The relationship between age of autism diagnosis and life satisfaction in adulthood

Abstract

This study examined how age of autism diagnosis relates to adult life satisfaction in a sample of 769 self-reporting autistic adults. We analyzed how demographic and clinical variables related to age of diagnosis and then analyzed the relationship between age of diagnosis and scores on four measures of life satisfaction while controlling for variables significantly associated with age of diagnosis. Participants diagnosed in adulthood were older, less likely to have an intellectual disability, more likely to be assigned female at birth, more likely to identify as a sexual minority, and had higher self-reported autistic traits than those diagnosed earlier. Controlling for these factors, participants diagnosed between ages 3 and 5 reported higher levels of flourishing, autonomy satisfaction, and social satisfaction than those diagnosed in adulthood. Diagnosis before 3 was also associated with more social satisfaction and autonomy satisfaction than adult diagnosis. Individuals diagnosed in adulthood did not significantly differ from those diagnosed between ages 6 and 11 or 12 and 17 on any outcome. These findings indicate that age of autism diagnosis is nonlinearly related to adult life satisfaction. Early childhood diagnosis was associated with more life satisfaction, but beyond early childhood, age of diagnosis was not reliably linked to adult life satisfaction.

Lay Abstract

More people are getting diagnosed with autism as teens and adults, and autism affects people throughout their lives. We need to know what factors, including age of diagnosis, affect how autistic adults are doing so that we can support them and create a world where they can thrive. In this study, we wanted to understand how people’s age of diagnosis relates to their life satisfaction as adults. Most of the research about the age of autism diagnosis focuses on childhood diagnosis and outcomes; thus, we wanted to study a wider range of diagnosis ages (including adult diagnosis) and life satisfaction in adulthood, an understudied area that is a focus for the autistic community. We surveyed 769 autistic adults about the age they were diagnosed, aspects of their identity (e.g., race/ethnicity, sex, gender, sexual orientation), and four measures of life satisfaction: flourishing and satisfaction with social relationships, employment/school, and autonomy. We used this data to look for patterns about how parts of adults’ identity relate to their age of diagnosis and how age of diagnosis relates to life satisfaction. We found that people diagnosed between 3 and 5 years old reported more flourishing and more satisfaction with their autonomy and social lives than people diagnosed as adults. However, people diagnosed later in childhood or adolescence were not more satisfied with those things than people diagnosed as adults. This suggests there may be something especially helpful about being diagnosed early. It is important to note, however, that because the study was correlational, we cannot say that being diagnosed early causes better outcomes in adulthood.

Keywords

adult diagnosis adult outcomes age of diagnosis autism life satisfaction quality of life

Although clinicians can reliably diagnose autism in children as young as 2 years old (Lord et al., 2006), there is wide variability in when people receive an autism diagnosis, and diagnoses in adulthood are rapidly rising in recent years (Russell et al., 2022). A timely diagnosis facilitates the receipt of interventions and support and can lead to better cognitive, social, and academic outcomes in autistic children (Hyman et al., 2020). For example, autistic children with an earlier autism diagnosis access more resources, demonstrate better verbal and overall cognitive outcomes, and are more likely to attend a mainstream school (Okoye et al., 2023). Although researchers have studied diagnostic timing and early intervention effects in childhood samples, less is known about how age of autism diagnosis (AoD) relates to adult outcomes, especially positive life outcomes (e.g., life satisfaction). Furthermore, prior work has focused primarily on samples diagnosed in childhood (e.g., comparing diagnosis in early childhood to diagnosis in later childhood); therefore, we know very little about diagnostic timing outcomes after childhood. In other words, is there still a benefit to being diagnosed earlier once you are out of the early childhood period? In the present study, we aimed to fill these gaps by investigating the relationship between AoD and life satisfaction in adulthood. Because there are a number of sociodemographic and clinical variables that have been shown to be associated with AoD (Loubersac et al., 2023) and adult life outcomes in autistic individuals, we first determine sociodemographic and clinical variables that are associated with AoD in the present sample and then analyze the relationship between AoD and measures of life satisfaction while controlling for these variables.

Prior research on age of diagnosis and positive life outcomes in adulthood

Only a handful of studies, mostly published in the last 5 years, have specifically examined the association between AoD and positive life outcomes in adulthood, and results from these studies are mixed. Three studies found that later AoD, or age of learning one is autistic, is associated with worse adult life outcomes (Atherton et al., 2022; Kamio et al., 2013; Oredipe et al., 2022). Atherton and colleagues (2022) examined the association between AoD and quality of life in a sample of 210 British autistic adults. Adults who were diagnosed earlier in life had a higher quality of life, although no control variables were included in this analysis. Oredipe and colleagues (2022) used a sample of 78 mostly American autistic university students and found that a younger age of learning one is autistic was associated with a higher quality of life and higher well-being, controlling for current age, self-reported autistic traits, and gender. It is important to note that this study focused on when participants learned they were autistic rather than the age they were diagnosed, although other research suggests these two variables are very closely associated (Leung et al., 2024). Finally, Kamio and colleagues (Kamio et al., 2013) used a sample of 154 Japanese autistic adults and found that an AoD under 4 years old predicted a higher quality of life compared to being diagnosed above 4, although they used a stepwise regression procedure and ultimately did not control for common demographic or clinical variables in these models.

Other studies did not find a significant association between AoD and adult quality of life after controlling for relevant variables (Leung et al., 2024; Mason et al., 2018). Leung and colleagues (2024) attempted to replicate findings from Oredipe and colleagues (2022) in a sample of 300 adults from the United Kingdom; while both a higher AoD and age of learning one is autistic were associated with worse quality of life in bivariate correlations, neither AoD nor the age of learning one is autistic were significant predictors of quality of life when controlling for other variables (i.e., autistic traits, age, sex, ethnicity, relationship status, living status, education level, employment status, adjusted income, and co-occurring mental health conditions). Finally, Mason and colleagues (2018) used a sample of 370 autistic people from the United Kingdom and found that AoD approached but did not reach significance for predicting quality of life after controlling for other variables (i.e., relationship status, living status, employment status, co-occurring mental health conditions, physical health conditions, financial support, education level, autism traits), although it did reach significance when only considering participants with a formal diagnosis.

There are key patterns to note when examining the differences between the papers that found a relationship between AoD and adult quality of life and those that do not. First, both the Leung and colleagues (2024) and Mason and colleagues (2018) studies included co-occurring mental health conditions as an additional predictor of quality of life, which may have masked the association between AoD and quality of life. Co-occurring mental health conditions are associated with both a later AoD and with quality of life (Jadav & Bal, 2022; Leung et al., 2024); however, it is not clear from these cross-sectional studies whether co-occurring mental health conditions should be considered a predictor of quality of life or an associated outcome. In addition, those papers that found a significant relationship between AoD and quality of life had participants who were younger at the time of participation and diagnosed earlier on average than the participants in the studies that found no relationship. This brings into question whether there may be some “tipping point” after which differences in AoD no longer incrementally improve positive adult life outcomes (Russell et al., 2025). Perhaps the difference between being diagnosed in early childhood rather than adolescence is significant, while the difference between being diagnosed in adolescence versus adulthood is not. In addition, the ages of diagnosis tended to cluster to the mean in all studies, meaning that we do not have a clear picture of how a broad range of ages of diagnosis might impact positive adult outcomes.

Sociodemographic and clinical characteristics

When considering the association between AoD and positive adult outcomes, it is important to consider the sociodemographic and clinical characteristics that have been shown to be associated with both AoD and outcomes, as these may represent confounding variables. For example, a 2023 systematic review of predictors of AoD in autism reported that higher levels of autistic traits (e.g., more social communication challenges and/or restricted and repetitive behaviors) and the presence of an intellectual disability are generally associated with an earlier AoD (Loubersac et al., 2023) among studies of autistic children. The review reported mixed findings with regard to associations between sociodemographic variables like sex, race, parental education, and socioeconomic status and AoD, noting that some studies reported female sex at birth, Black or Hispanic racial/ethnic identity, lower parental education, and lower socioeconomic status to be associated with a later AoD, and other studies not find these associations (or even found reverse associations; Loubersac et al., 2023). Notably, the vast majority of studies on this topic have focused on child samples, thus excluding individuals diagnosed later in adolescence and adulthood. More recent research suggests that, in samples of self-reporting autistic adults, higher levels of autistic traits and female sex assigned at birth are both associated with a later age of diagnosis (Atherton et al., 2022; Leung et al., 2024; Milner et al., 2024).

Importantly, some of these same sociodemographic and clinical characteristics have been found to be associated with quality of life. For example, several studies have reported that higher levels of autistic traits and female sex assigned at birth relate to a lower quality of life in autistic adults (Kamio et al., 2013; Lin & Huang, 2019; Mason et al., 2018). Taken together, it is clear that certain sociodemographic and clinical characteristics are likely associated with both AoD and positive adult life outcomes and thus need to be considered when attempting to understand the association between these two variables.

The present study

Researchers are only beginning to understand how AoD and positive adult life outcomes are related. Prior work has key limitations (e.g., sample diversity, sample size). Most notably, all existing studies lacked sufficient variability in AoD and a sufficiently large sample size to provide a full understanding of how AoD relates to adult outcomes across a broad range of AoD. The present study uses a large sample with sufficient variability in AoD, aiming to fill key gaps in the literature on this topic. The primary aim of the present research was to assess the association between AoD and positive life outcomes in adulthood, with a focus on life satisfaction. Prior research in this area has focused almost exclusively on “quality of life,” most commonly measured using the World Health Organization Quality of Life Assessment-Brief (WHOQOL-BREF; THE WHOQOL GROUP, 1998). However, emerging work indicates that the WHOQOL-BREF was not designed for autistic respondents and that autistic adults can struggle to interpret several of its items, raising concerns about its content validity for this population (Beck et al., 2024). In contrast, the present study focuses on life satisfaction, assessed using the Relationships, Employment, Autonomy, and Life Satisfaction (REALS) measure—a questionnaire developed for and with autistic adults and shown to be understandable and psychometrically robust in this population (Conner et al., 2025; MacKenzie et al., 2025)—and the Adapted Flourishing Scale (AFS), another measure of life satisfaction developed by and for autistic adults. Life satisfaction and quality of life are highly related constructs; however, quality of life measures often integrate both subjective evaluations and externally defined criteria for what constitutes a “good life,” whereas life satisfaction reflects an individual’s subjective appraisal of how their life is going, without imposing external standards or expectations. By focusing on life satisfaction, we aimed to capture autistic adults’ own evaluations of their well-being using measures developed specifically for this community, thereby strengthening the conceptual and methodological relevance of our findings.

In order to accomplish our primary aim of examining the association between AoD and adult life satisfaction, we first assess the relationship between key demographic (i.e., age, sex assigned at birth, gender diversity, sexual orientation, and race/ethnicity) and clinical (i.e., self-reported autism traits, presence of an intellectual disability) variables and AoD. We then examined the association between AoD and positive life outcomes in adulthood while accounting for relevant demographic and clinical variables. We predicted that an earlier AoD would predict more positive life outcomes in adulthood, with this relationship decreasing in strength as the AoD increases. In other words, we predicted that the difference between being diagnosed in early childhood versus middle childhood would be greater than the difference between being diagnosed in adolescence versus adulthood.

Method

Participants and procedures

We conducted secondary analysis on a completed study, the REALS measure development study, a study aimed at developing and testing the psychometric properties of this measure among autistic adults and adults with other intellectual and developmental disabilities (Conner et al., 2025; MacKenzie et al., 2025). We collected data from July 2022 to August 2023 online via the Simons Powering Autism Research (SPARK) registry and via local recruitment. The study recruited a total of 910 self-reporting participants between ages 18 and 78 years with either autism or other intellectual and developmental disabilities. For the present study, we used only autistic participants (N = 818) as indicated by self-report of a professional diagnosis. Since AoD is central to our aims, we only included participants who provided their AoD in our analysis (N = 769 participants, M [SD] age = 35.19 [12.57] years). Participant demographics and clinical characteristics are reported in Table 1. All procedures performed were in accordance with the ethical standards of the University of Pittsburgh Institutional Review Board (Study Number: 19080355) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Table 1.

Demographic and clinical characteristics by AoD group.

Variable	N (total)	Whole sampleN = 769n (%)/M (SD)	Diagnosed<3N = 70n (%)/M (SD)	Diagnosed3–5N = 85n (%)/M (SD)	Diagnosed6–11N = 96n (%)/M (SD)	Diagnosed12–17N = 103n (%)/M (SD)	Diagnosed 18+N = 413n (%)/M (SD)
Current age	768	35.24 (12.51)	26.71 (7.00)	27.92 (7.74)	29.03 (8.60)	29.50 (7.52)	41.08 (12.84)
Sex at birth	764
Male		317 (41.49%)	45 (64.29%)	58 (69.05%)	55 (56.12%)	45 (44.55%)	114 (27.74%)
Female		445 (58.27%)	25 (35.71%)	26 (30.95%)	42 (42.86%)	56 (55.45%)	296 (72.02%)
Intersex		2 (0.26%)			1 (1.02%)		1 (0.24%)
Gender diverse	762	119 (15.62%)	5 (7.14%)	5 (5.95%)	15 (15.46%)	18 (17.82%)	75 (18.29%)
Sexual minority	749	441 (58.88%)	17 (25%)	24 (29.27%)	42 (43.75%)	35 (36.08%)	190 (46.80%)
Race/ethnicity^a	767
White		606 (79.01%)	46 (65.71%)	72 (84.71%)	75 (78.13%)	82 (79.61%)	331 (80.15%)
Black		47 (6.13%)	12 (17.14%)	2 (2.35%)	2 (2.08%)	8 (7.77%)	23 (5.57%)
Hispanic		56 (7.30%)	10 (14.29%)	9 (10.59%)	10 (10.42%)	6 (5.83%)	21 (5.08%)
Another race/ethnicity		58 (7.56%)	2 (2.86%)	2 (2.35%)	9 (9.38%)	7 (6.80%)	38 (9.20%)
Intellectual disability	769	48 (6.24%)	9 (12.86%)	14 (16.47%)	8 (8.16%)	5 (4.85%)	12 (2.91%)
Mean SRS-2 score	716	70.28 (10.16)	66.02 (10.65)	66.12 (10.33)	68.99 (10.27)	69.25 (9.91)	72.38 (9.54)

Asian American/Pacific Islanders, Native Americans, and participants of another race were placed into the “another” category due to small sample sizes. Mixed-race participants were assigned to the racial group with the highest prevalence in the sample other than White. See section “Measures” of “Method” for more information.

Measures

Age of diagnosis

We asked participants, “How old were you when first diagnosed with ASD?” The participant could choose from five categories: under 3 years old, 3–5 years old, 6–11 years old, 12–17 years old, and 18+ years old. Our largest category of participants was people diagnosed in adulthood, with slightly more than half falling into this category. The other four categories were roughly evenly distributed, with each category containing between 69 and 102 participants (see Table 1). The AoD categories were designed by the original survey team to be easy for adults to report retrospectively and to reflect broadly meaningful developmental periods: very early diagnosis (before the age at which autism is typically identified), pre-school age, middle childhood/school age, adolescence, and adulthood. Although these categories were not created specifically for the present research questions, they reflect developmentally meaningful periods that differ in terms of diagnostic pathways, service availability, and social contexts.

Sociodemographic measures

We asked participants about their age at the time of the survey, sex assigned at birth (“Male,” “Female,” and “Intersex”), gender identity (“Male,” “Female,” “Nonbinary/Gender Fluid,” “Agender/No Gender,” “Unsure/Questioning,” and “Other”), and sexual orientation (“Lesbian,” “Gay,” “Bisexual,” “Pansexual,” “Queer,” “Straight/Heterosexual,” “Asexual/Aromantic,” “Unsure/Questioning,” and “Other”) . For analyses, participants whose sex at birth aligned with their gender identity were categorized as “cisgender,” while everyone else (including transgender men, transgender women, and people who identified as “Nonbinary/Gender Fluid,” “Agender/No Gender,” “Unsure/Questioning,” and “Other”) was categorized as “gender diverse.” For sexual orientation, many categories had small samples, so we created two categories for analysis: “straight” and “sexual minority.” The “sexual minority” category included everyone except for people who selected “Straight/Heterosexual” and those who declined to answer (i.e., those selecting “Lesbian,” “Gay,” “Bisexual,” “Pansexual,” “Queer,” “Asexual/Aromantic,” “Unsure/Questioning,” “Other”).

We also asked participants about their race and Hispanic/Latine ethnicity. For analysis, we used a deterministic bridging method to assign multi-racial/ethnic participants to the single race/ethnicity they identified with that had the highest prevalence in the sample other than White (thus prioritizing their minoritized racial identity; Grieco, 2002; Northrup et al., 2024; Sivathasan et al., 2024). This resulted in racial categories of Asian American and Pacific Islander, Black or African American, Hispanic/Latine, Native American, White, or Another Race. Because the “Native American” (N = 28), “Asian American and Pacific Islander” (N = 19), and “Another Race” (N = 11) categories were so small, they were grouped together to form a larger category, which we have labeled “Another Race.”

Clinical characteristics

Intellectual Disability. We asked participants to report whether or not they had an intellectual disability diagnosis.

Social Responsiveness Scale, Second Edition (SRS-2). We used the SRS-2 as a measure of level of autistic traits. This self-report measure assesses five key domains: Social Awareness, Social Cognition, Social Communication, Social Motivation, and Restricted and Repetitive Behavior (Constantino, 2002). This scale has been shown in prior research to have excellent reliability and internal consistency and is commonly used to screen for autism (Constantino, 2002).

Outcome measures

To assess life satisfaction in adulthood, we used the AFS and the satisfaction domains from the REALS scales. Means and standard deviations of participant scores for each outcome measure are reported in Table 1.

AFS. The AFS is an adapted version of Diener’s Satisfaction with Life Scale (Beck et al., 2024; Diener et al., 1985) for autistic adults. The scale was developed by and for autistic adults through the Academic Autism Spectrum Partnership in Research and Education (AASPIRE; aaspire.org; Nicolaidis et al., 2020, 2025), a partnership between the academic community and the autistic community. The AFS includes eight self-reported items, with items related to life satisfaction, meaning, and other measures of flourishing on a 7-point Likert-type scale of 1 (strongly disagree) to 7 (strongly agree). This scale is in development, and currently no norms exist. Thus, we used the sum score of the eight items as a total score. Internal consistency for this scale in the REALS sample was strong (Cronbach’s alpha = .92; Conner et al., 2025).

REALS Measures. The REALS consists of a suite of self- and proxy-report measures that were developed to measure key areas of adult life for autistic adults and adults with other intellectual and developmental disabilities (Conner et al., 2025; MacKenzie et al., 2025). The REALS includes 25 total items about life satisfaction in the following domains: social activity (6 items), autonomy (14 items), and work/school (5 items). These items were rated on a 4-point satisfaction scale (0 = not at all, 1 = a little bit, 2 = quite a bit, 3 = completely), with higher scores indicating more life satisfaction in the domain. These items load onto the three scales: satisfaction with social activity; satisfaction with work/school; and satisfaction with autonomy. Previous work using the REALS sample demonstrated excellent internal consistency in the satisfaction scales (Cronbach’s alphas = 0.90–0.92; Conner et al., 2025).

Data analytic plan

Missing data occurred for several reasons typical of online survey designs. Because the study was administered entirely online, some participants skipped individual items, omitted entire measures, or discontinued the protocol before reaching the final section. As a result, the number of participants with complete data varies across questions and measures; sample sizes for each are reported in Tables 1 and 2. For all regression analyses, we employed listwise deletion, such that only participants with complete data on all variables included were retained.

Table 2.

Outcome measures by AoD group.

Measure	N (total)	Whole sampleN = 769M (SD)/range	Diagnosed<3N = 70M (SD)/range	Diagnosed3–5N = 85M (SD)/range	Diagnosed6–11N = 96M (SD)/range	Diagnosed12–17N = 103M (SD)/range	Diagnosed 18+N = 413M (SD)/range
Adapted flourishing scale (mean item score)	704	4.93 (1.35)1.00 to 7.00	5.56 (1.22)1.75 to 7	5.60 (1.33)1.75 to 7	4.90 (1.33)1 to 7	4.76 (1.38)1 to 7	4.74 (1.30)1 to 7
REALS satisfaction with autonomy (theta)	695	-0.10 (0.91)-2.90 to 2.28	0.31 (0.84)-1.43 to 2.28	0.47 (0.92)-1.53 to 2.28	-0.06 (0.88)-2.99 to 2.28	-0.11 (0.98)-2.90 to 2.28	-0.29 (0.83)-2.59 to 2.28
REALS satisfaction with social activity (theta)	705	-0.07 (0.93)-1.90 to 1.86	0.33 (0.88)-1.45 to 1.86	0.34 (0.93)-1.90 to 1.86	-0.17 (0.97)-1.90 to 1.86	0.08 (0.95)-1.90 to 1.86	-0.22 (0.88)-1.90 to 1.86
REALS satisfaction with work/school (theta)	696	-0.04 (0.93)-1.87 to 1.44	0.11 (0.79)-1.40 to 1.44	0.03 (0.97)-1.87 to 1.44	-0.11 (1.03)-1.87 to 1.44	0.01 (0.90)-1.87 to 1.44	-0.01 (0.92)-1.87 to 1.44

Prior to conducting analyses for our primary aim, we explored the associations between sociodemographic (i.e., age, sex at birth, gender diversity, sexual orientation, race/ethnicity) and clinical (i.e., autism traits, intellectual disability) variables and AoD. These preliminary analyses were conducted to characterize participants in the various AoD categories and to screen for potential confounding variables to include in the primary analyses. We analyzed the bivariate associations between AoD and each variable of interest. Because AoD was treated as a categorical variable, we used chi-square tests to examine associations with other categorical variables (e.g., race, sex, sexuality) and one-way analyses of variance (ANOVAs) for continuous variables (i.e., age, autism traits). Due to the large number of analyses (seven) in this aim, we applied a Bonferroni correction to reduce the likelihood of Type 1 errors when interpreting these results (adjusted alpha = .007). Significant chi-square tests were followed up with pairwise comparisons using chi-square or Fisher’s exact tests, depending on expected cell sizes, with the Bonferroni correction applied to control for multiple comparisons. Significant ANOVAs were followed up with post hoc pairwise comparisons with the Tukey adjustment.

Next, in order to determine whether AoD predicted scores on the four life satisfaction measures (i.e., AFS, 3 REALS Satisfaction scales), above and beyond the effects of significant sociodemographic and clinical variables, we conducted four multiple regressions predicting each of the outcome variables of interest with AoD and any sociodemographic/clinical variables that were significantly associated with AoD. In determining which sociodemographic and clinical variables to include in regression analyses, we included any variable that reached a significance level of <.05 (rather than the stricter Bonferroni-corrected alpha) in bivariate analyses. We entered AoD as a factor variable with diagnosis in adulthood (18+ years) as the reference group. In order to fully understand these associations, we ran exploratory post hoc analyses where we rotated the intercept (i.e., selected a new reference group) for the AoD variable to examine additional group comparisons as warranted by the results.

Results

Data descriptives

Table 1 shows our sample’s sociodemographic and clinical characteristics. The sample had a mean age of 35.24 years, and 58.27% of the participants were assigned female sex at birth. Participants were predominantly non-Hispanic White (79.01%). Our proportion of sexual minority (i.e., not straight; 41.2%) and gender-diverse (i.e., not cisgender; 15.6%) people was higher than the general population (Conron & Goldberg, 2020), which is consistent with prior research in adult autistic samples (McQuaid et al., 2022; Weir et al., 2021). As this was a self-report survey, our sample had a lower proportion of individuals with intellectually disability (6.24%) than published rates in the autistic population (Shaw et al., 2025). The mean total SRS-2 T-score of our sample was 70.28 (indicating “moderate impairment”).

Preliminary analyses: relationship between demographic and clinical variables and age of diagnosis

Table 1 displays descriptive statistics for sociodemographic and clinical characteristics within each AoD category. Analyses revealed that AoD was significantly (Bonferroni adjusted alpha < .007) associated with age at time of the study, F(4, 763) = 66.04, p < .001; participant sex, χ²(4, N = 762) = 82.46, p < .001; sexual orientation, χ²(4, N = 749) = 18.75, p < .001; race and ethnicity, χ²(12, N = 767) = 38.42, p < .001; the presence of intellectual disability, χ²(4, N = 749) = 18.75, p < .001; and SRS-2 scores, F(4, 711) = 11.49, p < .001. Only gender minority identity was not significantly associated with AoD after accounting for multiple comparisons, χ²(4, N = 762) = 12.45, p = .014.

Results of post hoc pairwise comparisons are reported in Supplemental Materials. Participants diagnosed in adulthood were significantly older at the time of the study than participants in all other groups, and other groups did not differ from one another. Similarly, the adult-diagnosed group included a significantly higher proportion of participants assigned female sex at birth than any other group. Participants diagnosed in adolescence (12–17 years) also had a significantly higher proportion of participants assigned female at birth than those diagnosed between 3 and 5 years. With regard to sexual orientation, the adult-diagnosed group had significantly more sexual minority participants than the group diagnosed under age 3 and the group diagnosed between 3 and 5 years.

Follow-up analyses also indicated differences in race/ethnicity between participants diagnosed under 3 and those diagnosed between 6 and 11 or diagnosed in adulthood. Specifically, participants diagnosed under 3 were significantly more likely to be Black or Hispanic/Latine (and less likely to be White) than participants in the other AoD groups. The adult-diagnosed group had a significantly smaller proportion of participants with intellectual disability than the groups diagnosed in early childhood (<3 and 3–5). Finally, participants diagnosed in adulthood also had significantly higher self-reported SRS-2 scores than participants in all other age groups, and no other AoD groups differed from one another in SRS-2 scores.

Aim 2: associations between age of diagnosis and life satisfaction in adulthood

Next, we ran multiple-linear regressions to determine the relationship between AoD and each outcome variable, controlling for the significant sociodemographic and clinical characteristics from our Aim 1 analyses. Table 1 and Figure 1 present the descriptive statistics for each outcome measure within each AoD category, and Table 3 reports all regression results.

Figure 1.

Means and 95% confidence intervals of standardized (z) scores for four measures of life satisfaction across age of diagnosis groups.

Table 3.

Results of regression analyses predicting adult life satisfaction measures.

	Adapted flourishing		REALS autonomy		REALS social		REALS school/employ
Predictor	B	β	B	β	B	β	B	β
AoD (18+ reference group)
Under 3	0.34°	0.25	0.21°	0.24	0.32*	0.34	0.01	0.01
3 to 5	0.41*	0.31	0.44***	0.49	0.36**	0.39	-0.05	-0.05
6 to 11	-0.13	-0.09	0.02	0.02	-0.10	-0.10	-0.12	-0.13
12 to 17	-0.14	-0.10	0.06	0.06	0.18	0.20	0.05	0.05
Sex: male	-0.02	-0.01	-0.02	-0.02	0.004	0.005	-0.01	-0.01
Gender diverse	-0.34*	-0.08	-0.32***	0.15	-0.06	-0.11	-0.15	-0.16
Age	-0.0007*	-0.44	-0.0003	-0.05	-0.0002	-0.04	-0.00	-0.01
SRS-2 score	-0.06***	0.07	-0.04***	-0.43	-0.03***	-0.37	-0.03***	-0.32
Intellectual disability	0.10	-0.25	0.14	-0.35	-0.10	-0.07	-0.14	-0.15
Sexual orientation	0.06	0.04	-0.13	-0.14	0.07	0.07	-0.04	-0.04
Race/ethnicity (White, non-Hispanic reference group)
Black	0.31	0.23	-0.09	-0.10	-0.02	-0.02	-0.02	-0.02
Hispanic	0.48**	0.36	0.01	0.01	0.19	0.20	-0.05	-0.05
Other race	0.36*	0.26	0.02	0.02	0.15	0.16	-0.07	-0.08
Intercept	9.23***	—	2.79***	—	2.29***	—	2.14***	—
F-statistic	18.63, p < .01		22.84, p < .01		12.06, p < .01		6.68, p < .01
R ²	0.27		0.30		0.18		0.12

AoD = Age of autism diagnosis; SRS = Social Responsiveness Scale.

p < .10. *p < .05. **p < .01. ***p < .001.

For flourishing (AFS), we found a significant overall model, which accounted for approximately 27% of the variance in flourishing scores, F(13, 662) = 18.63, p < .001. Being in the 3–5 AoD group was associated with higher flourishing than being in the 18+ years AoD reference group (p < .05). The <3 AoD group also had higher flourishing than the 18+ AoD group, although this pattern did not reach significance (p = .059). Exploratory post hoc analysis with the 3–5 AoD group as the reference group revealed that the 3–5 AoD group had higher flourishing than all other AoD groups except the <3 AoD group (ps < .05). In addition to AoD, higher SRS-2 total scores, older age at the time of the study, and gender minority identity were associated with lower flourishing scores. Overall, non-White participants had higher flourishing scores than White participants. Specifically, Hispanic participants and participants identifying with our “Another race” category had significantly higher flourishing than White participants.

For autonomy satisfaction (REALS Satisfaction with Autonomy), we found a significant overall model, which accounted for approximately 31% of the variance in autonomy satisfaction scores, F(13, 650) = 22.84, p < .001. Being in the 3–5 AoD group was associated with more satisfaction in autonomy than being in the 18+ AoD group (p < .001). The <3 AoD group also had higher autonomy satisfaction than the 18+ AoD group, although this pattern did not reach significance (p = .077). No other AoD category differed from the 18+ AoD group in autonomy satisfaction. Post hoc analysis with the 3–5 AoD group as the reference group revealed that the 3–5 AoD group had significantly higher autonomy satisfaction scores than all other AoD groups except the <3 AoD group. Like previous findings, higher SRS-2 scores and gender minority identity were associated with lower scores for autonomy satisfaction.

For social satisfaction (REALS Satisfaction with Social Activity), we found a significant overall model, which accounted for approximately 19% of the variance in social satisfaction scores, F(13, 661) = 12.06, p < .001. Being in the <3 AoD group (p < .05) or the 3–5 AoD (p < 0.01) was associated with more social satisfaction than being in the 18+ AoD reference group. No other AoD category differed from the 18+ group in social satisfaction. Post hoc analysis with the 3–5 AoD group as the reference group revealed that the 3–5 AoD group had significantly higher social satisfaction scores than the 6–11 and 18+ AoD groups but did not differ significantly from the <3 and 12–17 AoD groups. A higher SRS-2 score was associated with lower social satisfaction.

Finally, for school/work satisfaction (REALS Satisfaction with school/work), we found that the overall model was significant and accounted for approximately 12% of the variance in school/employment satisfaction scores, F(13, 651) = 6.68, p < .001. Only a higher SRS-2 score was associated with less school/work satisfaction. No other variables, including AoD, were significant.

Discussion

This study examined how the AoD relates to life satisfaction in adulthood, leveraging a large community-based sample with substantial variability in diagnostic timing. We found that earlier diagnosis—particularly between ages 3 and 5—was consistently associated with more positive outcomes in adulthood compared to later AoD. These associations remained significant even after accounting for key demographic and clinical variables linked to AoD, including autism traits, intellectual disability status, sex, race/ethnicity, sexual orientation, and current age. These findings suggest that the timing of diagnosis is meaningfully related to adult outcomes, independent of these other factors. Implications of these associations are discussed in greater detail below.

Association between age of diagnosis and adult life satisfaction

We found that AoD was meaningfully associated with multiple measures of life satisfaction in adulthood, even after controlling for relevant sociodemographic and clinical factors. In particular, individuals diagnosed between ages 3 and 5 consistently reported more satisfaction than those diagnosed in adulthood (18+ years), with significant differences observed for flourishing, autonomy satisfaction, and social satisfaction. Similarly, individuals diagnosed before age 3 reported higher flourishing, autonomy satisfaction, and social satisfaction than those diagnosed in adulthood (although some of these comparisons did not reach conventional significance thresholds) and did not differ from individuals diagnosed between 3 and 5 on any outcome measure. Individuals diagnosed in middle childhood (6–11) and adolescence (12–17), on the contrary, had significantly worse outcomes on several measures compared to the 3–5 AoD group and did not differ significantly from those diagnosed in adulthood on any measure (see Figure 1).

Our findings both corroborate and extend previous research on AoD and adult outcomes. The significant relationship between early diagnosis and better life satisfaction aligns with previous findings on quality of life (Atherton et al., 2022; Kamio et al., 2013; Oredipe et al., 2022) and extends it to several new and more specific outcome measures, including flourishing and satisfaction with social relationships and autonomy. Our study also adds nuance to this literature by demonstrating that the relationship between AoD and adult outcomes may not be strictly linear. Specifically, we found that diagnosis during early childhood (3–5 years) was consistently associated with the best outcomes, while diagnosis during middle childhood or adolescence was not associated with improved outcomes compared to diagnosis in adulthood. This pattern may help explain why some previous studies did not find significant associations between AoD and quality of life (Leung et al., 2024; Mason et al., 2018). These studies had participants with higher mean ages of participation and later mean ages of diagnosis, with relatively few participants diagnosed in early childhood. Of note, the difference in findings between these prior studies and ours could also be explained by our specific focus on life satisfaction rather than quality of life, though these are highly related constructs.

Our findings suggest that there may indeed be a “tipping point” after which differences in AoD no longer incrementally improve positive life outcomes in adulthood. The difference between being diagnosed in early childhood rather than adolescence appears more significant than the difference between being diagnosed in adolescence rather than adulthood. This may suggest a “critical period” for diagnosis after which interventions and supports are perhaps not as impactful for adult outcomes. This may be because interventions and supports are more impactful in early childhood during periods of neuroplasticity (Herzberg et al., 2025), because there are not as many helpful interventions and supports available to families after the early childhood period (Anixt et al., 2024), and/or because receiving a diagnosis later in life (and thus not knowing about your diagnosis in early childhood) may come with its own inherent social and emotional stressors (Jadav & Bal, 2022). For example, entering school age and/or adolescence without an understanding of the reasons behind one’s challenges might have a lasting emotional impact. Moreover, adolescence is characterized as a particularly stressful and demanding developmental period, especially with regard to peer relationships and identity formation. Thus, for some individuals, receiving a diagnosis during this time may be an added stressor within an already challenging developmental period.

Regardless of the reason, the consistent relationship between early childhood diagnosis and better adult life satisfaction provides support for the importance of timely diagnosis. Early diagnosis facilitates access to early intervention services during a critical developmental period and the benefits of these interventions may persist into adulthood, leading to better adult outcomes. In addition, early diagnosis may help foster a positive autistic identity and self-understanding. Qualitative research suggests that many late-diagnosed adults report having felt “different” or “alien” throughout childhood without understanding why (Kelly et al., 2024). Early diagnosis may help individuals and their families develop adaptive coping strategies and reduce the psychological burden of unexplained differences.

It is important to note another potential explanation for this pattern of findings. Rather than earlier diagnosis causing better outcomes later, it may be that being diagnosed after early childhood is reflective of something (possibly not captured in the present study) that is also associated with poorer positive life satisfaction. For example, co-occurring conditions like attention deficit hyperactivity disorder (ADHD) and emotional/behavioral challenges might make differential diagnosis in early childhood more difficult, delaying diagnosis of autism, and would also be associated with poorer adult outcomes (Lin & Huang, 2019). Childhood socioeconomic factors, like parental education or income, might also be predictive of both a later diagnosis and poorer long-term positive life outcomes. Ultimately, it is important to consider that the present study cannot determine causality or directionality of associations, and alternative explanations are possible.

Notably, we did not find significant associations between AoD and school/work satisfaction, suggesting that certain life domains are less influenced by diagnostic timing than others. Instead, school/work satisfaction was predicted only by level of autism traits. In fact, the level of autism traits was consistently the strongest predictor of adult life satisfaction across all measures. This aligns with previous research on correlates of quality of life in autistic adults (Lin & Huang, 2019; Mason et al., 2018). While the present study was aimed primarily at understanding age of diagnosis as a predictor of later adult outcomes, the consistency of this association across domains underscores an important direction for future research. In particular, prior studies (including this one) have used broad measures of autism traits that encompass a number of autism-related characteristics (e.g., social difficulties, communication, social anxiety, social understanding, cognitive style) and thus cannot disentangle which specific characteristics may be most strongly related to outcomes. In addition, it will be important for future studies to examine how external factors, such as societal stigma, lack of appropriate accommodations, and experiences of discrimination, might mediate the relationship between autism traits and poorer life satisfaction.

Beyond the influence of autism traits, we found that being gender diverse (i.e., not identifying as cisgender) was significantly associated with lower scores on adapted flourishing and satisfaction with autonomy. This finding is important given the higher prevalence of gender diversity reported within the autistic population compared to the general population (McQuaid et al., 2022; Weir et al., 2021). The association between gender diversity and reduced well-being is often explained by the Minority Stress Model (Meyer, 2003), which posits that the elevated stress experienced by minority groups—stemming from stigma, prejudice, and discrimination—negatively impacts mental health and life outcomes. Autistic and gender-diverse individuals are likely to be at particularly high risk for this type of stigma, prejudice, and discrimination, and it will be important for future research to focus on the intersection of autism, gender identity, and positive life outcomes to identify potential areas for prevention, intervention, and support.

Associations between age of diagnosis and demographic and clinical features

While not a primary aim of this study, we found that several demographic and clinical variables were significantly associated with AoD in this sample. Results suggest that individuals who receive their diagnoses in adulthood differ in a number of ways from participants who received their diagnosis earlier. Consistent with prior work, participants diagnosed in adulthood were less likely to have an intellectual disability than those diagnosed in early childhood (Loubersac et al., 2023). Adult-diagnosed participants were also older at the time of the study and more likely to be female sex assigned at birth than all other age groups and were more likely to be a sexual minority than participants diagnosed in early childhood (<3 or 3–5). While previous reviews of the association between sex and age of diagnosis have been inconclusive (Loubersac et al., 2023), these have focused only on childhood diagnoses and largely excluded individuals diagnosed in adulthood. Our finding that participants assigned female sex at birth were more likely to be diagnosed in adulthood aligns with other studies of self-reporting autistic adults (Huang et al., 2021; Leung et al., 2024; Milner et al., 2024). We found that the adult-diagnosed group, in particular, had a much higher proportion of participants assigned female sex at birth, with the sex ratio nearly flipped from early childhood (~30:70 female to male) to adulthood (~70:30 female to male). Autistic people assigned female at birth may be under-recognized or misidentified earlier in life, possibly reflecting gender-based differences in symptom presentation, social camouflaging, or diagnostic bias (Lai et al., 2015; Werling & Geschwind, 2013).

We also found that the adult-diagnosed group had higher SRS-2 scores (a self-report measure of autistic traits) than participants in all other AoD groups. These results are consistent with other recent research on self-reporting autistic adults that has found a positive correlation between self-reported autistic traits and age of diagnosis (Atherton et al., 2022; Huang et al., 2020; Leung et al., 2024; Milner et al., 2024). Although previous research on children has found the opposite association between autistic traits and AoD (Loubersac et al., 2023), several possible explanations may account for this discrepancy. First, although the SRS-2 is a measure of autistic traits, it captures broader social differences and behaviors related to mental health challenges. Thus, it is possible that adult-diagnosed participants may have higher SRS-2 scores because of co-occurring mental health challenges, which are known to occur at higher rates in autistic people diagnosed in adulthood versus childhood (Jadav & Bal, 2022). Furthermore, it is possible that those diagnosed in adulthood are more aware of their autistic traits due to recently going through the diagnostic process (Huang et al., 2020). In addition, our adult-diagnosed group has a strong representation of women, and there is evidence to suggest that autistic women may score higher than autistic men on some self-report autism scales (Atherton et al., 2022). Finally, individuals diagnosed earlier may have also had more access to interventions and supports that led to reduced self-reported autism traits in adulthood.

Finally, participants diagnosed in very early childhood (<3) in this study were more likely to be Black or Hispanic/Latine and less likely to be White than most other age groups. These findings add to a mixed literature on sociodemographic and clinical features associated with AoD (Loubersac et al., 2023), with some other studies finding a similar association between racial/ethnic minority status and an earlier age of diagnosis (Darcy-Mahoney et al., 2016), but others finding the opposite (Daniels & Mandell, 2014; Mandell et al., 2002). Overall, we recommend interpreting this finding with caution, as our sample only had a small proportion of Black and Hispanic/Latine participants.

The main purpose of examining the associations between these demographic and clinical variables and AoD in this study was to appropriately control for variables that may have been associated with both AoD and quality of life in the sample. It is important to note that this study used a self-selected online sample of autistic adults who could read and complete a series of online questionnaires and only included data collected in adulthood. As a result, the data and the sample are not ideally suited to understanding the true causal nature of these associations. Nonetheless, most prior research on AoD predictors has excluded individuals diagnosed in adolescence or adulthood—a significant limitation. Our findings help fill this gap and highlight the need for further research on factors associated with adult diagnosis.

Limitations and future directions

The study has several limitations to consider when interpreting results. First, as with all non-experimental studies, we cannot establish directionality or causality. There is no clear way to establish causality in this area, but a longitudinal study following individuals from childhood to adulthood would provide stronger evidence for causal relationships between AoD and positive life outcomes in adulthood. That said, prospective studies of this sort would typically exclude individuals who are not diagnosed until adulthood. Leveraging large longitudinal datasets that incidentally include autistic individuals may help to circumvent these challenges.

Second, our measure of AoD was categorical. While these categories were designed in the original survey to be easy for adults to report retrospectively and reflect broadly meaningful developmental periods—ranging from very early diagnosis (under 3 years) to adulthood (18+ years)—they were not selected specifically for the present research questions. Using categorical AoD allowed us to examine broad group differences, but it may obscure subtleties in the relationships between AoD and adult outcomes. This is particularly true for the middle childhood categories; for example, there can be substantial developmental differences between 6-year-olds and 12-year-olds that are not captured by a single category. Measuring AoD continuously, or using more fine-grained developmental intervals, may provide additional insight in future research.

Related to measurement, we included the AFS (Nicolaidis et al., 2020, 2025), as this measure was developed using community-based participatory research methods by and for autistic adults to assess a concept important to autistic people. However, it is important to note that this measure is still in development, and there may be changes to items or scoring in the final measure, which could limit the generalizability of our AFS findings.

In addition, although our sample size was larger than any other study on this topic, it is important to highlight limitations to its generalizability. Only 6.24% of our sample had an intellectual disability, which is strikingly small compared to the general autistic population (Shaw et al., 2025). We also had limited racial/ethnic diversity. Our sample was 79.01% non-Hispanic White, and samples for all minority race/ethnicity categories were fairly small. In addition, because of small sample sizes for several racial and ethnic groups, we combined them into a single “Another Race” category, which likely obscures important cultural and experiential differences among these groups. Future studies should focus on recruiting more people of color, as a more diverse sample would allow for more generalizability.

Finally, the study is entirely based on self-report data, which has several limitations. First, associations between variables may be biased by shared method variance. In addition, some potentially important variables are difficult to capture from self-reporting adults. For example, family socioeconomic status in childhood (including variables like parent education and family income) could be seen as a predictor of both AoD (i.e., access to care) and adult outcomes (i.e., having resources throughout childhood and into adulthood), but it is difficult to capture in this context. Similarly, we were not able to capture information about the interventions, supports, or co-occurring diagnoses that people received throughout their lives, which would be related to both AoD and adult outcomes.

Conclusion

This study provides evidence that AoD is significantly associated with life satisfaction in adulthood, with diagnosis in early childhood (ages 3–5) consistently associated with the best outcomes across multiple measures. These associations remained significant even after controlling for level of autism traits, intellectual disability status, sex, age, and other demographic variables, suggesting that the timing of diagnosis has an independent association with adult positive life outcomes. The findings underscore the importance of early screening and diagnosis and highlight the need for diagnostic practices that are sensitive to diverse autism presentations. While diagnosis at any age may be beneficial, our results suggest that particular attention should be paid to identifying and supporting children in the critical early childhood period and developing better supports for autistic people diagnosed later in childhood, adolescence, and adulthood.

Supplemental Material

sj-docx-1-aut-10.1177_13623613261416672 – Supplemental material for The relationship between age of autism diagnosis and life satisfaction in adulthood

Supplemental material, sj-docx-1-aut-10.1177_13623613261416672 for The relationship between age of autism diagnosis and life satisfaction in adulthood by Stacy Cremer, Ligia Antezana, Caitlin M Conner, Shaun M Eack, Carla A Mazefsky and Jessie B Northrup in Autism

Footnotes

Acknowledgements

This research was completed as part of Stacy Cremer’s undergraduate honors thesis. The authors would like to thank honors thesis committee member Dr. Emily K. Lindsay for her insightful comments and suggestions. The authors thank the REALS participants that made this work possible. The authors also thank the REAACT Program investigator team and research staff.

ORCID iDs

Ligia Antezana

Caitlin M Conner

Carla A Mazefsky

Jessie B Northrup

Ethical approval and informed consent statements

All participants provided their consent to participate in accordance with University of Pittsburgh ethical standards and the 1964 Helsinki declaration and its later amendments.

Author contributions

Stacy Cremer: Conceptualization; Formal analysis; Writing—original draft; Writing—review & editing.

Ligia Antezana: Conceptualization; Methodology; Supervision; Writing—review & editing.

Caitlin M Conner: Investigation; Methodology; Project administration; Supervision; Writing—review & editing.

Shaun M Eack: Funding acquisition; Investigation; Methodology; Writing—review & editing.

Carla A Mazefsky: Funding acquisition; Investigation; Methodology; Writing—review & editing.

Jessie B Northrup: Conceptualization; Methodology; Supervision; Writing—original draft; Writing—review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; R01HD100392, PI: C.M.) and Autism Speaks (11923). During preparation of this manuscript, Dr. L.A. was supported by the NIMH T32MH018951 grant (PI: Goldstein), and Dr. J.B.N. was supported by NIMH K23MH127420.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

Approved researchers can obtain the SPARK population dataset described in this study by applying at . The complete dataset will also be made publicly available through the NIMH archive.

Supplemental material

Supplemental material for this article is available online.

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