Physical and Extracurricular Activity in Adolescents With and Without ADHD: Examining Group Differences and the Role of Cognitive Disengagement Syndrome Symptoms

Abstract

Objective:

This study examined extracurricular and physical activity related to ADHD (diagnosis and symptoms) and cognitive disengagement syndrome (CDS) symptoms.

Methods:

Participants were 302 adolescents (ages 12–14) with and without ADHD and primary caregivers. ADHD diagnosis was determined with parent interview. Questionnaires provided information on parent-reported demographic characteristics, ADHD symptoms, and extracurricular activity involvement; and adolescent-reported ADHD and CDS symptoms and indices of physical activity.

Results:

Although ADHD diagnosis and symptom dimensions were correlated with less extracurricular and physical activity involvement, CDS symptoms were most often independently associated with these outcomes. Females and adolescents from lower income homes also often had less involvement in extracurricular and physical activity.

Conclusions:

Findings point to the need for more research in this area, careful assessment of risk factors (i.e., CDS symptoms, economic burden), and interventions that address inactivity in adolescents with ADHD, including those that address inequity related to income and sex.

Physical Activity in Adolescents With ADHD

Regular physical activity in adolescence is a critical health-related behavior associated with better academic performance, cardiovascular health, cognitive functioning, and overall mental health (Biddle & Asare, 2011; Doré et al., 2020). Physical activity may take the form of independent exercise, sports participation, and/or organized clubs and activities, with moderate-to-vigorous activity (i.e., 64%–95% of maximum heart rate) regarded as beneficial for health maintenance (Biddle et al., 2019; Rodriguez-Ayllon et al., 2019; Seiffer et al., 2022).

Despite the many benefits of regular physical activity for health and wellbeing, research suggests that certain groups of adolescents are at higher risk of physical inactivity, including adolescents with attention-deficit/hyperactivity disorder (ADHD; Nigg, 2013; Wang et al., 2022). Much of the research connecting ADHD and physical activity examines physical activity as a possible treatment for ADHD (Cerrillo-Urbina et al., 2015; Cornelius et al., 2017; Seiffer et al., 2022; Sun et al., 2022), and there are few studies examining differences in adolescent-specific samples. Population-based studies of school-aged children and adolescents have found that youth with ADHD are significantly less likely to engage in physical activity and organized sports compared to peers without ADHD (Kim et al., 2011; Mercurio et al., 2021; Tandon et al., 2019). These findings may be driven by the inclusion of adolescents, as hyperactivity tends to decline with age (Willcutt et al., 2012), and research exclusively in younger samples supports higher levels of physical activity in children with ADHD compared to same-age peers measured via accelerometry (Villalba-Heredia et al. 2022). There is also evidence from a longitudinal twin study that higher levels of physical activity is associated with reduced ADHD symptoms in adolescence, even after accounting for genetic and environmental confounding shared between identical twins (Rommel et al., 2015).

In addition to group-based differences, a few studies point to ADHD inattentive (ADHD-IN) symptoms specifically, rather than ADHD hyperactive-impulsive symptoms (ADHD-HI), as being closely linked to physical inactivity. For instance, Khalife et al. (2014) found that childhood ADHD-IN symptoms were prospectively associated with obesity via physical inactivity. Another study found ADHD-IN symptoms, but not ADHD-HI symptoms, to predict less physical activity in adolescence, after controlling for demographic factors (Selinus et al., 2021). Although the proposed mechanism linking ADHD and physical inactivity at the neurobiological level does not differentiate ADHD-IN and ADHD-HI symptoms given the proposed widespread impact on dopamine and norepinephrine release throughout the brain (including proposed differential regions underlying ADHD-IN and ADHD-HI symptoms; Chang et al., 2012; Wigal et al., 2013), the behavioral link between ADHD-IN and physical inactivity has been hypothesized to be related to executive functioning deficits that could be specific to ADHD-IN symptoms (e.g., difficulties with meta-cognitive awareness, difficulties with structure and organization that would be required within team-based sports; Khalife et al., 2014).

Despite the extant literature documenting less physical activity in adolescents with ADHD, a major limitation is that the majority of these studies are drawn from population-based samples where ADHD is defined based solely on caregiver report that their child had been previously diagnosed with ADHD by a clinician (Kim et al., 2011; Tandon et al., 2019; Wang et al., 2022), and the measurement of physical activity includes one-item assessing exercise frequency (Kim et al., 2011; Selinus et al., 2021; Tandon et al., 2019; Wang et al., 2022). In order to augment our understanding of the nature of physical inactivity in adolescents with ADHD, it is important to utilize more comprehensively diagnosed samples and to examine the type (e.g., independent exercise, structured activities like sports participation), frequency (e.g., times each week), intensity (e.g., breathing hard), duration (e.g., 20-min, 60-min), and timing (e.g., after school, on weekends, in free time) of physical activity in adolescents diagnosed with ADHD. For instance, a recent study found that intensity and duration of physical activity may have more impact on ADHD symptom management than frequency of physical activity (Aranas & Leighton, 2022), and a recent review found that the benefit of physical activity for the cognitive impairments related to ADHD depends on frequency, intensity, and duration of the physical activity (Suarez-Manzano et al., 2018). Thus, research that accounts for the multi-dimensional nature of physical activity is needed in order to advance our understanding of the relationship between physical activity and ADHD in adolescence.

ADHD and Engagement in Extracurricular Activities

Another current gap in the literature is whether individuals with ADHD exhibit physical inactivity specifically, or if they are at higher risk for general lack of engagement in various types of activities (e.g., arts, musical theater), including those that may inherently include physical activity (e.g., participation in sports teams). In fact, the executive functioning and social impairments related to ADHD might apply other types activities that involve team work, cooperation, and getting along well with peers (Khalife et al., 2014), rather than specifically to those that involve physical activity. Understanding whether adolescents with ADHD are more or less likely to engage in some activities over others may shed further light on underlying mechanisms, either broad or specific, in the relationship between ADHD and inactivity, as well point toward prevention and intervention strategies (e.g., encouragement of activity types in which adolescents with ADHD may be more likely to experience enjoyment and self-efficacy).

The Role of Cognitive Disengagement Syndrome (CDS)

Elevated cognitive disengagement syndrome (CDS) symptoms co-occur in 25% to 40% of youth with ADHD (Becker, Willcutt, et al., 2022). CDS, until recently referred to as sluggish cognitive tempo, refers to a set of symptoms marked by excessive mind-wandering, mental confusion and fogginess, and slowed behaviors that are related yet empirically distinct from ADHD-IN symptoms (Becker et al., 2016). One of the defining characteristics of CDS includes “motor symptoms involving hypoactivity as manifested in underactivity, periods of passive or sedentary movement, and slow, reduced, or delayed motor movements” (Becker, Wilcutt, et al., 2022, p. 11). Yet, despite clear connections between CDS and physical activity, only one study has examined whether co-occurring CDS symptoms contribute to physical activity in individuals with ADHD, which found less engagement in sports activities in children and adolescents with high levels of CDS both with and without ADHD compared with comparison participants (Barkley, 2013). Clearly, more research is needed to examine this further.

CDS is not only defined in part by hypoactivity, but is also associated with domains that may further link it to less physical activity and less involvement other extracurricular activity types. First, CDS is strongly associated with depressive symptoms, and prospective studies have shown CDS symptoms to predict increases in depressive symptoms over time (Becker, Webb, & Dvorsky, 2021; Fredrick, Langberg, & Becker, 2022). Further, CDS is associated with increased social withdrawal (Fredrick & Becker, 2023), and several studies have linked CDS to increased sleep problems and daytime sleepiness (Fredrick et al., 2022; Rondon et al., 2020; Smith et al., 2019). It has also been suggested that poor energy regulation, defined by variability in activity or both overactivity and underactivity (i.e., core symptom of CDS), might account for the reduced involvement in physical activity in ADHD (Nigg, 2013). Taken together, the current evidence points to a potential role of CDS in understanding the findings related to reduced physical activity—and general inactivity—among adolescents with ADHD.

Current Study

The current study aimed to (a) examine group differences in engagement in extracurricular activities (including those involving physical exercise) and physical activity between adolescents comprehensively assessed and diagnosed with ADHD relative to comparison adolescents without ADHD, and (b) examine the extent to which ADHD symptom dimensions and/or CDS symptoms explain any differences in extracurricular and physical activity between adolescents who do and do not have ADHD. Consistent with prior studies (Aranas & Leighton, 2022; Holton & Nigg, 2020; Khalife et al., 2014; Kim et al., 2011; Mercurio et al., 2021; Nigg, 2013; Rommel et al., 2015; Suarez-Manzano et al., 2018; Tandon et al., 2019; Wang et al., 2022), we expected that adolescents diagnosed with ADHD would be involved in fewer extracurricular activities, and would also engage in physical and other types of activities less often than adolescents without ADHD. Following prior studies linking ADHD-IN symptoms to less physical activity (Khalife et al., 2014; Selinus et al., 2021), and hypotheses that behaviors of hypoactivity (which are key in CDS) might be a risk factor for physical inactivity (Nigg, 2013), we hypothesized that ADHD-IN and CDS symptoms would both be associated with less exercise and activity involvement. Importantly, we addressed limitations to the prior literature by using both parent- and self-report of ADHD symptoms and using multi-dimensional measures of physical activity. We also sought to expand current understanding of the unique association between ADHD and physical activity by examining independent associations for ADHD symptom dimensions and CDS symptoms. Our inclusion of non-physical extra-curricular activities also adds to the literature, as this is a relatively understudied topic that may provide insight into the types of activities adolescents with ADHD and CDS engage in relative to physical activities. It also provides additional examination of whether physical inactivity may be a distinct target for intervention, or whether interventions targeting general inactivity may be warranted, particularly given the broad dopaminergic and norepinephrine effects physical activity interventions are hypothesized to have to improve ADHD symptoms (Chang et al., 2012; Wigal et al., 2013).

Methods

Participants

Participants were 302 adolescents (ages 12–14 years) in eighth grade (Mage = 13 years) who were recruited from local schools across two sites in the Southeastern and Midwestern United States over the course of 2 years starting in 2016/2017. Targeted recruitment was used to enroll an approximately equal number of participants with and without ADHD. Thus, approximately half (n = 162) of the sample was diagnosed with the Fifth Edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) ADHD (n = 120 with Predominantly Inattentive Presentation or ADHD-IN and n = 42 with Combined Presentation, or ADHD-C), with remaining participants (n = 140) comprising a comparison sample without ADHD. The sample was 44.7% female (n = 135) and 4.6% Hispanic or Latiné (n = 14). The racial distribution of the sample is as follows: 0.3% (n = 1) American Indian/Alaskan, 4.6% (n = 14) Asian, 5.3% (n = 16) Black, 7.9% (n = 24) biracial or multiracial, and 81.8% (n = 247) White.

Procedures

Adolescents in eighth grade and their parents were recruited across two consecutive years for a prospective study of adolescents with and without ADHD (see Becker et al., 2019 for additional details). The study was approved by the Virginia Commonwealth University and the Cincinnati Children’s Hospital Medical Center Institutional Review Boards, and written informed consent and assent were obtained. Families meeting screening criteria were invited to receive a comprehensive assessment, during which adolescents and their parents were administered study measures. Inclusion criteria included the following: (a) enrolled in eighth grade; (b) estimated Full Scale IQ ≥80 based on the Wechsler Abbreviated Scale of Intelligence, Second Edition (WASI-II; Wechsler, 2011); and (c) enrolled in regular education classes for the majority of the day. Exclusion criteria were as follows: (a) meeting criteria for autism spectrum disorders, bipolar disorder, a dissociative disorder, or a psychotic disorder; (b) previous diagnosis of an organic sleep disorder according to parent report during the initial phone screen; and (c) not meeting criteria for either the ADHD or comparison groups as described below.

Participants underwent a comprehensive ADHD diagnostic evaluation in accordance with the Fifth Edition of DSM-5 criteria. Adolescents met criteria for ADHD on the basis of the parent version of Children’s Interview for Psychiatric Syndromes (P-ChIPS; Weller, Weller, Rooney, & Fristad, 1999). To be eligible for participation in the ADHD group, adolescents were required to meet all DSM-5 criteria for either the ADHD Combined Presentation or Predominantly Inattentive Presentation on the P-ChIPS. Specifically, adolescents were included in the ADHD group if parents reported ≥6 symptoms of inattention at clinically significant levels; presence of ADHD symptoms prior to age 12 years, presence of ADHD symptoms in two or more settings (e.g., home, school), evidence that symptoms contribute to home, academic, and/or social impairment, and symptoms of ADHD were not better explained by another mental disorder. Adolescents were included in the comparison group if the parent endorsed <4 symptoms of ADHD in both domains (i.e., inattention, hyperactivity/impulsivity) on the P-ChIPS. Additionally, both parent and adolescent report on the P-ChIPS and ChIPS were used to determine other common mental health diagnoses.

Measures

Demographics.

Caregivers reported on adolescent sex, race (coded White and Other in the present study), and annual family income (0–6 ordinal scale), which may be likely to vary by ADHD status or symptoms, CDS, and physical activity (Becker, Willcutt, et al., 2022; Mercurio et al., 2021; Tandon et al., 2019).

ADHD Self-Report Scale (ASRS).

Adolescents’ self- reported DSM-5 ADHD symptoms were assessed with the 18-item ASRS (Kessler et al., 2005). Items assess the frequency of inattentive and hyperactive-impulsive symptoms on a four-point scale (0 = never; 1 = occasionally, 2 = often, 3 = very often). The ASRS has well-documented internal validity and convergent validity with interview-assessed ADHD symptoms (Sonnby et al., 2015) and discriminative validity from CDS symptoms (Becker et al., 2020). In the present study, internal consistencies for inattention and hyperactivity/impulsivity were αs = .86 and. 84, respectively.

Vanderbilt ADHD Diagnostic Rating Scale (VADRS).

The VADRS was used to measure parent ratings of adolescents’ ADHD symptoms (Wolraich, 2003) on a four-point scale (0 = never; 1 = sometimes, 2 = often, 3 = very often). Parent ratings on the VADRS have demonstrated strong internal consistency, factor structure, and concurrent validity with other ADHD assessment instruments (Wolraich, 2003). In the present study, internal consistencies for inattention and hyperactivity/impulsivity were αs = .95 and .90, respectively.

Child Concentration Inventory, Second Edition (CCI-2).

Given emerging research that CDS may be best conceptualized in the internalizing realm of psychopathology representing internal experiences (e.g., mind-wandering, feeling easily tired), adolescents’ self-reported ratings of CDS was used (Becker et al., 2020; Smith et al., 2019). The CCI-2 is a 16-item measure of adolescents’ self-reported ratings of CDS (Sáez et al., 2019) (e.g., My mind feels like it is in a fog”) on a 4-point scale (0 = never, 1 = sometimes, 2 = often, 3 = always). Of note, the two CDS items included on the CCI-2 that failed to show strong convergent validity (i.e., factor loadings) on the CDS factor in a sample of adolescents with and without ADHD were items related to hypoactivity (i.e., “I am slow at doing things,” “I am not very active”;Becker et al., 2020). These two items were not included in the CDS scale used in this study, which bolsters confidence that any associations between CDS symptoms and physical activity are not attributable to item overlap. In addition, one item related to motivation was not used as it failed to show discriminant validity in previous studies (see Becker, 2021). The remaining 13 items included have shown strong convergent validity and discriminative validity from ADHD-IN symptoms (Becker et al., 2020). In the present study, internal consistency was α = .92.

Activities and Time Questionnaire (ATQ).

The ATQ is a 16-item parent-reported scale developed for purposes of the current study. We included seven items from this measure that were relevant to our aim to examine extracurricular activities of adolescents, which assessed whether adolescents were involved in the following activities on school nights, not during school hours: sports teams at school, sports teams in the community (e.g., club sports, private lessons), school arts (e.g., music, theater, art rehearsals and/or lessons), community-based or private arts, clubs or organizations (e.g., Boy/Girl Scouts, Big Brothers/Big Sisters), religious groups (e.g., church youth group), and volunteer or service activities. In order to also capture frequency of activity involvement, parents also rated how often adolescents attended each activity (i.e., every school day, 3–4 school days per week, 1–2 school days per week, once a week, once every 2 weeks, once a month). For analyses (see below), parent-reported no activity involvement was the referent category.

Exercise Questionnaire (EQ).

The EQ is a self-reported measure adapted from items on the Physical Activity Questionnaire, Adolescent version (PAQ-A; Kowalski et al., 1997) and the Youth Risk Behavior Survey (YRBS; Brener et al., 2002). Items examining both frequency, intensity, and duration included: “on how many of the past 7 days did you exercise or participate in physical activity for at least 20 min that made you breathe hard,” and the same item that instead asked on how many of the past days the adolescent exercised or participate in physical activity of at least 60 min. An additional three items examined the frequency of very active physical activity involvement (i.e., sports, dance, or game play) outside of school (rather than during school, an adaptation from the PAQ-A) on a 5-point scale, with the three items differing by when the activity occurred: right after school (1 = none, 2 = one time last week, 3 = two or three times last week, 4 = four times last week, 5 = five times last week), in the evenings after school (same scale), and/or over the last weekend (1 = none, 2 = one time, 3 = two or three times, 4 = four times, 5 = five times). Finally, we also included an item to capture adolescents’ general engagement during their free time in activities that require physical effort, even if not with the explicit intention for exercise (e.g., riding one’s bike). Specifically, adolescents rated which of five options described them best over the previous 7 days: (a) all or most free time spent doing things that involve little physical effort, (b) sometimes (1–2 times) doing physical thing in free time, (c) often (3–4 times) doing physical things in free time, (d) quite often (5–6 times) doing physical things is free time, or (e) very often (7 or more times) doing physical things in free time. Items on the EQ have demonstrated convergent validity with other measures of physical activity and moderate test-retest reliability (Brener et al., 2002; Kowalski et al., 1997).

Analyses

SPSS version 26 was used to conduct all analyses, with the exception of logistic regression models, which were estimated in SAS version 9. First, we estimated bivariate associations between participant demographic characteristics, ADHD status, self-reported ADHD symptoms, self-reported CDS symptoms, parent-reported activity involvement, and self-reported physical activity using bivariate correlations, independent samples t-tests, and chi-square tests. Significant associations among demographic characteristics and our predictors and outcomes of interest were then included as covariates in regression analyses (see below). We also include effect estimates for included covariates, as any significant independent associations may provide important context for any differences in extracurricular and physical activity involvement as a function of ADHD and CDS, particularly given recent calls for research examining social determinants of health.

Second, we examined whether participant demographic characteristics (e.g., sex, race, family income), ADHD status or symptoms, and/or CDS symptoms were uniquely associated with parent-reported activity involvement. We conducted these analyses in two ways: initial models examined the odds of activity involvement (yes/no) using logistic regression, and models using multiple linear regression analyses examined linear relationships to frequency of activity involvement. Estimates were examined separately for ADHD diagnosis, self-reported ADHD symptoms, and parent-reported ADHD symptoms. Multicollinearity statistics were assessed in regression models, yielding no concerns for multicollinearity (Cohen et al., 2014).

Third, we examined whether our predictors were uniquely related to indices (including frequency, intensity, and duration) of self-reported physical activity using multiple linear regression.

Results

We first present descriptive statistics, including associations between demographic characteristics, predictors of interest and outcome variables, separated by parent-reported activity involvement and self-reported physical activity. We next report descriptive and modeling results for parent-reported adolescent involvement in extracurricular activities, including those that involve physical activity. Finally, we report on results focused on the frequency, intensity, and duration of adolescent-reported physical activity.

Descriptive Statistics and Bivariate Associations

Parent-Reported Activity Involvement.

The most commonly reported extracurricular was involvement in community sports (47.68%), followed by school sports (41.68%), a religious group that meets on a week day (35.76%), school arts programming (27.15%), volunteer work (19.87%), clubs (14.57%), and community arts programming (13.91%).

Bivariate associations among demographic characteristics, study predictors, and extracurricular activities and physical activity are reported in Tables 1 to 4. Of the demographic variables, sex and income were most commonly related to other variables, whereas race was not related to any ADHD or CDS indices, nor any extracurricular involvement. Females were less likely to be diagnosed with ADHD and had lower mean parent-reported ADHD symptoms and higher mean parent-reported CDS symptoms compared with males; though there were no differences between males and females regarding parent-reported activity involvement. Individuals from households with higher annual income were less likely to be diagnosed with ADHD or exhibit ADHD and CDS symptoms. Higher income was also related to more time spent in school sports and community sports involvement.

Table 1.

Descriptive Statistics and Bivariate Correlations Between Study Variables and Parent-Reported Activity Involvement.

Variable	1	2	3	4	5	6	7	8	9	10	11	12	13
1. Income	—	−.224**	−.172**	−.196**	−.271**	−.232**	.207**	.278**	−.011	.103	.067	.020	.048
2. SR ADHD-IN		—	.722**	.681**	.540**	.356**	−.258**	−.201**	.028	.053	.067	.030	−.112
3. SR ADHD-HI			—	.654**	.410**	.429**	−.223**	−.179**	.049	.023	.088	.051	−.100
4. SR CDS				—	.333**	.190**	−.211**	−.188**	.082	.005	.073	.047	−.135*
5. PR ADHD-IN					—	.610**	−.241**	−.159**	−.033	−.046	.051	−.068	−.148**
6. PR ADHD-HI						—	−.204**	−.087	−.070	−.066	.013	−.023	−.148*
7. School sports (freq)							—	.105	−.166**	−.106	−.081	.032	.073
8. Community sports (freq.)								—	−.118*	−.076	.015	.036	.148*
9. School arts (freq)									—	.158**	−.050	.065	−.006
10. Community arts (freq)										—	.083	−.020	.057
11. Clubs (freq)											—	.015	.191**
12. Religious group (freq)												—	.181**
13. Volunteer work (freq)													—
		2	3	4	5	6	7	8	9	10	11	12	13
M	4.24	1.044	0.892	0.878	1.130	0.538	2.18	1.90	1.20	0.48	0.36	1.01	0.321
SD	1.82	0.564	0.548	0.585	0.845	0.580	2.633	2.119	2.108	1.241	0.974	1.460	0.773

Note. Income is an ordinal variable ranging from 0 to 6. SR = self-report; ADHD = attention-deficit/hyperactivity disorder; ADHD-IN = ADHD inattentive symptoms; ADHD-HI = ADHD hyperactive/impulsive symptoms; CDS = cognitive disengagement syndrome; PR = parent-re port; Freq. = frequency.

^*p < .05.

^**p < .01.

Table 4.

Chi-Square Tests Between Sex, Race, ADHD Status, and Dichotomous Variables.

	Sex	Race	ADHD status
Sex	—	2.64	12.80***
Race	—	—	1.09
School sports (Y/N)	0.25	0.79	7.36**
Community sports (Y/N)	0.01	3.45	6.75**
School arts (Y/N)	0.76	0.00	0.27
Community arts (Y/N)	0.01	0.02	4.74*
Clubs (Y/N)	0.30	0.71	0.73
Religious group (Y/N)	3.48	0.04	0.22
Volunteer work (Y/N)	0.003	0.16	7.06**

Note. For sex, 0 = male, 1 = female. For race, 0 = non-White, 1 = White. For ADHD status, 0 = non-ADHD comparison group, 1 = ADHD. ADHD = attention-deficit/hyperactivity disorder.

^*p < .05.

^**p < .01.

^***p < .001.

ADHD status, parent-reported ADHD-IN symptoms, and self-reported CDS symptoms were all negatively related to school and community sports involvement, whereas ADHD-HI symptoms were only significantly negatively related to school sports involvement. ADHD diagnosis and parent-reported ADHD symptom dimensions were negatively related to volunteer work. Finally, ADHD diagnosis was related to less involvement in community arts.

Self-Reported Physical Activity Involvement.

Given that the importance of capturing information on frequency, intensity, and duration of physical activity related to ADHD, we first examined differences in the percentage of self-reported frequency of exercise/physical activity of at least 20 min and of at least 60 min. Results showed that 60% of adolescents with ADHD and 75% of adolescents without ADHD reported obtaining a minimum of 20 min of exercise at least three/days per week (x² = 5.05, p = .025). Further, 51.3% of adolescents with ADHD and 65.6% of adolescents without ADHD reported obtaining a minimum of 60 min of exercise at least 3 days/per week (x² = 6.46, p = .011). Finally, daily reports of at least 60 min of physical activity per day occurred in 12% of adolescents without ADHD compared with 9% of adolescents with ADHD (though chi-square test was not statistically significant).

Of the demographic variables, sex and income were again most often related to indices of self-reported physical activity, with females and individuals from lower income homes reporting less physical activity overall. ADHD diagnosis and higher parent-reported ADHD-IN symptoms were related to less frequent reports of at least 20 and 60 min of intense physical activity during the previous week, as well as less engagement in activities involving physical exertion during free time. In addition, higher parent-reported ADHD-IN symptoms were also related to less frequent physical activity in the evenings. Higher parent-reported ADHD-HI symptoms were correlated with less frequent reports of at least 60 minutes and physical activity in the evenings during the previous week. Finally, CDS symptoms were correlated with all physical activity indices, such that higher CDS ratings were related to less frequent physical activity.

Regression Analyses

Regression models were conducted with participant demographic characteristics (i.e., sex and family income), indices of ADHD status/symptoms, and CDS simultaneously included as independent variables, with three separate reports for ADHD status, self-reported ADHD symptom dimensions, and parent-reported ADHD symptom dimensions. We do not include results for models that included self-reported ADHD symptoms in the main text, although they can be found in supplemental text and tables. Race was not included as a covariate in models because it was not correlated with any study variable except minimum physical activity 20 min in the previous week. Although correction for multiple comparisons is important in order to reduce the likelihood of Type I error, corrections like a Bonferroni correction have also been criticized for being too conservative (i.e., increasing the likelihood of false negatives or Type II error; Moran, 2003). In order to balance this tension, we indicate which of our regression results are significant with and without correction for multiple comparisons using the Bonferroni correction (Bonferroni, 1936). We interpret our findings based on our less conservative alpha threshold, while acknowledging which findings are most robust (i.e., still significant with the more conservative alpha threshold).

Logistic Regression Models Examining Likelihood of Parent-Reported Extracurricular Activity Involvement.

We present results of our logistic regression analyses in Table 5, including results that are significant with Bonferroni correction (α of .05 divided by seven outcome variables). We modeled the odds that adolescents were not involved in each extracurricular activity (i.e., event = “0” or “no involvement”). Among models that included ADHD diagnosis in models, ADHD diagnosis was only independently associated with community arts programing, such that adolescents with ADHD had over double the odds of not being involved in community arts programming (odds ratio [OR] = 2.21, 95% CI [1.05, 4.64], p = .037) and volunteer work (OR = 1.92, [1.02, 3.64], p = .044) compared with adolescents without ADHD. In the same models, higher CDS symptoms were also associated with higher odds of not being involved in school sports (OR = 1.89, [1.19, 2.99], p = .007) compared with adolescents reporting lower CDS levels. Finally, higher income was associated with higher likelihood of being involved in school (OR = 0.84, [0.73, 0.97], p = .05) and community sports (OR = 0.77, [0.67, 0.89], p < .001). Finally, models including parent-reported ADHD symptom dimensions symptoms provided converging evidence for models that included ADHD status, though ADHD symptoms were not significantly associated with any outcome. See Supplement and Table S1 for self-reported ADHD model estimates.

Table 5.

Logistic Regression Analyses Estimating Associations Between Predictors and Parent-Reported Activity Involvement (Y/N).

	School sports	Community sports	School art	Community art	Clubs	Religious groups	Volunteer work
	OR [95% CI]	OR [95% CI]	OR [95% CI]	OR [95% CI]	OR [95% CI]	OR [95% CI]	OR [95% CI]
Models using ADHD status
ADHD status	1.34 [0.80, 2.24]	1.37 [0.82, 2.29]	1.25 [0.71, 2.19]	2.21 [1.05, 4.64]	1.44 [0.71, 2.90]	1.05 [0.63, 1.77]	1.92 [1.02, 3.64]
SR CDS	1.89 [1.19, 2.99] a	1.45 [0.94, 2.26]	0.72 [0.46, 1.14]	0.78 [0.43, 1.42]	0.75 [0.42, 1.32]	0.84 [0.55, 1.29]	1.48 [0.85, 2.60]
Sex	0.89 [0.54, 1.48]	1.02 [0.62, 1.68]	0.91 [0.53, 1.55]	1.26 [0.62, 2.54]	1.35 [0.68, 2.67]	0.66 [0.40, 1.08]	1.06 [0.58, 1.93]
Income	0.84 [0.73, 0.97]	0.77 [0.67, 0.89] a	0.98 [0.85, 1.14]	0.89 [0.69, 1.06]	0.94 [0.78, 1.14]	0.98 [0.86, 1.13]	0.98 [0.83, 1.17]
Models using PR ADHD symptom dimensions
PR ADHD-IN	1.27 [0.86, 1.87]	1.27 [0.87, 1.85]	1.08 [0.71, 1.64]	1.22 [0.71, 2.23]	0.93 [0.56, 1.54]	1.23 [0.83, 1.81]	1.14 [0.71, 1.83]
PR ADHD-HI	1.32 [0.77, 2.29]	0.83 [0.49, 1.40]	1.14 [0.64, 2.03]	1.20 [0.54, 2.70]	0.89 [0.45, 1.75]	0.88 [0.52, 1.48]	1.91 [0.90, 4.08]
SR CDS	1.73 [1.08, 2.77]	1.44 [0.92, 2.26]	0.71 [0.45, 1.14]	0.82 [0.45, 1.52]	0.85 [0.47, 1.53]	0.79 [0.51, 1.23]	1.45 [0.81, 2.60]
Sex	0.99 [0.59, 1.64]	1.01 [0.61, 1.67]	0.92 [0.53, 1.56]	1.18 [0.58, 2.39]	1.16 [0.58, 2.31]	0.69 [0.42, 1.14]	1.08 [0.59, 1.99]
Income	0.86 [0.74, 0.99]	0.77 [0.67, 0.89] a	0.99 [0.85, 1.15]	0.84 [0.68, 1.05]	0.90 [0.74, 1.10]	0.99 [0.86, 1.14]	0.99 [0.83, 1.18]

Note. Logistic regression models predict odds of not participating in activity. For ADHD status, 0 = no ADHD, 1 =ADHD. For sex, 0 = male, 1 = female. For race, 0 = non-White, 1 = White. Bolded estimates reflect statistically significant models without p-value correction.

SR = self-report; CDS = cognitive disengagement syndrome; PR = parent-report; ADHD-IN = ADHD inattentive symptoms; ADHD-HI = ADHD hyperactive/impulsive symptoms.

^aEstimates that are significant with Bonferroni correction (p < .007). ADHD = attention-deficit/hyperactivity disorder.

Linear Regression Models Examining Parent-Reported Extracurricular Activity Involvement Frequency.

We present our estimation of linear associations between demographics, ADHD indices, CDS symptoms, and parent-reported activity extracurricular involvement in Table 6, including results that are significant with Bonferroni correction (α of .05 divided by seven outcome variables). In models including ADHD status, adolescents diagnosed with ADHD less frequently engaged in community arts programming compared with adolescents without ADHD (β = −.127, p = .044), though we did not observe similar statistically significant associations in models including parent-reported ADHD-IN and ADHD-HI symptom dimensions.

Table 6.

Linear Regression Analyses Estimating Associations Between Predictors and Parent-Reported Activity Involvement Frequency.

	School sports	Community sports	School art	Community art	Clubs	Religious groups	Volunteer work
	β (p)	β (p)	β (p)	β (p)	β (p)	β (p)	β (p)
Models using ADHD status
ADHD Status	−.104 (.090)	−.077 (.205)	−.097 (.126)	−.127 (.044)	−.044 (.489)	−.060 (.343)	−.099 (.115)
SR CDS	−.156 (.009)	−.125 (.034)	.105 (.089)	.055 (.374)	.111 (.072)	.057 (.356)	−.114 (.064)
Sex	.025 (.663)	.009 (.878)	−.030 (.623)	−.045 (.457)	−.072 (.232)	.079 (.195)	.038 (.531)
Income	.151 (.010)	.235 (<.001) a	−.015 (.804)	.081 (.177)	.076 (.208)	.019 (.759)	.001 (.980)
Models using PR ADHD symptom dimensions
PR ADHD-IN	−.109 (.146)	−.077 (.304)	−.042 (.592)	−.024 (.764)	.051 (.517)	−.083 (.290)	−.051 (.513)
PR ADHD-HI	−.077 (.271)	.038 (.585)	−.083 (.254)	−.055 (.449)	−.018 (.801)	.037 (.610)	−.092 (.202)
SR CDS	−.133 (.029)	−.126 (.038)	.109 (.087)	.040 (.532)	.086 (.173)	.062 (.362)	−.106 (.092)
Sex	.006 (.921)	.014 (.810)	−.033 (.587)	−.030 (.623)	−.051 (.409)	.078 (.205)	.030 (.617)
Income	.134 (.022)	.242 (<.001)a	−.021 (.732)	.091 (.135)	.092 (.131)	.021 (.733)	−.008 (.899)

Note. For ADHD status, 0 = no ADHD, 1 = ADHD. For sex, 0 = male, 1 = female. For race, 0 = non-White, 1 = White. ADHD = attention-deficit/hyperactivity disorder. Bolded estimates reflect statistically significant models without p-value correction. SR = self-report; CDS = cognitive disengagement syndrome; PR = parent-report; ADHD-IN = ADHD inattentive symptoms; ADHD-HI = ADHD hyperactive/impulsive symptoms.

^aEstimates that are significant with Bonferroni correction (p < .008).

In contrast, higher CDS symptoms were associated less frequent involvement in school sports and community sports throughout the week in both our models including ADHD status (school sports: β = −.156, p = .009; community sports: β = −.125, p = .034) and our model including parent-reported ADHD symptom dimensions (school sports: β = −.133, p = .029, community sports: β = −.126, p = .038). Interestingly, higher CDS ratings were also trending significant in their association with more frequent involvement in school arts in models including ADHD status (β = .105, p = .089) and parent-reported ADHD symptom dimensions (β = .109, p = .087) and more involvement in clubs in models including ADHD status (β = .111, p = .072).

Finally, income was independently and positively associated with the frequency of involvement in several extracurricular activities, including school (ADHD status: β = .151, p = .010; parent-reported ADHD dimensions: β = .134, p = .022), and community sports (ADHD status: β = .235, p < .001; parent-reported ADHD symptoms: β = .242, p < .001). See Supplement and Table S2 for self-reported ADHD model estimates.

Linear Regression Models Examining Physical Activity Involvement.

We present estimates of associations for self-reported physical activity in Table 7, including results that are significant with Bonferroni correction (α of .05 divided by six outcome variables). The only significant independent association between indices of ADHD and self-reported physical activity was the association between higher parent-reported ADHD-IN symptoms and less self-reported engagement in activities during free time that are more physical (β = −.161, p = .029).

Table 7.

Linear Regression Analyses Estimating Associations Between Predictors and Self-Reported Physical Activity Indices.

	PA ≥ 20 min	PA ≥ 60 min	PA after school	PA in evening	PA on weekend	PA in free time
	β (p)	β (p)	β (p)	β (p)	β (p)	β (p)
Models using ADHD status
ADHD Status	−.086 (.161)	−.065 (.273)	.010 (.869)	−.057 (.350)	.030 (.628)	−.066 (.268)
SR CDS	−.088 (.139)	−.149 (.011)	−.073 (.233)	−.192 (.001) a	−.160 (.009)	−.195 (.001) a
Sex	−.112 (.056)	−.077 (.176)	−.121 (.044)	−.111 (.060)	−.132 (.027)	−.123 (.031)
Income	.218 (<.001)a	.266 (<.001) a	.125 (.036)	.098 (.096)	.067 (.258)	.197 (.001) a
Models using PR ADHD symptom dimensions
PR ADHD-IN	−.114 (.133)	−.097 (.188)	−.014 (.859)	−.065 (.393)	−.054 (.480)	−.161 (.029)
PR ADHD-HI	.042 (.552)	.013 (0.851)	.006 (.935)	−.039 (.579)	.034 (0.634)	.116 (.091)
SR CDS	−.080 (.192)	−.136 (.023)	−.067 (.288)	−.178 (.004) a	−.140 (.025)	−.180 (.003) a
Sex	−.113 (.055)	−.085 (.140)	−.127 (.038)	−.122 (.041)	−.148 (.014)	−.129 (.026)
Income	.220 (<.001) a	.261 (<.001) a	.121 (.045)	.087 (.140)	.056 (.350)	.199 (.001) a

Note. For ADHD status, 0 = no ADHD, 1 = ADHD. For sex, 0 = male, 1 = female. For race, 0 = non-White, 1 = White. Bolded estimates reflect statistically significant models without p-value correction. SR = self-report; CDS = cognitive disengagement syndrome; PR = parent-report; ADHD-IN = ADHD inattentive symptoms; ADHD-HI = ADHD hyperactive/impulsive symptoms.

^aEstimates that are significant with Bonferroni correction (p < .008).

However, more CDS symptoms were independently associated with lower levels of several self-reported physical exercise indices, including all models of self-reported intense physical exercise of at least 60 min (ADHD status model: β = −.149, p = .011; parent-reported ADHD symptom models: β = −.136, p = .023), physical activity in the evenings during the previous week (ADHD status model: β = −.192, p = .001; parent-reported ADHD symptom models: β = −.178 p = .004), and activities requiring more physical exertion during free time (ADHD status model: β = −.195, p = .001; parent-reported ADHD symptom models: β = −.180 p = .003; see Supplement and Table S3 for self-reported ADHD model estimates). Higher CDS symptoms were also significantly associated with less frequent physical activity during the previous weekend in both models that included ADHD status (β = −.160, p = .009) and parent-reported ADHD symptom dimensions (β = −.140, p = .025).

Finally, income and sex were associated with several physical activity indices. Higher income was associated with higher frequency of at least 20 (ADHD status model: β = .218, p <.001; parent-reported ADHD symptom models: β = .220, p < .001) and 60 (ADHD status model: β = .266, p < .001; parent-reported ADHD symptom models: β = .261, p < .001) minutes of intense exercise in the previous week, higher frequency of physical activity after school in the previous week (ADHD status model: β = .125, p = .036; parent-reported ADHD symptom models: β = .121, p = .045), and higher frequency of engagement in activities during free time that involve physical exertion (ADHD status model: β = .197, p = .001; parent-reported ADHD symptom models: β = .199, p = .001), across all models (see Supplement and Table S3 for self-reported ADHD symptom model estimates). Females were less likely to be involved in physical activity after school (ADHD status model: β = −.121, p = .044; parent-reported ADHD symptom models: β = −.127, p = .038), on the weekend (ADHD status model: β = −.132, p = .027; parent-reported ADHD symptom models: β = −.148, p = .014), and during free time (ADHD status model: β = −.123, p = .031; parent-reported ADHD symptom models: β = −.129, p = .026).

Discussion

Although physical inactivity has been documented as a health-related outcome of adolescents with ADHD (Kim et al., 2011; Mercurio et al., 2021; Tandon et al., 2019), our understanding of individual factors associated with specific types of activity engagement, including physical activity, is limited. The current study advances the literature by using a multi-informant approach to characterizing ADHD, CDS, and physical and other types of activity, including multiple indices of frequency, intensity, and duration of activities, in a sample of adolescents with and without ADHD. We also examined key correlates of physical activity and ADHD, including demographic characteristics, ADHD symptoms, and CDS symptoms. A few key findings emerged.

CDS Symptom Findings

Although ADHD diagnosis, as well as continuous ADHD symptom dimensions, were correlated with lower levels of involvement in several indices of extracurricular activities and self-reported physical activity, CDS symptoms, rather than ADHD status or symptoms, were more robustly uniquely related to lower likelihood of being involved in school sports, lower frequency of sports involvement (school- or community-based), and lower frequency, intensity, and duration of most self-reported physical activity indices (i.e., physical activity after school, on the weekend, and during free time, across all models). This also includes several estimates (e.g., school sports involvement, physical activity in the evening) after correction for multiple comparisons. These findings are consistent with the only other study we are aware of that found less engagement in sports among children and adolescents with high levels of CDS (with and without ADHD) compared with comparisons (Barkley, 2013). These findings also contrast to the trending significant associations between higher self-reported CDS symptoms and higher frequency of involvement in school arts programming (in models including ADHD diagnosis and parent-reported ADHD symptoms), clubs (in models including ADHD diagnosis), and religious groups (in models including self-reported ADHD symptoms) during school nights (these findings should be considered cautiously particularly given these trends were prior to correction for multiple comparisons). These findings may suggest differential activity involvement types related to ADHD and CDS symptoms. For instance, higher levels of CDS symptoms may be specifically related to more physical inactivity, including involvement in more structured extracurricular activities involving physical activity (i.e., sports) and general exercise, but not extracurricular inactivity more generally. This may, in part, explain mixed findings regarding whether physical activity interventions improve ADHD symptoms in children and adolescents (Cerrillo-Urbina et al., 2015; Cornelius et al., 2017; Sun et al., 2022) and suggests that it may be more important to measure and target CDS symptoms.

In contrast, there has been recent interest in examining positive outcomes associated with CDS, including creativity and meaning-making (Becker & Barkley, 2021), and recent evidence also supports the possibility of mind-wandering and daydreaming contributing to creativity and imagination among youth with elevated levels of CDS (Becker, Fredrick, et al., 2022). Although not part of the current study’s aims, our findings also highlight the need for additional focus on positives and strengths associated with CDS and ADHD.

Although the cross-sectional nature precludes making interpretations regarding the directionality of CDS and less physical (and other types of) activity, it is possible executive functioning and motivational-based deficits that cut across both ADHD and CDS may interfere with adolescents’ ability to initiate and maintain regular physical exercise and activity engagement more broadly, especially those that are more structured and require organization and cooperation with others (Khalife et al., 2014; Nigg, 2013). Given the nature of CDS symptoms (e.g., mind-wandering, mental fogginess, slowed behaviors, lethargy) and the depressive symptoms (Becker, Mossing, & Dvorsky, 2021; Fredrick, Langberg, & Becker, 2022), daytime sleepiness (Fredrick et al., 2022; Rondon et al., 2020; Smith et al., 2019), and social withdrawal (Fredrick & Becker, 2023) associated with CDS, there are also several additional possible mechanisms to investigate. For instance, the underlying deficits in the arousal system related to CDS, may give rise to many of the behaviors that define CDS (e.g., hypoactivity, lethargy, mind-wandering) and its correlates (e.g., depressive symptoms, social withdrawal). These deficits in the arousal system may also explain the reduced frequency of activity involvement, including exercise (Yung et al., 2020). Alternatively, cognitive disengagement, including maladaptive mind-wandering that interferes with goal-directed behavior (Buckley et al., 2014), may link CDS, its correlates (e.g., social withdrawal, anhedonia-related depressive symptoms), and inactivity. However, more research with longitudinal and experimental designs is clearly needed to better understand these links and identify potential mechanisms.

ADHD Diagnosis and Symptom Findings

ADHD diagnosis was, however, independently associated with lower likelihood and lower frequency of involvement in community-based arts programming, as well as lower likelihood of involvement in volunteer work prior to correction for multiple comparisons. Symptom dimensions of ADHD were not independently associated with lower likelihood or frequency of these extracurricular activities, however, which does not support the hypothesis that ADHD-IN symptoms may be more related to less activity engagement in these areas compared with ADHD-HI symptoms (Khalife et al., 2014).

Regarding self-reported physical activity, the only unique and significant finding we observed was between higher parent-reported ADHD-IN ratings and less frequent involvement in activities during free time in the previous week that involve more physical exertion prior to correction for multiple comparisons, which is consistent with previous research specifically linking ADHD-IN symptoms to physical inactivity (Khalife et al., 2014; Selinus et al., 2021).

Taken together, our findings across physical and non-physical activities suggest that adolescents with ADHD may be less likely to engage in at least some types of non-physical extracurricular activities, suggesting need for further examination of broader levels of inactivity in order to inform intervention. Further, our findings may point toward clues to explain why research has also produced mixed results regarding the relevance of the type, frequency, intensity, and duration of physical activity interventions (Cerrillo-Urbina et al., 2015; Cornelius et al., 2017; Sun et al., 2022), as adolescents exhibiting high levels of ADHD-IN symptoms may be in particular need of interventions that either address inactivity during free time and/or provide structured physical activity engagement to compensate for inactivity during free time.

Income and Sex Findings

Although not the primary focus of our study, we also found that adolescents with lower parent-reported family income had lower parent-reported frequency of activity involvement and self-reported physical activity, with most findings remaining significant following correction for multiple comparisons. Finally, although parent-reported activity involvement did not differ by sex, self-reported physical activity after school, on weekends, and during free time was lower in females than males prior to correction for multiple comparisons. These findings are consistent with studies of community (Heath et al., 2022) and ADHD (Kim et al., 2011; Mercurio et al., 2021; Tandon et al., 2019) children and adolescents identifying individuals with lower socioeconomic status and females having higher risk for physical inactivity. Due to the barriers that families with lower income experience (e.g., finances, work demands, caregiving, transportation), adolescents may have less opportunities to participate in both organized and non-organized activities. Similarly, there are disparities in the opportunities and encouragement for females to engage in physical activity and sports compared with male counterparts (Solmon, 2014). Although we did not observe differences in belonging to physically active types of activities (i.e., sports), such disparities may still contribute to frequency, intensity, and duration of physical activity outside of such extracurricular activities, which is consistent with our findings. Specific to ADHD, research has also shown lower rates of hyperactive-impulsive symptoms in girls with ADHD compared with boys with ADHD (Fraticelli et al., 2022), and higher engagement in less active hobbies (e.g., more time on social media) being tied to risk for obesity in girls with ADHD that are not being treated with medication (Kim et al., 2011).

Implications for Intervention and Treatment

Given the well-documented physical and mental health benefits of physical activity (Biddle & Asare, 2011; Doré et al., 2020), these findings highlight the importance of considering socioeconomic status (e.g., barriers to accessing opportunities for physical activity), sex, and co-occurring symptoms of CDS in assessment and intervention. Although no current evidence-based interventions exist for CDS, researchers recommend cognitive-behavioral therapy, mindfulness, and behavioral sleep interventions to address the core features of CDS (Becker, Willcutt et al., 2022). Given the acute and chronic benefits of physical activity for enhanced cognitive and mental health that occur from frequent (e.g., ≥3 days per week) intervals of moderate-to-vigorous exercise (e.g., 20–30 min practices of 40%–75% intensity) within typically developing populations (Suarez-Manzano et al., 2018), our finding of the low prevalence of teens with ADHD obtaining the recommended 60 min of physical activity per day (United States Department of Health and Human Services, 2008), for instance, is concerning. Adolescents with ADHD and high levels of CDS may benefit by increasing the frequency and intensity of exercise, though more work is needed to specifically test this hypothesis, particularly given the current exercise intervention literature has produced mixed findings regarding core ADHD symptoms, pooled children and adolescents together, and not examined the impact of exercise on CDS symptoms (Cerrillo-Urbina et al., 2015; Cornelius et al., 2017; Sun et al., 2022).

In addition to the numerous beneficial effects of regular exercise, participating in extracurricular activities improves adolescent’s and parents’ well-being (Heath et al., 2022; Vella et al., 2014), and may particularly improve academic and emotional adjustment for adolescents who are disadvantaged. As such, interventions may also expand their focus not only to include increasing physical activity in adolescents with higher ADHD and CDS symptoms, but engagement in extracurricular activities more broadly (possibly drawing upon behavioral activation strategies commonly used for depression, which often emphasizes physical activity in addition to activities associated with mastery, pleasure, and closeness with others; Cuijpers et al., 2007; Dimidjian et al., 2011). This broader approach may provide the opportunity to lead with activities that patients may have more natural interest and affinity for, working toward building skills and routine with regard to other activity types over time. The use of motivational interviewing techniques and/or identification of barriers (e.g., financial resources to participate in organized activities, areas to exercises, school involvement) to exercise and other activity involvement may also prove to be useful (Mutschler et al., 2018), particularly among adolescents from low income homes and females.

Limitations and Future Directions

Despite strengths of the current study, including a sample of adolescents who underwent an assessment to determine ADHD status and assessment of both exercise and extracurricular activity involvement, a few limitations are worth noting. Primarily, the cross-sectional nature of the study precludes any causal or temporal interpretations. Future prospective and experimental studies are encouraged to test the interrelations of CDS symptoms and physical activity in adolescents with ADHD. Second, although we assessed both self- and parent-reported ratings, device-assessed indices of movement and heart rate provide a more information regarding physical activity intensity (Seiffer et al., 2022). Along these lines, although we assessed for different types of activity involvement, we did not assess the frequency of exercise or movement during these activities. Additionally, although we have improved upon prior work that uses caregiver reports that their children have been previously diagnosed with ADHD by a clinician, our lack of inclusion of teacher- or other informant-report is an important limitation to the current study. Finally, given that we utilized a convenience sample for the current study, we cannot be sure how well our findings will generalize to other populations. Future research would also benefit from examining activity involvement in more financially and racially/ethnically diverse samples, as well as direct assessment of social determinants of health, to further understand the complex relationships among factors such as cultural expectations and access related to physical and extracurricular activities.

Conclusions

In conclusion, the current study examined whether ADHD diagnosis or symptoms and CDS symptoms were uniquely related to several indices of physical activity and extracurricular activity involvement more broadly in a sample of adolescents. Although ADHD diagnosis, ADHD-IN symptoms, and ADHD-HI symptoms were all correlated with lower likelihood and frequency of involvement in extracurricular activities and lower frequency, intensity, and duration of physical activity, CDS symptoms were most robustly associated with less involvement in extracurricular activities involving physical activity and other physical activity indices. Adolescents from lower income homes and female adolescents were also independently more likely to have less involvement in several extracurricular activities and physical activity. Findings suggest the need for (a) assessment of co-occurring CDS symptoms among adolescents with ADHD, as this may provide better understanding of distinct symptoms that may be related to physical inactivity among this population, (b) discussion of barriers to accessing opportunities for physical and extracurricular activities among families with fewer resources and among female adolescents, and (c) more experimental and intervention research specifically among adolescents with ADHD who exhibit physical inactivity and/or disengagement from extracurricular activities more broadly.

Supplementary Material

Supplemental material for this article is available online.

Table 2.

Descriptive Statistics and Bivariate Correlations Between Study Variables and Self-Reported Physical Activity.

Variable	7	8	9	10	11	12
1. Income	.258**	.313**	.139*	.152**	.093	.254**
2. SR ADHD-IN	−.096	−.137*	−.079	−.157**	−.136*	−.167**
3. SR ADHD-HI	−.073	−.106	−.102	−.125*	−.095	−.099
4. SR CDS	−.170**	−.230**	−.116*	−.245**	−.188**	−.271**
5. PR ADHD-IN	−.153**	−.187**	−.046	−.152**	−.071	−.179**
6. PR ADHD-HI	−.078	−.120*	−.029	−.119*	−.021	−.045
7. PA ≥ 20 min	—	.825**	.559**	.603**	.523**	.549**
8. PA ≥ 60 min		—	.602**	.628**	.489**	.547**
9. PA after school			—	.677**	.619**	.448**
10. PA in evening				—	.651**	.481**
11. PA on weekends					—	.492**
12. PA in free time						—
M	3.75	3.40	1.69	1.74	1.51	1.68
SD	2.226	2.237	1.486	1.448	1.217	1.153

Note. Income is an ordinal variable ranging from 0 to 6. For sex, 0 = male, 1 = female. For race, 0 = non-White, 1 = White. SR = self-report; ADHD = attention-deficit/hyperactivity disorder; ADHD-IN = ADHD inattentive symptoms; ADHD-HI = ADHD hyperactive/impulsive symptoms; CDS = cognitive disengagement syndrome; PR = parent-report; PA = physical activity.

^*p < .05.

^**p < .01.

Table 3.

Independent Samples t-Tests Between Sex, Race, and ADHD Status for Continuous Variables.

	Sex	Race	ADHD status
Income	0.42	−4.04***	4.46***
SR ADHD-IN	1.01	0.33	—
SR ADHD-HI	0.90	0.57	—
SR CDS	−2.64**	0.56	−4.65***
PR ADHD-IN	3.84***	0.68	—
PR ADHD-HI	2.77**	1.11	—
School sports (freq.)	−0.30	−0.95	3.34**
Community sports (freq.)	−0.05	−1.86	2.94**
School arts (freq.)	−0.20	0.37	0.97
Community arts (freq.)	0.08	0.07	2.04*
Clubs (freq.)	0.87	−0.10	0.35
Religious group (freq.)	−1.68	−0.96	1.19
Volunteer work (freq.)	−0.69	0.26	2.41*
PA ≥ 20 min	1.94	−2.09*	2.43*
PA ≥ 60 min	1.57	−0.79	2.69**
PA after school	2.44*	0.83	0.30
PA in evening	2.31*	−0.71	1.92
PA on weekends	2.93**	0.24	0.06
PA in free time	2.51*	−1.72	2.46*

Note. Income is an ordinal variable ranging from 0 to 6. For sex, 0 = male, 1 = female. For race, 0 = non-White, 1 = White. For ADHD status, 0 = non-ADHD comparison group, 1 = ADHD. SR = self-report; ADHD = attention-deficit/hyperactivity disorder; ADHD-IN = ADHD inattentive symptoms; ADHD-HI = ADHD hyperactive/impulsive symptoms; CDS = cognitive disengagement syndrome; PR = parent-report; Freq. = frequency; PA = physical activity.

^*p < .05.

^**p < .01.

^***p < .001.

Biographies

Kelsey K. Wiggs, Ph.D. is a Post-Doctoral T32 Research Fellow at Cincinnati Children’s Hospital. Her research broadly focuses on the predictors, correlates, and treatment of attention-deficit/hyperactivity disorder and cognitive disengagement syndrome.

Keely Thornton, B.S., is a Clinical Research Coordinator at the Center for ADHD at Cincinnati Children’s Hospital. Her research interests include the prediction and intervention of suicidal thoughts and behaviors, specifically among individuals with attention-deficit/hyperactivity disorder.

Joseph W. Fredrick, Ph.D., is an Assistant Professor of Pediatrics in the Division of Behavioral Medicine and Clinical Psychology at Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine.

Caroline Lowman, M.S. is a PhD candidate in the Clinical Psychology Doctoral Program, Child/Adolescent concentration at Virginia Commonwealth University (VCU). Her research focuses on health behaviors (e.g., physical activity, sleep, caffeine use) in youth with ADHD.

Joshua M. Langberg, Ph.D., is a licensed clinical psychologist, Professor of Psychology in the Graduate School of Applied and Professional Psychology (GSAPP), and Director of the Center for Youth Social Emotional Wellness (CYSEW) at Rutgers University. His clinical and research interests focus on improving the academic and behavioral functioning of adolescents and emerging adults with ADHD and the dissemination and implementation of evidence-based practices in school and community settings.

Stephen P. Becker, Ph.D., is an Associate Professor of Pediatrics, Director of Research, and Endowed Chair in the Division of Behavioral Medicine and Clinical Psychology at Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine. His research, funded by the National Institute of Mental Health (NIMH) and the Institute of Education Sciences (IES), focuses on cognitive disengagement syndrome and sleep in youth with and without ADHD.