“Second guessing yourself all the time about what they really mean…”: Cognitive differences between autistic and non‐autistic adults in understanding implied meaning

Abstract

This study investigated cognitive differences between autistic and non‐autistic people in understanding implied meaning in conversation using a novel computerized test, the Implicature Comprehension Test. Controlling for core language ability, autistic participants (N = 66) were over twice as likely to endorse a non‐normative interpretation of an implied meaning and over five times as likely to select “do not know” when asked about the presence of an implied meaning, compared to non‐autistic participants (N = 118). A further experiment suggested that the selection of “do not know” reflected a cognitive preference for certainty and explicit communication, and that the normative inference could often be made when the test format was more constrained. Our research supports the hypothesis that autistic individuals can find it challenging to process language in its pragmatic context, and that cognitive preferences play a role in this. Lay summary We investigated differences between autistic and non‐autistic people in understanding implied meanings in conversation. We found that autistic people were more likely to select a different interpretation of implied meanings compared to other people, and also much more likely to avoid processing implied meanings when the task allowed this. Our research supports the view that autistic people can find it challenging to process indirect meanings, and that they tend to prefer explicit forms of communication.

Judging meaning: A domain-level difference between autistic and non-autistic adults

“…With respect to the Implicature Comprehension Test, some of the group difference on this task was 'fractionated' at the general factor level, and in explaining the nature of that difference, we appeal to a domain-general information-integration account. In Wilson & Bishop [43], we provided evidence that a cognitive preference for certainty and explicit communication played a role in performance on the task, so perhaps the group difference 'fractionated' at the specific test-level reflected that cognitive preference. This is speculative, but suggests we ought to move away from a cognitive model that suggests there is one source of the communication phenotype in autism.…”

Registered report: investigating a preference for certainty in conversation among autistic adults compared to dyslexic adults and the general population

“…In the second example, the speaker communicates implicitly, leaving the listener to process the implicature that they would probably prefer to stay inside. In a previous study, we provided evidence for cognitive differences between autistic and non-autistic people in processing implicatures ( Wilson & Bishop, 2020b ). Crucially, it seemed that a cognitive preference for certainty and explicit communication, and not simply reduced ability, may account for some of the differences.…”

“…Participants completed the Implicature Comprehension Test, which required individuals to listen to short conversational interchanges that are followed by a comprehension question to assess whether an implied meaning has been processed; test-takers responded with ‘yes’, ‘no’ or ‘don’t know’. Controlling for grammar/vocabulary ability, we found that autistic adults ( N = 66) were 6.19, 95% CI [3.63–10.39], times more likely to select the ‘don’t know’ rather than the correct response compared to non-autistic people ( N = 118), and also 2.56, 95% CI [1.76–3.77], times more likely to choose the ‘incorrect’ response ( Wilson & Bishop, 2020b ). Group differences were large, and performance on the test gave 76% sensitivity and specificity for differentiating between autistic and non-autistic groups.…”

Peer Review #1 of "Registered report: investigating a preference for certainty in conversation among autistic adults compared to dyslexic adults and the general population (v0.1)"

“…We determined power to detect the three-way interaction described in Hypothesis 1 using simulations. We used data reported in Wilson and Bishop (2020b) to estimate the likely size of fixed and random effects in the mixed model described in Data Analysis below. Using R package simr (Green & MacLeod, 2016) we ran 1000 simulations with a sample size of 200 people (100 autistic, 100 non-autistic) and a significant three-way interaction was found in 9830 simulations, indicating that power was over 98% to detect our effect of interest at an alpha level of .05.…”