Autistic Intelligence: Interaction, Individuality, and the Challenges of Diagnosis

Autistic Intelligence: Interaction, Individuality, and the Challenges of Diagnosis by Maynard and Turowetz (2022) addresses the importance of exploring language used in interactions during the diagnostic process of autism spectrum disorder. The authors analyze interaction in order to clarify the ambiguity in understanding autism that exists across several fields of study. Drawing on their sociological backgrounds, the authors use an ethnomethodological conversation analytic approach to show that interaction has been overlooked in the autism diagnostic process. This research makes an important contribution to existing conversation analytic and psychological literature by reframing autism spectrum disorder as a difference rather than a deficit.

Journal Article Social Actions, Gestalt Coherence, and Designations of Disability: Lessons from and about Autism Get access Douglas W. Maynard Douglas W. Maynard University of Wisconsin Direct correspondence to: Douglas W. Maynard, Department of Sociology, University of Wisconsin, Madison, WI 53706. E-mail: maynard@ssc.wisc.edu Search for other works by this author on: Oxford Academic PubMed Google Scholar Social Problems, Volume 52, Issue 4, 1 November 2005, Pages 499–524, https://doi.org/10.1525/sp.2005.52.4.499 Published: 30 July 2014

BackgroundStudies on autistic strengths are often focused on what they reveal about autistic intelligence and, in some cases, exceptional and atypical reasoning abilities. An emerging research trend has demonstrated how interests and strengths often evident in autism can be harnessed in interventions to promote the well-being, adaptive, academic and professional success of autistic people. However, abilities in certain domains may be accompanied by major limitations in others, as well as psychiatric and behavioral issues, which may challenge their inclusion in support programs.ObjectivesTo provide an in-depth, pragmatic, real-life example of the psychological and psychiatric management of interests and strengths in an autistic adolescent.MethodAn autistic teenager, C.A., with above-average calendar calculation and musical abilities, received psychiatric, neuropsychological, and language standardized and clinical assessments, combined with a measurement of his musical and calendar calculation abilities. C.A. and his parents then received psychiatric and psychological support over a 14-month period, targeting their perceptions of C.A.’s interests, strengths, and co-occurring difficulties.ResultsC.A. had a verbal IQ within the intellectual disability range and a non-verbal IQ in the low mean range. Modest calendar calculation, absolute pitch, and matrix abilities coexisted with severe receptive and expressive language disorder. The discrepancy between his abilities in areas of strengths and his limitations in other domains led to anxiety, frustration, and sometimes behavioral issues. Displacing the focus from academic performance to interests, as well as promoting the use of his strengths to develop new skills independently of their short-term adaptive benefits yielded positive effects on C.A.’s self-assessment, quality of life, and behavior at follow up.DiscussionThe appealing idea that abilities mostly found in autistic people, such as calendar calculation, can be directly harnessed into academic achievement and lead to paid employment may have detrimental effects, especially when such abilities are modest and associated with other limitations. These abilities should be primarily used to maximize well-being and quality of life, independently of their short-term adaptive function, which may or may not be positive.

Douglas W. Maynard and Jason Turowetz. Autistic Intelligence: Interaction, Individuality, and the Challenges of Diagnosis. Chicago: University of Chicago Press, 2022

Review of “Autistic Intelligence: Interaction, Individuality, and the Challenges of Diagnosis”

This article contributes to the sociology of science and technology through the study of language use and social interaction. As an analysis of how clinicians examine children to diagnose developmental disabilities, it involves the sociology of testing and standardization, with our particular focus on Autism Spectrum Disorders. Whereas previous research has concentrated primarily on the outcomes of testing, such as diagnostic trends, little has been written about the tests by which these trends are produced. Our analysis shows how psychometric tests operate to shape the interactive environments (those established by the test instrument, scoring metrics, etc.). Additionally, the interactional environment (the practices by which protocols are implemented as clinician and child do the test) exerts an influence on performance. In short, the interactive and interactional environment may affect the measurement of ability and difference in children. We propose that the emphasis of clinical tests on measuring second-order, abstract competence—or the ability to produce general answers to theoretical questions—may obscure various kinds of first-order, concrete competence and “autistic intelligence” a child displays. As forms of first-order, concrete competence, we examine orientation in situ to testing history, narrative combinations of test items, and using filler words for test item answers.

:<i>Autistic Intelligence: Interaction, Individuality, and the Challenges of Diagnosis</i>

This paper was originally published in 1992. It arose out of a project to study how clinicians tell parents a diagnosis of a developmental disability. That specific project was part of a larger one conducted in 1985-1986 to study the delivery of bad and good news in both ordinary and medical settings (Maynard, 2003). As part of the developmental disabilities study, we also examined how testing was done as a precedent to deciding on diagnosis (Marlaire and Maynard, 1989), and the paper here about the “interactional substrate” was meant to show the orderliness of testing interactions – the basic structures that made it possible to generate valid and reliable examination scores that could lend to the official assessment. More recently (2013-2015), a research team and I returned to the same clinic with a grant from the U.S. National Science Foundation, to study more intensively the testing and diagnosis of Autism Spectrum Disorders (ASD). In the time between the 1985 study and the recent one, the prevalence of ASD had skyrocketed in the U.S. from 1 in 5000 children to the current rate of 1 in 68. A study of the micro-interactions surrounding testing and diagnosis does not explain the increase in prevalence but it does say just how testing is done and how clinicians use results and other information to diagnose children. With regard to testing, in particular, we have come back to the paper on the interactional substrate again and again because probing this substrate and the practices by which it is constituted remains as an avenue in to understanding ASD as not just a condition of the child but as something that is manifested as a feature of social interaction. There are ways in which ASD as a child’s condition is co-produced by way of (i) the orderliness of interactions between clinicians and children, and (ii) how tests constrain both the clinician and the child in terms of what is visible as “competence.” Thus, in current work, we distinguish between what we call first-order, or concrete competence, which, by way of the interactional substrate, allows testing to be done, regardless of what the official results may be, and second-order displays of abstract competence (Maynard and Turowetz, 2016). Abstract competence involves the ability to produce general answers or ones that are shorn of embodied or other contextual orientations to questions or that involve what Donaldson (1978) has called “disembedded knowledge.” The emphasis of clinical tests on measuring second-order, abstract competence may obscure various kinds of first-order, concrete competence and “autistic intelligence” a child displays (Maynard, 2005). By doing so, testing can potentially make the child seem more impaired than he or she is, or at least suppress information that could improve performance and/or be informative for how to design home and schooling environments that enhance a child’s skills and integration into these social units. Keywords: psychological testing, conversation analysis, disability.

At the time of diagnosis, parents of autistic children frequently wonder what the future holds for their children in terms of intellectual development. It remains however difficult to answer this question at such a young age. Indeed, while early precursors of intelligence are well known for children following a typical development, these precursors remain to be identified for autistic children. Some theoretical models of intelligence suggest that perceptual abilities or behaviors, as seen early in autistic cognitive development, could be early indicators of intelligence. However, research examining the relation between early perceptual predictors and autistic intelligence over time is needed. This article is the first to consider a variety of early perceptual abilities and behaviors as precursors/predictors of intelligence at school age in autistic children. We showed that better performance in perceptual tasks at preschool age predicted better intellectual abilities measured later in autistic children. Importantly, our sample of autistic children represented the whole spectrum, including children with few to no spoken words, who are an important proportion of autistic preschoolers. While early perceptual abilities and behaviors may not substitute for a formal intellectual assessment, our results support that these indices may help estimate later intellectual level in autistic children. Perceptual abilities have the advantage to be easy to observe at preschool age and seem to fit the cognitive style of autistic children. Assessment methods could probably gain from including and focusing more on the perceptual strengths of autistic children.

Wechsler Intelligence Scale for Children (WISC) is widely used to estimate autistic intelligence (Joseph in The neuropsychology of autism. Oxford University Press, Oxford, 2011; Goldstein et al. in Assessment of autism spectrum disorders. Guilford Press, New York, 2008; Mottron in J Autism Dev Disord 34(1):19-27, 2004). However, previous studies suggest that while WISC-III and Raven's Progressive Matrices (RPM) provide similar estimates of non-autistic intelligence, autistic children perform significantly better on RPM (Dawson et al. in Psychol Sci 18(8):657-662, doi: 10.1111/j.1467-9280.2007.01954.x , 2007). The latest WISC version introduces substantial changes in subtests and index scores; thus, we asked whether WISC-IV still underestimates autistic intelligence. Twenty-five autistic and 22 typical children completed WISC-IV and RPM. Autistic children's RPM scores were significantly higher than their WISC-IV FSIQ, but there was no significant difference in typical children. Further, autistic children showed a distinctively uneven WISC-IV index profile, with a "peak" in the new Perceptual Reasoning Index. In spite of major changes, WISC-IV FSIQ continues to underestimate autistic intelligence.

:<i>Autistic Intelligence: Interaction, Individuality, and the Challenges of Diagnosis</i>

Book Review: Douglas Maynard and Jason Turowetz, <i>Autistic Intelligence: Interaction, Individuality, and the Challenges of Diagnosis</i>

4. Autistic Intelligence as Uncommon Sense

: <i>Autistic Intelligence: Interaction, Individuality, and the Challenges of Diagnosis</i>

Across the autism spectrum, level of intelligence is highly dependent on the psychometric instrument used for assessment, and there are conflicting views concerning which measures best estimate autistic cognitive abilities. Inspection time is a processing speed measure associated with general intelligence in typical individuals. We therefore investigated autism spectrum performance on inspection time in relation to two different general intelligence tests. Autism spectrum individuals were divided into autistic and Asperger subgroups according to speech development history. Compared to a typical control group, mean inspection time for the autistic subgroup but not the Asperger subgroup was significantly shorter (by 31%). However, the shorter mean autistic inspection time was evident only when groups were matched on Wechsler IQ and disappeared when they were matched using Raven's Progressive Matrices. When autism spectrum abilities are compared to typical abilities, results may be influenced by speech development history as well as by the instrument used for intelligence matching.