SSRD and FGID. Several categories of psychotropic medications have been found to be efficacious in many of these disorders, including antidepressants, anticonvulsants, benzodiazepines, and antipsychotics. Novel approaches to somatization include treatment with cannabinoids, ketamine, opioid antagonists, and peppermint oil. Data on pharmacological management of heterogeneous somatoform disorders ranges from sparse to substantial. A rehabilitative intervention model consisting of pharmacological and nonpharmacological modalities with simultaneous treatment of psychiatric comorbidities is recommended.

In order to simplify a complex mixture of soluble proteins from tissues, a protocol to fractionate samples prior to two-dimensional (2D) gel electrophoresis has been developed. These methods involve the use of DEAE-Sepharose, SP-Sepharose, and phenyl Sepharose chromatographic columns and the fractionation of the protein mixtures based on differential anionic, cationic, and hydrophobic properties of the proteins, respectively. Fractionation of the soluble proteins with DEAE-Sepharose can result in an increase in the number of detectable 2D gel spots. These gel spots are amenable to protein identification by using in-gel trypsin digestions, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, and peptide mass fingerprinting. The DEAE-Sepharose column fractionation acts to partition soluble proteins from cell extracts. Similarly, a SP-Sepharose column can fractionate soluble proteins and increase the number of detectable gel spots. Lastly, fractionation of cell extract with a phenyl Sepharose column can also result in an increase in the number of detectable 2D gel spots. This chapter describes an easy, inexpensive way to fractionate soluble proteins and a way to better profile proteomes.