Autism Identity and the “Lost Generation”: Structural Validation of the Autism Spectrum Identity Scale and Comparison of Diagnosed and Self-Diagnosed Adults on the Autism Spectrum

Abstract

Background: A population segment of autistic adults are underidentified 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 selfdiagnosed 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 well-being. The diagnosed data set was randomly split with exploratory factor analysis performed on a training data set. Split-half crossvalidation was used to predict the factor structure of the holdout data set. Then, the full diagnosed data set structure was used to determine the generalizability of the factor structure to the self-diagnosed data set. 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 selfdiagnosed data set from the diagnosed data set ranged from 0.97 to 1.00 with similar internal consistency. Selfdiagnosed 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 samples. The profile of self-diagnosed participants matches the profile hypothesized for the ''lost generation'' and others at risk of being underidentified 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.

Autism Through the Ages: A Mixed Methods Approach to Understanding How Age and Age of Diagnosis Affect Quality of Life

“…Study 1 suggested that autistic adults experience lower QoL than TDs, as has been found by other studies (McDonald, 2020 ; van Heijst & Geurts, 2015 ). However, in contrast to other research (van Heijst & Geurts, 2015 ), autistic adults in our study were found to have a different developmental trajectory than TDs regarding age and its relation to QoL outcomes.…”

The Impact of COVID-19 on Sleep in Autistic Adults: Longitudinal Comparisons pre and During Lockdown

“…Evidence has suggested that following a diagnosis of ASD, anxiety reduces in autistic adults, it is also possible that anxiety is related to camouflaging practises often seen in self-diagnosed individuals ( 24 ). This finding could also reflect a lack of healthcare support provided to autistic individuals who have not received a diagnosis leading to higher anxiety outcomes ( 25 ).…”

“…However, during the Time 1 survey we did ask participants to provide information on their diagnosis (e.g., age of diagnosis, professional who gave the diagnosis and month and year of the diagnosis) to potentially limit this issue. A recent study by McDonald ( 25 ) provided a comparison between autistic adults that are self-diagnosed vs. diagnosed by a HCP, the study found the inclusion of self-reported autistic adults in online surveys likely represents the “lost generation” of autistic adults, such as older females. In our sample there are three times more females than males included aged between 18 and 65 years old.…”

Anxiety, Insomnia, and Napping Predict Poorer Sleep Quality in an Autistic Adult Population

“…Further, participants who self-reported their autism diagnosis were also included in the sample. That said, McDonald [ 44 ] compared autistic adults self-diagnosed to autistic adults diagnosed by a HCP and found the inclusion of self-reported autistic adults in online surveys likely represents the “lost generation” of autistic adults, such as older females. In the present sample, there were twice as many females than males, aged between 18 and 73 years old.…”

“…Participants were recruited for an online survey, between November 2019 to February 2020, via social media and autism support groups. All adults that identified as an autistic adult were included in our sample to allow access to a more diverse population and reduce barriers related to accessing an autism diagnoses in adulthood [ 43 , 44 ]. Of the 837 UK participants that responded to the online Qualtrics XM survey, 58.90% fully completed the survey ( n = 493 final sample).…”