COVID-19 Health Beliefs Regarding Mask Wearing and Vaccinations on Twitter: Deep Learning Approach.

Background: Amid the global COVID-19 pandemic, a worldwide infodemic also emerged with large amounts of COVID-19-related information and misinformation spreading through social media channels. Various organizations, including the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC), and other prominent individuals issued high-profile advice on preventing the further spread of COVID-19. Objective: The purpose of this study is to leverage machine learning and Twitter data from the pandemic period to explore health beliefs regarding mask wearing and vaccines and the influence of high-profile cues to action. Methods: A total of 646,885,238 COVID-19-related English tweets were filtered, creating a mask-wearing data set and a vaccine data set. Researchers manually categorized a training sample of 3500 tweets for each data set according to their relevance to Health Belief Model (HBM) constructs and used coded tweets to train machine learning models for classifying each tweet in the data sets. Results: In total, 5 models were trained for both the mask-related and vaccine-related data sets using the XLNet transformer model, with each model achieving at least 81% classification accuracy. Health beliefs regarding perceived benefits and barriers were most pronounced for both mask wearing and immunization; however, the strength of those beliefs appeared to vary in response to high-profile cues to action. Conclusions: During both the COVID-19 pandemic and the infodemic, health beliefs related to perceived benefits and barriers observed through Twitter using a big data machine learning approach varied over time and in response to high-profile cues to action from prominent organizations and individuals.

Relationship between brain stem volume and aggression in children diagnosed with autism spectrum disorder.

BACKGROUND: Aggressive behaviors are common in individuals diagnosed with autism spectrum disorder (ASD) and may be phenotypic indicators of different subtypes within ASD. In current research literature for non-ASD samples, aggression has been linked to several brain structures associated with emotion and behavioral control. However, few if any studies exist investigating brain volume differences in individuals with ASD who have comorbid aggression as indicated by standardized diagnostic and behavioral measures. METHOD: We examined neuroimaging data from individuals rigorously diagnosed with ASD versus typically developing (TD) controls. We began with data from brain volume regions of interest (ROI) taken from previous literature on aggression including the brainstem, amygdala, orbitofrontal cortex, anterior cingulate cortex, and dorsolateral prefrontal cortex. We defined aggression status using the Irritability subscale of the Aberrant Behavior Checklist and used lasso logistic regression to select among these predictor variables. Brainstem volume was the only variable shown to be a predictor of aggression status. RESULTS: We found that smaller brainstem volumes are associated with higher odds of being in the high aggression group. CONCLUSIONS: Understanding brain differences in individuals with ASD who engage in aggressive behavior from those with ASD who do not can inform treatment approaches. Future research should investigate brainstem structure and function in ASD to identify possible mechanisms related to arousal and aggression.

Sticking with it: Psychotherapy outcomes for adults with autism spectrum disorder in a university counseling center setting.

Young adults with autism spectrum disorders (ASD) experience high rates of comorbid mental health concerns in addition to distress arising from the core symptoms of autism. Many adults with ASD seek psychological treatment in outpatient facilities in their communities that are not specifically geared toward individuals with ASD. However, few studies have looked at the effectiveness of standard psychotherapeutic care in adults with ASD. This study aimed to discover how individuals with ASD fare in psychotherapy within a college counseling setting, compared to their neurotypical peers. Clients with ASD (n = 76) or possible ASD (n = 91) were retrospectively identified from counseling center case notes. Data from the Outcome Questionnaire-45 (OQ) were retrieved for each therapy session as a measure of client distress. Clients with ASD showed no difference in level of distress at intake compared to their neurotypical peers (n = 21,546), and improved about the same amount from pre- to post-treatment. However, students with ASD stayed in treatment for significantly more sessions than neurotypical clients, and took significantly longer to achieve maximum improvement on OQ reports. Results are discussed with implications for university and other community based treatment settings. Autism Res 2017, 10: 2048-2055. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This study aimed to discover how individuals with autism spectrum disorders (ASD) fare in psychotherapy within a university counseling setting, compared to their neurotypical peers. Clients with ASD showed no difference in level of distress at intake compared to their neurotypical peers, and improved about the same amount from pre- to post-treatment. However, students with ASD stayed in treatment for significantly more sessions than neurotypical clients, and took significantly longer to achieve maximum improvement on Outcome Questionnaire-45 reports.