Spoken Narratives by Autistic Adults of Under-represented Genders
Open Access
- Author:
- Coburn, Kelly
- Graduate Program:
- Communication Sciences and Disorders
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- June 15, 2021
- Committee Members:
- Krista Wilkinson, Major Field Member
Diane Williams, Chair & Dissertation Advisor
Carol Miller, Major Field Member
Susan Strauss, Outside Unit & Field Member
Diane Williams, Program Head/Chair - Keywords:
- autism
gender
transgender
nonbinary
gender variance
women
narrative - Abstract:
- Current diagnostic models for autism are largely based on research with male children. Growing evidence suggests that sex and/or gender may affect autism presentation. Clinicians who diagnose autism tend to formally or informally elicit some narratives about the person’s experience during assessment. However, it is unknown whether the narratives of transgender, nonbinary, or female autistic individuals share common features to those reported for cisgender autistic males or whether they differ from those expectations. The present mixed-methods study collected and analyzed narratives told by 20 autistic adults, 20 to 57 years of age, whose genders are under-represented in the research literature. Participants scored above threshold for autism on the short form of the Ritvo Autism and Asperger Diagnostic Scale (RAADS-14). They completed a virtual interview, during which they told four stories: (1) about a personal interest, (2) about an interpersonal activity, (3) about a picture, and (4) an imagined story based on the picture. They also completed an online survey that included measures of camouflaging and psychological distress. Qualitative analyses followed the principles of discourse analysis to inductively examine the microstructure (i.e., words and grammar), mesostructure (i.e., themes), and macrostructure (i.e., cohesion) of participant responses. Common themes across participants and narrative tasks included attempts to maximize the correctness of responses by asking clarifying questions and revising sentences in progress. Within- and across-task thematic patterns revealed consistent emphasis on human characters and interpersonal connections. Macrostructural analysis revealed that participants used traditional narrative arcs as well as other cohesive strategies like listing. Notable key features of the microstructure included: verbs of agency (e.g., “I can”); epistemic markers (e.g., “I don’t know”); references to persons, time, and space; implicature (e.g., whether too much or too little information was provided); and formulaic expressions (e.g., “before I knew it”). Participants almost always introduced characters in their stories by role before referring to them by pronouns. Nonbinary participants tended not to use gendered terms to refer to characters they did not personally know. Non-parametric statistical analyses revealed significant effects of narrative task on length, vocabulary diversity, and the use of internal state terms. Although statistical tests indicated no statistically significant effects of gender on any quantitative variable, some gender-related patterns emerged suggesting that women may tell longer stories with less diverse vocabulary than men and nonbinary people do. Analyzing the discourse produced by diverse autistic people will contribute to a greater understanding of different communication styles, informing all people of possible ways to communicate more respectfully and supportively.