Absent or Hidden? Hyperactivity in Females With ADHD

Abstract

Objective:

This study aimed to objectively assess signs of hyperactivity in adults suspected of having ADHD, addressing potential sex bias in diagnosis.

Methods:

About 13,179 (49% female) adults with an average age of 33 years with ADHD and 1,910 (41% female) adults with an average age of 36 years without ADHD were included. Motor activity was measured using the Quantified Behavioral Test, analyzing “provoked,” and “basal” activity. Sex by group differences were analyzed using analysis of variance.

Results:

Results showed significant ADHD effects on the basal and provoked activity measures, while sex effects were only notable for provoked activity. Males, irrespective of diagnosis, exhibited higher provoked activity than females, while both sexes with ADHD displayed approximately twice the basal activity and about three times the provoked activity compared to their respective sex controls.

Conclusion:

These findings suggest that females with ADHD suffer equally from hyperactivity compared to males, challenging the notion of a sex-dependent presentation of hyperactivity. This may lead to more accurate and timely diagnoses, reducing ADHD-related burdens and comorbidities in females.

Keywords

adult ADHD gender differences hyperactivity QbTest

ADHD is recognized as a disorder present across the lifespan (Faraone et al., 2021; Franke et al., 2018; Kooij et al., 2019) and is characterized by persistent patterns of inattention, hyperactivity, and impulsivity. Depending on the severity, individuals with ADHD present with different levels of impairment in their development and daily functioning (Franke et al., 2018). The DSM-V divides ADHD into three primary presentations (previously referred to as subtypes); predominantly inattentive, predominantly hyperactive/impulsive or combined.

Historically, ADHD was clinically regarded as a disorder that mainly affected boys (Arnold, 1996; Biederman et al., 2002; Faraone et al., 2015; Gaub & Carlson, 1997; Martin, 2024; Ramtekkar et al., 2010; Willcutt, 2012, Zakariyah, 2023). Although the male to female ratio has declined over time, reflecting an increased awareness that ADHD affects females as well, clinically referred patients are still more likely to be male (Rucklidge, 2010). This could be related to the fact that in the societal view ADHD is often simplified and related to the noticeable hyperactive symptoms, which anecdotally are more explicit in males (Holthe & Langvik, 2017; Mueller et al., 2012). This view is consistent with parent- and teacher-rated scales indicating that girls with ADHD exhibit less socially disruptive symptoms related to hyperactivity, and show more signs of inattention compared to boys (Arnett et al., 2015; Carbonneau et al., 2021; Slobodin & Davidovitch, 2019). Therefore, girls with ADHD are more likely to be overlooked and less likely to be referred for ADHD diagnostics (Faraone et al., 1998; Gaub & Carlson, 1997; Gershon & Gershon, 2002; Hinshaw et al., 2022; Mowlem et al., 2019; Quinn & Madhoo, 2014; Ramtekkar et al., 2010) and when girls are diagnosed, they are more often diagnosed with predominantly inattentive presentation (Ayano et al., 2020; Biederman et al., 2002; Willcutt, 2012).

However, the disproportional prevalence of ADHD between genders during childhood and adolescence does not continue into adulthood, where the male-to-female ratio is more equally distributed (Biederman et al., 2004; Bitter et al., 2010; Friedrichs et al., 2012; Solberg et al., 2018). This difference in the prevalence ratios across the lifespan may be explained by underdiagnosis and thereby undertreatment of females with ADHD during their childhood or adolescence (Nøvik et al., 2006; Rucklidge, 2010), which can be attributed to referral or diagnostic bias rather than a fundamental difference in expression of ADHD in men and women (Williamson & Johnston, 2015). For example, symptoms of hyperactivity in females may be missed when compared to the hyperactivity symptoms presented by males. In fact, females tend to be diagnosed later in life and are less frequently prescribed medication for ADHD compared to males (Agnew-Blais et al., 2016; Mowlem et al., 2019; Rucklidge, 2010; Solberg et al., 2018).

While the psychopathology of ADHD is currently assumed to consist of three core symptoms, being hyperactivity, impulsivity, and inattention, various theoretical perspectives hypothesize that excessive motor activity and impaired executive functioning in ADHD result from underlying inhibitory deficits. These deficits include the inability to halt pre-potent or ongoing responses and difficulties with interference control, which is the capacity to exclude non-goal-directed information (Barkley, 1997). Alternatively, excessive motor activity may stem from compensatory efforts to activate arousal mechanisms. These efforts aim to reach an optimal stimulation threshold to meet the demands of attention, working memory tasks, or delay of gratification (Dekkers et al., 2021; Kofler et al., 2016; Sonuga-Barke, 2002). Both perspectives have gained support from studies showing that ADHD-related signs of hyperactivity become most evident under environmental conditions that combine high cognitive demands and low external stimulation, such as Continuous Performance Tests (CPT; Burley et al., 2022; Kofler et al., 2016). Including such objective measures of motor activity during the diagnostic assessment, in addition to subjective assessments, may reduce the gender bias by allowing direct comparison to the respective sex controls (Williamson & Johnston, 2015). The QbTest is an FDA approved aid for the clinical assessment of ADHD and provides an objective measure of ADHD associated hyperactivity. The QbTest is a Continuous Performance Task that assesses motor activity, which typically increases during the task performance (duration 20 minutes) as a result of continuous cognitive demand and an associated competition with and ultimately decline of behavioral self-regulation (Burley et al., 2022; Caswell et al., 2013; Dekkers et al., 2021; Ferguson et al., 2023; Friedman & Miyake, 2017; Valori et al., 2022). Motor activity during a CPT has been consistently found to be higher in patients with ADHD relative to “healthy” individuals (Dekkers et al., 2021; Kofler et al., 2016; Lis et al., 2010; Murillo et al., 2015; Teicher et al., 2012). However, the main output of the QbTest is a sex adjusted index score, and as such, not suitable for comparing absolute differences between sexes. Moreover, the index score adjustment is proprietary information of QbTech and is not disclosed. Therefore, we used the untransformed motor activity data and defined two outcome measures: “basal activity”—the motor activity in the first quarter as a measure of everyday or unprovoked motor activity, and “provoked activity”—the increase of motor activity in the fourth and last quarter of testing. To test our hypothesis that females with ADHD show comparable signs of hyperactivity to males with ADHD, we compared both “basal activity” and “provoked activity” between adult males and females with and without ADHD.

Methods

Data Source

Data from patients that underwent diagnostic assessment between 1 March 2013 and 1 February 2020 were obtained from the clinical electronic health records (EHR) of ADHDcentraal. ADHDcentraal is a multicenter mental health care facility specialized in the diagnostics and treatment of adult ADHD in the Netherlands. ADHDcentraal operates in the second line of mental health care, to which patients are referred by a general practitioner (GP) when ADHD is suspected. This retrospective study was approved by an Institutional Review Board. Patients were eligible for inclusion if they were older than 17 years at the time of diagnostic assessment and had completed the adult version of the Quantified behavior Test (QbTest) as part of the diagnostic process. Patients younger than 17 years or older than 61 years of age were not eligible because the QbTest is validated up to the age of 61 years (QbTech, 2018).

Study Sample

The dataset contains data from 15,934 patients. Patients were grouped based on the diagnostic outcome as “ADHD” or “NoADHD.” The diagnostic procedures were performed by an experienced clinical team composed of a psychiatrist, a nurse practitioner, and a psychologist, who assessed each patient utilizing the DSM-5 criteria for ADHD. The diagnostic protocol consisted of a structured psychiatric interview, including mental status examination, a Diagnostic Interview for ADHD in adults (DIVA 2.0) and a QbTest (QbTech, 2018). All participants provided informed consent. Individuals that did not meet the clinical DSM-5 criteria for ADHD were re-referred to the GP.

Data Collection

Demographic information, including age and sex, and the ADHD diagnosis with its presentation type were obtained from the Electronic Health Record (EHR). The objectified motor activity (i.e., QbTest results) was collected from the QbTech database.

QbTest

The QbTest is a Continuous Performance Test (Epstein et al., 2001; Reh et al., 2015) combined with a Motion Tracking System (MTS). The QbTest provides relevant data used for assessing the three core symptoms of ADHD: inattention, hyperactivity, and impulsivity. The QbTest is a validated, CE marked and FDA-approved aid for clinical assessment with a high ability to differentiate between the diagnosis ADHD (sensitivity 79-96%) and no ADHD in children and adults (specificity 81-94%; Ulberstad, 2012).

During the QbTest, patients perform a CPT task on a computer for 20 minutes. A stimulus that matches the previous stimulus is considered a target, while a non-matching stimulus is a non-target. In total, 600 stimuli are shown at a 25% target ratio. The participant is instructed to respond to a target by pressing a clicker with the dominant hand’s thumb and to inhibit responses to non-targets.

The MTS consists of a reflector attached to a headband placed on the forehead of the participant and a high-resolution infrared camera that captures the head movements, representing motor activity during the QbTest. The QbTest measures four parameters of motor activity, which are converted into an index score QbActivity. The four different parameters consist of: (1) the percentage of time the reflector moved more than one cm per second (Time Active), (2) the distance traveled in meters by the reflective marker (Distance), (3) the surface covered in cm² (Area), and (4) the number of changes in the position of more than one mm (Micro Events). The parameters are considered as signs of hyperactivity (Fuermaier et al., 2018; Lee et al., 2021; Teicher et al., 2012) and clinically relate to hyperactivity as follows; “Time Active” ensures that movements due to drifting and breathing will not be registered, “Distance” reflects how far (in meters) the participant has moved cumulatively during the test, “Area” reflects the vividness of the movements, and Micro Events quantifies how active the participant was during testing. The QbTest results of each parameter are divided by QbTech into four quarters, each representing 5 minutes (e.g., Micro Events: MEv1; MEv2; MEv3; and MEv4). The last 10 minutes observed for each parameter are weighted differently by a patented algorithm and transformed into the QbActivity index score (i.e., z-score) using a normative database matched for age and gender. According to QbTech a QbActivity index score of <1 is considered as normal, between 1 and 1.5 as slight atypical, and >1.5 as atypical and gives cause for clinical concern.

Outcome Measures

Since QbActivity is transformed using a normative database matched for age and gender, the QbActivity score is unsuitable for analyzing sex effects. Hence, raw data was inquired from the QbTech database and used for analysis. From the four parameters, Micro Events has the highest relative weight in the QbActivity index score calculation (Ulberstad, 2012), and we thus focused on Micro Events as main outcome measure. The results for the other parameters (i.e., Time Active, Area, and Distance) are reported in the Supplemental Material information.

As the CPT maximal discriminative power is in the last 5 minutes of testing, due to the expected trade-off between increasing cognitive load of maintaining task performance and behavioral inhibition, the change in Micro Events from baseline (i.e., MEv4–MEv1) is reported as “provoked activity.” The initial 5 minutes of testing are reported as “basal activity” and reflects motor activity without a high cognitive load, and as such, is considered a measure of everyday or unprovoked activity.

Statistical Analysis

For our primary analyses, we compared sex and the “NoADHD” and “ADHD” groups by means of a 2 × 2 analysis of variance (using R, version 4.2.1.) for the defined outcome measures. Degrees of freedom were corrected according to Greenhouse and Geisser (1959). An alpha of <.05 was considered significant and effect sizes using the partial eta squared ( $η_{p}^{2}$ ) were reported as small ( $η_{p}^{2}$ = .01), medium ( $η_{p}^{2}$ = .06), or large ( $η_{p}^{2}$ = .14; Cohen, 1992). Post hoc t-tests were conducted in case of a significant main effect. Secondly, we performed a chi-square test of independence to analyze the relation between sex and diagnosis to assess the difference in referrals between sexes, and the relation between sex and the different presentations of ADHD (i.e., combined, predominantly hyperactive/impulsive, predominantly inattentive, and Other Specified).

Results

Characteristics

From the total database, data of N = 15,089 participants were included for this study. In total, data of N = 845 (0.05%) participants were excluded based on the standardization procedures of outlier analysis by QbTest (Ulberstad, 2012).

All characteristics from the included sample are summarized in Table 1. N = 13,179 (87%) were clinically diagnosed with ADHD. Sex was equally distributed in the ADHD group, but not in the NoADHD group which included significantly fewer females (41%, χ² = 36.23, p < .001). Within the ADHD group most participants were considered to have ADHD combined presentation, followed by predominant inattentive and hyperactive/impulsive presentations. Sex had a significant effect regarding the ADHD presentations, where males were associated with the predominantly hyperactive/impulsive presentation (χ² = 23.49, p < .001).

Table 1.

Characteristics.

	ADHD			NoADHD
	Male	Female	p	Male	Female	p
No. (%)	6,740 (51.1)	6,439 (48.9)		1,118 (58.5)	792 (41.5)	<.001*
Age (Mdn, range)	33.1 (17.1–60.8)	32.8 (17.4–60.9)	.023*	36.5 (17.2–60.8)	36.4 (17.5–60.9)	.743
DSM Diagnosis no. (%)			<.001*
Combined presentation	5,134 (39)	4,971 (37.7)
predominately inattentive pres.	836 (6.3)	870 (6.6)
pred. hyperactive/impulsive pres.	622 (4.7)	456 (3.5)
Not other specified	148 (1.1)	142 (1.1)
QbActivity (M ± SD)	2.1 ± 1.1	2.1 ± 1.1	.217	0.7 ± 1.0	0.9 ± 1.0	<.001*

Note. QbActivity is an output index score returned by the Quantified behavior Test (QbTest) which is an FDA-approved aid for the clinical assessment of ADHD and provides an objective measure of ADHD-associated hyperactivity. A QbActivity index score of <1 is considered normal, between 1 and 1.5 slightly atypical, and >1.5 is atypical and gives cause for clinical concern.

Significant at p < .05.

Within the ADHD group, both males and females presented a comparable QbActivity index score above the clinical threshold. Participants within the NoADHD group presented scores within the normal range.

Basal Activity

The “basal activity” is depicted in Figure 1 and summarized in Table 2. A significant main effect of group was found (F(1, 15,085) = 992.9, p < .001, medium effect size ( $η_{p}^{2}$ = .06)) and adults with ADHD showed an increased “basal activity” (218%) compared to adults with ADHD.

Figure 1.

The averages of the basal and provoked activity (along with the SEM) for adults with ADHD and their gender controls. Basal activity reflects the initial 5 minutes of motor activity as a measure of everyday or unprovoked motor activity. Provoked activity reflects the increase in motor activity in the last 5 minutes of testing as a measure of behavioral disinhibition. Micro Events measures the number of movements >1 mm.

Table 2.

Mean and Standard Deviation (SD) of the Basal and Provoked Activity for Males and Females With Attention-deficit/Hyperactivity Disorder (ADHD) and Their Sex Controls That Did Not Meet Clinical Criteria for Diagnosis (No ADHD) With Results of 2 × 2 Analysis of Variance With Factor “Group” and “Sex.”.

Sex	NoADHD (n = 1,910)	ADHD (n = 13,179)	ANOVA	p	$η_{p}^{2}$ ^a
Sex	M ± SD	M ± SD	Effect	p	$η_{p}^{2}$ ^a
Micro events (count)
Basal activity			Group	<.001*	.06
M	708.7 ± 471.7	1,614.8 ± 1,196.5	Sex	—
F	786.0 ± 560.0	1,610.5 ± 1,186.2	Group × sex	—
Provoked activity			Group	<.001*	.04
M	419.0 ± 607.1	1,108.8 ± 1,149.0	Sex	<.001*	.02
F	289.9 ± 535.0	759.2 ± 1,018.0	Group × sex	<.001*	<.01

Note. Basal activity reflects the initial 5 minutes of motor activity as a measure of everyday or unprovoked motor activity. Provoked activity reflects the incremental increase in motor activity in the last 5 minutes of testing compared to the first 5 minutes. Micro events are the number of changes in the position of more than one mm and quantifies the motor activity during a Continuous Performance Test.

Effect size is indicated by partial eta squared.

Significant at p < .05.

Provoked Activity

The means and SD of the provoked activity for group and sex are summarized in Table 2 and shown in Figure 1. Significant main effects for group by sex (F(1, 15,085) = 18.39, p < .001, $η_{p}^{2}$ < .01), group (F(1, 15,085) = 550.86, p < .001, $η_{p}^{2}$ = .04), and sex (F(1, 15,085) = 363.33, p < .001, $η_{p}^{2}$ = .02) were found.

Males with ADHD exhibited greater “provoked activity” than females with ADHD (t = 18.51, p < .001), while males without ADHD also showed greater “provoked activity” compared to females without ADHD (t = 4.91, p < .001).

When comparing “provoked activity” to their respective sex control group, males with ADHD exhibited higher (265%) “provoked activity” than males without ADHD (t = 30.09, p < .001). A similar increase in “provoked activity” (262%) was found for females with ADHD compared to females without ADHD (t = 20.53, p < .001).

Discussion

To our knowledge, this is the first study that shows that females with ADHD exhibit comparable signs of hyperactivity as males with ADHD when compared to their respective sex controls. In line with our hypothesis, basal activity was comparable between males and females with ADHD. Although males did show higher provoked activity compared to females, this effect was independent of group, that is, when compared to their respective sex, both males and females with ADHD showed roughly 260% higher provoked activity. Thus, while females, regardless of diagnosis, showed less provoked activity when compared to males, this refers to sex differences, and not necessarily a sex specific presentation of ADHD. In other words, when females with ADHD are compared to female controls, the increase in motor activity, and by inference the burden of hyperactivity under cognitively demanding situations, is comparable to that of males. These findings align with previous reports that females may have more robust behavioral self-regulation mechanisms and may be more inclined to conform to socially accepted standards (Else-Quest et al., 2006; Franklin et al., 2018; Petersen & Grahe, 2012), which in turn may result in masking hyperactivity (Young et al., 2020). Thus, the clinical perspective that the diagnosis of ADHD may be sex-dependent, that is, males are more likely to present hyperactive symptoms while females are more likely to present inattentive symptoms, is likely an artefact of comparing females to males, rather than indicating a variance in the severity or burden (Arnett et al., 2015; Faheem et al., 2022; Robison et al., 2008). This may explain the widespread societal labeling and (mis)assumption that in males the hyperactive/impulsive presentation predominates, while in females the inattentive presentation is more common, even leading to a different (incorrect) label of ADD (Attention Deficit Disorder).

Our findings that more males than females did not meet the clinical criteria for diagnosis, indicates that males were more likely to be suspected of having ADHD and thus more easily referred, and males were also significantly more often diagnosed with the predominantly hyperactive/impulsive presentation underscores this conclusion. We suggest that this is not a sex specific presentation at all, but rather a clinician bias, where male hyperactivity is perceived as the norm, and thus females are perceived as less hyperactive, or more inattentive.

The less overt presentation of motor activity may come at a considerable toll, as females manifest a higher prevalence of internalizing comorbidity compared to males (Faheem et al., 2022; Lau et al., 2021; Solberg et al., 2018), whereas males exhibit more disruptive and externalizing comorbidity (Abikoff et al., 2002; Biederman et al., 2004; Gaub & Carlson, 1997; Ghanizadeh et al., 2008; Jackson & King, 2004; Levy et al., 2005). The less disruptive and overt presentation of females with ADHD compared to males with ADHD is probably clinically relevant as it may be related to the fact that females with ADHD are less likely to be referred for ADHD diagnostics (Agnew-Blais et al., 2016; Faraone et al., 1998; Gaub & Carlson, 1997; Gershon & Gershon, 2002; Hinshaw et al., 2022; Mowlem et al., 2019; Nøvik et al., 2006; Quinn & Madhoo, 2014; Ramtekkar et al., 2010; Rucklidge, 2010). Delaying or even missing an ADHD diagnosis can have long lasting implications in self-perception and well-being that persist into adulthood (Attoe & Climie, 2023) and increase the risk of developing other comorbid psychiatric disorders that are associated with ADHD (Dalsgaard et al., 2015; Quinn & Madhoo, 2014). Thus, including objective measures of (hyper)activity in addition to the subjective assessment of ADHD may reduce potential bias and improve ADHD assessment in females. Furthermore, changing both the societal view and clinical understanding of the presentations of ADHD in both females and males is also important because outdated terms like ADD underestimates the severity, burden and impairments stemming from hyperactivity in ADHD, irrespective of gender.

Limitations

Our main limitation is the uneven group size, with the ADHD group representing 87% of the total sample, and the lack of additional information regarding the diagnosis of the participants in the NoADHD group. However, considering that our controls consisted of adults suspected of having ADHD who did not meet the clinical criteria, the results of this study are more likely to be an underestimation of the true effect size.

Furthermore, we acknowledge that motor activity is a very complex function, in which there are almost infinite multidimensional position changes conceivable (Teicher et al., 1996). Although we analyzed all available activity measures returned by QbTech (see Supplemental Materials) we did not compare the motor activity measures to other measures that assessed the severity of hyperactivity in ADHD (e.g., the Diagnostic Interview for ADHD in adults—DIVA) or looked for correlations with the other core symptoms of inattention and impulsivity. To better understand the underlying mechanisms of excessive motor activity and impaired executive functioning in ADHD, future studies would benefit by combining objective measures of motor activity with measures for cognitive control, inhibition, and arousal, in different settings. However, as we assume that the core symptoms of inattention and impulsivity are likely to correlate with hyperactivity via a common mechanism of impaired inhibition, we do not expect marked variance between these core symptoms on a group level.

In summary, we show that males and females with ADHD both exhibit clinically relevant signs of hyperactivity. Although males with ADHD showed higher “provoked activity” than females with ADHD, both sexes showed a comparable increase in “provoked activity” compared to their respective sex controls and as such are likely equally impaired by the burden of hyperactivity. This is clinically relevant because women with ADHD are less recognized as hyperactive, and thus, referred less, more often misdiagnosed, or diagnosed later in life, and less likely to be prescribed medication for ADHD. By acknowledging the hyperactivity severity in females with ADHD and challenging the existing diagnostic framework, more accurate and timely diagnoses and treatment for females with ADHD may be achieved.

Supplemental Material

sj-docx-1-jad-10.1177_10870547241273152 – Supplemental material for Absent or Hidden? Hyperactivity in Females With ADHD

Supplemental material, sj-docx-1-jad-10.1177_10870547241273152 for Absent or Hidden? Hyperactivity in Females With ADHD by Ravian Wettstein, Valentina Navarro Ovando, Esra Pirgon, Jeroen Kroesen, Karl Wettstein, Hans Kroesen, Ron Mathôt and Glenn Dumont in Journal of Attention Disorders

Footnotes

Acknowledgements

We are extremely grateful to all adults that took part in our research.

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: One of the co-authors, K. Wettstein, is a shareholder in ADHDcentraal, which may be perceived as a potential conflict of interest related to this research. ADHDcentraal was not involved in the design, analysis, or reporting of this study. The remaining authors declare no conflicts of interest.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Ravian Wettstein

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Ravian Wettstein is a PhD candidate at the Department of clinical pharmacology at Amsterdam University Medical Centers, Amsterdam, The Netherlands, as well as a physician at ADHD centraal, the Netherlands.

Valentina Navarro Ovando is a PhD candidate at the Department of clinical pharmacology at Amsterdam University Medical Centers, Amsterdam, The Netherlands.

Esra Pirgon is a PhD candidate at the Department of clinical pharmacology at Amsterdam University Medical Centers, Amsterdam, The Netherlands, as well as a junior research assistant at ADHDcentraal, The Netherlands.

Jeroen Kroesen is the chief of data science and analytics at ADHDcentraal, The Netherlands.

Karl Wettstein is a psychiatrist and the Medical Director at ADHDcentraal, The Netherlands.

Hans Kroesen is a retired physician assistant with extensive experience in the field of ADHD and previously served as the Director at ADHDcentraal, The Netherlands.

Ron Mathôt is a hospital pharmacist as well as a professor in Clinical Pharmacology at Amsterdam University Medical Centers, The Netherlands.

Glenn Dumont is an associate professor in Clinical Pharmacology at Amsterdam University Medical Centers, The Netherlands, as well as a senior research advisor at ADHDcentraal, The Netherlands.

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