Intersections between Racial Biases and Implicit and Explicit Stigma Towards Autism in Two Cultural Contexts within the United States.

Poster Presentation
Saturday, May 4, 2019: 11:30 AM-1:30 PM
Room: 710 (Palais des congres de Montreal)
R. Obeid1, J. Bailey Bisson2, A. Cosenza3, A. J. Harrison4, F. James5, S. Saade6 and K. Gillespie-Lynch7, (1)Department of Psychological Sciences, Case Western Reserve University, Cleveland, OH, (2)Clemson University, Clemson, SC, (3)College of Staten Island, City University of New York, Staten Island, NY, (4)Educational Psychology, University of Georgia, Athens, GA, (5)Psychology, College of Staten Island, City University of New York, Staten Island, NY, (6)American University of Beirut, Beirut, Lebanon, (7)Department of Psychology, College of Staten Island; CUNY Graduate Center, Brooklyn, NY
Background: Disparities in access to care and stigma negatively impact autistic individuals (Durkin et al., 2010; Gray, 2002). Disparities in access to care may constitute a form of structural stigma, or “cultural norms and institutional policies that constrain the opportunities, resources, and wellbeing of the stigmatized” (Hatzenbeuler & Link, 2014, p. 2). Racial biases in autism identification have been documented among clinicians and educators (Beeger et al., 2009). Ethnic minorities are less likely to be diagnosed with autism and are diagnosed later than white children (Valicenti-McDermott et al., 2012). Black children in the US are often misclassified with conduct disorder (CD; Mandell et al., 2007). To the best of our knowledge, no prior study has examined implicit biases in autism identification.

Objectives: To examine implicit and explicit biases in autism identification among college students at two universities within the US (New York and Georgia).

We hypothesized that participants would:

  1. Express heightened explicit and implicit stigma towards CD relative to ASD.
  2. Be more likely to implicitly associate black children with CD rather than ASD while associating white children with ASD over CD.


Participants (N = 510) were recruited from public universities in NY (n = 381; Female: 264, Mean Age:19.37; White: 37%) and Georgia (n = 129; Female:105, Mean Age: 20.17; White: 80%). Participants evaluated two vignettes depicting a child with ASD or CD after being randomly assigned to view either a photo of an African-American or a European-American male child (CAFE Set; LoBue, 2014; Figure 1).

Participants rated explicit stigma towards the children in the vignettes using an adapted Social Distance Scale (Bogardus, 1933), in addition to a measure of explicit racism (Symbolic Racism Scale; Henry & Sears, 2002). Participants also qualitatively evaluated the children’s condition (Figure 1). We created two Implicit Association Tests (IATs): “Disability Valence” and “Racial Bias.” (Figure 2).


Regardless of race depicted, participants reported heightened explicit stigma towards CD (M=21.63, SD=5.37) compared to ASD (M=11.15, SD=4.17), t(509)=40.05, p<.001 and did not differ in their accuracy in describing the child’s condition as ASD (African-American vignette: 75.6%; European-American vignette: 72.8%) or CD (African-American vignette: 53.5%; European-American vignette: 62.4%). Participants were more likely to implicitly associate good words with ASD and bad words with CD (M=.270, SD=.29), t(498)=20.83, p<.001, and to associate European-American images with ASD and African-American images with CD (M= -.064, SD=.29), t(483)= -4.82, p<.001. No associations were observed between social distance and performance on the IATs. Racism was associated with racial bias in NY (r = -.11, p = .04) but not Georgia (r = -.09, p = .33).

Conclusions: This evidence of implicit but not explicit racial bias in autism identification among non-specialists, in conjunction with prior research demonstrating that checklists fail to avert misclassification of ethnic minorities by specialists (Burke et al., 2015), suggests that implicit biases contribute to disparities in access to autism care. Future research should evaluate whether implicit attitudes contribute to diagnostic and policy decisions by specialists to clarify contributions of implicit stigma to structural stigma.

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