Faculty Bibliography

Purpose: There are an ever increasing number of social media platforms available for people to connect and build online communities. Pro-eating disorder communities, notably anorexia nervosa (AN), have developed a steady presence on Twitter. While these communities can be beneficial for individuals who are not yet ready or able to seek professional help, multiple studies have revealed the detrimental side effects these communities can have on users, such as normalization of maladaptive behaviors, encouragement of behaviors and sharing new ways to perpetuate behaviors. To date, few studies have investigated the ways in which available social media data from self-identified anorexic individuals could be used to better inform screening, treatment, and follow-up with these individuals. This study evaluated the ways in which natural language processing (NLP) and machine learning algorithms, coupled with qualitative methods, could collect, categorize, and inform clinician insights about pro-eating disorder communities. Method(s): Twitter crawling algorithms were developed and deployed through the Twitter API to find tweets based on key words such as: "ana" "proana" "thinspo" and "meanspo." This initial corpus of tweets containing the identified keywords was then qualitatively assessed to further refine the algorithmic process of identifying appropriate tweets and removing irrelevant tweets. This process resulted in a cleaned corpus of 970 unique tweets over a ten-day period. This cleaned dataset was then utilized for NLP to identify common words, phrases, and topics. Concurrently, data was hand coded in a thematic analysis process to identify deeper themes within the dataset. These themes could inform qualitative lines of inquiry as well as machine learning systems. Qualitative insights were utilized to improve sentiment analysis as well as classification of unstructured data though a semi-supervised machine learning process. Result(s): Analysis revealed that emotional restraint was not present and judgement of one's self on external standards was present within these Twitter communities. Additionally, users' frequently requested "meanspo," an extension of thinspo that serves as an inspiration for thinness by using aggressive and abrasive rhetoric to encourage users to aspire for thinness. Additionally, posts asking for an "ana buddy," a partner to help users hold each other accountable to their AN behaviors, were extremely common. Additional information about caloric restrictions, weekly weight loss goals, and a large number of individuals tweeting from residential treatment for ED about lying about wanting to get better as a means to be released, as well as genuine statements about wanting to change. Conclusion(s): AN is a complicated disease with multiple causes, side effects and comorbid illnesses. This pilot study offers a promising 'first-step' approach towards understanding the mindset, experiences, and potential gaps within current ED treatment approaches from a patient perspective. NLP and ML processes are now developed to scan, collect, and analyze this data in an ongoing way to develop new AI processes with the ultimate goal of identifying individuals with a higher likelihood of wanting to enter treatment. Overall, the present study highlights the benefits of using new available data streams to develop patient-informed comprehensive care models. Sources of Support: NYU CAMS Undergaduate Internship

OBJECTIVE:This study describes the experiences of adult psychiatry residents working in an established faculty-led asylum clinic within a community-based, academic residency program at the Cambridge Health Alliance. METHODS:Eighteen psychiatry residents who participated in the asylum clinic were sent electronic surveys asking about their background and experience. Respondents' responses were collected anonymously. RESULTS:Sixteen out of 18 (89%) trainees responded. Thirteen respondents had a personal history with immigration. Fifty-three percent of residents wanted to utilize their professional standing to advance moral good. Writing up affidavits was noted to be challenging by nine (60%) of 15 trainees. Ninety-four percent (15/16) of trainees noted that they would be willing to perform future evaluations. Most noted that performing evaluations had a significant impact on their clinical practice and their conceptualization of their own roles as psychiatrists. CONCLUSIONS:Participating in asylum evaluations impacts residents' sense of themselves as psychiatrists and expands their views about psychiatrists' roles.

AIM/OBJECTIVE:Data pertaining to child and adolescent psychiatry (CAP) training systems are limited as extant research has mostly been derived from one-time data collection. This 5-year follow-up survey collects updated information on CAP training systems in the Far East, allowing for the tracking of system changes over the past 5 years. METHODS:Data were obtained from 18 countries, or functionally self-governing areas, in the Far East, 17 of which were also included in the original study. An online questionnaire was completed by leading CAP professionals in each country. Questions were expanded in the present study to capture the contents of CAP training. RESULTS:When compared to data from the original study, there has been progress in CAP training systems in the last 5 years. Specifically, there has been an increase in the number of countries with CAP training programs and national guidelines for the training. In addition, the number of CAP departments/divisions affiliated with academic institutions/universities has increased. Findings from 12 of 18 countries in the present study provide data on clinical contents. All informants of the present study reported the need for more child and adolescent psychiatrists and allied professionals. CONCLUSION/CONCLUSIONS:Despite progress in CAP training systems over the last 5 years, the need for more professionals in child and adolescent mental health care in all the relevant areas in this region have yet to be adequately addressed. Continued national efforts and international collaborations are imperative to developing and sustaining new CAP training systems while facilitating improvements in existing programs.

Spectral imaging is a ubiquitous tool in modern biochemistry. Despite acquiring dozens to thousands of spectral channels, existing technology cannot capture spectral images at the same spatial resolution as structural microscopy. Due to partial voluming and low light exposure, spectral images are often difficult to interpret and analyze. This highlights a need to upsample the low-resolution spectral image by using spatial information contained in the high-resolution image, thereby creating a fused representation with high specificity both spatially and spectrally. In this paper, we propose a framework for the fusion of co-registered structural and spectral microscopy images to create super-resolved representations of spectral images. As a first application, we super-resolve spectral images of retinal tissue imaged with confocal laser scanning microscopy, by using spatial information from structured illumination microscopy. Second, we super-resolve mass spectroscopic images of mouse brain tissue, by using spatial information from high-resolution histology images. We present a systematic validation of model assumptions crucial towards maintaining the original nature of spectra and the applicability of super-resolution. Goodness-of-fit for spectral predictions are evaluated through functional R² values, and the spatial quality of the super-resolved images are evaluated using normalized mutual information.

OBJECTIVE:Network meta-analyses (NMAs) are gaining traction as the preferred method for evidence synthesis of intervention studies. This review aimed to summarize the basics of NMAs and conduct a meta-review of available NMAs on the treatment of child and adolescent psychiatric disorders by appraising their quality. METHOD/METHODS:PubMed (Medline), PsycInfo, Embase, Ovid Medline, and Web of Knowledge were systematically searched (last update January 9, 2018). The quality of each included NMA was appraised using the AMSTAR-2 tool and the PRISMA-NMA checklist, which includes specific items for NMAs. RESULTS:Eighteen NMAs (6 on attention-deficit/hyperactivity disorder; 4 on psychotic disorders; 2 on depression; 2 on anxiety disorders; 1 on obsessive-compulsive disorder; 1 on disruptive behavior disorder, 1 on bipolar disorder, and 1 on antipsychotics across disorders) were retrieved. Results from the AMSTAR-2 assessment showed that only 27% of appraised NMAs were rated as moderate quality; most were rated as low (33%) or critically low (40%) quality. Only 3 of the appraised NMAs reported on all PRISMA-NMA items specific for NMAs; the network structure was graphically presented in most NMAs (80%), and inconsistency was described in only 47%. CONCLUSION/CONCLUSIONS:Given the paucity of head-to-head trials in child and adolescent psychiatry, NMAs have the potential to contribute to the field, because they provide evidence-based hierarchies for treatment decision making, even in the absence of trials directly comparing at least 2 treatments. However, because of important limitations in the included NMAs, additional methodologically sound NMAs are needed to inform future guidelines and clinical practice in child and adolescent psychiatry.

Over the past two decades, research on pediatric bipolar disorder has grown geometrically. The diagnosis of pediatric bipolar disorder was met with enthusiasm, which in healthy doses catalyzed change, and skepticism, which in good measure pushes for rigor. Skepticism led to productive questions about the phenomenology of pediatric bipolar disorder and how best to diagnose and treat it. With regard to prevalence, key questions included whether it was increasing over time, and whether it was limited to the United States. In 2011, we published a meta-analysis addressing the prevalence questions; results indicated that bipolar disorder manifested at statistically indistinguishable rates in youth community samples across the world. In their recent paper, Parry et al. examine the studies included in the 2011 meta-analysis using a qualitative approach. Their opinion piece represents a step backwards; every study has shortcomings, but in focusing on a dozen individual studies, Parry et al. fail to take into account the preponderance of evidence - literally thousands of articles across countries, cohorts and methodologies - that support the existence of bipolar disorder in both prepubescent youth and adolescents. This commentary addresses misperceptions regarding the diagnosis of bipolar disorder in youth, particularly with regard to cross-informant agreement, to present converging data from international sources regarding the onset of bipolar disorder in childhood, and to correct the false claim that pediatric bipolar disorder is controversial. As clinicians and researchers, we have an obligation to do what we can to improve the lives of youth affected by mental illness. Denying the existence of a serious mood disorder will not serve the best interests of young people and will perpetuate the long delays many experience before getting an accurate diagnosis, appropriate treatment, and a fair chance at a good quality of life.

Spatiotemporal shape models capture the dynamics of shape change over time and are an essential tool for monitoring and measuring anatomical growth or degeneration. In this paper we evaluate non-parametric shape regression on the challenging problem of modeling early childhood sub-cortical development starting from birth. Due to the flexibility of the model, it can be challenging to choose parameters which lead to a good model fit yet does not over fit. We systematically test a variety of parameter settings to evaluate model fit as well as the sensitivity of the method to specific parameters, and we explore the impact of missing data on model estimation.

Purpose: In 2016 there were roughly 77,000 PrEP users in the United States, while over 1.2 million Americans were identified as "high-risk" for HIV infection. The reasons for this discrepancy are vast; however, potential reasons that have been identified are stigma, ineffective or poorly targeted marketing, access, and cost, amongst other factors. This pilot project seeks to understand the ways in which people and companies talk about PrEP on social media to glean deeper insights on methods to increase PrEP use. The increased use of social media gives researchers, clinicians, policymakers, and health organizations the opportunity to have access to real time data and potentially influence awareness of PrEP. This inductive exploratory study uses natural language processing (NLP) and content analysis to examine the ways in which people are using social media to talk about PrEP. Method(s): An R script was utilized to crawl Twitter the Twitter API based on keywords related to PrEP and HIV, plus all lemmatized variations related to the word pair. Data cleaning was then performed to remove tweets that were not in English, tweets that had been retweeted, as well as removing any identifying information. The resulting data frame was then used both qualitatively and quantitatively for analysis. Qualitative analysis involved a comprehensive reading of tweets, development of a category dictionary, and identification of themes that would help to train an algorithm to automatically process and count tweets based on its category. The quantitative process involved further cleaning and removing of stop-words to develop a Ngram frequency cloud as well as development of a process to automatically categorize the different types of tweets based on the type of tweet (advertisement, question about PrEP, comment on cost or availability, criticism of manufacturer, etc.). Result(s): This processes resulted in identification of 587 unique HIV related PrEP tweets. Qualitative insights from this reduced dataset indicated that there are preventative concerns related to access and cost which may be preventing high-risk individuals from getting PrEP. Algorithmic sorting and categorization processes also identified concerns about targeted marketing, specifically the lack of campaigns focusing on transgender, female, and minority communities. Our bootstrap method of training and testing resulted in a process that had an 80% likelihood of identifying, analyzing, and classifying HIV related PrEP tweets. Once classified, 40% of tweets were advertising and messaging, the rest were concerns about cost (31%), requests for info/ways to pay for PrEP (20%), as well as other non-classified comments. Conclusion(s): There are a number of different conversations about HIV/PrEP awareness happening on Twitter. However, access and cost were consistently the most common themes being discussed. Currently, a 30-day supply of PrEP costs between 0-$1600, in the US, which may be creating a substantial barrier to further reducing HIV rates. Additionally, Improving online marketing strategies of PrEP could increase awareness and use by offering targeted information as well as identification of local resources to those interested or in need. Sources of Support: NYU CAMS Undergradaute Internship