Services

Seed Grant Awards, 2017-2018

Congratulations to the 2017-2018 Seed Grant Award Recipients! Scroll down to see project abstracts.

Resilience in migrant youth exposed to violence and hunger, an examination of participants in the CAMINANDO study

Manuela Orjuela (Epidemiology)
Lindsay Stark (Population and Family Health)
Maria Marti (Population and Family Health)
Xinhua Liu (Biostatistics)
Alexandra Restrepo Henao (Doctoral Candidate)
Ezra Susser (Epidemiology)
Charlie Branas (Epidemiology)

Abstract:
We propose to examine the impact of exposure to hunger, food insecurity and violence on emotional health in a group of migrant Latino youth. In these youth, we will also examine the roles of resilience and use of community supports in mitigating the impact of these adverse exposures. Emotional health which includes the full spectrum of emotional life (not limited to impairment or symptoms) is a predictor of later physical and mental health outcomes. Our study of migrant teens presents a unique opportunity to examine the role of hunger, food insecurity and exposure to violence with outcomes in emotional health and a biological marker of cellular aging. This proposed study which builds on a small ongoing study with a well-developed infrastructure, addresses several CPRC priority areas including migration, adolescence, urban neighborhoods, and mental health. Additionally, the study includes advising from key senior faculty within the CPRC, and a multidisciplinary approach involving senior and junior faculty, trainees, international experts, and community partner organizations.

Service Utilization and Stress of Chinese Dementia Caregivers in New York City

Jinyu Liu (Social Work)

Abstract:
For the 4.6 million U.S. older immigrants, family is the especially crucial source of support and is often the only care provision, given that older immigrants tend to be less resourceful in seeking out assistance and thus more likely to fall through the cracks of government-funded social safety nets compared to their native-born cohorts. On top of adapting to new environments and finding appropriate niches in host societies, family caregiving can be very demanding and stressful for immigrants, in particular for those who take care of their family members with Alzheimer’s disease and related dementias (ADRD). The purpose of this study is to investigate the effectiveness of existing services for family caregivers in the population of Chinese Americans who attract less attention in part due to the “Model Minority” myth, despite the fact that recent studies show vulnerabilities among this population in physical and mental health and accessing supportive services. In particular, this study aims to address two questions: (1) what services lessen stress of Chinese American caregivers? (2) How ethnic culture and migration experience are associated with service utilization and effectiveness among Chinese American caregivers?

Innovating Youth Gang Violence Prevention with Natural Language Processing and Qualitative Analysis.

Desmond Patton (Social Work)

Abstract:
This proposed study uses a novel integration of qualitative analysis and natural language processing (NLP) within a machine learning framework to detect aggression and loss related tweets from Chicago youth who identify as being gang involved. At present, community-based violence prevention organizations must manually observe activity on social media, so they may intervene to de-escalate potentially violent conflicts and change social behaviors and norms or not they are not connected to interactions occurring on social media. However, the sheer volume of relevant activity on social media has made it impossible for such organizations to identify all indications of future violence. Computer-based tools have already been used successfully to identify suicide risks and instances of cyberbullying. This study is designed to analyze and automatically detect expressions of aggression and loss in archived social media content from multiple social media platforms. Target areas for the study include neighborhoods with high rates of violence in Chicago. This approach will enable community-based organizations to quickly identify a much broader range of threats using computer-based tools that automatically monitor social media activities and alert them to online conversations that could lead to offline acts of violence.