2023 APA Dissertation Research Award recipients

The American Psychological Association congratulates the outstanding graduate students who have been awarded 2023 Dissertation Research Awards. These awards are made annually by the APA Science Directorate to assist with the costs of dissertation research. From 100 excellent applications, three students received awards of up to $10,000 and seven students received awards of up to $5,000. All awardees will receive travel funds to present their research at the 2024 APA Convention. 

See the APA Dissertation Research Award website for more information.

Katharine Galbraith, University of Southern California
Using Integrative Data Analysis to evaluate gender differences in Multisystemic Therapy effects for justice-involved youth

Girls are a minority group within the juvenile justice system. Justice-involved girls often possess gender-specific developmental risk factors and behavioral health needs relative to their male counterparts. Existing, gender-neutral interventions designed to reduce delinquency and mental health problems among justice-involved youth typically target male-specific, rather than female-specific, factors in treatment. Whether existing interventions work as well for females as they do for males remains inconclusive because individual studies often have too few females to generate the statistical power needed to test gender differences in effects. Pooling data can address power limitations. Integrative Data Analysis (IDA) is a powerful statistical framework that researchers to do “more with less,” by pooling multiple datasets to create a larger, “mega” dataset – thereby increasing statistical power to detect differences among minority subgroups, such as females. In her dissertation, Katie will use IDA to pool raw data from three randomized trials of Multisystemic Therapy, a widely used intervention that aims to reduce delinquency and mental health problems among justice-involved youth, to determine whether it is equally effective for girls relative to boys.

Katie is a doctoral candidate in clinical science (psychology) at USC, where she works with Stan Huey, PhD. Her research focuses on psychosocial intervention development, refinement, evaluation, and implementation for justice-involved and justice-at-risk youth. She earned her bachelor’s degree in psychology at Yale University.

Chenglin Hong, University of California, Los Angeles
Utilizing Machine Learning and Technology-Based Intervention for Intimate Partner Violence and HIV Prevention Among Gay, Bisexual, and Other Men Who Have Sex With Men – A Mixed Method Study

Gay, bisexual, and other men who have sex with men (GBMSM) experience intimate partner violence (IPV) at substantially high rates compared to their heterosexual counterparts. Little is known about the IPV help-seeking process of GBMSM survivors and the impact of these experiences on utilizing pre-exposure prophylaxis for HIV prevention, and how new technologies and advanced data science approaches could be used for integrated IPV and HIV prevention. Chenglin’s mixed-method dissertation aims to understand the barriers and facilitators to help-seeking and the impact of IPV experiences on PrEP use and persistence among GBMSM and examine the mediating effects of stigma and substance use between this association. This work also aims to explore the feasibility and acceptability of using a technology-based intervention for IPV services and build and verify a machine-learning model to determine the extent to which social media messages can be used to predict self-reported IPV victimization. The anticipated results of the study will fill in a critical gap in the social work and public health literature and will provide evidence and may inform intervention strategies to prevent IPV victimization and promote PrEP use and help-seeking among GBMSM.

Chenglin Hong, is a PhD Candidate in Social Welfare at UCLA. His research focuses on addressing health inequities among sexual and gender minorities and other LGBTQ+ populations. His work is centered primarily on the development and testing of interventions that aim to improve sexual health and mental health outcomes among gay, bisexual, and other sexual minority men (SMM), with a particular focus on HIV and intimate partner violence (IPV) in the U.S. and globally. Chenglin’s work lies at the intersection of social work, public health, psychology, and data science, with the aim of developing interventions that disrupt violence, stigma, HIV, and other syndemics among SMM communities. He is particularly interested in understanding the feasibility and acceptability and developing and testing eHealth, mHealth, and other technology-based interventions and data science approaches (e.g., Machine Learning, natural language processing) to promote IPV help-seeking and HIV prevention services such as pre-exposure prophylaxis (PrEP) among SMM.

Laura P. Valderrama, University of Illinois at Urbana-Champaign
The Effects of Dual Language Programs on L1 and L2 Reading Processing and Comprehension of Academic Texts: An Eye-Tracking Study

Academic texts contain more abstract and logical relations than non-academic texts. These texts can be especially challenging for bilingual students who are trying to master academic language demands while also trying to learn content. Through two eye-tracking experiments, middle- and high-schoolers in Spanish-English Dual Language Programs (DLPs) will read short academic texts in their L1 and L2. Their reading will be compared to mainstream bilingual students and monolingual L1 English students. Eye movements and comprehension probes will be analyzed to compare reading times and attentional allocation to coherence devices common in academic texts, in particular nominal and conceptual anaphors. The working hypothesis is that reading performance in L2 and in L1 are yoked, and strengthening L1 reading skills positively transfers to L2. We predict bilinguals in DLPs will be better able to leverage shared L1 and L2 reading skills than bilinguals in mainstream programs. DLP bilinguals may even perform similarly to English L1 speakers.

Laura Valderrama is a doctoral candidate in Educational Psychology at the University of Illinois at Urbana-Champaign, the lab manager for the Educational Psychology Psycholinguistics Lab at the Beckman Institute, and former TA for several courses of the teacher training program in the College of Education at the University of Illinois at Urbana-Champaign, including courses such as Educational Psychology, Language Varieties, Culture, and learning, and ESL Methods and Materials. Her research interests focus on the biliteracy practices of Latino children and in the training of future teachers on issues pertaining to how language diversity affects cognitive aspects of literacy development. The majority of her professional experience has focused on teaching English speakers of other languages both in the US and Colombia, linguistics, and language acquisition. Upon graduation, she intends to be a faculty member in a bilingual teacher training program and a researcher in the field of linguistics and educational psychology.

Seoyoung Ahn, State University of New York at Stony Brook
Using generated object reconstructions to study object-based attention

Humans can dream and imagine things. These quintessentially human capabilities require the brain to generate percepts. Ahn’s dissertation study explores how these generated representations can be used as inference tools by downstream perceptual and cognitive processes. Through a combination of computational modeling and behavioral experiments, her dissertation will demonstrate that the generative visual system–that works by actively reconstructing the most probable object from incomplete retinal input–can use this reconstruction as top-down attention feedback, thereby supporting cases where object recognition is challenging. The findings of her research will provide supporting evidence that the generative process is what endows humans with a powerful attention mechanism that enables robust object perception, bringing a new perspective to object-based attention in this new era of AI.

Seoyoung Ahn is a PhD candidate in cognitive science, working with Greg Zelinsky, PhD, at Stony Brook. Her research interests broadly span understanding how humans can obtain stable, yet flexible, representations of their visual environment. She combines computational, behavioral, and neuroscientific methods to study this question. She received her BA and MA in cognitive science from Seoul National University. To learn more about her research, visit https://ahnchive.github.io/opens in new window

Mary Beth Hall, University of Delaware
The effects of prenatal maternal immune activation on behavioral and neural outcomes in offspring across development

Early-life immune activation has been associated with increased risk for neurodevelopmental disorders such as autism, schizophrenia, and general learning disabilities, of which males are more likely to be diagnosed than females. Exposure to prenatal immune activation may increase one’s vulnerability for symptoms of these disorders, including learning disabilities, sleep disturbances, and altered social interactions. Hall’s dissertation examines how maternal immune activation during gestation may impact offspring’s neural development in early life, contribute to learning deficits in adulthood, and alter neuroimmune functioning throughout the lifespan. Her research also investigates whether these processes become differently dysregulated in male and female offspring. The findings of this study will allow us to characterize the neurobiological processes that underlie specific symptoms of neurodevelopmental disorders, which may ultimately help to inform future intervention and treatment options for such symptoms.

Mary Beth Hall is a PhD candidate in Interdisciplinary Neuroscience at the University of Delaware, working with Dr. Jaclyn Schwarz in the department of Psychological and Brain Sciences. Her research broadly focuses on how exposure to immune activation during critical periods of early development may impact brain, behavioral, and immune processes in male and female offspring. She is passionate about promoting careers and education in STEAM (Science, Technology, Engineering, Art, and Mathematics) and about bridging the knowledge gap between the general population, the leaders of businesses, and the scientific community. Hall earned a Bachelor of Arts in psychology with a minor in neuroscience from Gettysburg College.

Shana Harris, University of Iowa
Is practitioners’ appraisal of facial expressivity and emotional engagement in Parkinson’s disease affected by race?

Black people are diagnosed with Parkinson’s disease (PD) at half the rate as White people. The reasons for this large disparity in the prevalence of PD between these racial groups are not well understood. One unexplored possibility is that racial bias in practitioners, specifically when appraising motor signs of PD such as hypomimia (reduced facial expressivity), may cause delays or errors in the diagnosis of PD in Black versus White people. Shana’s dissertation will compare practitioners’ (1) appraisal of facial expressivity and (2) perception of pathology, emotional engagement and necessity for referral, in Black versus White people with hypomimia. The results have the potential to identify a target for intervention (racial bias) and to reduce health disparities for patients with PD.

Shana is a PhD candidate in the Department of Psychological and Brain Sciences at the University of Iowa, working with Daniel Tranel, PhD. She is interested in reducing disparities in health and neuropsychological outcomes of Black patients with neurodegenerative disorders such as PD. Shana earned her Bachelor of Arts in forensic psychology from John Jay College of Criminal Justice.

Erin C. Standen, University of Minnesota
Mapping the beneficial and adverse consequences of receiving weight-related advice from a healthcare provider: Identifying strategies to optimize well-being

It is standard practice for healthcare providers to recommend weight loss to patients with higher weight, but evidence for the efficacy of behavioral weight loss counseling is limited. Moreover, this practice may carry the unintended consequence of making people feel stigmatized for their body size. To the extent that weight-related advice is perceived as stigmatizing, the advice itself may undermine patients’ health via stress, reduced engagement in healthy behaviors, and delay or avoidance of future healthcare visits. Erin’s dissertation explores this issue in a series of three studies, in which she examines the motivational and stigma-related consequences of receiving weight-related advice from a healthcare provider.

Erin earned her PhD in Social Psychology from the University of Minnesota under the direction of Dr. Traci Mann and Dr. Alex Rothman. Her research explores the psychological, behavioral, and stigma-related consequences of common weight loss practices, such as low-calorie dieting, mobile health tracking, and behavioral weight loss counseling. She recently began a postdoctoral position at Mayo Clinic, where she is conducting research related to weight bias and discrimination in healthcare settings. She earned her bachelor’s degree in psychobiology from the University of California, Los Angeles.

Chongzheng Wei, University of California, Santa Barbara
Bisexuals living in Chinese cultures: Characteristics, internalized stigma, and psychosocial health risks

There are a conservatively estimated 30 million bisexual people living in China if 2% of the population identifies as bisexual. The applicability of this study’s findings to serve the mental health and well-being of this vast yet underserved population is highly critical. This dissertation study is the first study to capture the characteristics of Chinese bisexuals across Mainland China, Hong Kong, and Taiwan. Furthermore, in an effort to better understand the psychological mechanisms of internalized stigma, this study uses latent profile analysis to explore distinct subgroups of bisexual people in their experience of both internalized binegativity (IB) and internalized homonegativity (IH), as well as resulting psychosocial health risks. Finally, this study examines the effect of LGBT community connectedness on bisexual mental health, to better understand Chinese bisexual people’s struggles and strengths in order to inform clinical and policy interventions.

Chongzheng Wei (he/they) is a PhD candidate in Counseling and Clinical Psychology at the University of California Santa Barbara. His research focuses on reducing suffering and promoting wellness among historically marginalized populations facing systemic oppression based on gender, sexual orientation, class, sex, and/or race/ethnicity. Prior to their doctoral studies, Chongzheng worked at UNESCO in France and Thailand, on education for gender equality and LGBTQI+ inclusion. Currently, they are completing their pre-doctoral internship in health service psychology at Richard J. Donovan State Prison in San Diego, California.

Michelle A. Worthington, Yale University
Individualized prediction of clinical outcomes in youth at clinical high-risk for psychosis

This program of research in the realm of outcome prediction and intervention in the clinical high-risk for psychosis (CHR-P) population is motivated by two primary questions: How could we better alleviate suffering if we knew from an early stage what someone’s likely clinical trajectory was? With this information, how could we optimize treatment selection to ensure the highest likelihood of positive outcomes? In my dissertation studies, I use data-driven machine learning approaches to develop prediction models that address barriers to advancement in the area of prediction in the CHR-P population and, ultimately, clinical implementation.

Worthington is a doctoral candidate in clinical psychology at Yale University, where she is advised by Ty Cannon, PhD. Her research examines how improving prediction of outcomes from the clinical high-risk for psychosis population can inform prevention efforts and treatment selection. Worthington earned her bachelor’s degree in psychology and music at Columbia University and her master’s degree in psychology at Teachers College, Columbia University, and is currently completing her clinical internship at Yale Psychiatry and the Connecticut Mental Health Center.

Steven Zhou, George Mason University
The Negative Effects of Shared Leadership: Understanding Why and When Shared Leadership Does Not Work Through an Experiment and Agent-Based Modeling

In the past two decades, there has been a significant shift in the study of leadership from traditional vertical leadership models to shared leadership (SL) models, where two or more leaders share in leadership responsibility. However, SL research so far – including four recent meta-analyses – has focused almost exclusively on its positive benefits, ignoring several potential issues that can lead to negative implications and outcomes. This dissertation investigates the negative effects of SL using a unique approach combining a lab experiment with agent-based modeling (ABM). The lab experiment assigns participants into teams of four to play a simulation game that requires SL, and teams are randomly assigned to different conditions to utilize a different type of SL. Next, this dissertation builds upon the growing trend of computational modeling as a method of studying complex situations. The ABM will program individual team members to simulate performance on a SL team as a function of all these different parameters, using the data collected from the lab experiment to inform the parameters written in the code.