Faculty Bibliography

BACKGROUND:Using data from the English & Romanian Adoptees (ERA) study, we recently reported that early time-limited exposure to severe institutional deprivation is associated with early-onset and persistent neurodevelopmental problems and later-onset emotional problems. Here, we examine possible reasons for the late emergence of emotional problems in this cohort. Our main focus is on testing a developmental cascade mediated via the functional impact of early-appearing neurodevelopmental problems on late adolescent functioning. We also explore a second putative pathway via sensitization to stress. METHODS:The ERA study includes 165 Romanian individuals who spent their early lives in grossly depriving institutions and were subsequently adopted into UK families, along with 52 UK adoptees with no history of deprivation. Age six years symptoms of neurodevelopmental problems and age 15 anxiety/depression symptoms were assessed via parental reports. Young adult symptoms of depression and anxiety were assessed by both parent and self-reports; young adults also completed measures of stress reactivity, exposure to adverse life events, and functioning in work and interpersonal relationships. RESULTS:The path between early institutional deprivation and adult emotional problems was mediated via the impact of early neurodevelopmental problems on unemployment and poor friendship functioning during the transition to adulthood. The findings with regard to early deprivation, later life stress reactivity, and emotional problems were inconclusive. CONCLUSIONS:Our analysis suggests that the risk for adult depression and anxiety following extreme institutional deprivation is explained through the effects of early neurodevelopmental problems on later social and vocational functioning. Future research should more fully examine the role of stress susceptibility in this model.

The COVID-19 pandemic dramatically affected the operations of New York City hospitals during March and April of 2020. This article describes the transformation of a neurology division at a 450-bed tertiary care hospital in a multi-ethnic community in Brooklyn during this initial wave of COVID-19. In lieu of a mass redeployment of staff to internal medicine teams, we report a novel method for a neurology division to participate in a hospital's expansion of care for patients with COVID-19 while maintaining existing team structures and their inherent supervisory and interpersonal support mechanisms.

There is a significant knowledge gap in research on Attention-Deficit/Hyperactivity Disorder (ADHD) in older adults. Via a systematic review and meta-analysis, we aimed to investigate the prevalence of ADHD in older adults, considering different assessment methods. We searched five electronic databases up to June 26, 2020. We identified 20 relevant studies with 32 datasets providing a total sample size of 20,999,871 individuals (41,420 individuals with ADHD). The pooled prevalence estimates differed significantly across assessment methods: 2.18 % (95 % CI = 1.51, 3.16) based on research diagnosis via validated scales, 0.23 % (0.12, 0.43) relying on clinical ADHD diagnosis, and 0.09 % (0.06, 0.15) based on ADHD treatment rates. Heterogeneity was significant across studies for all assessment methods. There is a considerable number of older adults with elevated levels of ADHD symptoms as determined via validated scales, and the prevalence of treated ADHD is less than half of the prevalence of clinically diagnosed ADHD. This highlights the need for increased awareness of ADHD clinical diagnosis and treatment in older adults.

BACKGROUND:Recent research has emphasized the need for accessing information about patients to augment mental health patients' verbal reports in clinical settings. Although it has not been introduced in clinical settings, computational linguistic analysis on social media has proved it can infer mental health attributes, implying a potential use as collateral information at the point of care. To realize this potential and make social media insights actionable to clinical decision making, the gaps between computational linguistic analysis on social media and the current work practices of mental health clinicians must be bridged. OBJECTIVE:This study aimed to identify information derived from patients' social media data that can benefit clinicians and to develop a set of design implications, via a series of low-fidelity (lo-fi) prototypes, on how to deliver the information at the point of care. METHODS:A team of clinical researchers and human-computer interaction (HCI) researchers conducted a long-term co-design activity for over 6 months. The needs-affordances analysis framework was used to refine the clinicians' potential needs, which can be supported by patients' social media data. On the basis of those identified needs, the HCI researchers iteratively created 3 different lo-fi prototypes. The prototypes were shared with both groups of researchers via a videoconferencing software for discussion and feedback. During the remote meetings, potential clinical utility, potential use of the different prototypes in a treatment setting, and areas of improvement were discussed. RESULTS:Our first prototype was a card-type interface that supported treatment goal tracking. Each card included attribute levels: depression, anxiety, social activities, alcohol, and drug use. This version confirmed what types of information are helpful but revealed the need for a glanceable dashboard that highlights the trends of these information. As a result, we then developed the second prototype, an interface that shows the clinical state and trend. We found that focusing more on the changes since the last visit without visual representation can be more compatible with clinicians' work practices. In addition, the second phase of needs-affordances analysis identified 3 categories of information relevant to patients with schizophrenia: symptoms related to psychosis, symptoms related to mood and anxiety, and social functioning. Finally, we developed the third prototype, a clinical summary dashboard that showed changes from the last visit in plain texts and contrasting colors. CONCLUSIONS:This exploratory co-design research confirmed that mental health attributes inferred from patients' social media data can be useful for clinicians, although it also revealed a gap between computational social media analyses and clinicians' expectations and conceptualizations of patients' mental health states. In summary, the iterative co-design process crystallized design directions for the future interface, including how we can organize and provide symptom-related information in a way that minimizes the clinicians' workloads.

This article reports on a study aimed to elucidate the complex etiology of post-traumatic stress (PTS) in a longitudinal cohort of police officers, by applying rigorous computational causal discovery (CCD) methods with observational data. An existing observational data set was used, which comprised a sample of 207 police officers who were recruited upon entry to police academy training. Participants were evaluated on a comprehensive set of clinical, self-report, genetic, neuroendocrine and physiological measures at baseline during academy training and then were re-evaluated at 12 months after training was completed. A data-processing pipeline-the Protocol for Computational Causal Discovery in Psychiatry (PCCDP)-was applied to this data set to determine a causal model for PTS severity. A causal model of 146 variables and 345 bivariate relations was discovered. This model revealed 5 direct causes and 83 causal pathways (of four steps or less) to PTS at 12 months of police service. Direct causes included single-nucleotide polymorphisms (SNPs) for the Histidine Decarboxylase (HDC) and Mineralocorticoid Receptor (MR) genes, acoustic startle in the context of low perceived threat during training, peritraumatic distress to incident exposure during first year of service, and general symptom severity during training at 1 year of service. The application of CCD methods can determine variables and pathways related to the complex etiology of PTS in a cohort of police officers. This knowledge may inform new approaches to treatment and prevention of critical incident related PTS.

In this commentary on Osiurak and Reynaud's target article, we argue that action is largely missing in their account of the ascendance of human technological culture. We propose that an action-based developmental account can help to bridge the cognitive-sociocultural divide in explanations of the discovery, production, and cultural transmission of human tool use.

A systematic review with meta-analysis was performed to: 1) estimate the prevalence of both mental and physical health problems in older offenders; 2) calculate relative risks for the health conditions in relation to non-offender older adults and; 3) explore the potential confounding role of several variables. We searched five databases up to August 2019. Studies involving offenders older than 50 years old were included. Fifty-five publications met criteria. The pooled prevalence for 18 mental and 28 physical health problems was calculated. In comparison with non-offender older adults, older offenders showed significantly higher risk for Hypertension (RR = 1.16, CI = 1.1, 1.2), Cardiovascular Diseases (RR = 1.24, CI = 1.09, 1.41), Respiratory diseases (RR = 1.75, CI = 1.29, 2.35), and Arthritis (RR = 1.19, CI = 1.12, 1.25). Heterogeneity was significant for all meta-analyses and partially explained by the confounding effect of country, the diagnosis assessment method, and the sample characteristics. Future research should include comparison groups of non-offender older adults and use longitudinal study designs to identify risk factors that can be targeted in preventive programmes.

A common coordinate space enabling comparison across individuals is vital to understanding human brain organization and individual differences. By leveraging dimensionality reduction algorithms, high-dimensional fMRI data can be represented in a low-dimensional space to characterize individual features. Such a representative space encodes the functional architecture of individuals and enables the observation of functional changes across time. However, determining comparable functional features across individuals in resting-state fMRI in a way that simultaneously preserves individual-specific connectivity structure can be challenging. In this work we propose scalable joint embedding to simultaneously embed multiple individual brain connectomes within a common space that allows individual representations across datasets to be aligned. Using Human Connectome Project data, we evaluated the joint embedding approach by comparing it to the previously established orthonormal alignment model. Alignment using joint embedding substantially increased the similarity of functional representations across individuals while simultaneously capturing their distinct profiles, allowing individuals to be more discriminable from each other. Additionally, we demonstrated that the common space established using resting-state fMRI provides a better overlap of task-activation across participants. Finally, in a more challenging scenario - alignment across a lifespan cohort aged from 6 to 85 - joint embedding provided a better prediction of age (r2 = 0.65) than the prior alignment model. It facilitated the characterization of functional trajectories across lifespan. Overall, these analyses establish that joint embedding can simultaneously capture individual neural representations in a common connectivity space aligning functional data across participants and populations and preserve individual specificity.

OBJECTIVE:We examined the acceptability, integrity, and symptom trajectories associated with FIRST, a principle-guided treatment for youth internalizing and externalizing problems designed to support efficient uptake and implementation. METHOD/METHODS:= 26 youths, ages 11-17, 42.31% female, 65.38% Caucasian, 7.69% Latinx). In Study 3, the original study therapists - now practitioners - evaluated FIRST's effectiveness and implementation difficulty, and reported their own post-study FIRST use. RESULTS:ES = 1.10 in the 2017 trial, 0.83 in Study 1, and 0.81 in Study 2. Study 3 showed high effectiveness ratings, low difficulty ratings, and continued use of FIRST by a majority of clinicians. CONCLUSIONS:Across two open trials and a follow-up survey, FIRST showed evidence of acceptability and integrity, with youth symptom reduction comparable to that in prior research.