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Beyond the Lorna Wing Typologies: Personality Profiles in Autism Spectrum Disorder Reconsidered
Recent research has highlighted the substantial association between personality traits as assessed by the Five-Factor Model (FFM) and autism spectrum disorder (ASD) characteristics (Lodi-Smith et al., 2018). Notably, FFM personality domain scores appear to differ across the typically-developing and ASD populations and are correlated to some extent with measures of core ASD features. Despite these findings, there is a great deal of variability in personality profiles of individuals with ASD (Schwartzman et al., 2016). This heterogeneity of personality trait expression in the ASD population reflects the notion of “multiple autisms” found in the ASD genetics and neuroscience literatures. By observing ASD symptomatology through a personality lens, it may be possible to better identify ASD subtypes, and to understand variability in symptom profiles. Establishing these links and subtypes could ultimately contribute to efforts to understand developmental pathways and moderators of these pathways for people with ASD.
Objectives:
The current study aimed to extend previous findings on differences in personality traits between typically-developing and ASD populations, determine the extent to which personality traits predict autism symptom expression, and identify common personality profiles that may be representative of autism subtypes in the ASD population.
Methods:
Personality and ASD symptom expression data were collected in a sample consisting of both typically-developing individuals and individuals with ASD ages 12 to 22 (N=176). Youth with ASD (cASD; n=47; Mage=14.49 years) were compared with typically-developing youth (cTYP; n=49; Mage=14.47 years) and adults with ASD (aASD; n=41; Mage=19.88 years) were compared with typically-developing adults (aTYP; n=39; Mage=19.95 years) on each Big Five Inventory (BFI) domain (Extraversion, Agreeableness, Conscientiousness, Negative Emotionality, Open-Mindedness) and on secondary personality facets. Regression models were used to calculate the amount of variance accounted for by BFI domains and facets in Social Responsive Scale (SRS) scores. A K-means cluster analysis was used to examine the score patterns to identify common profiles within the ASD subsample (n=81).
Results:
T-tests revealed significant differences (p<.05) across three personality domains (Extraversion, Conscientiousness, Negative Emotionality) between the cTYP and cASD groups; significant differences (p<.05) were also found across all five domains between the aTYP and aASD groups. Personality facets accounted for 30% and 37% of variance in autism core symptom expression in the youth and adult subgroups, respectively. Three distinct personality profiles were identified in the ASD subsample (37%, 35%, and 28% of the sample, respectively). The clusters differed markedly on Extraversion, Agreeableness, Conscientiousness, and Negative Emotionality. These groups had unique associations with other clinical characteristics such as SRS scores.
Conclusions:
The present results converge with previous findings, suggesting a significant association between personality traits and ASD characteristics. The three identified cluster subgroups present distinct personality profiles that are indicative of notably heterogeneous ASD phenotypes. Future research should use the FFM framework to better understand the substantial heterogeneity within ASD and investigate the degree to which personality may moderate or mediate the relationship between core neurocognitive processes and ASD symptom expression as individuals develop.