Divergent Patterns of Speaker-Intention Discrimination and Emotional Valence Ratings in Self-Reported Autistic and Non-Autistic Adults

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Rothermich, K., Rountree, M., Ahn, S., Caldwell-Harris, C. L., & Dannhauer, M. (2026). Divergent Patterns of Speaker-Intention Discrimination and Emotional Valence Ratings in Self-Reported Autistic and Non-Autistic Adults. Autism. https://doi.org/10.1177/13623613261487284

Journal or book title
Autism
Publisher
SAGE Publications
Article number
13623613261487284
Publication date: 27 Sep 2026 Added to AutiHub: 29 Sep 2026 Type: Article Article language: English
Publisher source (DOI) OpenAlex source

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Authors

Publication authors
5
Publication authors identified as autistic
1 / 5 (20.0%)
  1. Kathrin Rothermich
  2. Mackenzie Rountree
  3. Sungwoo Ahn
  4. Catherine L. Caldwell-Harris *
  5. Moritz Dannhauer

Abstract

Autistic adults often interpret verbal and non-verbal cues underlying non-literal language differently compared to non-autistic people, reflecting differences in communicative style and shared context. Research on non-literal language in autism in controlled settings has typically depended on static stimuli that lack ecological validity and primarily focused on children, leaving non-literal language processing in autistic adults relatively understudied. The present study examined how self-reported autistic and non-autistic adults infer speaker intentions and emotional valence in dynamic, naturalistic videos. Participants (N = 66) viewed 50 brief videos from the Relational Inference in Social Communication database, depicting literal, sarcastic, teasing, or prosocial lie scenarios. After each video, they identified the speaker’s communicative intent and rated the emotional response of the addressee. Participants also completed two measures of autistic characteristics (Autism Spectrum Quotient; Comprehensive Autistic Trait Inventory). Self-reported autistic participants showed lower speaker-intention discrimination than non-autistic participants, whereas valence ratings were similar across intentions. Autistic traits predicted lower speaker-intention discrimination in non-autistic adults but were unrelated (Comprehensive Autistic Trait Inventory) or positively associated (Autism Spectrum Quotient) in self-reported autistic adults. These findings highlight shared and differing aspects of social communication and support combining categorical and trait-based approaches to understand individual differences. Lay Abstract Autistic adults often interpret non-literal language such as sarcasm differently, which can affect everyday communication. However, prior research studies have often used written or static materials that do not reflect real-life conversations. In this study, we examined how self-reported autistic and non-autistic adults understand sarcasm, teasing, and prosocial lies using short, realistic video clips. We used videos showing actors having a short conversation. After each video, we asked participants to identify the intention that was used (literal, sarcastic, teasing, or prosocial lie) and to evaluate how happy the person receiving the statement felt. Participants also reported whether they had an autism diagnosis or self-identified as autistic and completed two questionnaires measuring autistic traits (Autism Spectrum Quotient; Comprehensive Autistic Trait Inventory). We found that autistic adults were less accurate than non-autistic adults in identifying speaker intentions, but both groups judged the emotional impact of the statements in similar ways. Among non-autistic adults, higher levels of autistic traits were linked to more difficulty identifying speaker intentions. In contrast, autistic traits were not linked, or were even linked to better performance, in autistic adults. These findings suggest that autistic and non-autistic people may use both shared and different strategies when interpreting social communication and highlight the importance of considering both diagnosis and individual traits.

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Cited references
75
With a DOI
72
Without a DOI, from raw bibliography text
3
8 / 75 (10.7%) cited references include at least one author identified as autistic.
References with data to complete
0 / 75 (0.0%)
References with detected author names
75 / 75 (100.0%)
Without detected author names
0
Without a structured title
0
Without a stable identifier
3
References with raw author names still to review
0
References with external metadata lookup issues
0
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
276
From DOI or external metadata
276
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
0
74 / 276 (26.8%) names are linked to an author already present in AutiHub. 202 / 276 (73.2%) names are not yet linked.
Names linked to a person identified as autistic
9 / 276 (3.3%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 9 / 74 (12.2%). Distinct people identified as autistic: 8 / 241 (3.3%).
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