Dataset Information

Autism Identity and the "Lost Generation": Structural Validation of the Autism Spectrum Identity Scale (ASIS) and Comparison of Diagnosed and Self-Diagnosed Adults on the Autism Spectrum.

ABSTRACT:

Background

A population segment of autistic adults are under-identified due, in part, to historic changes in criteria for diagnosing autism and diagnostic biases related to gender, socioeconomic status, and other individual characteristics such as intellectual functioning. Some of these individuals, described as the "lost generation", may choose to self-diagnose. Although little is known about this population, it is possible that they share similar self-conceptualizations or internalized stigma as their diagnosed counterparts. This study reports on the structural validity of the Autism Spectrum Identity Scale (ASIS) with individuals diagnosed and self-diagnosed with autism and compares the demographic characteristics, stigma, self-concept, and quality of life of these two groups.

Methods

Over 1000 adults diagnosed (n = 893) or self-diagnosed (n = 245) with autism were recruited through organizations serving the autism community to participate in a nationally distributed online survey that included demographic questions and measures for stigma, self-concept, quality of life, and wellbeing. The diagnosed dataset was randomly split with exploratory factor analysis performed on a training dataset. Split-half cross-validation was used to predict the factor structure of the holdout dataset. Then, the full diagnosed dataset structure was used to determine the generalizability of the factor structure to the self-diagnosed dataset. The diagnosed and self-diagnosed were also compared for differences in gender, age, employment status, diagnostic term preference, and factors of self-concept (autism identity and self-esteem), stigma, and quality of life.

Results

Factor analysis of diagnosed participants yielded a four-factor structure, consistent with previous research, with strong split-sample cross-validation and good internal consistency. Factor predictions of the self-diagnosed dataset from the diagnosed dataset ranged from .97 - 1.00 with similar internal consistency. Self-diagnosed participants were more likely to be older, women, or employed and less likely to be students or prefer the term "autism" than those with an autism diagnosis. The groups were remarkably similar in reported stigma, self-esteem, quality of life and in ASIS factors; both groups reported lower quality of life than the general population.

Conclusions

The ASIS demonstrated the same internal structure with both the diagnosed and self-diagnosed. The profile of self-diagnosed participants matches the profile hypothesized for the "lost generation" and others at risk of being under-identified for autism. Both populations appear to be similarly struggling with employment, stigma, and quality of life. Future research should examine whether self-diagnosed individuals meet criteria for autism or could benefit from interventions, programs, or services serving autism communities.

SUBMITTER: McDonald TAM

PROVIDER: S-EPMC8415774 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background:The aim of this paper was to provide an initial validation of a newly developed parent questionnaire-the Stanford Social Dimensions Scale (SSDS), designed to capture individual differences across several key social dimensions including social motivation in children and adolescents with and without psychiatric disorders. Methods:The initial validation sample was comprised of parents of 175 individuals with autism spectrum disorder (ASD) (35 females, 140 males; M age = 7.19 years, SD age = 3.96) and the replication sample consisted of 624 parents of children who were either typically developing or presented with a range of neurodevelopmental and neuropsychiatric disorders (302 females, 322 males; M age = 11.49 years, SDage = 4.48). Parents from both samples completed the SSDS and the Social Responsiveness Scale (SRS-2). Results:Exploratory Structural Equation Modeling indicated that a 5-factor model provided adequate to excellent fit to the data in the initial ASD sample (comparative fit index [CFI] = .940, Tucker-Lewis Index [TLI] = .919, root mean square error of approximation [RMSEA] = .048, standardized root mean square residual [SRMR] = .038). The identified factors were interpreted as Social Motivation, Social Affiliation, Expressive Social Communication, Social Recognition, and Unusual Approach. This factor structure was further confirmed in Sample 2 (CFI = 946, TLI = .930, RMSEA = .044, SRMR = .026). Internal consistency for all subscales was in the good to excellent range across both samples as indicated by Composite Reliability scores of ≥ .72. Convergent and divergent validity was strong as indexed by the pattern of correlations with relevant SRS-2 and Child Behavior Checklist domains and with verbal and non-verbal intellectual functioning scores in Sample 1 and with the Need to Belong Scale and Child Social Preference Scale scores in Sample 2. Across both samples, females had higher social motivation and expressive social communication scores. Discriminant validity was strong given that across all SSDS subscales, the ASD sample had significantly higher impairment than both the typically developing group and the group with other clinical conditions, which in turn, had significantly higher impairment than the typically developing group. Conclusions:Our findings provide initial validation of a new scale designed to comprehensively capture individual differences in social motivation and other key social dimensions in ASD.

Project description:BackgroundAlmost all children with autism spectrum disorder (ASD) have experienced challenging behavior, including disruptive and aggressive behavior symptoms to both themselves and others. In conjunction with appropriate strategic parenting, challenging behavior can be prevented by empowering children's sociality and optimizing their environment. However, a means of measuring such parenting has yet to appear. This study developed the Parental Self-Efficacy Scale for Preventing Challenging Behaviors in Children with Autism Spectrum Disorder (PASEC) and evaluated its reliability and validity.MethodSelf-administered questionnaires were distributed to 1,344 parents of children with ASD at all 521 child development support centers in Japan. Confirmed construct validity of the PASEC was determined using confirmatory factor analysis. Internal consistency of the PASEC was calculated using Cronbach's alpha. The self-efficacy subscale of the Parenting Sense of Competence (PSOC) was administered to assess criterion-related validity of the PASEC.ResultsIn total, 260 parents provided valid responses. Exploratory and confirmatory factor analyses identified six items from two factors: empowerment of children's sociality and optimization of children's environment. The final model showed goodness-of-fit index, 0.981; adjusted goodness-of-fit index, 0.944; comparative fit index, 0.999; and root mean square error of approximation, 0.019. Cronbach's alpha for the entire PASEC was 0.82; that for each factor was above 0.70. The correlation coefficient between the self-efficacy subscale of the PSOC and the entire PASEC was r = 0.52 (P <0.001).ConclusionsThe PASEC demonstrated adequate reliability and validity to assess parents' self-efficacy for preventing challenging behavior for children with ASD. That scale can help prevent challenging behavior; it can contribute to improving the mental health of parents and children with ASD as well as to primary prevention of child maltreatment and abuse.