Symptom Presentation and Neurocognitive Performance Following Sport-Related Concussion in Adolescents with and without ADHD

Abstract

The possible impact of premorbid Attention-Deficit/Hyperactivity Disorder (ADHD) in the recovery process following sport-related concussion (SRC) in adolescents is not clear. The purpose of this study was to investigate the impact of ADHD together with other selected variables on symptom presentation and neurocognitive performance in a well-matched sample of adolescents with SRC. We hypothesized that more symptoms and poorer neurocognitive performance would be observed in those with ADHD. Symptoms from the Sideline Concussion Assessment Tool-5 and cognitive test results from the Immediate Post-Concussion Assessment and Cognitive Test (ImPACT) were examined at initial visit, and symptoms were re-assessed at 3-months in a sample of 112 participants with (n = 56) and without (n = 56) ADHD (ages 12 to 18 years; M = 14.68, SD = 1.77) who were matched by age, sex, ethnicity/race, and days post-injury. Exclusion criteria included severe medical illness or moderate/severe brain injury, and lack of English fluency. No significant group differences were found in total symptoms (p = .145), symptom severity (p = .179), or neurocognitive functioning at initial visit (all p > .79) or at 3 months. However, athletes with ADHD reported more nausea (p = 0.22) and feeling slowed down at initial testing (p = .021). Additionally, premorbid anxiety influenced symptom report (p = .010). ADHD did not appear to pose a specific risk for greater symptom burden or neurocognitive deficits in the first 3 months post-concussion.

Introduction

An important topic in pediatric concussion research is the examination of premorbid factors and their effects on cognitive and symptom outcomes. Premorbid factors have the potential to increase the risk of concussion, exacerbate post-concussion symptoms, delay recovery time, and influence treatment decisions (Collins et al., 2016; Iverson et al., 2017; Iverson et al., 2020; Zuckerman et al., 2013). One such factor is Attention-Deficit/Hyperactivity Disorder (ADHD), a neurodevelopmental disorder characterized by problems with attention and distractibility and/or problems with hyperactivity and impulse control (see Diagnostic and Statistical Manual of Mental Disorders 5^th ed.; DSM-5; American Psychiatric Association, 2013). ADHD occurs in approximately ten percent of children and adolescents in the U.S. (Centers for Disease Control and Prevention, 2024), and concussion literature has described chronic cognitive issues in youth with ADHD. Because ADHD can involve difficulty concentrating, and one of the cognitive sequelae of concussion is difficulty with attention/concentration (Giza & Kutcher, 2014), it gives rise to the question of how symptoms of ADHD may interfere with post-concussion symptom presentation and recovery in adolescents. Compared to adolescents without ADHD, adolescents with ADHD have reported cognitive difficulties at baseline on the Immediate Post-Concussion Assessment and Cognitive Test (ImPACT; Covassin et al., 2009), including lower scores in verbal memory (Mautner et al., 2015), visual memory, and visual-motor functioning (Elbin et al., 2013; Gardner et al., 2017; Zuckerman et al., 2013). Children with ADHD also reported significantly more symptoms and greater severity of symptoms at preseason assessment on the SCAT-5 (Echemendia et al., 2017) than children without ADHD (Cook et al., 2019). Specific symptoms include concentration problems, sleep disturbance, and fatigue at baseline (Cook et al., 2020). Because premorbid symptoms could be misinterpreted following a concussion in adolescents with ADHD, they merit special attention for healthcare professionals to make return-to-learn and/or play decisions appropriately.

Some disagreement exists about concussion recovery in adolescents with ADHD, as findings have been mixed with regard to prolonged symptom recovery in this population. Iverson et al. (2017) conducted a systematic review of 240 published studies focused on potential clinical predictors of post-concussion recovery. Of the 10 studies that included ADHD as a variable in this review, most did not find that ADHD posed a risk for slower recovery. For example, Zemek et al. (2016) found no difference in the proportion of patients with and without ADHD who had persistent symptoms at 28 days post-concussion. In a smaller case-control study matched by age and sex, no difference in persistent post-concussion symptoms at 3 months post-injury was found for athletes with a history of ADHD versus those without (Morgan et al., 2015). In contrast, one study (Miller et al., 2016) in this review reported that ADHD was more likely to be associated with delayed recovery following concussion. Mautner et al. (2015) found adolescents with ADHD took an average of three days longer to return to baseline than those without ADHD, which was not statistically significant, but described by the authors as potentially clinically relevant.

Regarding return-to-learn and/or play, adolescents with ADHD who sustained a SRC were not found to be delayed in returning to school or sports compared to adolescents without ADHD (Cook et al., 2021; Cook et al., 2022). However, adolescents with ADHD who experienced various mechanisms of concussion (e.g., non-sport collisions and falls) had a significantly longer time to return to sports or normal activities compared to adolescents without ADHD in a retrospective study of clinical records (Aggarwal et al., 2020). In another retrospective study, employing a longer time period (i.e., 180 days) post-injury, median times to symptom resolution were significantly longer in children and adolescents with ADHD versus those without ADHD, although all recovery times were notably long in this study (Martin et al., 2022).

One challenge in interpreting the published research on post-concussion symptoms and recovery in adolescents with ADHD is that some studies used no control group or inconsistent methodologies to select non-ADHD controls. Furthermore, possible confounding factors generally have not been considered. For example, sex typically is not specifically addressed, although greater concussion symptom burden has been reported for females with ADHD compared to males with ADHD (Lambert et al., 2021). Given the inconsistencies in the literature, the aim of this study was to investigate the effects of premorbid ADHD on self-reported symptom levels and computerized neurocognitive test performance using a carefully selected adolescent concussion control group individually matched for age, sex, ethnicity/race, and days post-injury. These variables were chosen based upon previous research (Howell et.al., 2019; Iverson et al., 2017; Kontos et al., 2020), and our ability to provide a well-matched sample with the available demographic data. We hypothesized that adolescent athletes with premorbid ADHD would endorse more symptoms and greater symptom severity levels and exhibit worse neurocognitive test performance than those without ADHD.

Method

Participants

Participants for this study, aged 12 to 18 years (M = 14.67, SD = 1.75), were selected from a larger database of athletes with sport-related concussion (SRC) who were enrolled in the North Texas Concussion Network registry (ConTex) (Cullum et al., 2020) between October of 2015 and July of 2022. ConTex is a state-funded initiative of the Peter J. O’Donnell Jr. Brain Institute at the University of Texas Southwestern Medical Center and includes four specialized concussion clinics in the Dallas Metroplex. Inclusion criteria for the ConTex registry were fluency in English, functional vision and hearing, and availability of a parent/guardian to provide informed consent and to complete parent questionnaires. ConTex registry exclusion criteria were loss of consciousness lasting > 30 minutes, known skull fracture or intracranial bleed, injury > 6 months prior to clinical evaluation, and spinal cord injury with American Spinal Injury Association (ASIA) score of C or worse. Participants were further excluded for severe premorbid medical illness or a history of headaches/migraines severe enough to have involved treatment by a physician. Of all concussion patients at these clinics, 37% were not eligible, 15% declined enrollment, and 48% were enrolled in ConTex.

Participants in this study were seen at one of the ConTex concussion clinics within 30 days of injury (M = 8.47, SD = 7.03 days). Medical history, including ADHD, was provided by parents and reviewed by clinicians to confirm diagnoses. A total of 56 participants whose parents reported a history of ADHD in the clinical interview were identified and matched with 56 participants without a reported history of ADHD based on exact age (year and month), sex, ethnicity/race, and days post-injury (± 1 day). Table 1 shows demographic and premorbid information for the sample.

Table 1.

Group Characteristics and ImPACT^© Scores at Initial Visit

	ADHD (n = 56)	Non-ADHD (n = 56)	p value
History of Anxiety % (n)	32.1% (18)	10.7% (6)	.010*
History of Depression % (n)	10.7% (6)	1.8% (1)	.113*
History of Headache/Migraine % (n)	19.6% (11)	16.1% (9)	.806*
History of Prior Concussions % (n)	33.9% (19)	39.3% (22)	.695*
ImPACT© Scores
Memory Composite Verbal Score M (SD)	76.11 (17.20)	76.77 (15.35)	.830**
Memory Composite Visual Score M (SD)	64.27 (15.19)	64.21 (14.07)	.985**
Visual Motor Speed Composite Score M (SD)	33.33 (8.44)	33.76 (8.62)	.792**
Reaction Time Composite Score M (SD)	0.71 (0.15)	0.71 (0.18)	.909**
Impulse Control Composite Score M (SD)	11.84 (8.75)	8.89(7.31)	.056**
Cognitive Efficiency Index M (SD)	0.26 (0.13)	0.48 (1.32)	.279**
Number of Reported Symptoms M (SD)	10.07 (6.56)	7.94 (6.60)	.092**
Total Symptom Score M (SD)	26.18 (24.17)	18.91 (19.84)	.085**

Note: ImPACT = Immediate Post-concussion Assessment and Cognitive Testing^©, ADHD = Attention-Deficit/Hyperactivity Disorder,

^{* =}Fisher’s Exact Test,

^{** =}t-test.

Measures

At initial visit, participants completed the ImPACT as an objective measure of cognitive functioning. ImPACT provides scores for verbal memory, visual memory, visual motor speed, reaction time, impulse control, and cognitive efficiency, as well as symptoms at time of testing. For this study, rather than the ImPACT symptom scale, participants completed a separate post-concussion symptom evaluation from the Sideline Concussion Assessment Tool-5 (SCAT-5; Echemendia et al., 2017). The SCAT-5 consists of 22 items that assess presence and severity of symptoms, each measured on a 7-point scale ranging from 0 (none) to 6 (severe). In addition, the SCAT-5 asks if either cognitive or physical activity exacerbates these concussion-related symptoms, and it includes the question “If 100% is feeling perfectly normal, what percent of normal do you feel?” which also was analyzed in this study. Participants and parents/guardians provided demographic information, medical history, and injury characteristics in a clinical interview.

Procedure

ConTex is a multisite study with participant enrollment from specialty concussion clinics at the University of Texas Southwestern Medical Center, Children’s Health, Texas Scottish Rite Hospital for Children, and Texas Health Sports Medicine. The study was approved by Institutional Review Boards of the participating institutions prior to enrollment of participants. Written consent was obtained from all parents/guardians and written assent was obtained from all participants. A standardized, multimodal approach (see McCrory et al., 2017) was used at all sites to confirm diagnosis. All participants completed an initial clinic visit and a remote three-month follow-up. The timing of the ConTex three-month follow up was based on review of concussion recovery research (Elbin, et al., 2016; Iverson et al., 2017). Study data were collected and managed using REDCap (Research Electronic Data Capture) tools (Harris et al., 2009, 2019) hosted at the University of Texas Southwestern Medical Center. REDCap is a secure, web-based software platform designed to support data capture for research studies, providing 1) an intuitive interface for validated data capture; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for data integration and interoperability with external sources.

Statistical analyses

Prior to analysis, statistical assumptions on all measures were verified through use of log base 10 transformations to address possible issues of unequal group variances and non-normal distributions. Sample means and standard deviations were used to describe continuous variables, such as number of reported concussion symptoms, symptom severity, and ImPACT test scores. Frequencies (i.e., percentages) were used to characterize categorical variables. ANOVA and t-tests were conducted to determine differences between ADHD and non-ADHD groups. When the effects for analysis of variance (ANOVA) were significant, Bonferroni post hoc pairwise group comparisons were performed. Pearson’s Chi-Square analyses or Fisher’s exact tests, as appropriate, were used to examine differences in participant categorical demographics, medical history, and injury characteristics by sex. Partial eta squared (Richardson, 2011) was used to measure effect sizes of the ANOVA.

Separate linear mixed models analysis of covariance (ANCOVA) examined groups at two time points (i.e., initial clinical visit and remote three-month follow-up) based on the total number of reported concussion symptoms, total symptom severity, and participants’ perception of their recovery (“percent of normal”). Because there was a significant difference between the groups (p = .010) in reporting of premorbid anxiety, and literature has shown post-concussion outcome differences associated with a history of anxiety (Iverson et al., 2017; Martin et al., 2020), premorbid anxiety was included as a covariate in these models.

Comparison of groups for presence of each concussion symptom on the SCAT-5 at initial and three-month follow-up was examined by Chi-Square analysis. All statistical analyses were carried out using SPSS V26. The level of significance was set at α = .05 (two-tailed), unless otherwise specified.

Results

Demographics and group characteristics

In the study sample of 112 participants, 32.1% (n = 36) were female and 67.9% (n = 76) were male. Average age of participants was 14.68 years (SD = 1.77, Median = 15). For ethnicity/race, 8.9% (n = 10) were self-identified as Hispanic/Latino and 83.9% (n = 94) identified as White. Average time from injury to initial clinical visit was 8.47 days (SD = 7.03, Median = 6). All concussions were sport-related, and primarily from football (34.8%, n = 39), soccer (14.3%, n = 16), and basketball (12.5%, n = 14). As shown in Table 1, no significant overall differences were found between matched groups of concussed adolescents with ADHD versus those without ADHD on ImPACT scores of verbal memory, visual memory, visual motor speed, reaction time, or cognitive efficiency at the initial clinic visit. The findings for impulse control, number of reported symptoms, and total symptom score also were not statistically significant; inspection of the data for those three variables reveals that scores for the adolescents with ADHD were worse than scores for those without ADHD (although this difference might have been obtained by chance).

Concussion symptoms

Number of symptoms.

Repeated measures ANCOVA for the number of concussion symptoms endorsed over time found no main effect for ADHD group, F(1, 109) = 2.15, p = .145, ηp² =.019). As shown in Table 2, groups were similar in number of concussion symptoms endorsed at the initial clinic visit (p = .281) and at three-month follow-up (p = .146). A main effect for time was found, with both groups endorsing fewer symptoms at three-month follow up, (F(1, 109) = 71.14, p < .001, ηp² =.548). No significant ADHD group by time interaction was found, F(1, 109) = 0.11, p = .740, ηp² =.001). A significant interaction of anxiety by time was found, F(1, 109) = 5.14, p = .025, ηp² =.045); at the initial visit, adolescents with premorbid anxiety endorsed a greater number of symptoms (M = 12.54, SD = 6.78) than those without a previous history of anxiety (M = 8.36, SD = 7.0), (p = .010). At three-month follow-up, no significant difference in number of endorsed symptoms was found between these groups (M = 2.85, SD = 3.17 vs. M = 2.23., SD = 3.72), (p = .642).

Table 2.

Number of Symptoms Reported and Total Symptom Severity Scores for ADHD and non-ADHD Groups on SCAT-5

SCAT-5 Number of Symptoms Reported
Group	Initial Visit M (SD)	Three Month Follow-Up M (SD)	Interaction Anxiety x Time	Interaction ADHD Group x Time	Main Effect Time	Main Effect Anxiety	Main Effect ADHD Group
ADHD	10.39 (7.21)	2.82 (3.99)	F1,109 = 5.140 p =.025 ηp2 = .045	F1,109 = .111 p= .740 ηp2 = .001	F1,109 = 71.139 p < .001 ηp2 = .548	F1,109 = 3.229 p = .075 ηp2 = .029	F1,109 = 2.149 p = .145 ηp2 = .019
non-ADHD	8.13 (6.94)	1.79 (3.10)
SCAT-5 Total Symptom Severity Scores
Group	Initial Visit M (SD)	Three Month Follow-Up M (SD)	Interaction Anxiety x Time	Interaction ADHD Group x Time	Main Effect Time	Main Effect Anxiety	Main Effect ADHD Group
ADHD	28.29 (29.55)	4.52 (7.54)	F1,109 = .1.989 p = .161 ηp2 = .018	F1,109 = .656 p = .420 ηp2 = .006	F1,109 = 50.062 p < .001 ηp2 = .315	F1,109 = 1.035 p = .311 ηp2 = .009	F1,109 = 1.827 p = .179 ηp2 = .016
non-ADHD	20.66 (23.86)	2.68 (5.41)
Percent Back to Normal
Group	Initial Visit M (SD)	Three Month Follow-Up M (SD)	Interaction Anxiety x Time	Interaction ADHD Group x Time	Main Effect Time	Main Effect Anxiety	Main Effect ADHD Group
ADHD	62.15 % (29.55)	93.83% (10.96)	F1,92 = 10.815 p = .001 ηp2 = .105	F1,92 = .533 p = .459 ηp2 = .006	F1,92 = 64.108 p < .001 ηp2 = .411	F1,92 = 7.329 p = .008 ηp2 = .074	F1,92 = .132 p = .717 ηp2 = .001
non-ADHD	66.29% (26.73)	96.61% (7.47)

Note: SCAT-5 Number of Symptoms Reported Range 0–22; SCAT-5 Total Symptom Severity Score Range 0–94; Percent Back to Normal Range 0% to 100%; ADHD = Attention-Deficit/Hyperactivity Disorder; η_p² = Partial Eta Squared

Symptom severity.

Analysis of total concussion symptom severity determined that both groups improved significantly over time, F(1, 109) = 50.06, p < .001, ηp² =.315). No significant difference in total symptom severity was found between groups overall (F (1, 109) = 1.83, p = .179, ηp² =.016). No significant group by time interaction was found, F(1, 109) = 0.66, p = .420, ηp² =.006). The groups were similar in reported symptom severity at the initial clinic visit (p = .260) and at three-month follow-up (p = .130).

“Back to Normal.”

Both groups reported a significantly higher percentage of “back to normal” at three-month follow-up compared with the initial visit (F (1, 92) = 64.11, p < .001, ηp² =.411). No main effect for group was seen in “percent of normal” ratings (F (1, 92) = 0.13, p = .717, ηp² =.001). Moreover, the groups were similar in “percent of normal” at both their initial clinic visit (p = .843) and at three-month follow-up (p = .108). Similar to the findings for the number of symptoms reported over time, in the analysis of “percent of normal,” a significant interaction was found for anxiety by time (F (1, 92) = 10.82, p = .001, ηp² =.105). At the initial visit, adolescents with a previous history of anxiety reported a lower percentage (M = 50.14%, SD = 24.89) compared to those without a previous history of anxiety (M = 68.88%, SD = 26.88), p = .004).

Additional analyses

Exacerbation of symptoms.

Analysis of reported exacerbation of overall symptoms by cognitive or physical activity found no significant group differences at either time point. At three-month follow-up, less than 11% of the participants in either group reported exacerbation of symptoms with cognitive or physical activity. Information about exacerbation of symptoms is provided in Table 3.

Table 3.

Exacerbation of SCAT-5 Symptoms during Recovery for ADHD and non-ADHD Groups

Visits	ADHD (n = 56)	Non-ADHD (n = 56)	p value
Initial Visit
Exacerbation of Symptoms from Physical Activity, % (n)	51.8% (29)	36.4% (20)	.171*
Exacerbation of Symptoms from Cognitive Activity, % (n)	57.1% (32)	53.6% (30)	.676*
Three-Month Follow-Up
Exacerbation of Symptoms from Physical Activity, % (n)	10.7% (6)	8.9% (5)	.893*
Exacerbation of Symptoms from Cognitive Activity, % (n)	7.1% (4)	8.9% (5)	.770*

Note: ADHD = Attention-Deficit/Hyperactivity Disorder,

^{* =}Chi-Square Analysis

Symptoms at initial visit.

Although there were no overall group differences in overall symptom reporting, a few differences between groups were found in planned analyses for the presence of individual symptoms at the initial clinic visit. At the initial visit, significantly more adolescents with ADHD reported problems with nausea (72%, n = 81 vs. 28%, n = 7, Fisher’s p = .022) and “feeling slowed down” (53.6%, n = 30 vs. 30.4%, n = 17, Fisher’s p = .021) compared to those without ADHD. No other significant differences in individual SCAT-5 symptoms were found at either initial visit or three-month follow-up.

Discussion

In general, our results did not support the hypotheses that adolescent athletes with premorbid ADHD would endorse more symptoms and greater symptom severity and would have poorer performance on ImPACT cognitive assessments than those without ADHD. At both initial visit and three-months post-concussion, participants who reported premorbid ADHD endorsed a similar overall number of symptoms and symptom severity level as non-ADHD counterparts carefully matched by age, sex, ethnicity/race, and days post-injury. All participants, both ADHD and non-ADHD improved significantly over time. Time was the only variable demonstrating a medium to large effect size (Richardson, 2011) for symptom endorsement (ηp² = .315), symptom severity (ηp² = .548), and “percent of normal” over time (ηp² = .411). However, planned analyses of individual symptoms revealed that significantly more athletes with ADHD reported problems with nausea (72% vs. 28%) and “feeling slowed down” (53.6% vs. 30.4%) at initial visit compared to those without ADHD, which may be indicative of between-group differences in anxiety history, as premorbid anxiety has been shown to be associated with increased self-reporting of post-injury nausea (Kent et al., 2020). In our sample, participants with ADHD did not report more trouble sleeping than those without ADHD at initial visit (34%, n = 22 vs. 29%, n = 16) or three-month follow-up (21%, n = 12 vs. 13%, n = 7), or more sensitivity to light at initial visit (63%, n = 35 vs. 61%, n = 34) or three-month follow-up (7%, n = 4 vs. 5%, n = 3), as was reported by Cook et al. (2020). Further, a history of ADHD did not appear to adversely affect SRC recovery, as the two matched groups reported a significant decrease in symptoms across a 3-month follow-up period, with similar symptom severity ratings at follow-up.

Surprisingly, despite a self-reported history of ADHD, athletes with ADHD in our sample did not report significantly more difficulty with concentration post-concussion compared to the control group. At initial visit, 61% (n = 34) of the adolescent athletes with ADHD reported difficulty with concentration compared with 52% (n = 29) of those without ADHD; at three-month follow-up, 23% (n = 13) of the athletes with ADHD reported concentration difficulties compared with 18% (n = 10) of those without ADHD. Several factors may account for this absence of group effect. Because problems with concentration are common in the initial short-term period after concussion, it may be that most concussed adolescent athletes experience disrupted concentration to a degree that interferes with daily functioning that is not unlike the chronic experiences of adolescents with ADHD. Furthermore, adolescents with ADHD may not perceive post-concussion disruption any worse than they have chronically experienced, as was suggested by Cook et al. (2020). Viewing the baseline data from Cook et al. (2020), more than 25% of adolescent athletes with ADHD may experience chronic sleep disturbance and fatigue, along with difficulty concentrating. Given that they report these symptoms at baseline, we do not know how they perceive and report symptoms such as these after concussion. It may be that adolescent athletes with ADHD experience concentration difficulties at a higher rate at baseline, and therefore the relative increase in concentration-related symptoms experienced post-injury may be perceived as less noticeable. Instead, athletes with ADHD may view concentration difficulties as a regular part of daily life, leading to diminished concern about these issues. This may prompt an underreporting of experienced concentration issues, as athletes with ADHD may be less inclined to attribute experienced concentration issues as an effect of the injury. Furthermore, previously developed coping strategies used to manage concentration difficulties could decrease the salience of these post-injury symptoms.

Limitations

A factor that complicates interpretation of findings in our study, as in other studies, is that we did not collect information about current use of medication for ADHD. In a previous investigation of non-concussed youth, those with ADHD reported higher somatic symptom scores and performed worse on CNS Vital Signs, a computerized neurocognitive battery, compared with healthy youth without ADHD, but only when they were not taking medication; on medication, there were no group differences (Littleton et al., 2015). Additionally, small but significantly lower ImPACT scores were obtained by adolescent athletes with ADHD who were not taking medication, especially for visual-motor speed, compared with adolescent athletes with ADHD taking medication and controls (Cook et al., 2017). Immediately after concussion, measured changes in cognitive scores from baseline on ImPACT were worse for adolescents with ADHD not taking medication compared with participants with ADHD taking medication, and this difference also was observed at 7-day follow-up (Ali et al., 2021). However, Cook et al. (2020) found no difference in recovery time between adolescent athletes with ADHD who were taking medication versus those who were not. Furthermore, Gardner et al. (2017) reported that children and adolescents with ADHD who were taking stimulant medication endorsed more symptoms at baseline than did the participants with ADHD who were not taking medications. Because it was difficult to ascertain the validity of information obtained from self-report about medication and dosage both at time of injury and during recovery, these data were not collected in our study. Thus, medication use may have affected our results, and we are not able to contribute to this body of literature. Furthermore, our database does not include details about treatment/rehabilitation subsequent to the concussion, and we could not include this as a variable.

An additional limitation is that self-report data did not appear to provide reliable information about types of ADHD (Inattentive vs. Hyperactive/Impulsive vs. Combined) in our participants, so this variable could not be investigated. The absence of these data may limit conclusions that can be drawn about the impact of concussion in adolescents with specific subtypes of ADHD. Sex is another factor that has been investigated in concussion research, but not as it differentially affects athletes with ADHD. The proportion of females in any concussed ADHD sample may bias findings, since poorer concussion outcomes have been reported for females with ADHD (Lambert et al., 2021). However, in matching the two groups by sex, we attempted to account for any effect of sex upon our outcomes, although sex differences were not measured directly. Interpretation of our results may also be limited by potential bias involved in utilizing a sample of participants who sought care at specialty concussion clinics. Various factors may influence a family’s choice of health care services after concussion, including accessible medical insurance or parents’ emotional reaction following concussion. We did not have access to that information, which may limit generalizability. We also were unable to add to our analysis the specific concussion treatment regimens prescribed by providers. However, the strength of our study is the use of a carefully matched control group to reduce any potential influence of age, sex, ethnicity/race, and days since injury upon the comparison between concussed athletes with and without ADHD.

Future directions

Future research should seek to clarify discrepancies in the literature related to potential factors such as participants’ use of medication for their ADHD, and additionally further address the influence of sex and socioeconomic factors. Defining participants by ADHD subtype may also yield important information. Better methods of obtaining self-reported symptoms in children and adolescents with ADHD also need to be investigated to improve accuracy of symptom reporting as a result of a concussion event rather than a chronic condition. Finally, with the introduction of the revisions to the SCAT-5 (i.e., Child Sport Concussion Office Assessment Tool-6©; Patricios et al., 2023), there is the potential to examine newer methods not included in the ImPACT and SCAT-5. These address evaluation of symptoms in relation to cervical spine injury (Cheever, et al., 2016), orthostatic vitals (Sas, et al., 2024), and vestibular/ocular-motor functioning (Anzalone et al. 2017).

Although Iverson et al. (2017) noted that there was no significant risk for negative outcomes imposed by premorbid ADHD, they nevertheless concluded their review by suggesting that youth with ADHD might require more careful attention to their return-to-learn plans. Other published research (e.g., Mautner et al., 2015) also suggests that the presence of premorbid ADHD in concussed adolescents may need to be considered in decision-making regarding timing of return to normal activities. In general, determining the degree of short-term functional impairment for the adolescent with ADHD and the extent of the adolescent’s recovery depends upon clinicians’ understanding of what to expect when premorbid ADHD is present. Our results generally support the statements from Iverson et al. (2017) and Cook et al. (2021) that premorbid ADHD does not appear to pose a specific risk for poor recovery in concussed children and adolescents. However, in a clinical setting, it would be unwise to apply nomothetic data and ignore the individual experiences of the patient. Cook et al. (2021) remarked that assessing post-concussion recovery in youth with ADHD can be difficult because of the presence of various clinical symptoms that are reported in the absence of concussion. The range of possible outcomes for youth with ADHD needs to be carefully considered in evaluating post-concussion recovery, and individual differences addressed in treatment planning and return-to-learn and/or play decisions. Symptoms of ADHD, in general, have the potential to hinder academic, social, and personal functioning, and concussion may produce at least an additional short-term burden, even if it is no worse than that experienced by adolescent athletes without ADHD. In adolescents with ADHD, ongoing problems created by their baseline ADHD symptoms may have the potential to interact with their psychological state. In particular, based on our findings, a history of anxiety may produce greater symptom burden or more challenges during recovery from concussion, requiring additional clinical attention. Taken together, it appears that clinicians and parents should be able to approach the evaluation and management of concussion in adolescent athletes with and without ADHD similarly, with continued attention toward individual differences as adolescents return-to-learn and/or play.