Co-occurring ADHD symptoms in autistic adults are associated with less independence in daily living activities and lower subjective quality of life

Abstract

Outcomes for autistic adults are generally poor across multiple foundational metrics, including activities of daily living and quality of life. Co-occurring psychiatric conditions contribute to these poor outcomes. Attention-deficit/hyperactivity disorder is one of the most common co-occurring conditions among autistic individuals; however, we know little about the association of attention-deficit/hyperactivity disorder symptoms with autistic adult outcomes. A total of 724 autistic adults (18–83 years; 58% female) recruited via Simons Foundation Powering Autism Research (SPARK) Research Match completed questionnaires on demographics, co-occurring attention-deficit/hyperactivity disorder symptoms, activities of daily living, and subjective quality of life. After controlling for age, birth-sex, socioeconomic status, and autistic traits, attention-deficit/hyperactivity disorder symptoms explained an additional 2%−10% of variance across activities of daily living and all domains of subjective quality of life. This is the first study to demonstrate that autistic adults who rated themselves as having more attention-deficit/hyperactivity disorder symptoms also rated themselves as less independent in activities of daily living and experiencing a lower subjective quality of life. These findings highlight that additional research and better supports for co-occurring attention-deficit/hyperactivity disorder symptoms may be critical to enhancing independence and quality of life for autistic adults.

Lay abstract

Outcomes for autistic adults are generally poor, including activities of daily living and self-ratings of quality of life. Co-occurring psychiatric conditions contribute to these poor outcomes. Attention-deficit/hyperactivity disorder is one of the most common co-occurring conditions in autistic individuals. However, we know little about the association between attention-deficit/hyperactivity disorder symptoms and outcomes in autistic adults. A total of 724 autistic adults (18–83 years; 58% female) recruited from the Simons Foundation Powering Autism Research participant registry completed questionnaires on demographics, co-occurring psychiatric conditions, activities of daily living, and subjective quality of life. Autistic adults who rated themselves as having more attention-deficit/hyperactivity disorder symptoms also rated themselves as having less independence in activities of daily living and a lower quality of life. This is the first study to show these relationships in autistic adults. These findings highlight that additional research and better supports for co-occurring attention-deficit/hyperactivity disorder symptoms may be critical to improving independence and quality of life for autistic adults.

Keywords

adult attention-deficit/hyperactivity disorder autism daily living skills quality of life

Introduction

Adult outcomes in autism spectrum disorder (hereafter “autism”) are generally poor across many foundational metrics, such as objective and subjective quality of life (e.g. health, social relationships, independent living, employment/vocation, adequate supports) (Graham Holmes et al., 2020; Roux et al., 2015). Co-occurring psychiatric symptoms, including those associated with depression and anxiety, are correlated with decreased subjective quality of life among autistic adults (Lawson et al., 2020). Yet, little is known about the relationship between attention-deficit/hyperactivity disorder (ADHD) symptoms and adult outcomes in autistic adults. This dearth of knowledege about the impact of ADHD in adulthood is surprising, because ADHD is one of the most frequently co-occurring psychiatric disorders for autistic youth (Simonoff et al., 2008) and adults. The self-reported rate of clinically significant ADHD symptoms is 37% in autistic adults (Johnston et al., 2013), which is similar to the rate reported for autistic youth. Moreover, this rate of clinically significant ADHD symptoms among autistic adults is greatly elevated relative to the rate (2.5%) observed in the general population (Simon et al., 2009).

The clinical impact of elevated ADHD symptoms has been documented in autistic children via studies linking greater ADHD symptoms to poorer adaptive functioning (Sikora et al., 2012) and lower informant-rated and self-rated quality of life (Graham Holmes et al., 2020). For example, research focused on a large sample (N > 2000) of children aged 2–17 enrolled in the Autism Treatment Network found that autistic children with co-occurring ADHD completed fewer activities of daily living independently and were rated as experiencing lower overall health-related quality of life, school functioning, physical functioning, emotional functioning, and social functioning than autistic children without co-occurring ADHD (Sikora et al., 2012). Whether associations between ADHD symptoms and important markers of outcomes persist into adulthood is unclear, as there is no research on the association of ADHD symptoms with adaptive functioning and quality of life in autistic adults.

The present study fills this gap in the literature by being the first investigation of the relationship between self-reported ADHD symptoms and two key adult outcomes—activities of daily living and subjective quality of life—among autistic adults. Based on the pediatric literature, we hypothesized that increased ADHD symptoms would be associated with lower activities of daily living and lower subjective quality of life ratings across multiple domains of functioning. We also hypothesized that the association between ADHD symptoms and these adult outcomes would be maintained after controlling for individual characteristics (age, sex assigned at birth, autistic traits) and socioeconomic status (educational attainment). We examined these hypotheses by evaluating continuous self-report ratings of ADHD symptoms and their associations with activities of daily living and subjective quality of life. This approach was taken to examine whether the range of ADHD symptoms from mild (and insufficient for a diagnosis) to clinically meaningful ADHD symptoms have an impact on these markers of outcome. The long-term goal of this research is to identify malleable factors that are associated with important adult outcomes, which could serve as treatment targets that may enhance independent living and quality of life for autistic adults, consistent with research priorities identified by self-advocates (Autistic Self Advocacy Network, 2020).

Method

Participants

Simons Foundation Powering Autism Research (SPARK; Feliciano et al., 2018) Research Match was utilized to recruit autistic participants for a larger study of adult outcomes that did not explicitly target those with co-occurring ADHD. Thus, study ads did not include ADHD as a research focus. A total of 724 (58% assigned female at birth) autistic adults ranging in age from 18 to 83 (M = 40.39) years were included in analyses. The relatively even birth-sex ratio reflects that the study targeted an approximate 50/50 recruitment ratio of those assigned female versus male at birth. The recruited autistic adults were designated as “independent” by SPARK meaning that they can consent for themselves, and none reported a co-occurring intellectual disability on a health history questionnaire. Inclusion in the SPARK participant registry requires that participants have an autism spectrum disorder diagnosis given by a medical/clinical professional. Providing further validation for these clinical diagnoses are the following: (1) 98.8% of a large sample of SPARK participants had a confirmed autism spectrum disorder diagnosis based on examination of electronic medical records (Fombonne et al., 2022) and (2) 95% of the current sample met screening criteria (scores > 65) on the Autism spectrum Quotient-Short Form (AQ-28; Hoekstra et al., 2011). For detailed demographic characteristics of the sample, see Table 1. This project was approved by the institutional review board at the George Washington University.

Table 1.

Participant characteristics and mean self-report ratings.

Constructs	Summary statistics
Age, M (SD)	40.39 years (13.93)
Range	18–83 years
Birth-sex, female:male (%)	422 (58%):302 (42%)
Race and ethnicity (%)
Race
Asian	10 (1%)
Black/African-American	15 (2%)
More than one race	69 (10%)
Native American/Alaska Native	5 (<1%)
White	607 (84%)
Other	16 (2%)
Missing	2 (<1%)
Ethnicity
Latinx	61 (8%)
Non-Latinx	651 (90%)
Unknown	11 (2%)
Missing	1 (<1%)
Educational attainment (%)
Did not complete a bachelor’s degree	383 (53%)
Completed a bachelor’s degree	340 (47%)
Educational attainment not reported	1 (<1%)
Age of autism diagnosis, M (SD)	28.01 years (17.23)
AQ-28, M (SD)	84.36 (11.46)
Met AQ-28 Screening Criteria (yes (%):no (%))	688 (95%):35 (5%)
Range	47–112
Taking ADHD Medication yes:no:missing (%)	103 (14%):514 (71%):107 (15%)
ASRS
Total raw score (Parts A and B), M (SD)	37.17 (12.69)
Range	0–72
Met Part A Screening Criteria (yes (%):no (%))	332 (46%):392 (54%)
Activities of daily living and quality of life measures
W-ADL
Total raw score, M (SD)	30.69 (4.40)
Range	7–34
WHOQOL-BREF-Physical Health
Mean item score (SD)	3.41 (0.76)
Range	1.86–5.00
WHOQOL-BREF-Psychological Health
Mean item score (SD)	3.06 (0.77)
Range	1.50–5.00
WHOQOL-BREF-Social Relationships
Mean item score (SD)	3.08 (0.97)
Range	1.00–5.00
WHOQOL-BREF-Environmental Health
Mean item score (SD)	3.56 (0.71)
Range	2.00–5.00
ASQOL
Mean item score (SD)	3.18 (0.78)
Range	1.00–5.00

AQ-28: Autism spectrum Quotient–Short Form; ADHD: attention-deficit/hyperactivity disorder; ASRS: ADHD Self-Report Scale; W-ADL: Waisman Activities of Daily Living; WHOQOL-BREF: World Health Organization Quality-of-Life-BREF; ASQOL: Autism Spectrum Quality of Life; SD: standard deviation.

Measures

Predictor

Adult ADHD Self-Report Scale

The Adult ADHD Self-Report Scale (ASRS) is a well-validated, self-report measure designed to screen for adult ADHD (Kessler et al., 2005). Participants are asked to report on the previous 6 months, responding on a 5-point Likert-type scale (“Never” to “Very Often”) for each item. The scale includes 18 items, with higher scores associated with greater ADHD symptoms. Here, we assigned a number value to each category (e.g. “Never” = 0, “Sometimes” = 1) and used the sum of the scores from the 18 items (range, 0–72) as the independent variable. Higher scores denote more frequent and impairing ADHD symptoms. The ASRS items and anchors are worded similarly to pediatric ADHD symptom scales (e.g. ADHD Rating Scale), and like these types of scales (e.g. Green et al., 2015), the ASRS (e.g. Gray et al., 2014) has been used successfully and meaningfully in linear regressions in prior studies.

Outcomes

Waisman Activities of Daily Living

The self-report version of the 17-item Waisman Activities of Daily Living (W-ADL) was used to assess independence in performing activities of daily living (Bishop-Fitzpatrick et al., 2017). Participants responded on a 3-point Likert-type scale (0 = “Does not do at all”; 1 = “Does with help”; 2 = “Independent, or does on own”). Items of the W-ADL are summed to generate a total score ranging from 0 to 34, with higher scores representing greater independence in activities of daily living. Here, we used the total score as a dependent variable.

World Health Organization Quality-of-Life-BREF module

The World Health Organization Quality-of-Life-BREF (WHOQOL-BREF) is an abbreviated version of the WHOQOL-100; it has 26 items across 4 domains—Physical Health, Psychological Health, Social Relationships, and Environmental Health—and 2 questions about overall quality of life (The WHOQOL Group, 1998). Higher scores indicate greater quality of life. Here, we used the mean score from each domain (range, 1–5) as a dependent variable. Higher scores indicate higher subjective quality of life.

Autism Spectrum Quality of Life

The Autism Spectrum Quality of Life (ASQoL) consists of nine items, answered on a 5-point Likert-type scale (1 = “Not at All/Never,” 5 = “Totally/Always”) (McConachie et al., 2018). A total ASQoL score is calculated by averaging the responses to the initial eight items of the survey. A final ninth item, which asks about “autistic identity,” is not included in the calculation of the total ASQoL score. Higher ASQoL total scores indicate better subjective autism spectrum quality of life. Here, we used the total mean score (range, 1–5) from the ASQoL as a dependent variable.

Covariates

Autism Spectrum Quotient-28 item

The 28-item self-report version of the Autism Spectrum Quotient (AQ) was used to measure autistic features on a 4-point Likert-type scale (1 = “definitely agree” to 4 = “definitely disagree”) (Hoekstra et al., 2011). The mean AQ-28 item score, with higher scores indicative of greater autistic features, was used as a covariate here.

Educational attainment

Participants reported on educational attainment based on nine categories ranging from “did not attend high school” through “graduate/professional degree.” Participants could also indicate that they preferred not to disclose this information. As seen in Table 1, ~47% of the sample completed a bachelor’s degree or more; therefore, we binarized this variable (i.e. completed vs did not complete a bachelor’s degree). This variable served as a proxy for socioeconomic status.

ADHD medications

Participants reported on their medication usage at the time of study completion. Each participant received a code indicating whether they reported current ADHD medication usage. ADHD medications included central nervous system stimulants (e.g. methylphenidate) as well as non-stimulant medications (e.g. atomoxetine).

Data analysis

Multiple linear regressions examined associations between continuous ADHD symptoms and activities of daily living (hypothesis 1), physical health, social relationships, environmental health, and autism spectrum quality of life (hypothesis 2), after controlling for the effects of age, sex assigned at birth, educational attainment, and autistic traits. Of note, ~10% of our sample opted not to report medication usage. Given the large amount of missing data for this variable (N = 97) and the observation that ADHD medication had no significant effects in our models (all ts < |0.9|, all ps > 0.41), we removed this variable which enabled analyses to be completed with the entire study sample. All raw scores were transformed to z-scores prior to analyses. Bonferroni corrections were applied to the regression analyses (adjusted threshold: p < 0.01; 0.05/5 regression analyses) to account for multiple comparisons. We used the standardized beta coefficients for ADHD symptoms as measures of effect size. Given that aging-related declines have the potential to impact associations evaluated here, we re-ran these regression-based analyses excluding participants who were 65 years of age or older at the time of the study (n = 42) to assess the robustness of the reported findings.

Community involvement

No autistic community members were involved in the development or execution of this study.

Results

Self-reported ADHD symptoms contributed significant variance to activities of daily living and quality of life. For hypothesis 1, increasing ADHD symptoms (even after accounting for the effects of all covariates and correcting for multiple comparisons) were significantly associated with less independent activities of daily living (β = −0.21, t = −5.66, p < 0.001, ▲R² = 0.04). For hypothesis 2, greater ADHD symptoms were associated with lower quality of life in the domains of physical health (β = −0.33, t = −9.49, p < 0.001, ▲R² = 0.10), psychological health (β = −0.28, t = −7.63, p < 0.001, ▲R² = 0.07), social relationships (β = −0.16, t = −4.25, ▲R² = 0.02), environmental health (β = −0.32, t = −8.69, p < 0.001, ▲R² = 0.09), and autism spectrum (β = −0.34, t = −10.00, p < 0.001, ▲R² = 0.10; see Table 2). Re-running regression analyses excluding participants who were 65 years of age or older at the time of the study (n = 42) did not alter the pattern of findings, with all ▲R² values reported above remaining identical (see Supplementary Table 1). As a post hoc analysis, we also re-ran all regressions using the traditional ADHD categorical classification (ADHD risk (n = 332) vs not (392)) provided by Part A (the first six items) of the ASRS, and we observed a very similar pattern of results, albeit with weaker effects due to the reduced statistical power and variance in scores afforded by employing a categorical variable (data not shown).

Table 2.

Regressions of activities of daily living and subjective quality-of-life domains on control variables and ADHD symptoms.

	W-ADL					Physical health					Psychological health
	B	SE	95% CI for β	β	t	B	SE	95% CI for β	β	t	B	SE	95% CI for β	β	t
Baseline model:	R² = 0.08, F = 14.78, p < 0.001					R² = 0.13, F = 27.44, p < 0.001					R² = 0.08, F = 14.63, p < 0.001
Age	0.00	0.00	[0.03, 0.18]	0.11	2.76^a	–0.01	0.00	[–0.20, –0.05]	–0.12	–3.33^b	0.00	0.00	[–0.07, 0.08]	0.01	0.16
Sex at birth	0.02	0.02	[–0.04, 0.10]	0.03	0.90	–0.35	0.05	[–0.30, –0.16]	–0.23	–6.54^b	–0.12	0.06	[–0.15, –0.01]	–0.08	–2.07^c
Education^d	0.11	0.02	[0.13, 0.28]	0.21	5.45^b	0.30	0.06	[0.12, 0.27]	0.19	5.28^b	0.14	0.06	[0.02, 0.17]	0.09	2.41^c
AQ	–0.10	0.02	[–0.23, –0.09]	–0.16	–4.33^b	–0.37	0.07	[–0.27, –0.13]	–0.20	–5.53^b	–0.48	0.07	[–0.33, –0.18]	–0.26	–6.93^b
Test model:	ΔR² = 0.04, ΔF = 32.03, Δp < 0.001					ΔR² = 0.10, ΔF = 89.97, Δp < 0.001					ΔR² = 0.07, ΔF = 58.19, Δp < 0.001
Control covariates
ADHD Self-Report Scale	–0.07	0.01	[–0.28, –0.14]	–0.21	–5.66^b	–0.29	0.03	[–0.40, –0.26]	–0.33	–9.49^b	–0.26	0.03	[–0.35, –0.21]	–0.28	–7.63^b
	Social relationships					Environmental health					Autism spectrum QOL
	B	SE	95% CI for β	β	t	B	SE	95% CI for β	β	t	B	SE	95% CI for β	β	t
Baseline model:	R² = 0.05, F = 9.49, p < 0.001					R² = 0.06, F = 12.24, p < 0.001					R² = 0.15, F = 32.23, p < 0.001
Age	–0.01	0.00	[–0.20, –0.04]	–0.12	–3.08^a	–0.00	0.00	[–0.13, 0.02]	–0.06	–1.44	–0.01	0.00	[–0.20, –0.05]	–0.13	–3.43^b
Sex at birth	0.07	0.07	[–0.04, 0.11]	0.03	0.92	–0.12	0.05	[–0.16, –0.01]	–0.08	–2.31^c	–0.19	0.06	[–0.19, –0.05]	–0.12	–3.51^b
Education^d	0.16	0.08	[0.01, 0.16]	0.08	2.08^c	0.28	0.06	[0.12, 0.27]	0.20	5.12^b	0.18	0.06	[0.04, 0.19]	0.11	3.14^a
AQ	–0.42	0.09	[–0.25, –0.10]	–0.18	–4.65^b	–0.29	0.07	[–0.24, –0.09]	–0.16	–4.39^b	–0.63	0.07	[–0.40, –0.26]	–0.33	–9.20^b
Test model:	ΔR² = 0.02, ΔF = 18.04, Δp < 0.001					ΔR² = 0.09, ΔF = 75.58, Δp < 0.001					ΔR² = 0.10, ΔF = 99.92, Δp < 0.001
Control covariates
ADHD Self-Report Scale	–0.18	0.05	[–0.24, –0.09]	–0.16	–4.25^b	–0.27	0.03	[–0.39, –0.24]	–0.32	–8.69^b	–0.29	0.03	[–0.41, –0.27]	–0.34	–10.00^b

ADHD: attention-deficit/hyperactivity disorder; AQ: Autism Spectrum Quotient; QOL: quality of life; W-ADL: Waisman Activities of Daily Living; SE: standard error; CI: confidence interval.

p < 0.01.

p < 0.001.

p < 0.05.

Completed a bachelor’s degree versus did not complete a bachelor’s degree.

Discussion

The current study documents high screen positive rates for ADHD among autistic adults in line with prior studies of primarily autistic children and adolescents (Leyfer et al., 2006; Simonoff et al., 2008). Moreover, this study is the first to document significant links between co-occurring ADHD symptoms and critically important outcomes for autistic adults. Utilizing self-ratings to tap into the lived autistic experience, this investigation revealed greater ADHD symptoms were associated with diminished independence in activities of daily living and lower subjective quality of life among autistic adults. Taken together, the current study fills an important gap in the literature focused on adulthood in autism, documenting the potential impact of ADHD symptoms, thus raising several issues that need to be addressed during this understudied period of development.

The present study provides an important new lead for understanding activities of daily living for autistic adults by showing that ADHD symptoms may play an important role. Our findings converge with a robust literature demonstrating the same association in preschoolers through age 21 (Sikora et al., 2012). The small-to-medium effect sizes observed in the present study suggest that ADHD symptoms have a clinically significant link to activities of daily living and the effect may be larger with a measure of activities of daily living that captures a wider range of (particularly more advanced) skills than what was used in the present study. Our findings highlight co-occurring ADHD as a potential factor that may hinder achievement of independence among autistic adults.

The present study is the first to use self-ratings to associate greater ADHD symptoms with lower subjective quality of life during adulthood in autism. Our findings are important because the literature on subjective quality of life among autistic adults consistently finds lower ratings compared to both adult psychiatric populations and non-autistic adults (Graham Holmes et al., 2020). However, our study highlights an important point that has been described previously: lower ratings of quality of life cannot be solely attributed to autistic traits—other factors can and do play a role (Michael, 2021).

Although the current study is the first of its kind and includes a large sample of autistic adults, limitations should be considered. This study relied on self-report; thus, inclusion of other informant reports could have provided convergent validity, particularly concerning the severity of ADHD symptoms and their association with outcome measures. This study also had an intentional sampling strategy to recruit a near 50/50 split of those assigned female versus male at birth that may bias findings; a future investigation will examine the effect of sex assigned at birth directly. In addition, this study focused exclusively on autistic adults without co-occurring intellectual disability and this resulted in near ceiling effects for our measure of activities of daily living. We believe this limited variability likely led to an underestimate of the association between ADHD symptoms and activities of daily living. Finally, diversity in terms of race, ethnicity, and socioeconomic status in our sample was limited relative to US population-based expectations (Dillon et al., 2021), which SPARK is actively addressing in this cohort.

This study indicates that targeting ADHD symptoms in autistic adults and curbing their severity may have important implications for improving both independent living and quality of life. To that end, it will be critical to address the following issues in future research to further support autistic adults. We must address how access to care for ADHD, and treatment effectiveness for ADHD symptoms during childhood and into adulthood for autistic adults, relates to these important outcomes. We must also determine whether there are critical windows in childhood and adolescence for intervening on ADHD symptoms in the life of an autistic individual to optimize outcomes in adulthood. Alternatively, we may also reverse poorer outcomes with successful treatment in adulthood; see Young et al. (2020) for a recent consensus statement on treatment of ADHD symptoms in autistic people. Furthermore, it will be important to examine other critical risk and protective factors that may influence the trajectory of activities of daily living and quality of life for autistic individuals across their lifespan, including genetic vulnerabilities, trait vulnerabilities (e.g. emotion dysregulation), parenting factors, socioeconomic status, and other social determinants of health.

Supplemental Material

sj-docx-1-aut-10.1177_13623613221112198 – Supplemental material for Co-occurring ADHD symptoms in autistic adults are associated with less independence in daily living activities and lower subjective quality of life

Supplemental material, sj-docx-1-aut-10.1177_13623613221112198 for Co-occurring ADHD symptoms in autistic adults are associated with less independence in daily living activities and lower subjective quality of life by Benjamin E Yerys, Goldie A McQuaid, Nancy Raitano Lee and Gregory L Wallace in Autism

Footnotes

Acknowledgements

We are grateful to all the autistic adults and their families in SPARK, the SPARK clinical sites, and SPARK staff. We appreciate obtaining access to recruit participants through SPARK research match on SFARI Base.

Declaration of conflicting interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by an Autism Speaks Postdoctoral Fellowship (Grant ID 11808) to Goldie A. McQuaid, and by startup funds from The George Washington University to Gregory L. Wallace.

ORCID iDs

Benjamin E Yerys

Nancy Raitano Lee

Gregory L Wallace

Supplemental material

Supplemental material for this article is available online.

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