Faculty Bibliography

OBJECTIVE:Examine social media experiences of the suicidal adolescent presenting to the emergency department with an acute mental health crisis. METHODS:We used qualitative interviews to obtain in-depth understanding of both negative and positive impacts of social media use on acute adolescent suicidal behavior. A bilingual transcriptionist transcribed audio recordings. Three investigators independently reviewed transcripts to identify themes and develop initial coding scheme through "open coding." Using grounded theory, data collection proceeded along with cultivation of themes until thematic saturation was achieved. Thematic saturation was determined when no new themes were generated from the data. Data were coded in Dedoose software to facilitate reporting of themes and quotes. Techniques to ensure trustworthiness included iterative data collection, use of a coding framework, and multiple coders. RESULTS:Seventeen interviews were conducted from May to October 2020. Median participant age was 15 years. Twenty-four percent were of Hispanic ethnicity and 82% identified as cisgender. Major themes include distraction from negative emotions; facilitated communication resulting in improved social connectedness; metric of connectedness; comparison of self to others; and desensitization and normalization to suicidal acts. Minor theme of increased time on social media is also discussed. These themes echoed components of current suicide theory. CONCLUSIONS:Acutely suicidal adolescents report social media experiences that reflect themes of social alienation and learned capacity for suicidal acts. Themes echo components of current suicide theory. Our participants also reported positive uses of social media. These protective experiences should be leveraged to inform strategies to interrupt behaviors leading to acute suicidality.

The e-cigarette (EC) epidemic began in the United States (US) in 2007; since 2014 EC is the most commonly used form of tobacco. However, the mental health implications of vaping are grossly unknown. The aim of this umbrella review is to provide astate-of-the-art summary of existing research concerning vaping and mental health conditions in children. Following the PRISMA Statement 2020 guidelines, a systematic search was conducted across PubMed, Cochrane Library, and Google Scholar up to April 15th, 2022 to locate relevant studies. The Joana Briggs Institute (JBI) methodology for umbrella reviews and quality appraisal tool was utilized. Six studies, pooling a total of 846,510 adolescents aged 21 years or below, were included by collating 85 primary clinical studies. Of these, 58.8% of the primary clinical studies originated in the US, with 4.7% from Canada, South Korea, and the United Kingdom each; 3.5% each from England and Taiwan; 2.4% each from Australia, France, Hawaii, Mexico, and Russia; and 1.2% each from Denmark, Greece, Hong Kong, Iceland, New Zealand, Poland, and Switzerland. Overall, significant associations were found between mental health outcomes, including depression and suicidality, among current EC users and those who had ever used EC. Compared to adolescents who had never used EC, both depression and anxiety were reportedly higher among EC users. Impulsive behaviors, reported as impulsivity, were also found to be correlated with the adoption of EC use. However, there is a lack of evidence regarding the impact of EC use on mental health outcomes in children. This umbrella review highlights the urgent need to further explore the effects of current EC use from a psychiatric and public health perspective.

INTRODUCTION:There is a striking knowledge gap on ADHD in older adults, and the diagnosis as well as treatment for ADHD in this age group. AREAS COVERED:The authors first review the literature on the prevalence, functional impairment, and health comorbidities of ADHD across the lifespan. Next, they address the diagnostic criteria for ADHD in adults according to the DSM/ICD, available screening/diagnostic tools, differential diagnosis, and the validity of diagnostic criteria for ADHD in older adults. Finally, the authors focus on empirical evidence on the prevalence rates, medication response, and safety of pharmacological treatment of ADHD in older adults, and national and international clinical guidelines on the treatment of ADHD in this age group. EXPERT OPINION:It is expected that future editions of the DSM and ICD will provide specifiers to the standard ADHD criteria, to better inform the diagnosis of ADHD in older adults. It is also expected that the increasing number of epidemiological studies will provide rigorous estimates on the prevalence, incidence, and burden of ADHD in older adults. One may expect an increasing number of RCTs assessing the efficacy/effectiveness and tolerability/safety of pharmacological as well as non-pharmacological interventions which will inform future guidelines on ADHD in older adults.

BACKGROUND:Internalizing and externalizing problems account for over 75% of the mental health burden in children and adolescents in the US, with higher burden among minority children. While complex interactions of multilevel factors are associated with these outcomes and may enable early identification of children in higher risk, prior research has been limited by data and application of traditional analysis methods. In this case example focused on Asian American children, we address the gap by applying data-driven statistical and machine learning methods to study clusters of mental health trajectories among children, investigate optimal predictions of children at high-risk cluster, and identify key early predictors. METHODS:Data from the US Early Childhood Longitudinal Study 2010-2011 were used. Multilevel information provided by children, families, teachers, schools, and care-providers were considered as predictors. Unsupervised machine learning algorithm was applied to identify groups of internalizing and externalizing problems trajectories. For prediction of high-risk group, ensemble algorithm, Superlearner, was implemented by combining several supervised machine learning algorithms. Performance of Superlearner and candidate algorithms, including logistic regression, was assessed using discrimination and calibration metrics via crossvalidation. Variable importance measures along with partial dependence plots were utilized to rank and visualize key predictors. FINDINGS/RESULTS:We found two clusters suggesting high- and low-risk groups for both externalizing and internalizing problems trajectories. While Superlearner had overall best discrimination performance, logistic regression had comparable performance for externalizing problems but worse for internalizing problems. Predictions from logistic regression were not well calibrated compared to those from Superlearner, however they were still better than few candidate algorithms. Important predictors identified were combination of test scores, child factors, teacher rated scores, and contextual factors, which showed non-linear associations with predicted probabilities. CONCLUSIONS:We demonstrated the application of data-driven analytical approach to predict mental health outcomes among Asian American children. Findings from the cluster analysis can inform critical age for early intervention, while prediction analysis has potential to inform intervention programing prioritization decisions. However, to better understand external validity, replicability, and value of machine learning in broader mental health research, more studies applying similar analytical approach is needed.

Translational neuroscience for anxiety has had limited success despite great progress in understanding the neurobiology of Pavlovian fear conditioning and extinction. This chapter explores the idea that conditioning paradigms have had a modest impact on translation because studies in animals and humans are misaligned in important ways. For instance, animal conditioning studies typically use imminent threats to assess short-duration fear states with single behavioral measures (e.g., freezing), whereas human studies typically assess weaker or more prolonged anxiety states with physiological (e.g., skin conductance) and self-report measures. A path forward may be more animal research on conditioned anxiety phenomena measuring dynamic behavioral and physiological responses in more complex environments. Exploring transitions between defensive brain states during extinction, looming threats, and post-threat recovery may be particularly informative. If care is taken to align paradigms, threat levels, and measures, this strategy may reveal stable patterns of non-conscious defense in animals and humans that correlate better with conscious anxiety. This shift in focus is also warranted because anxiety is a bigger problem than fear, even in disorders defined by dysfunctional fear or panic reactions.

BACKGROUND:In the short term, parental presence while a human infant is in pain buffers the immediate pain responses, although emerging evidence suggests repeated social buffering of pain may have untoward long-term effects. METHODS/FINDING/UNASSIGNED:To explore the short- and long-term impacts of social buffering of pain, we first measured the infant rat pup's [postnatal day (PN) 8, or 12] response to mild tail shock with the mother present compared to shock alone or no shock. Shock with the mother reduced pain-related behavioral activation and USVs of pups at both ages and reduced Fos expression in the periaqueductal gray, hypothalamic paraventricular nucleus, and the amygdala at PN12 only. At PN12, shock with the mother compared to shock alone differentially regulated expression of several hundred genes related to G-protein-coupled receptors (GPCRs) and neural development, whereas PN8 pups showed a less robust and less coherent expression pattern. In a second set of experiments, pups were exposed to daily repeated Shock-mother pairings (or controls) at PN5-9 or PN10-14 (during and after pain sensitive period, respectively) and long-term outcome assessed in adults. Shock+mother pairing at PN5-9 reduced adult carrageenan-induced thermal hyperalgesia and reduced Fos expression, but PN10-14 pairings had minimal impact. The effect of infant treatment on adult affective behavior showed a complex treatment by age dependent effect. Adult social behavior was decreased following Shock+mother pairings at both PN5-9 and PN10-14, whereas shock alone had no effect. Adult fear responses to a predator odor were decreased only by PN10-14 treatment and the infant Shock alone and Shock+mother did not differ. CONCLUSIONS/SIGNIFICANCE/CONCLUSIONS:Overall, integrating these results into our understanding of long-term programming by repeated infant pain experiences, the data suggest that pain experienced within a social context impacts infant neurobehavioral responses and initiates an altered developmental trajectory of pain and affect processing that diverges from experiencing pain alone.

This study examined the association of gestational diabetes mellitus (GDM), prenatal, and postnatal maternal depressive symptoms with externalizing, internalizing, and autism spectrum problems on the Preschool Child Behavior Checklist in 2379 children aged 4.12 ± 0.60 (48% female; 47% White, 32% Black, 15% Mixed Race, 4% Asian, <2% American Indian/Alaskan Native, <2% Native Hawaiian; 23% Hispanic). Data were collected from the NIH Environmental influences on Child Health Outcomes (ECHO) Program from 2009-2021. GDM, prenatal, and postnatal maternal depressive symptoms were each associated with increased child externalizing and internalizing problems. GDM was associated with increased autism behaviors only among children exposed to perinatal maternal depressive symptoms above the median level. Stratified analyses revealed a relation between GDM and child outcomes in males only.

IMPORTANCE/OBJECTIVE:Pregnancy induces unique physiologic changes to the immune response and hormonal changes leading to plausible differences in the risk of developing post-acute sequelae of SARS-CoV-2 (PASC), or Long COVID. Exposure to SARS-CoV-2 during pregnancy may also have long-term ramifications for exposed offspring, and it is critical to evaluate the health outcomes of exposed children. The National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC aims to evaluate the long-term sequelae of SARS-CoV-2 infection in various populations. RECOVER-Pregnancy was designed specifically to address long-term outcomes in maternal-child dyads. METHODS:RECOVER-Pregnancy cohort is a combined prospective and retrospective cohort that proposes to enroll 2,300 individuals with a pregnancy during the COVID-19 pandemic and their offspring exposed and unexposed in utero, including single and multiple gestations. Enrollment will occur both in person at 27 sites through the Eunice Kennedy Shriver National Institutes of Health Maternal-Fetal Medicine Units Network and remotely through national recruitment by the study team at the University of California San Francisco (UCSF). Adults with and without SARS-CoV-2 infection during pregnancy are eligible for enrollment in the pregnancy cohort and will follow the protocol for RECOVER-Adult including validated screening tools, laboratory analyses and symptom questionnaires followed by more in-depth phenotyping of PASC on a subset of the overall cohort. Offspring exposed and unexposed in utero to SARS-CoV-2 maternal infection will undergo screening tests for neurodevelopment and other health outcomes at 12, 18, 24, 36 and 48 months of age. Blood specimens will be collected at 24 months of age for SARS-CoV-2 antibody testing, storage and anticipated later analyses proposed by RECOVER and other investigators. DISCUSSION/CONCLUSIONS:RECOVER-Pregnancy will address whether having SARS-CoV-2 during pregnancy modifies the risk factors, prevalence, and phenotype of PASC. The pregnancy cohort will also establish whether there are increased risks of adverse long-term outcomes among children exposed in utero. CLINICAL TRIALS.GOV IDENTIFIER/BACKGROUND:Clinical Trial Registration: http://www.clinicaltrials.gov. Unique identifier: NCT05172011.