Silver Center on Data Science and Social Equity Awards Inaugural Faculty Research Grants
The Constance and Martin Silver Center on Data Science and Social Equity has awarded its inaugural faculty research grants to Associate Professor Doris F. Chang and Professor Victoria Stanhope for their projects leveraging data science and related technologies to understand Asian American responses to racism in the time of COVID-19 and to measure person-centered care in behavioral health settings respectively. The Center was established in June 2021 to stimulate interest in and support early development of innovations in the field of data science broadly, with a specific focus on topics with potential to promote social equity.
Professor Marya Gwadz, NYU Silver’s Associate Dean for Research and the Inaugural Director of the Center, said “We are excited to award these first two early developmental grants related to data science in what will be an annual competition among NYU Silver full-time faculty. Social work scholars clearly have an important role to play in data science, in domains such as “big data” and artificial intelligence, and the new Center will be vital to inspiring and supporting our faculty in shaping these new and emerging fields for maximum impact and social equity.”
Dr. Chang and Co-Investigators Drs. Sumie Okazaki of NYU Steinhardt, Thu Nguyen of University of Maryland School of Medicine, and Maureen Craig of NYU Arts and Science will explore how geocoded indices of sociocultural climate and structural inequalities interact with individual psychological variables to predict Asian Americans’ experiences, attitudes, and behavioral responses to racism in the time of COVID-19. The research team will use geocoded Twitter racial sentiment data from the preceding year combined with individual level responses from a new national survey of 1,050 Chinese, Indian, and Filipino Americans ‒ with 350 responses from each of these three largest Asian American groups ‒ to examine how regional variations in racial climate are associated with a) racial discrimination and mental health, b) intergroup attitudes (structural awareness, sense of belonging, political commonality/coalitional attitudes), and c) collective action and coalitional support (own-group benevolent support and political activism, Asian-Black allyship behaviors). They will also use place-based demographic data from the U.S. Census to examine how regional variations in residential segregation/integration and income inequality reflect community contexts for intergroup conflict, cooperation and competition, and may be associated with the same three outcomes listed above.
“News reports suggest that the hypervisibility of Asian Americans during the pandemic and their increased sense of vulnerability as a racialized group may be shifting their racial attitudes, and impacting mental health outcomes and intergroup relations, but also catalyzing collective action to address the systemic causes of inequality and oppression,” said Dr. Chang. “However, as Asian Americans are frequently marginalized in contemporary discussions about race, research is needed to understand how local racial climate ‒ assessed through both social media as well as residential indicators ‒ interacts with direct experiences of racial discrimination to shape Asian Americans’ sense of belonging, intergroup race relations, and collective action, which are crucial community-level indicators of well-being and societal integration.”
In their study, Dr. Stanhope, Co-Investigator Dr. Elizabeth Matthews of Fordham University, and consultant Dr. Sarah Shugars of NYU’s Center for Data Science and George Washington University’s School of Media & Public Affairs will use Natural Language Processing, a branch of artificial intelligence, to examine Collaborative Documentation (CD), a strategy to promote person-centered care (PCC) in behavioral health clinics. PCC, which ensures that care is individualized and that service users are active and empowered partners in their treatment, is widely recognized as a solution to the persistent problem of service disengagement within the mental health system. Nonetheless, there remain challenges in translating this individualized approach into specific clinical practices.
This new study builds on prior studies conducted by the investigative team, two of which demonstrated the effectiveness of CD in promoting service engagement and a third which developed a valid and reliable objective measure of PCC, the PCCP Assessment Measure (PCCP-AM). Still, more work is needed to substantiate the value of CD as a mechanism to improve PCC. Moreover, even with the PCCP-AM, an obstacle to scalability within and across clinics remains the time needed for manual content analysis of clinical visit notes. In the new study, Drs. Stanhope and Matthews will overcome the limitations of manual narrative analysis by applying Natural Language Processing, a text mining technique that translates complex narrative text into structured data, using an algorithm informed by the PCCP-AM. Using a pretest posttest design, they will sample visit notes before and after implementation of CD at a behavioral health clinic where providers have been trained in CD. The algorithm will analyze notes for indicators of PCC to measure change in frequency and content at the provider level. “This will be the first study to utilize artificial intelligence techniques to measure PCC in behavioral health settings,” said Dr. Stanhope. “It will contribute to the evidence base on Collaborative Documentation and provide much needed objective, scalable methods to examine a critical quality indicator in behavioral health services.”
Dr. Gwadz noted that the Center’s two funded projects were selected after a review process modeled on that used by the National Institutes of Health. The proposals were reviewed by a five-member research advisory committee that Dr. Gwadz chaired in her capacity as NYU Silver’s Associate Dean for Research. Each application was subjected to independent peer review by three members of the committee and was read, discussed, and scored by the full committee. Final decisions were made by the Office of the Associate Dean for Research and the Dean based on the scores.
Established in June 2021, the Constance and Martin Silver Center on Data Science and Social Equity supports NYU Silver scholars conducting work in data science for social equity impact including studies harnessing big data and using artificial intelligence. In order to leverage the growing availability and complexity of such data, the Center helps to develop and nurture the scientific skill set of Silver faculty, doctoral students, and researchers. Harnessing big data for social good is one of the Grand Challenges for Social Work.