Research
Our focus on understanding each person rather than the hypothetical “average person” was very much the focus of the idiographic approach to psychology (e.g., Allport, 1937). But our lab does so quantitatively. We do so by collecting many data points from the same person, in an approach we call the Highly Repeated Within Person (HRWP) design (e.g., Whitsett & Shoda, 2014; Zayas, et al, 2019). Using this approach, we seek to identify the features or aspects of situations that are most “psychologically active” for each person. For example, based on daily diary data, we have identified what kinds of situations are most stress-inducing for each person, which we call the stress vulnerability signature (Shoda et al., 2013), and applied this approach to understanding racial microaggression (Wang, Leu & Shoda, 2011). The goal of “quantitative idiography” can be thought of as developing an evidence-based “user’s manual” for one’s mind.
More recently, we have applied the HRWP approach to examine people’s responses to statements conveying colorblind ideology, such as “I don’t see people’s race; race does not matter.” Many people of color experience such statements as offensive, because these statements ignore the experience of being a racial minority and implicitly condone racial injustice. But the same statements could also be interpreted as saying the people of different races are not fundamentally different, and as a call to recognize common, shared humanity, channeling that recognition into action for social and cultural change to eradicate racial discrimination. Our studies (Chang & Shoda, in preparation) found that one reason for the different interpretations is how people understand the word “race.” Some see it as categories of people created in the interest of those in power, to justify unequal treatment and unequal opportunity. Then saying “race does not matter” amounts to denying the social reality, asserting there is no racial discrimination any more. Others have an essentialist view of “race” as an immutable category of people (e.g., based on genetics).
Education
- November 22, 2023 Yuichi Shoda and co-authors Adam Smiley and Jessica Glazier published in Royal Society Open Science journal
- August 11, 2023 Yuichi Shoda received two-year, $287,320 grant from the NSF's Social, Behavioral and Economic Sciences Directorate
- April 15, 2020 Yuichi Shoda and the Marshmallow Test are cited in this Medium.com article about COVID-19.
- November 7, 2019 Yuichi Shoda cited in this Elemental article. Analysis and new studies involving the Marshmallow Test reveal complexity.
- February 14, 2019 Yuichi Shoda and colleague Vivian Zayas explore the complication underlying love in this article in The Conversation.
- December 10, 2018 UW News discusses the lack of diversity in research subjects and cites a paper by Laura Brady, Yuichi Shoda and Stephanie Fryberg, in this article
- December 6, 2018 Yuichi Shoda is quoted in this Right as Rain article on self-control
- July 3, 2018 Yuichi Shoda is cited in this EurekAlert! article about children’s capacity for delayed gratification.
- September 27, 2016 Alicia Shen’s summer data science for social good project, which analyzed ORCA card data for the City of Seattle just got covered by both the Seattle Times and GeekWire!
- January 11, 2016 Yuichi Shoda was one of the 2015 Golden Goose Awardees for his work on the famous Marshmallow Test.
- October 15, 2014 Yuichi Shoda’s work is mentioned in this story -
- September 6, 2011 Jennifer Wang was lead author on "When the Seemingly Innocuous' Stings': Racial Microaggressions and Their Emotional Consequences," that was published in Personality and Social Psychology Bulletin XX(X) 1-13.
- Smiley*, A. H., Glazier*, J. J., & Shoda, Y. (2023). Null regions: a unified conceptual framework for statistical inference. Royal Society Open Science, 10(11), https://doi.org/10.1098/rsos.221328. ("*" indicates authors who were students whose Ph.D. committee I served on, or postdocs for whom I served as the supervisor.)
- Zayas*, V., Lee, R. T., & Shoda, Y. (2021). Modeling the mind: Assessment of if … then … profiles as a window to shared and idiosyncratic psychological processes. In D. Wood, S. J. Read, P.D. Harms, & A Slaughter (Eds), Measuring and Modeling Persons and Situations, Academic Press, 145-192.
- Brady*, L. M., Fryberg, S. A., & Shoda, Y. (2018). Expanding the interpretive power of psychological science by attending to culture. PNAS Proceedings of the National Academy of Sciences of the United States of America, 115, 11406–11413. https://doi.org/10.1073/pnas.1803526115.
- Sheldon*, O., Plaks*, J., Sridharan*, V., & Shoda, Y. (2018). Strategic actors' in situ impressions of systematically- versus unsystematically-variable counterparts, Social Cognition, 36, 324-344.
- Simons, D. J., Shoda, Y., & Lindsay, D. S. (2017). Constraints on Generality (COG): A proposed addition to all empirical papers. Perspectives On Psychological Science, 12, 1123-1128. doi:10.1177/1745691617708630.
- Whitsett*, D. D., & Shoda, Y. (2014). Examining the Heterogeneity of the Effects of Situations across Individuals Does Not Require A Priori Identification and Measurement of Individual Difference Variables. Journal of Experimental Social Psychology, 50, 94-104.
- Shoda, Y., Wilson*, N. L., Chen, A., Gilmore, A., & Smith, R. E. (2013). Cognitive-Affective Processing System Analysis of Intra-individual Dynamics in Collaborative Therapeutic Assessment: Translating Basic Theory and Research into Clinical Applications. Journal of Personality, 81, 554-568.
- Plaks*, J.E., Malahy*, L.W., Sedlins*, M. & Shoda, Y. (2012). Folk beliefs about human genetic variation predict discrete versus continuous race categorization and evaluative bias. Social Psychological and Personality Science, 3, 31-39.