Neuropsychological Deficits in Adult ADHD: Evidence for Differential Attentional Impairments,Deficient Executive Functions,and High Self-Reported Functional Impairments

Abstract

Objective: This study is aimed to investigate neuropsychological deficits in adult ADHD. Method: Neuropsychological deficits in terms of executive functions, divided, selective, and sustained attention, were investigated in a group of adults with ADHD using a series of neuropsychological tests as well as electroencephalography (EEG). Subjective ratings of everyday life attention and memory problems were also collected. Results: Adults with ADHD showed impairments in executive functions, divided attention and sustained attention, compared with adult controls. Performance on selective attention tasks in adults with ADHD was instead no different from control participants’ performance. EEG results confirmed neuropsychological findings by showing a selective impairment on P3 event-related potential (ERP) amplitude indicative of sustained attention deficits. Higher subjective ratings of everyday attentional and memory problems were also found in the ADHD group compared with the control group. Conclusion: This pattern of results suggests differential impairments of attentional skills. Impaired executive functions and higher subjective functional impairments were also found.

Keywords

adult ADHD neuropsychological functioning sustained attention selective attention

Introduction

ADHD is a neuropsychiatric condition characterized by difficulties in attention, hyperactivity, and impulsivity. Although onset is usually during childhood, research suggests that ADHD can persist into adulthood in some cases (Faraone, Biederman, & Mick, 2006; Kessler et al., 2006). Prevalence estimates vary because of differences in research methodology such as differing cutoff scores and diagnostic criteria (Wender, Wolf, & Wasserstein, 2001), although both longitudinal studies (Hart, Lahey, Loeber, Applegate, & Frick, 1995) and prospective studies (Wilens et al., 2009) suggest that 30% to 60% with childhood ADHD show symptoms into adulthood. Adulthood ADHD has significant consequences; many tend to have lower socioeconomic status and higher rates of unemployment (Sobanski et al., 2007), and suffer comorbid disorders such as antisocial, addictive, and mood disorders (Biederman et al., 2006). Given these personal costs, and the high cost to society in terms of treatment (Matza, Paramore, & Prasad, 2005) and higher criminality rates (Fischer et al., 2007), effective intervention is critical.

Currently, the most common treatment for ADHD is the administration of psychostimulants which have disadvantages such as side effects, high costs for long-term prescriptions, and limited effectiveness, especially in adults (Asherson, 2005). Cognitive and behavioral treatments have not been shown to be consistently effective and do not specifically target the underlying neuropsychological deficits in ADHD (Toplak, Connors, Shuster, Knezevic, & Parks, 2008).

This study aims to investigate the neuropsychological deficits underlying ADHD to develop new and effective interventions, specifically focusing on sustained and selective attention and executive function deficits. There has been previous research investigating these neuropsychological functions in ADHD, which will be presented here, but the literature has been mainly focused on children and yielded inconsistent results, especially regarding selective attention and executive dysfunction. Therefore, this study aims to address this gap in the adult ADHD literature and clarify previous findings.

First, deficits in sustained attention, the ability to maintain attention to a stimulus over an extended period of time (DeShazo Barry, Klinger, Lyman, Bush, & Hawkins, 2001), have been documented in adults with ADHD (Tucha et al., 2017). Adults with ADHD perform more poorly on tasks designed to assess sustained attention in comparison with controls, indicated by a higher error rate and increased reaction times (RTs; Schoechlin & Engel, 2005; Tucha et al., 2008). Neuroimaging and electroencephalography (EEG) studies and research using different modalities provide further evidence of a positive association between ADHD and sustained attention deficits. Functional magnetic resonance imaging (fMRI) shows that adults with ADHD have deficits in lateral frontostriatal and superior parietal regions associated with sustained attention (Cubillo, Halari, Smith, Taylor, & Rubia, 2012). EEG studies, although mainly carried out in children with ADHD, have also found reduced P3 components in those with ADHD, which are associated with attentional deficits (Loiselle, Stamm, Maitinsky, & Whipple, 1980; van Leeuwen et al., 1998). The P3 component has been associated with attentional allocation, as neuropsychological tasks that produce the largest correlation between performance and the waveform assess attentional processes (Polich & Kok, 1995).

Impairments in executive function have also been found in adults with ADHD. Executive functions are defined as neurocognitive processes that maintain an appropriate problem-solving set to attain a future goal (Welsh & Pennington, 1988) and include processes such as verbal fluency, working memory, planning, and problem solving. Although much of past research showing those with ADHD have executive function deficits has been based on children (Shallice et al., 2002), adult studies replicate these findings (Hervey, Epstein, & Curry, 2004). Meta-analyses of studies on adults with ADHD found that they were significantly impaired on executive tasks in comparison with controls, with effect sizes in the medium range for the majority of deficits (Boonstra, Oosterlaan, Sergeant, & Buitelaar, 2005; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). Imaging studies suggest that the abnormalities in the prefrontal region found in those with ADHD (Castellanos et al., 1996) are associated with executive dysfunction, as studies of individuals with traumatic brain injury (TBI) in the frontal lobe exhibit a similar pattern of impairments (Gioia, Isquith, Kenworthy, & Barton, 2002). Although, again, some research has suggested that executive function deficits are not consistently found in those with ADHD (Sergeant, Geurts, & Oosterlaan, 2002; Van Mourik, Oosterlaan, & Sergeant, 2005), some of these studies (Van Mourik et al., 2005) were based on the Stroop task which may not be the most accurate measure of interference and inhibition (Van Mourik et al., 2005).

On the contrary, there is a lack of studies investigating selective attention in adults with ADHD, and findings from studies of both children and adults have been inconsistent. Selective attention is defined as the ability to focus attention on relevant stimuli while ignoring irrelevant stimuli at any given point in time (DeShazo Barry et al., 2001). Studies comparing children with ADHD with controls have often found no difference in performance on selective attention tasks (Booth et al., 2005; Van der Meere & Sergeant, 1988). However, other research suggests that children with ADHD have a greater performance deficit than controls on both visual and auditory selective attention tasks when influenced by distractors (Brodeur & Pond, 2001), a finding supported by an EEG study showing that the component response associated with selective attention was lower in children with ADHD in comparison with controls while performing selective attention tasks (Satterfield, Schell, Nicholas, Satterfield, & Freese, 1990). The few studies carried out with adults with ADHD have similarly contradictory findings. One study showed that adults diagnosed with three different subtypes of ADHD all displayed deficits in selective attention in comparison with controls (Tucha et al., 2008), a finding supported by previous research (Dinn, Robbins, & Harris, 2001). However, another study assessing 439 adults with ADHD using neuropsychological tests and informant ratings suggested that any selective attention deficits apparent in younger individuals decrease with age (Bramham et al., 2012). However, this study was cross-sectional and lacking in age-matched controls. Variability in findings could be due to methodology differences such as varying task difficulty (Ceci & Tishman, 1984) and participant ages (Brodeur & Pond, 2001).

This article aims to further explore and better characterize the neuropsychological deficits in adults with ADHD, given that much of past research has been based on children and has yielded inconsistent findings, in the case of executive functioning and selective attention deficits in particular. Specifically, executive function deficits, as well as divided, selective, and sustained attention deficits in adults, will be assessed using a battery of neuropsychological tests and an EEG assessment. In addition, the subjective everyday life functional impairments in adults with ADHD and their relationship with the neuropsychological and electrophysiological findings will be investigated.

Method

Participants

Fifty-one adults diagnosed with the combined subtype of ADHD and 28 adult control participants participated in this study. Adults with ADHD reported persisting childhood ADHD. Adults with ADHD were recruited from a specialist adult ADHD service, the Dean Clinic at St. Patrick’s Hospital, Dublin, through referral from psychiatrists and from ADHD support groups. Adults without ADHD were recruited via poster advertisements in libraries, universities, and general pratictioner (GP) clinics. This study was granted ethical approval by St. Patrick’s Hospital Ethics Committee, Dublin, and the School of Psychology Ethics Committee, Trinity College Dublin. All participants gave written informed consent before participation. In the ADHD group, diagnosis of ADHD was established according to Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) criteria in both childhood and at present in adulthood using the Conners’ Adult ADHD Diagnostic Inventory for DSM-IV (CAADID; Epstein, Johnson, & Conners, 2000), the Conners’ Adult ADHD Rating Scales–Self Report: Long Version (CAARS-S:L; Conners, Erhardt, & Sparrow, 2003), and the Wender Utah Rating Scale (WURS; Ward, Wender, & Reimherr, 1993), a retrospective measure of ADHD symptoms in childhood. The observer versions of both scales (CAARS and WURS) were also administered to a close family member or partner. Detailed investigation of self-reported clinically significant problems in daily life attributable to attentional, executive, or arousal deficits was also undertaken through interview by a trained clinical psychologist. Twenty-two participants with ADHD were taking psychostimulant medication for ADHD, whereas the others had either taken stimulant medication in the past but had stopped and/or were stimulant-naïve.

All participants were excluded if they had history of pervasive developmental disorders (e.g., Asperger’s syndrome, autism) or intellectual disability (IQ < 80); history or current diagnosis of epilepsy or other neurological conditions (e.g., multiple sclerosis, motor neuron disease); history or current diagnosis of schizophrenia, bipolar disorder, or other equivalently severe psychiatric condition; and current primary diagnosis of substance misuse requiring treatment with priority (i.e., dependent on alcohol or other illicit substances). However, ADHD individuals with recreational alcohol and drug use were included as they are representative of the adult ADHD population. Control participants were also excluded if they had family history of ADHD. Comorbid disorders in the ADHD group included history of depression (n = 7), current depression (n = 5), history of anxiety (n = 5), current anxiety disorder (n = 4), and substance abuse (n = 3, alcohol and cannabis use).

Adults in each group were matched in terms of gender, age (t(65) = −0.72, p = .63), estimated IQ (t(65) = 2.76, p = .54), as measured by the Wechsler Adult Intelligence Scale–III (WAIS-III; Wechsler, 1997), and mean years of education (t(65) = 1.97, p = .12). All participants reported normal or corrected-to-normal vision. ADHD participants were withdrawn from any psychostimulant medication 24 hr prior to testing. All participants completed the CAARS self-report. The demographic and clinical characteristics of the two participant groups are summarized in Table 1.

Table 1.

Summary of Demographic Characteristics and CAARS Self-Report Scores in the ADHD and Control Group.

	ADHD group^a	Control group^a	t(65)	p
n	51 (11 F, 2 LH)	28 (9 F, 2 LH)
Age	32.78 (10.96)	30.6 (10.3)	−0.92	.63
Estimated IQ	111.23 (6.01)	113.09 (5.03)	2.76	.54
Years of education	15.56 (3.63)	17.5 (1.53)	1.97	.12
CAARS-DSM-IV inattention self	80.54 (11.52)**	46.88 (12.12)	−12.00	<.001*
CAARS-DSM-IV hyperactivity self	65.73 (13.89)**	42.53 (10.68)	−6.96	<.001*
CAARS-DSM-IV total self	77.71 (12.70)**	44.21 (13.24)	−10.57	<.001*
CAARS-DSM-IV inattention other	69.10 (11.65)**
CAARS-DSM-IV hyperactivity other	63.81 (11.35)
CAARS-DSM-IV total other	68.74 (11.27)**
WURS self	55.39 (21.04)**
WURS other	19.15 (8.23)

Note. ADHD participants’ scores in the CAARS Observer and Wender Utah Rating Scales (WURS Self-Report and Observer Form) are also reported. T-scores are reported for each of the CAARS measures. CAARS = Conners’ Adult ADHD Rating Scale; F = female; LH = left handed; DSM-IV = Diagnostic and Statistical Manual of Mental Disorders (4th ed.); WURS = Wender Utah Rating Scales.

Values are M (SD)

Statistically significant difference. **Clinically significant symptoms.

Procedure

Participants were asked to attend Trinity College Institute of Neuroscience for a single testing session that lasted approximately 2 hr. In the first part of this session, a neuropsychological assessment was carried out consisting of a series of neuropsychological tests as well as scales and questionnaires. This first part of the session lasted approximately 1 hr and 15 min, and it was followed by an EEG assessment that lasted approximately 40 min. During the EEG assessment, participants were asked to perform an auditory oddball task while their EEG signals were recorded. ADHD participants were also given observer versions of the CAARS and the WURS to take home, and they were asked to post back these completed scales in stamped addressed envelope. All study procedures were approved by the Ethical Review Board of the School of Psychology, Trinity College Dublin, in accordance with the Declaration of Helsinki.

Measures

Neuropsychological tests

Divided attention

The Telephone Search While Counting from the Test of Everyday Life Attention (TEA), that is, a battery of neuropsychological tests that provides norm-referenced scores on eight different subtests that are sensible to selective attention, sustained attention and attentional switching. There is also a divided attention test in the battery (TEA; Robertson, Ward, Ridgeway, & Nimmo-Smith, 1994). The TEA has good reliability and is valid. In the Telephone Search While Counting, participant must again search in the directory while counting strings of tones presented by a tape recorder. The combined performance on the subtests “Telephone Search” and “Telephone Search While Counting” gives a measure of divided attention that is called “Dual Task Decrement.”

Selective attention

Two subtests of the TEA: Elevator Counting With Distraction—In this task, participants had to listen to a series of tones and count the high-pitched tones only. The score is the number of correctly counted tones. This task measures auditory selective attention. Telephone Search—In this test, participants had to select certain symbols on a telephone directory and circle them not only as accurately but also as fast as possible, while ignoring distractor symbols. The score is the number of correctly circled symbols. This test measures visual selective attention.

Sustained attention

Sustained Attention to Response Task—Fixed and random (SART)

The SART is a measure of sustained attention that can predict everyday life attentional lapses (Robertson, Manly, Andrade, Baddeley, & Yiend, 1997), and it has been shown to activate right frontoparietal attentional networks (Manly et al., 2003). In the SART, numbers from 1 to 9 are presented on a computer screen, and participants are asked to press the left key of a mouse for every number except for 3 s. In the fixed version of the SART, numbers appear in a fixed order (from 1 to 9 every time), while in the random SART, numbers are presented in a random order. Participants’ total number of commission errors, omissions, RT on corrected responses, and variability expressed as the RT coefficient of variation (CV—calculated by dividing the standard deviation in RT by their mean) were calculated in both the fixed and random SART.

Auditory oddball task

In this auditory oddball task, stimuli were presented through headphones using the “Presentation” software suite (NeuroBehavioural Systems, San Francisco, CA). They consisted of 60-ms-duration sinusoidal tones of frequencies 1000 Hz (“targets”) and 500 Hz (“standards”). Targets were pseudo-randomly interspersed throughout the task and constituted 20% of the total number of trials. Participants were instructed to press the left key of the mouse to target tones with a right index finger as quickly and accurately as possible, while ignoring presentation of the nontarget standard tones. Participants completed a practice run of the task to ensure that they were well acquainted with the instructions before beginning. They were seated at a distance of ~50cm from a 20″ light-emitting diode (LED) monitor (Dell P2011H; Dell Inc., Ireland) and were instructed to maintain gaze on a white fixation cross presented over a black background at the center of the monitor (font size = 48). The tasks were conducted in a dark room with the only ambient light provided by the fixation cross, and it lasted for approximately 17 min. Tones were presented at an interstimulus interval (ISI) which varied pseudo-randomly between 2.1 and 2.9 s, with an average of 66 target tones and 267 standard tones over the whole task. Omission errors, RT (ms), and RT CV on target stimuli were extracted. Independent-samples t tests were used to compare groups’ performance.

Executive functions

Hotel task

Manly, Hawkins, Evans, Woldt, and Robertson (2002) found that this task could detect deficits in a group of adult TBI patients compared with a group of matched controls. This measures executive functions and is designed to simulate typical day-to-day activities. The Hotel task is comprised of five distinct activities that would plausibly be completed in the course of running a hotel (i.e., checking guests’ bills, proofreading a leaflet on the hotel’s facilities, sorting money, etc.). The participants’ objective in this task is to try to complete as much as they can from each of the five activities over an allocated 10-min period. Performance in the Hotel task is scored within two categories: number of attempted tasks out of five, and time allocation, measured as the total deviation time from an optimal time allocation of 2 min per activity.

Subjective ratings of everyday life measures

The Attention-Related Cognitive Errors Questionnaire (ARCEQ)

The ARCEQ (adapted from Cheyne, Carriere, & Smilek, 2006) is a 12-item scale that was used as a self-report measure of attention slips and absentmindness in everyday life. Participants rate the frequency with which they experience such slips in attention on a scale ranging from 1 to 5, with higher scores indicating higher absentmindness.

The Everyday Memory Failures Questionnaire (EMFQ)

It is structured in the same way as the ARCEQ (adapted from Cheyne et al., 2006), and it is a self-report measure of minor memory failures that occur in everyday life. Participants rate the frequency with which they experience memory failures in a series of 12 items that are rated on a scale ranging from 1 to 5, with higher scores representing higher occurrence of memory failures.

EEG Data Acquisition and Processing

Continuous EEG was acquired using an ActiveTwo system (BioSemi, The Netherlands) from 32 scalp electrodes, configured to the standard 10/20 setup and digitized at 512 Hz. Vertical and horizontal eye movements were recorded using two vertical electroocculogram (EOG) electrodes placed above and below the left eye and two horizontal EOG electrodes placed at the outer canthus of each eye, respectively. Data from the 32 scalp electrodes for each participant were then subjected to temporal independent component analysis (ICA) using FASTER v1.2b (Nolan, Whelan, & Reilly, 2010) for removal of EOG and other noise transients. Event markers emitted by the stimulus presentation computer were recorded simultaneously during EEG and pupil diameter acquisition. Three-second epochs were extracted for EEG data sets around each stimulus marker from −1 to +2 s, and epochs were baseline corrected relative to the mean activity in the 100 ms directly preceding stimulus presentation. All further processing was carried out using a combination of in-house MATLAB scripting and EEGLAB. EEG data sets were subject to further artifact rejection criteria applied between −100 and +800 ms relative to the stimulus for the EEG epochs. Any epochs with an EEG amplitude >90 µV were rejected. All epochs on which participants responded to standard tones (false alarms), failed to respond to target tones (misses), or responded within the first 100 ms after target presentation (quick responses) were also removed from the data.

Event-related potential (ERP) measures

ERP component structure was confirmed by visual inspection of grand-average waveforms. The width of the latency window used to measure component amplitude was based on the duration and spatial extent of each component. Target stimuli evoked an auditory N1 component with a central topography and a large positive component over centroparietal scalp areas, the posterior P3. N1 amplitude and latency measures were extracted from three central electrodes (Cz, C3, C4) between 100 and 200 ms poststimulus presentation. P3 amplitude and latency measures were extracted from three central-parietal sites (Cz, CP1, and CP2) in the interval of 300 to 550 ms poststimulus presentation. The same ERP measures (N1 and P3 amplitudes and latencies) were also extracted for standard tones. ERP components were not analyzed for errors of omission, as the total rate of omission errors was too low to allow ERP analysis (M = 0.85, SD = 1.78).

Statistical Analysis

All ADHD participants were included in behavioral analysis, while seven participants were excluded from EEG analysis based on excessive artifacts, leaving 44 final participants (seven female, one left handed; M age = 29.8, SD = 10.44; mean years of education = 15.5, SD = 3.51; estimated IQ = 109.45, SD = 7.02). In total, 28 control participants were assessed and included in the behavioral analysis. Four control participants were excluded from EEG analysis due to the presence of excessive artifacts, leaving 24 final participants for EEG analysis (eight female, three left handed; M age = 28.5, SD = 9.02; mean years of education = 17.60, SD = 1.69; estimated IQ = 112.91, SD = 4.29). Independent-samples t tests with 95% confidence interval (CI) were used to investigate differences between the ADHD group and the control group on cognitive and ERP measures. Where Levene’s test for equality of variances was statistically significant, the t value corresponding to an analysis in which equal variances are not assumed was adopted. For measures belonging to the sustained attention domain, Bonferroni correction for multiple comparisons was applied, thus using a more stringent p value of .005 for significance. Effect sizes were calculated in the following manner: (M_control − M_ADHD) / SD_ADHD (Cohen’s d; Howell, 2008). Separate averages were also calculated for accuracy, omission errors, RT, and CV in the first and second half of the auditory oddball task, each lasting approximately 8 min and 30 s. This was aimed to evaluate the effects of time on participants’ performance, thus providing an indicator of sustained attention deficits. Group (ADHD vs. control) × Time (first half vs. second half) repeated-measures ANOVAs were carried out to investigate differences between groups.

Results

Neuropsychological Tests

Divided attention

A t test revealed that the ADHD group showed significantly higher dual task decrement’s scores compared with the control group, t(77) = 2.19, p = .04, indicating impaired performance.

Selective attention

No significant differences emerged between the ADHD group and the control group in the two selective attention subtests—Elevator Counting With Distraction: t(77) = 1.66, p = .67, and Telephone Search: t(77) = 1.85, p = .39.

Sustained attention

Independent-samples t tests using Bonferroni correction revealed that in the fixed SART, the ADHD group showed a higher number of omissions, t(69) = 3.46, p = .001, and higher commission errors, t(69) = 2.92, p = .005, compared with the control group. In the random SART, the ADHD group also showed higher commission errors, t(69) = 5.02, p = .000, than the control group.

In the auditory oddball task, repeated-measures ANOVAs showed a significant difference for RT between the ADHD group and the control group, F(1, 70) = 7.37, p = .03, η² = .07, indicating that ADHD participants became significantly slower in the second half of the task compared with the first half, while the control group did not exhibit this effect. A significant difference between the ADHD group and the control group, F(1, 70) = 10.34, p = .002, η² = .13, was also found for CV, indicating that ADHD participants were significantly more variable in the second half of the task compared with the first half, while no such difference emerged in the control group. Figure 1 illustrates differences between the ADHD group and the control group in the first and second half of the auditory oddball task for RT and CV.

Figure 1.

Behavioral results for the ADHD group and the control group in the auditory oddball task.

Executive functions

Significantly lower number of attempted tasks was found in the ADHD group compared with the control group, t(77) = −3.073, p = .004.

Subjective Ratings of Everyday Life Measures

Independent-samples t tests showed that ADHD participants reported higher subjective ratings in both the ARCEQ, t(48) = 16.30, p = .000, and the EMFQ, t(48) = 12.30, p = .000.

Table 2 presents the mean scores, standard deviation, effect sizes, and t-test results relating to comparisons between ADHD and control groups on each neuropsychological test and on the ARCEQ and EMFQ.

Table 2.

Mean Scores (and Standard Deviations) on Neuropsychological Tests, ARCEQ and EMFQ Ratings for the ADHD Group and Control Group, Normal Scores, t-Test Results, and Effect Sizes.

	ADHD group	Control group	Normal score (SD)	t tests	Effect size
	M (SD)	M (SD)	Normal score (SD)	t tests	Effect size
Sustained attention^a
SART fixed omission	9.4 (9.37)	2.05 (3.05)		t(69) = 3.46, p = .001*	0.79
SART fixed commission	5.21 (4.66)	1.90 (3.19)		t(69) = 2.92, p = .005*	0.71
SART fixed RT	178.35 (144.46)	129.81 (116.61)		t(69) = 1.34, p = .19	0.34
SART fixed CV	0.94 (0.35)	0.75 (0.24)		t(69) = 2.45, p = .018	0.54
SART random omission	4.46 (8.60)	1.00 (2.52)	1.06 (3.41)	t(69) = 2.57, p = .013	0.40
SART random commission	11.22 (5.61)	4.60 (2.76)	6.36 (4.36)	t(69) = 5.02, p = .000*	1.18
SART random RT	177.34 (81.99)	191.99 (127.20)	375 (65)	t(69) = −0.58, p = .57	0.18
SART random CV	0.64 (0.27)	0.50 (0.17)		t(69) = 2.64, p = .011	0.37
Oddball omission	2.51 (6.63)	0.14 (0.66)		t(69) = 2.52, p = .015	0.31
Oddball RT	522.68 (132.54)	480.57 (87.20)		t(69) = 1.34, p = .19	0.34
Oddball CV	0.31 (0.12)	0.27 (0.09)		t(69) = 2.14, p = .037	0.36
Divided attention
Dual task decrement (TEA)	1.32 (2.25)	0.61 (1.10)	≤2.5	t(77) = 2.19, p = .04*	0.32
Selective attention
Elevator Counting With Distraction	7.94 (1.77)	8.68 (2.09)	≥4	t(77) = 1.66, p = .101	0.67
Telephone Search	2.72 (0.95)	3.09 (0.44)	≤3.4	t(77) = 1.848, p = .075	0.39
Executive functions
Number of attempted tasks (HT)	3.72 (0.85)	4.43 (1.03)		t(77) = −3.073, p = .004*	0.82
Total deviation time (HT)	155.52 (86.39)	119.63 (66.25)		t(77) = 1.88, p = .063	0.41
Time in activity (HT)	582.63 (26.62)	575.47 (16.99)		t(77) = 1.28, p = .203	0.27
Everyday life functional impairment
ARCEQ	53.50 (11.45)	12.96 (3.31)		t(48) = 16.30, p = .000*	12.25
EMFQ	43.30 (11.50)	12.17 (4.13)		t(48) = 12.30, p = .000*	7.54

Note. ARCEQ = Attention-Related Cognitive Errors Questionnaire; EMFQ = Everyday Memory Failures Questionnaire; SART = Sustained Attention to Response Task; RT = reaction time; CV = coefficient of variation; TEA = Test of Everyday Life Attention; HT = Hotel task.

For the sustained attention tests, Bonferroni correction was applied and a p value of .005 was used. For the random SART ‘s reference scores, see Manly, Davison, Heutink, Galloway, and Robertson (2000).

Statistically significant difference.

ERPs

On target tones, no significant difference between the ADHD group and the control group was found on N1 amplitude, t(54) = 0.011, p = .99, and latency, t(54) = 0.34, p = .74. The ADHD group showed significantly smaller P3 amplitude compared with the control group, t(52) = −2.17, p = .035, while there was no significant difference between groups on P3 latency, t(52) = 0.201, p = .84. No significant differences between the ADHD and the control groups emerged on standard tones on N1 amplitude, t(54) = −0.45, p = .66, and latency, t(54) = −0.18, p = .786, as well as on P3 amplitude, t(54) = 1.11, p = .27, and P3 latency, t(54) = 0.32, p = .75. Figure 2 shows N1 and P3 ERP waves in the ADHD and control groups on target and standard tones as well as correspondent P3 topographies in the two groups on target tones.

Figure 2.

Differences in P3 and N1 ERPs waveforms on target and standard tones in the auditory oddball task between the ADHD group (red line) and the control group (blue line).

Correlations

Partial correlation analysis showed a significant negative correlation between ARCEQ scores and P3 amplitudes on target tones, r(45) = −.301, p = .040. Figure 3 shows a scatterplot that depicts the negative correlation between ARCEQ scores and P3 amplitudes.

Figure 3.

Scatterplot depicting the relationship between P3 amplitudes and scores in the ARCEQ.

Discussion

This study aimed to explore and better characterize the neuropsychological deficits in a group of adults with persisting childhood ADHD in terms of executive functions, divided, selective, and sustained attention, to clarify inconsistent findings in this area within the adult ADHD literature.

The results of this study showed that adults with ADHD have impaired performance in the Hotel task indicating impaired executive functions and planning compared with a group of adult controls. This finding is consistent with previous studies that have shown deficits in a range of different executive function domains in adults with ADHD (Hervey et al., 2004; Willcutt et al., 2005). Results have also shown that adults with ADHD exhibited impaired performance in a divided attention task, which is again consistent with previous research (Dinn et al., 2001; Tucha et al., 2008).

This study also showed that adults with ADHD have impaired sustained attention, as expressed by higher error rates in both the fixed and random SART. This finding was reinforced by the results of time-on-task analysis in the auditory oddball task that showed a decrement in task performance over time in terms of RT and CV in the ADHD group. This finding is consistent with previous research (Tucha et al., 2017), and it further confirms that impaired sustained attention is a hallmark characteristic of adult ADHD.

Another key finding that emerged from this study was that selective attention appeared to be spared in adults with ADHD compared with controls, as no difference between groups was found in two selective attention tasks. EEG results corroborate the neuropsychological findings by showing a selective impairment in P3 waveform on target tones indicative of sustained attention deficits (Polich & Kok, 1995), while there was no difference between adults with ADHD and controls in N1 early-sensory component on targets, suggesting that early-sensory selective attention is unaffected in this group of adults with ADHD. The finding that adults with ADHD have impaired sustained attention while preserved selective attention supports the notion of differential impairment of attentional functions in adult ADHD. These findings are consistent with the results of a previous study that found a dissociation between sustained attention deficits and selective attention deficit in 10-year-old boys with ADHD (DeShazo Barry et al., 2001). Similarly, in this study, children with ADHD were able to perform as well as non-ADHD children on the selective attention task, while their performance on the sustained attention task indicated impairment. On the contrary, the results of this study are not consistent with those of a previous EEG study that have demonstrated impairments in selective early-sensory processing, as expressed by deficits in P2 and N2 ERP components in adults with ADHD in an auditory/visual oddball task (Barry et al., 2009). This discrepancy may be caused by the fact that in this study a single-modality auditory oddball task was used to assess participants, while in Barry et al.’s (2009) study, an intermodality auditory/visual oddball task was employed. It may be that adults with ADHD experience more difficulties in selectively differentiating between two sensory modalities, thus resulting in impaired early-sensory ERP components in this study.

Another aim of this study was to investigate differences between adults with ADHD and adult controls in subjective measures of everyday life functional impairments in attention and memory. The results demonstrated that adults with ADHD experienced higher attention and memory subjective impairments in their day-to-day life compared with controls. Furthermore, subjective ratings of everyday life attentional deficits negatively correlate with P3 amplitude on target stimuli, indicating that higher subjective ratings correspond to smaller P3 amplitudes, indicative of reduced sustained attention. Recent research has suggested that the use of self-ratings of cognitive functioning during neuropsychological assessments can contribute to our understanding of the neuropsychology of adult ADHD, have high ecological validity, and can also facilitate the selection of treatment approaches (Furmaier et al., 2014). In this study, adults with ADHD appeared to be aware of their cognitive deficits in their day-to-day life. However, it had to be emphasized that these findings on functional impairments are entirely based on participants’ self-reports and should therefore be interpreted with caution. However, subjective ratings of everyday life attentional deficits were correlated with P3 amplitude on target tones, thus reinforcing the significance of this finding.

The pattern of results that emerges from this study can have some important clinical implications for developing new and more effective treatment strategies for adults with ADHD. For example, the dissociation found between sustained attention and selective attention performance, suggesting spared selective attention in this group of adults with ADHD, suggests that adults with ADHD may benefit from structuring long periods of activities to allow more frequent breaks and from breaking prolonged activities into smaller units to facilitate the learning process (DeShazo Barry et al., 2001; Tucha et al., 2017). However, in a recent study, it was argued that this strategy may not be ideal as it can be challenging for participants with ADHD to perform several different small activities for long time because of their difficulties with task initiation and task engagement (Tucha et al., 2017). Another option may be to teach people behavioral strategies to transiently increase their level of attention during long periods of activity to overcome attentional lapses. Recent studies have attempted this (O’Connell et al., 2008; Salomone et al., 2015) by using a behavioral technique called Self-Alert Training (SAT) that combine psychoeducation with a biofeedback protocol and is aimed to teach adults with ADHD to increase alertness when needed to refocus on current tasks. Results of a randomized controlled trial using SAT (Salomone et al., 2015) have shown that after a 5-week training, people with ADHD showed reduced ADHD symptoms, improved performance on cognitive tests, and improved everyday life functioning. Furthermore, some of these improvements were maintained 3 months after training.

One of the most influential models of ADHD focuses on impaired signaling of delayed rewards arising from disturbances in motivational processes (Sagvolden, 1991; Sonuga-Barke, 1998). It has recently been shown that enhancing motivation in individuals with ADHD can also improve their performance on executive functions and attention tasks (Dovis, Van der Oord, Wiers, & Prins, 2012). Future studies should explore the potential influence of motivation on ADHD participants’ performance in executive functions and attention tests by using measures from different cognitive and motivational domains (Sonuga-Barke, 2005). This can help to further clarify the mixed findings on executive functions and attentional deficits within the ADHD literature. Furthermore, motivation can affect the treatment of ADHD participants. Studies have found that motivation can increase treatment outcomes in people with ADHD (Prins, Dovis, Ponsioen, ten Brink, & van der Oord, 2011; Salomone et al., 2015). Therefore, it can be suggested that the role of participants’ motivation should be taken into account when designing interventions for people with ADHD, and it can help to develop more effective treatments for this syndrome.

This study can also suggest that the combination of knowledge emerging from neuropsychological tests and subjective measures of everyday life functional impairments in adults with ADHD may help to develop more individualized treatments for adult ADHD that can target relevant areas of functional impairments in adults with ADHD. It is also hoped that more individualized interventions may increase treatment compliance and lead to better outcomes in adults with ADHD.

Few limitations of this study should be mentioned. First, the sample size of this study is relatively small (51 adults with ADHD), and this limits the generalization of the results to the ADHD population. Nonetheless, results of this study still showed significant differences between groups. Second, given the heterogeneity of the ADHD syndrome and given that previous research has shown that differential neuropsychological deficits are associated with the different ADHD subtypes (Tucha et al., 2008), another limitation is that no distinction was made between different ADHD subtypes in this study. Differences in neuropsychological profiles between ADHD subtypes should be investigated in future research. Third, in this study, only the Hotel task was employed to evaluate executive function deficits in adult ADHD. Although this task has good ecological validity and it also involves different executive function skills, such as planning and problem solving, additional tests of executive functions should be used to assess all aspects of executive functions in adult ADHD. A similar limitation can apply to scales used to assess subjective ratings of everyday life cognitive impairments. More comprehensive scales, not limited to attention and memory, may be used to assess subjective ratings of everyday impairments in all areas of cognitive functioning in adults with ADHD.

In conclusion, this study has shown that adults with ADHD exhibit deficits in executive functions, divided attention and sustained attention while selective attention appeared to be spared. This suggests differential impairments of attentional skills in adult ADHD. EEG results have confirmed neuropsychological findings by showing sustained attention impairments in P3 amplitude on target stimuli, while target N1 early-sensory processing component was unaffected. Impaired subjective ratings of everyday life attention and memory functioning also emerged in this group of adults with ADHD compared with controls. The knowledge that emerged from the use of neuropsychological tests, EEG, and subjective ratings of everyday life functional impairment has enabled a more comprehensive delineation of attentional deficits experienced in adults with ADHD. This can also have clinical implications for developing new, more effective, and individualized treatments for adult ADHD.

Footnotes

Acknowledgements

The authors would like to thank all participants who took part in this study.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the Health Research Board (HRB).

Author Biographies

Simona Salomone is a postdoctoral researcher currently working at the Centre for Brain and Cognitive Development (CBCD), Birkbeck College, London. Her research interests include ADHD, cognitive rehabilitation and neurorehabilitation, and electrophysiology (EEG).

Grainne R. Fleming has worked as a research assistant at Trinity College Institute of Neuroscience, Dublin, on several research projects focusing on the neuropsychology of aging.

Jessica Bramham is a senior lecturer in clinical neuropsychology at University College Dublin (UCD). Her main research area is adulthood ADHD and its comorbidities.

Redmond G. O’Connell is assistant professor at Trinity College Dublin. His research focuses on understanding the neural mechanisms underpinning high-level cognition employing a range of psychophysiological techniques, including EEG and functional magnetic resonance imaging (fMRI).

Ian H. Robertson is professor of psychology at Trinity College Dublin and was the founding director of the Trinity College Institute of Neuroscience. His research interests include the neuropsychology of brain rehabilitation with an emphasis on attention and memory.

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