Fractionating Executive Functions of Adults With ADHD

Abstract

Objective: To evaluate the performance of adults with ADHD considering the fractionation of executive functions into six different domains. Method: Participants were adult ADHD patients who were not under the acute effects of medication (n = 48). Their performance was compared with that of a healthy control group (n = 20) of comparable age, education, and nonverbal intelligence quotient. The cognitive domains assessed were executive shifting, updating, inhibition of prepotent responses, dual-task performance, planning, and access to long-term memory. We also assessed the symptoms of inattention, hyperactivity/impulsivity, anxiety, and depression by validated questionnaires. Results: Compared with controls, patients reported more symptoms related to ADHD, anxiety and depression symptoms and were impaired in the shifting cost measure and phonemic fluency (measure of access to long-term memory). Conclusion: ADHD in adults selectively impaired executive shifting and access to long-term memory, domains that may alter performance in a wide range of daily tasks.

Keywords

ADHD executive function adult task-switching inhibition

Introduction

ADHD is characterized by symptoms of inattention, hyperactivity, and impulsivity that impair quality of life (Asherson, Manor, & Huss, 2014). Behavioral effects usually begin in childhood and, for approximately 50% of patients can persist into adulthood to varying degrees (see Asherson et al., 2014). However, cognitive characteristics of children and adults with ADHD can vary greatly (Barkley, 2002; Faraone et al., 2000), so we will focus on the effects in an adults which is the population of interest in the present study.

Adult patients with ADHD exhibit impairment in the ability to adapt to the demands of day-to-day activities and in social interactions (Barkley, 1997a, 2000; Brown, 2009; Faraone et al., 2000). These abilities are related to the concept of executive functions. This term refers to higher order cognitive abilities related to regulating cognition and behavior. These abilities are frequently associated with the functioning of the prefrontal cortex and are impaired in various clinical populations (e.g., see Lezak, Howieson, & Loring, 2004; Miyake & Friedman, 2012). “Executive functions” is an umbrella term that encompasses several domains that can be broadly divided into hot and cold processes (see Yang et al., 2011). Hot functions involve processing emotions and social behavior; these will not be discussed here due to the lack of a framework for studying variant subtypes of executively controlled emotional/social behavior. Rather, in this article, we focus on cold functions, which do not directly involve emotional processing and which include various correlated yet distinguishable domains that can be studied separately within the same experimental setting (see Borges et al., 2013; Ginani et al., 2011; Vaz, Pradella-Hallinan, Bueno, & Pompéia, 2011).

The work of Miyake et al. (2000), Friedman et al. (2008), and Miyake and Friedman (2012) pointed to the possibility of fractioning cold executive functions (the unity/diversity framework) into the following domains: updating or modifying the contents of working memory through suppression of irrelevant information and incorporation of relevant data necessary for the task at hand; shifting or switching, that is, the ability to switch between different tasks; and inhibition of prepotent responses, or the ability to override dominant responses. Miyake et al. also showed that performance in carrying out two tasks simultaneously (dual tasking) is not mathematically related to the above three domains, indicating that it can characterize a separate cognitive domain (see Logie, Cocchini, Della Sala, & Baddeley, 2004). In addition to these executive processes, there are two others that are frequently cited in the literature: (a) planning, the ability to organize behavior toward a specific goal that must be achieved through intermediate stages (Owen, 1997; Shallice, 1982), and (b) the efficiency of access to long-term memory (see Fisk & Sharp, 2004). Hence, cold executive functions can be fractionated into many separate cognitive processes.

The literature on ADHD includes very few studies that investigated executive functions considering executive fractionation (for an exception, see Miller, Ho, & Hinshaw, 2012). Previous studies that did consider executive fractionation usually included tests that are representative of only one or a few of these domains or assessed performance using classic executive tests that often involve a combination of these processes (see Miyake et al., 2000). The use of tasks that tap different executive domains or a mixture of executive domains in different studies may lead to the idea that ADHD is not consistently associated with alterations of executive functions. Hence, it is not surprising that the effects of ADHD on executive functions in adults are still a matter of debate (Hervey, Epstein, & Curry, 2004; Seidman, 2006). Possibly because of this lack of consistency, some consider executive deficits in ADHD are secondary to ADHD-induced impairment of nonexecutive cognitive abilities (e.g., Boonstra, Oosterlaan, Sergeant, & Buitelaar, 2005). Alternatively, if the fractionation of executive functions is taken into account, it stands to reason that different results are obtained based on the use of tasks that evaluate different domains.

Specific ADHD-related executive impairment has been shown in tasks that measure inhibition (Bekker et al., 2005; Boonstra, Kooij, Sergeant, & Buitelaar, 2010; Boonstra et al., 2005; Miller et al., 2012), shifting or set-shifting (Boonstra et al., 2010; Boonstra et al., 2005; Halleland, Haavik, & Lundervold, 2012; Marchetta, Hurks, Krabbendam, & Jolles, 2008; Pazvantoglu et al., 2012; Rohlf et al., 2012; Woods, Lovejoy, Stutts, Ball, & Fals-Stewart, 2002), and access to long-term memory as measured by verbal fluency (Boonstra et al., 2005; Tucha et al., 2005; Woods et al., 2002). Planning (Miller et al., 2012; Schreiber, Javorsky, Robinson, & Stern, 1999), updating (King, Colla, Brass, Heuser, & Von Cramon, 2007; White & Marks, 2004), and dual tasking (Armstrong & Munoz, 2003; Dige, Maahr, & Backenro-Ohsako, 2008) have been less studied in this population, but there are indications that these domains may also be affected. None of the previous studies, however, assessed various executive domains in the same test battery, so it is difficult to determine whether there are specific executive deficits in ADHD or whether general executive functioning is impaired. As executive tests that measure inhibition, updating and shifting seem to share some variance because all domains correlate with one another to a certain extent (see Miyake & Friedman, 2012), any change in this common factor could lead to an overall reduction in these executive domain, and possible others. This common variance seems to be undistinguishable from inhibitory processes (see Miyake & Friedman, 2012). Hence, changes in inhibition in ADHD could explain deficits in many different executive tasks, even those that load on other executive domains. This relationship fits nicely with the idea that ADHD-associated executive changes are solely due to impaired inhibition (Barkley, 1997b; Bekker et al., 2005; Boonstra et al., 2010). However, ADHD may be associated with impairment in selective executive domains together with, or separately from, this common process, especially as impairment in inhibitory processes is not consensual (see Sonuga-Barke, 2010). Sonuga-Barke (2010) proposed various levels of ambiguity in identifying inhibitory dysfunction in ADHD, including what he terms a neuropsychological level, which involves disentangling inhibitory from other cognitive abilities. A way to determine whether inhibition is the core dysfunction in this disorder is to evaluate ADHD effects considering the fractionation of executive functions. Inhibition deficits should lead to impairment in many executive domains as proposed by Miyake and Friedman’s (2012) data. A different patter of effects may show that inhibition is not the main deficit in this disorder.

Thus, the aim of the present study was to assess executive functions considering their fractionation in ADHD adult patients compared with healthy controls. An important issue to be considered with this clinical population is the use of medication for this disorder. Most patients are treated with methylphenidate, a drug that can have acute positive effects on executive functions (e.g., Advokat, 2010; MTA Cooperative Group, 1999). Thus, it is important that patients not be under the acute effects of this drug when testing takes place, as this can distort performance. However, most studies in this field do not mention the type of treatment received by patients, nor if they took their doses on the testing day.

Methylphenidate is available in various types of formulations, which have variable duration of action that, however, do not extend for more than approximately 12 hr (Coghill et al., 2013). Cognitive assessment can therefore be performed without the acute effect of the drug if patients are asked to refrain from medication for 24 hr (see Gualtieri et al., 1982). This is the approach used in the present study. In addition, we assessed patients who were on chronic medication and others who were nonmedicated so that any possible changes in executive functions due to chronic use of the drug could be determined.

The test battery included measures that are representative of the domains inhibition of prepotent responses, updating and switching (see Miyake et al., 2000). For the dual-task domain, we used a standardized task that includes tests that tap different systems of the multicomponent model of working memory, as this is considered important when defining this domain (Baddeley, Della Sala, Gray, Papagno, & Spinnler, 1997; Della Sala, Cocchini, Logie, & MacPherson, 2010). The planning task used was the Zoo Map task (Wilson, Alderman, Burgess, Emslie, & Evans, 1996), and access to long-term memory was evaluated using fluency tasks (see Lezak et al., 2004). Groups were matched by age, years of schooling, and nonverbal intelligence quotient (IQ), which are all factors that can influence cognitive performance (Mesquita, Coutinho, & Mattos, 2010).

We hypothesized that chronic use of methylphenidate would not alter the cognitive profile of patients, as this drug does not seem to exert effects once its bioavailability is below a certain threshold (Huang, Wang, & Chen, 2012), and participants were not under the acute effects of the drug during testing. Concerning which executive functions are affected, we predicted that if ADHD is related to impaired inhibitory control, we should find deficits in many executive tasks (at least in those that measure updating and shifting; see Miyake & Friedman, 2012). Alternatively, ADHD may be associated with specific executive effects, in which case we should find alterations in some domains and not in others. Based on the literature, apart from changes in inhibition (Barkley, 1997a, 1997b; Bekker et al., 2005; Boonstra et al., 2010; Boonstra et al., 2005; Miller et al., 2012) which are not consensual (see Sonuga-Barke, 2010), the most consistently altered domains in ADHD are access to long-term memory (Boonstra et al., 2005; Tucha et al., 2005; Woods et al., 2002) and switching (Boonstra et al., 2010; Boonstra et al., 2005; Halleland et al., 2012; Marchetta et al., 2008; Pazvantoglu et al., 2012; Rohlf et al., 2012; Woods et al., 2002), so we believed that tasks that evaluate these domains would be more affected.

Method

Participants

All participants were selected using the following eligibility criteria: between 18 and 40 years of age, having Portuguese as a first language, at least 11 years of schooling, and a coefficient of nonverbal IQ within the normal range (Raven, 1947; adapted for local use by Campos, 2003). All participants had normal or corrected vision, reported no hearing problems and were on no psychotropic medication at the time of testing other than methylphenidate (ADHD patients only). We also excluded patients who reported neurological and psychiatric disorders such as schizophrenia, bipolar disorder, psychosis, obsessive-compulsive disorder and Tourette syndrome (see more details below). Participants with scores above 30 in the Beck Depression Inventory (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961; adapted for local use Cunha, 2001) were excluded from the analysis because this is suggestive of severe depression in clinical samples (Beck, Steer, & Garbin, 1988). We also excluded participants if their scores were higher than the mean plus one standard deviation from the local population (see Andrade, Gorenstein, Vieira Filho, Tung, & Artes, 2001) in trait anxiety, evaluated using the State–Trait Anxiety Inventory (Spielberger, Gorsuch, & Lushene, 1970; adapted for local use by Biaggio & Spielberger, 1980).

Patients with ADHD

We selected 48 adults (24 men) diagnosed with ADHD according to the diagnostic criteria of the structured clinical interview of for Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association, 2000). Comorbidities were excluded through unstructured interviews and through the use of the DSM-IV-TR checklist. Fourteen of the 48 patients had never been medicated for the disorder. The remaining patients were treated with methylphenidate with doses that were stable for at least 2 months. Some patients were recruited from the Programa Déficit de Atenção e Hiperatividade (PRODATH). Others responded to advertisements in the media.

Control group

Twenty adults (12 men) who did not meet the criteria for ADHD described above were selected using the same eligibility criteria as the patients. Controls were recruited through advertisements in the media.

Procedure

The study was approved by the Ethics Committee of the Federal University of São Paulo and the University of São Paulo (CAAE 20530613.3.3001.0068). All participants signed informed consent forms. Participants were tested in the morning. The patients under medication were assessed before they ingested their daily dose so that methylphenidate could not interfere with performance. All patients ingested their daily doses of methylphenidate in the morning, so they had abstained from their medication for approximately 24 hr at the time of the tests.

Before the tests of executive functions (see below), participants carried out the multiple-choice Raven’s Progressive Matrices test (Raven, 1947; adapted for local use Campos, 2003) for assessment of nonverbal IQ, and filled in the Beck Depression Inventory and the Trait Anxiety Inventory. In addition, participants completed the Adult Self-Report Scale (ASRS; Kessler et al., 2005; adapted for local use by Mattos et al., 2006; see below). Participants then performed tests of executive functions that were presented in a fixed order (the same order in which they are listed in the description of tests below) for both groups in a battery lasting approximately 50 min. Other tests were also carried out, the results of which will be reported elsewhere. After their participation in this study, some of the patients and controls were included in another study, which investigated the cognitive effects of mindfulness practices in ADHD.

Questionnaire and tests

ASRS

This questionnaire (Kessler et al., 2005; adapted for local use by Mattos et al., 2006) was carried out to obtain measures of the severity of symptoms of inattention (Part A) and hyperactivity/impulsivity (Part B). It consists of 18 items with 9 domains of each symptom evaluated on a 5-point scale ranging from never (no symptoms) to very often (maximum symptoms).

Tests of executive functions

Plus–minus task (modified from Miyake et al., 2000): This is a measure of shifting that consisted of three lists of two-digit numbers (the numbers 10-99 prerandomized without replacement) on a single sheet of paper. When using the first list of 15 numbers, participants are instructed to add three to each number and write down their answers. For the second list of 15 numbers, they are instructed to subtract three from each number. Finally, on the third list of 30 numbers, the participants are required to alternate between adding and subtracting three (i.e., add three to the first number, subtract three from the second number, and so on). List completion times and shifting errors were determined. The cost of shifting between the operations of addition and subtraction was then calculated, as the difference between the time to complete the alternating list and the summation of the times required to complete the addition and subtraction lists.

Dual-task paradigm (Baddeley et al., 1997; Della Sala et al., 2010): This evaluates dual-task performance. This is a paper-and-pencil test that involves a visuospatial tacking task (circle crossing) and a phonological/verbal task (digit span). First, to determine participants’ spans, lists of increasing numbers of digits are read aloud at the rate of one digit per second and the participants are asked to repeat the digits in their order of presentation (forward digit span). Participants’ digit span was taken to be the maximum digit length at which they correctly repeated five of six sequences of digits. The phonological task consists of the 90-s-long repetition of digit sequences (of the length of each participant’s span) presented orally, which the participant has to repeat in the proper order. Scores are the number of sequences repeated correctly divided by the number of sequences presented. The circle-crossing task consists of traversing a chain of 240 circles linked with arrows to form a path laid out on an A3-sized sheet of paper. There was a practice trial with a path of 240 circles. Participants are required to follow the path crossing the circles as rapidly as possible for a period of 90 s. Scores are the number of circles traversed. The dual-task condition consists of the simultaneous execution of both tasks within a 90-s period. To quantify participant’s performance, we used the measure proposed by Baddeley et al. (1997), the mu index, which expressed the overall percentage loss in the dual tasks compared with the single tasks, considering the contributions of both tasks to be of equal weight.

Zoo Map Test (Wilson et al., 1996): This task measures planning abilities from the ecological Behavioural Assessment of the Dysexecutive Syndrome test battery (BADS). Participants are given a map of a zoo and a set of instructions relating to 12 places they had to visit (e.g., elephant house, lion cage) and rules they must adhere to (e.g., starting at the entrance and finishing at a designated picnic area, using designated paths in the zoo only once). Scores were the planning/thinking time plus the execution (drawing time) of the route; the same scoring procedure was used for errors (rule breaks).

Word fluency (Lezak et al., 2004): To test access to long-term memory, participants were told to verbally generate as many words as possible that begin with a given letter (F and S) or that belong to a certain category (animals and musical instruments) for 1 min each. The participants were instructed to not use proper nouns or morphological variations of words and to avoid repetitions. Participants were scored on the total number of words generated and the number of errors.

Random Number Generation (RNG; based on Miyake et al., 2000): This is a classic executive task in which participants are asked to generate digits in a random order. Participants had to generate 120 digits using the numbers 1 to 9 at 1-s intervals marked by a sound signal. Different indexes of departures from randomness were used and were calculated as suggested by Towse and Neil (1998) using the RgCalc Software (http://www.pc.rhbnc.ac.uk/cdrg/rgcpage.html): Redundancy (R), coupon, and mean repetition gap were used as measures of executive updating. Turning point index (TPI), runs, and adjacency indexes are related to inhibition of prepotent responses (see Miyake et al., 2000). These indexes also load together in factor analyses in other publication (e.g., Friedman & Miyake, 2004; Towse & Neil, 1998), suggesting that they measure two separate cognitive constructs. We considered that these domains would be affected if at least two out of three of these domain-specific measures were impaired.

Data Analysis

For inferential analysis, we used general linear models (GLM) with groups as an independent factor (comparing medicated and nonmedicated patients and comparing all patients and controls, as detailed below). The level of significance was set at 5%. Effect sizes of the differences between groups were determined using Hedges’s g metrics (Hedges, 1981). Effect sizes larger than .5 are indicative of clinical relevance; medium effect sizes are those between .50 and .79, and high effect sizes are those larger than .80. Pearson product–moment correlations were carried out between ADHD symptoms and test scores separately for controls and patients.

Results

Comparison Between Medicated and Nonmedicated Patients in Demographic Variables, Mood, and ADHD Symptoms

Initially, we compared performance of nonmedicated and medicated patients in terms of demographic variables, IQ, mood, symptoms of inattention, hyperactivity/impulsivity (Table 1), and executives test scores (Table 2). There were no differences between groups in demographic variables (all ps > .25), mood (all ps > .20) and ADHD symptoms (all ps > .64). We also verified that there were no differences between groups in their performance on most of executive function tests (ps > .12) except for the dual task for which we found a trend of better performance for the medicated patients with a medium effect size (p = .07; g = −.61). Overall, these data demonstrate that the chronic use of methylphenidate does not seem to alter ADHD symptoms or executive functioning when patients are not under the acute effects of the drug. As a consequence of this similarity between ADHD groups, the data were collapsed and compared with those of controls in other GLMs.

Table 1.

Mean (Standard Deviation) of Demographic and Affective Symptoms Per Group (Nonmedicated and Medicated Patients With ADHD and Controls), and Statistical Information of the General Linear Models.

Data	Control (n = 20)	Nonmedicated ADHD (n = 14)	Medicated ADHD (n = 34)	F(1, 46) Nonmedicated ADHD × Medicated ADHD	p	F(1, 66) Controls × All ADHD	p
Demographical
Age (years)	28.4 (5.4)	32.4 (6.2)	30.2 (8.1)	0.35	.55	1.80	.18
Education (years)	16.0 (2.5)	15.4 (3.2)	14.8 (3.1)	1.32	.26	1.64	.21
Nonverbal intelligence quotient–Raven (correct responses)	53.7 (5.2)	50.1 (5.3)	50.7 (6.3)	0.20	.66	1.35	.27
Mood (score)
Beck Depression Inventory^a	7.2 (6.3)	16.1 (8.3)	13.5 (8.4)	1.54	.22	11.79	.001
State–Trait Anxiety Inventory^a	39.2 (6.3)	55.9 (11.9)	52.5 (10.8)	1.66	.20	29.15	<.001
ASRS (score)
Inattention^a	13.4 (4.5)	28.4 (5.4)	28.7 (4.7)	0.05	.95	4.12	.046
Hyperactivity-impulsivity^a	13.3 (4.9)	21.7 (7.8)	23.2 (6.6)	0.22	.64	30.93	<.001

Note. ASRS = Adult Self-Report Scale.

ADHD patients (medicated and nonmedicated) presented more symptoms than controls.

Table 2.

Mean (Standard Deviation) Scores in the Executive Domains Per Group (Nonmedicated and Medicated Patients With ADHD), Statistical Information of the General Linear Models, and Effect Sizes (Hedges’s g).

Task—EXECUTIVE DOMAIN	Nonmedicated ADHD (n = 14)	Medicated ADHD (n = 34)	F(1, 46)	p	g
Plus Minus—SHIFTING
Shifting cost (s)	165.7 (41.0)	183.5 (87.0)	0.53	.47	−.23
Shifting cost errors (n)	12.8 (17.1)	14.1 (15.9)	0.06	.80	−.08
Dual task—DUAL TASK
Mu index (%)	90.5 (17.6)	100.8 (16.3)	3.54	.07	−.61
Zoo map task–PLANNING
Planning + execution (s)	220.8 (267.2)	286.8 (249.8)	0.67	.42	−.25
Fluency—ACCESS TO LTM
Phonemic fluency (n)	24.9 (6.4)	23.3 (4.5)	1.05	.31	.31
Semantic fluency (n)	30.6 (6.1)	30.1 (4.8)	0.10	.76	.09
RNG—UPDATING
Mean repetition gap	8.7 (0.3)	8.7 (0.3)	0.19	.67	zero
Coupon	19.9 (9.9)	21.3 (10.8)	0.33	.57	−.13
Redundancy	1.9 (2.0)	1.5 (1.1)	0.38	.54	.28
RNG—INHIBITION
TPI	95.5 (13.4)	98.2 (14.6)	2.46	.57	−.19
Runs	1.0 (0.4)	0.9 (0.4)	1.39	.72	.25
Adjacency combined	17.9 (7.8)	20.4 (10.0)	1.65	.46	−.26

Note. LTM = long-term memory; RNG = random number generation; TPI = Turning Point Index.

Comparison Between Patients and Controls in Demographic Variables, Mood, and ADHD Symptoms

Patients and control groups were similar in terms of age, education, and IQ (all ps > .18). Therefore, differences in performance could not be attributed to these characteristics.

The same analysis also showed that the scores of symptoms of inattention, F(1, 66) = 4.12, p < .05, and hyperactivity/impulsivity, F(1, 66) = 30.93, p < .001, evaluated by ASRS were higher for the ADHD group than for the control group, as expected. In addition, patients reported more depression and anxiety symptoms, as assessed by the Beck Depression Inventory, F(1, 66) = 11.79, p = .001, and Trait Anxiety Inventory, F(1, 66) = 29.15, p < .001, respectively.

Regarding executive functioning (Table 3), errors in the fluency tasks and the zoo map task were very low and scores contained mainly zeros, so they were not statistically analyzed. Patients performed worse on the shifting cost measure considering the time to complete the plus–minus task (cost shifting to time); F(1, 66) = 4.39, p = .04; Hedges’s g = .55, and on the total number of words generated in the phonemic fluency task, F(1, 66) = 5.17, p < .03; Hedges’s g = .59. These were not the last tasks in the test battery, so fatigue cannot explain these results. The other variables showed no significant or near-significant effects (all ps > .12).

Table 3.

Mean (Standard Deviation) Scores in the Executive Domains Per Group (Collapsed Nonmedicated and Medicated Patients With ADHD and Controls), Statistical Information of the General Linear Models, and Effect Sizes (Hedges’s g).

Task—EXECUTIVE DOMAIN	Controls (n = 20)	ADHD (n = 48)	F(1, 66)	p	g
Plus Minus—SHIFTING
Shifting cost (s)^a	138.6 (56.2)	178.3 (76.5)	4.39	.04	−.55
Shifting cost errors (n)	11.0 (9.9)	13.7 (16.1)	0.48	.49	−.18
Dual task—DUAL TASK
Mu index (%)	85.2 (9.6)	91.1 (21.0)	1.45	.23	−.32
Zoo Map task—PLANNING
Planning + execution (s)	205.4 (144.9)	159.8 (225.5)	0.69	.41	.22
Fluency—ACCESS TO LTM
Phonemic fluency (n)^a	26.9 (5.4)	23.8 (5.1)	5.17	.03	.59
Semantic fluency (n)	31.4 (5.7)	30.2 (5.1)	0.66	.42	.22
RNG—UPDATING
Mean repetition gap	7.6 (7.7)	7.6 (0.8)	0.05	.82	zero
Coupon	19.0 (3.9)	20.9 (10.5)	0.83	.37	−.21
Redundancy	1.5 (1.1)	1.6 (1.4)	0.16	.69	−.07
RNG—INHIBITION
TPI	103.2 (8.4)	97.5 (14.2)	2.46	.12	.44
Runs	0.8 (0.4)	0.9 (0.4)	1.39	.24	−.25
Adjacency combined	16.6 (8.5)	19.7 (9.4)	1.65	.20	−.33

Note. LTM = long-term memory; RNG = random number generation test; TPI = Turning Point Index.

ADHD impaired in relation to controls; For details on the calculations of measures see methods section.

The correlations between symptoms of depression, anxiety, inattention, and hyperactivity/impulsivity and executive functions were mostly low and nonsignificant and did not occur for the variables that showed differences between patients and controls. Among patients, the only significant correlations were between inattention and errors on the shifting cost measure (r = −.29, p = .05). For controls, there were significant correlations between inattention and the RNG indexes mean repetition gap (r = .47, p = .05), runs (r = −.55, p = .01) and adjacency (r = −.55, p = .01). There were not correlations between, hyperactivity/impulsivity, depression, nor anxiety symptoms and executive function performance for patients nor controls.

Discussion

The aim of this study was to compare the performance of ADHD patients and controls considering the fractionation of executive functions. Because the use of medication for this disorder (methylphenidate) can acutely alter executive functioning (Advokat, 2010; MTA Cooperative Group, 1999), we had medicated patients abstain from the use of this drug on the day of testing. With respect to the effects of chronic use of methylphenidate, we confirmed our predictions that that medicated and nonmedicated patients would not differ in general in terms of ADHD symptoms, mood, and executive performance, which is not surprising because this medication is for symptomatic treatment (Adler et al., 2009). Regarding executive performance in ADHD in comparison with controls, we corroborated our hypothesis of specific deficits in shifting and access to long-term memory which reached medium effect sizes, indicating their clinical relevance. No changes in inhibition measures were found, confirming that ADHD-induced executive deficits are not related to an impairment in this general executive ability (see Sonuga-Barke, 2010).

Despite overall lack of differences between medicated and nonmedicated patients, we found a tendency of difference with a medium effect size in the dual task. Even in the participants on extended-release formulation, after a period of 24 hr without methylphenidate, there should be no residual acute effects of this drug because of its short half-life. Duration of action of these formulations does not last for more than 12 hr (Coghill et al., 2013). Indeed, the review by Brams, Moon, Pucci, and López (2010) showed that cognitive effects lasted only 8 hr with long-acting methylphenidate. Hence, considering that there are very few studies that evaluated long-term treatment effects of methylphenidate on cognitive performance (see Hervey et al., 2004), this finding deserves further investigation as it may reveal a nonacute positive effect on neuropsychological functioning. Nevertheless, overall, we found that most executive domains were unaltered by chronic treatment with methylphenidate indicating that it improves skills needed to cope with the demands of everyday life (Hazell, 2011) while patients are under its acute effect. However, this enhancement is no longer present when blood concentrations fall below a certain threshold (Huang et al., 2012), with a possible exception in dual-task performance.

A comparison of patients and controls showed that ADHD can elicit selective effects on specific domains of executive function. As proposed, we showed that shifting cost, a measure of executive switching, was impaired in ADHD in accord with previous findings with other tests that measure a similar construct, such as the set-shifting measure from the color word interference test (Halleland et al., 2012), response to a change task (Boonstra et al., 2010), and the trail making or similar tests (Boonstra et al., 2005; Marchetta et al., 2008; Pazvantoglu et al., 2012; Rohlf et al., 2012; Seidman, 2006, for a review; Woods et al., 2002).

Nevertheless, it must be noted that in the ADHD literature, in some cases executive switching has not been found to be impaired (Boonstra et al., 2010; Mesquita et al., 2010; Miller et al., 2012; Walker, Shores, Trollor, Lee, & Sachdev, 2000), possibly due to the multifaceted nature of this domain (see Miyake & Friedman, 2012). This may stem from the characteristics of the tests used, which vary and can recruit different brain areas. While some tests are concerned with measuring an individual’s ability to change their strategies according to the contingencies of reinforcement, other tasks involve alternating (switching) between two different types of tasks (see Kramer et al., 2007), as was the case in the present study.

Apart from the executive switching measure, we also showed that ADHD patients were impaired in the measure of access to long-term memory (phonemic fluency) as hypothesized, similarly to other studies in the literature (Boonstra et al., 2005; Tucha et al., 2005; Woods et al., 2002). However, unlike Tucha et al. (2005) and Woods et al. (2002), we found no ADHD-induced deficits in semantic fluency (Boonstra et al., 2005). A possible explanation for this is that phonemic fluency is more sensitive to ADHD because it seems to be more dependent on frontal/executive functioning than semantic fluency (see Ho et al., 2002; Troyer, Moscovitch, Winocur, Alexander, & Stuss, 1998; Troyer, Moscovitch, Winocur, Leach, & Freedman, 1998).

Regarding other executive domains, our results corroborated those of previous studies of no changes in the updating n-back task (Valera, Faraone, Biederman, Poldrack, & Seidman, 2005), dual tasking (MacLaren, Taukulis, & Best, 2007), or planning (Boonstra et al., 2010; Marchetta et al., 2008; Murphy, 2002; Riccio, Wolfe, Romine, Davis, & Sullivan, 2004; Seidman, Biederman, Weber, Hatch, & Faraone, 1998). Reimer, Mehler, D’Ambrosio, and Fried (2010) found that ADHD patients were impaired in terms of driving skills when conducting a secondary task (talking on the phone); however, this dual task did not involve activities that tap separate memory systems (see Baddeley, 1992), so their results may have been due to the overloading of a particular system and not necessarily to the coordination of multiple independent processes. Planning has been assessed in various ways and has been found to be impaired in adult ADHD patients in some cases (Schreiber et al., 1999). However, unlike the Zoo Map task used here, these measures involved the copy strategy of the Rey-Osterrieth Complex Figure (ROCF), which may have been impaired in the ADHD patients with regard to configural accuracy and neatness (Schreiber et al., 1999) and not planning itself. Furthermore, the ROCF seems to constitute a global cognitive measure, as it involves multiple domains (Miller et al., 2012).

Importantly, our study and many other ADHD-related publications found inhibition not to be impaired in ADHD patients (Bekker et al., 2005; Boonstra et al., 2010; Boonstra et al., 2005; Miller et al., 2012). This result contradicts the idea proposed by others that ADHD elicits a specific deficit in this domain (Barkley, 1997b; Bekker et al., 2005; Boonstra et al., 2010) as discussed by Sonuga-Barke (2010). While we did not find a change in the inhibition indexes of the RNG test, Miller et al. (2012), Boonstra et al. (2005), and Boonstra et al. (2010) found an increase in commission errors on the Conners’ Continuous Performance Test (CCPT) in ADHD patients, whereas Bekker et al. (2005) found a slowed performance by ADHD patients on reaction times via the Stop Signal Task. It may be that these measures are more sensitive to ADHD (Woods et al., 2002) than the inhibition indexes of the RNG, or that the inhibition of motor control (see Heinrich, Hoegl, Moll, & Kratz, 2014), involved in these task but not in the RNG test, is specifically affected in this disorder. This must be further explored in future studies.

The lack of effects on inhibition, updating, dual tasking, and planning may explain why several publications highlight a lack of executive impairment in adult ADHD patients (e.g., Biederman et al., 2008; Gawrilow, Merkt, Goossens–Merkt, Bodenburg, & Wendt, 2011; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005) because few studies have accounted for the fractionation of executive functions.

ADHD patients had more symptoms of depression and anxiety compared with healthy participants, corroborating previous studies (Gawrilow et al., 2011; Kessler et al., 2006; Michielsen et al., 2013; Sandra Kooij, 2012; Sobanski, 2006), as well as more intense ratings of inattention, hyperactivity, and impulsivity evaluated by the ASRS, as expected (Greydanus, Pratt, & Patel, 2007; Mattos et al., 2006; Polanczyk, de Lima, Horta, Biederman, & Rohde, 2007; Valera et al., 2010). Nevertheless, the selective executive effects found here were not correlated with any of these symptoms, suggesting that they are not secondary to mood, inattention, hyperactivity, and impulsivity changes in these patients as suggested by Nigg et al. (2005). It cannot be excluded, however, that other ADHD symptoms that are not listed in the ASRS, such as emotional symptoms and disorganization, would have been correlated with impaired executive performance (see Rösler, Retz, & Stieglitz, 2010). Among all executive tasks, the only significant linear correlation that appeared in ADHD patients was between inattention and shifting cost errors, a measure that unlike shifting cost time did not differentiate patients from controls. This correlation was low (smaller than 0.30) but may nevertheless indicate that inattention in this disorder has a part to play in executive shifting performance. Inattention was also significantly correlated in a moderate way to various RNG indexes in control participants (correlation of approximately 0.50), suggesting that in the normal range of attentional performance this task is more clearly related to subjective attention. Hyperactivity/impulsivity, depression, and anxiety ratings did not explain these effects either as they did not correlate with executive performance significantly. Hence, ADHD symptoms, depression, and anxiety do not seem to be responsible for the ADHD effects on shifting and access to long-term memory.

In sum, we found a very similar pattern of executive performance between adult ADHD patients treated with methylphenidate who were not under acute effects of this drug and those under no pharmacological intervention. The most sensitive executive measures to ADHD were shifting and access to long-term memory and these effects were not secondary to the mains subjective ADHD symptomatology, or to a general impairment in executive inhibition. This suggest that considering the fractionation of executive functions is an valid approach in studying ADHD-induced cognitive alterations which has the potential to aid in the identification of specific deficits in this disorder that may ultimately lead to the development of novel treatments.

Limitations to our results must be pointed out, especially the small sample size which, however, was large enough to point to two executive domains that differentiate adult ADHD patients and controls. Thus, it cannot be excluded that the other domains can also be affected by this disorder in studies with higher power. It should be borne in mind, however, that many prior investigations have failed to show executive effects of ADHD in adults as occurred here for most domains. The use of a matched sample of control participants would have been ideal, but healthy individuals have less interest in being cognitively evaluated than clinical populations, so our sample of controls was smaller. We tried to circumvent this by carefully selecting groups of ADHD patients and healthy individuals that were equivalent in many sociodemographic indexes and IQ and determining correlation between depression, anxiety, mood, and ADHD symptoms, which differed between groups, with executive performance. Overall, patients’ scores were more heterogeneous which is not surprising as their performance in most tasks would have been affected by their more intense inattention and hyperactivity-impulsivity symptoms than those of controls. Until recently, this could have been interpreted as due to the inclusion of patients with different ADHD subtypes in the same group, but new guidelines no longer propose this as valid because these subtypes have not been shown to be developmentally stable and to constitute separate clinical representations (see Asherson et al., 2014). Despite this, there is an increasing body of literature that points to the heterogeneous nature of ADHD (see Sonuga-Barke, 2010), which may lead to a different categorization of subtypes that are as yet unrecognized and may have different executive functions profiles. In addition, the results may have differed had we assessed older participants, groups with different proportions of men and women, patients with more comorbidities or who used other medications. Finally, except for the Zoo Map task, the other tests used here are not ecological, so it remains to be determined whether and to what extent the executive deficits found here extend to daily activities.

Conclusion

Overall, our results showed that medicated and nonmedicated ADHD patients who are not under the acute effects of methylphenidate do not show significant differences in six separable executive domains. In contrast, ADHD patients exhibited selective executive impairment compared with controls in the domains of shifting and access to long-term memory, effects that were not secondary to subjective symptoms of ADHD, nor to impairment in executive inhibition. Hence, considering the fractionation of executive functions is important when characterizing ADHD-induced cognitive changes.

Footnotes

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: Professor Mario Louzã has served on an Advisory Board as a lecturer and has received grants unrelated to his contribution in this article from Janssen-Cilag, Novartis, and Shire.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by FAPESP (Project 2011/08547-3), Associação Fundo de Incentivo à Pesquisa, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). Sabine Pompeia receives a research grant from Conselho Nacional de Pesquisa (CNPq). All the above are nonprofit organizations that sponsor research in Brazil.

Author Biographies

Viviane Freire Bueno, PhD, is a clinical psychologist and a cognitive neuroscientist. She is a postdoctoral student at the Departamento de Psicobiologia at Universidade Federal de São Paulo. Her main research interests include attentional and emotional processes.

Maria Aparecida da Silva is a psychiatrist at Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo.

Tânia Maria Alves is a psychiatrist at Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo.

Mario Rodrigues Louzã is the coordinator of the Programa Déficit de Atenção e Hiperatividade no adulto (PRODATH) and psychiatrist at the Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo.

Sabine Pompéia, PhD, is a biologist and adjunct professor from the Departamento de Psicobiologia at the Universidade Federal de São Paulo. Her research has focused on human cognition, especially working memory.

References

Adler

L. A.

Zimmerman

Starr

H. L.

Silber

Palumbo

Orman

Spencer

(2009). Efficacy and safety of OROS methylphenidate in adults with attention-deficit/hyperactivity disorder: A randomized, placebo-controlled, double-blind, parallel group, dose-escalation study. Journal of Clinical Psychopharmacology, 29, 239-247.

Advokat

(2010). What are the cognitive effects of stimulant medications? Emphasis on adults with attention-deficit/hyperactivity disorder (ADHD). Neuroscience and Biobehavioral Reviews, 34, 1256-1266.

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author.

Andrade

Gorenstein

Vieira Filho

A. H.

Tung

T. C.

Artes

(2001). Psychometric properties of the Portuguese version of the State-Trait Anxiety Inventory applied to college students, factor analysis and relation to the Beck Depression Inventory. Brazilian Journal of Medical and Biological Research, 34, 367-374.

Armstrong

I. T.

Munoz

D. P.

(2003). Attentional blink in adults with attention-deficit hyperactivity disorder influence of eye movements. Experimental Brain Research, 152, 243-250.

Asherson

Manor

Huss

(2014). Attention-deficit/hyperactivity disorder in adults: Update on clinical presentation and care. Neuropsychiatry, 4, 109-126.

Baddeley

(1992). Working memory. Science, 255(5044), 556-559.

Baddeley

Della Sala

Gray

Papagno

Spinnler

(1997). Testing central executive functioning with a pencil-and-paper test. In Rabbitt

P. M.

(Ed.), Methodology of frontal and executive function (pp. 61-80). Hove, UK: Lawrence Erlbaum.

Barkley

R. A.

(1997a). Attention-deficit/hyperactivity disorder. In Mash

E. J.

Terdal

L. G.

(Eds.), Assessment of childhood disorders (pp. 71-129). New York, NY: Guilford Press.

10.

Barkley

R. A.

(1997b). Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121, 65-94.

11.

Barkley

R. A.

(2000). Genetics of childhood disorders: XVII. ADHD, part 1: The executive functions and ADHD. Journal of the American Academy of Child and Adolescent Psychiatry, 39, 1064-1068.

12.

Barkley

R. A.

(2002). Major life activity and health outcomes associated with attention deficit/hyperactivity disorder. Journal of Clinical Psychiatry, 63(Suppl. 12), 10-15.

13.

Beck

A. T.

Steer

R. A.

Garbin

M. G.

(1988). Psychometric properties of the Beck Depression Inventory twenty-five years of evaluation. Clinical Psychology Review, 8, 77-100.

14.

Beck

A. T.

Ward

C. H.

Mendelson

Mock

Erbaugh

(1961). An inventory for measuring depression. Archives of General Psychiatry, 4, 53-63.

15.

Bekker

E. M.

Overtoom

C. C. E.

Kooij

J. J. S.

Buitelaar

J. K.

Verbaten

M. N.

Kenemans

J. L.

(2005). Disentangling deficits in adults with attention-deficit/hyperactivity disorder. Archives of General Psychiatry, 62, 1129-1136.

16.

Biaggio

A. M. B.

Spielberger

C. D.

(1980). Manual do Inventário de Ansiedade Traço-Estado: IDATE [Manual of the state-trait inventory: IDATE]. Rio de Janeiro, Brazil: CEPA.

17.

Biederman

Petty

C. R.

Fried

Black

Faneuil

Doyle

A. E.

. . .Faraone

S. V.

(2008). Discordance between psychometric testing and questionnaire-based definitions of executive function deficits in individuals with ADHD. Journal of Attention Disorders, 12, 92-102.

18.

Boonstra

A. M.

Kooij

J. J.

Sergeant

J. A.

Buitelaar

J. K.

(2010). To act or not to act, that’s the problem: Primarily inhibition difficulties in adult ADHD. Neuropsychology, 24, 209-221.

19.

Boonstra

A. M.

Oosterlaan

Sergeant

J. A.

Buitelaar

J. K.

(2005). Does methylphenidate improve inhibition and other cognitive abilities in adults with childhood-onset ADHD? Journal of Clinical and Experimental Neuropsychology, 27, 278-298.

20.

Borges

J. G.

Ginani

G. E.

Hachul

Cintra

F. D.

Tufik

Pompéia

(2013). Executive functioning in obstructive sleep apnea syndrome patients without comorbidities: Focus on the fractionation of executive functions. Journal of Clinical and Experimental Neuropsychology, 35, 1094-1107.

21.

Brams

Moon

Pucci

López

F. A.

(2010). Duration of effect of oral long-acting stimulant medications for ADHD throughout the day. Current Medical Research and Opinion, 26, 1809-1825.

22.

Brown

T. E.

(2009). ADD/ADHD and impaired executive function in clinical practice. Current Attention Disorder Reports, 1, 37-41.

23.

Campos

(2003). Teste das Matrizes Progressivas—Escala Geral [Raven’s progressive matrices—General Scale]. Rio de Janeiro, Brazil: CEPA.

24.

Coghill

Banaschewski

Zuddas

Pelaz

Gagliano

Doepfne

(2013). Long-acting methylphenidate formulations in the treatment of attention-deficit/hyperactivity disorder: A systematic review of head-to-head studies. BMC Psychiatry, 13, Article 237.

25.

Cunha

J. A.

(2001). Manual da versão em português das Escalas Beck [Manual of the Portuguese version of the Beck Scales]. São Paulo, Brazil: Casa do Psicólogo.

26.

Della Sala

Cocchini

Logie

R. H.

MacPherson

S. E.

(2010). Dual task during encoding, maintenance and retrieval in Alzheimer disease and healthy ageing. Journal of Alzheimer’s Disease, 19, 503-515.

27.

Dige

Maahr

Backenro-Ohsako

(2008). Memory tests in subgroups of adult attention deficit hyperactivity disorder reveals simultaneous capacity deficit. International Journal of Neuroscience, 118, 569-591.

28.

Faraone

S. V.

Biederman

Spencer

Wilens

Seidman

L. J.

Mick

Doyle

A. E.

(2000). Attention-deficit/hyperactivity disorder in adults: An overview. Biological Psychiatry, 48, 9-20.

29.

Fisk

J. E.

Sharp

C. A.

(2004). Age-related impairment in executive functioning: Updating, inhibition, shifting, and access. Journal of Clinical and Experimental Neuropsychology, 7, 874-890.

30.

Friedman

N. P.

Miyake

(2004). The relations among inhibition and interference control functions: A latent-variable analysis. Journal of Experimental Psychology: General, 133, 101-135.

31.

Friedman

N. P.

Miyake

Young

S. E.

Defries

J. C.

Corley

R. P.

Hewitt

J. K.

(2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137, 201-225.

32.

Gawrilow

Merkt

Goossens–Merkt

Bodenburg

Wendt

(2011). Multitasking in adults with ADHD. Attention Deficit and Hyperactivity Disorders, 3, 253-264.

33.

Ginani

G. E.

Tufik

Bueno

O. F.

Pradella-Hallinan

Rusted

Pompéia

(2011). Acute effects of donepezil in healthy young adults underline the fractionation of executive functioning. Journal of Psychopharmacology, 25, 1508-1516.

34.

Greydanus

D. E.

Pratt

H. D.

Patel

D. R.

(2007). Attention deficit hyperactivity disorder across the lifespan: The child, adolescent, and adult. Disease a Month, 53, 70-131.

35.

Gualtieri

C. T.

Wargin

Kanoy

Patrick

Shen

C. D.

Young-Blood

. . .Breese

G. R.

(1982). Clinical studies of methylphenidate serum levels in children and adults. Journal of the American Academy of Child Psychiatry, 21, 19-26.

36.

Halleland

H. B.

Haavik

Lundervold

A. J.

(2012). Set-shifting in adults with ADHD. Journal of the International Neuropsychological Society, 18, 728-737.

37.

Hazell

(2011). The challenges to demonstrating long-term effects of psychostimulant treatment for attention-deficit/hyperactivity disorder. Current Opinion in Psychiatry, 24, 286-290.

38.

Hedges

(1981). Distribution theory for Glass’s estimator of effect size and related estimators. Journal of Educational Statistics, 6, 107-128.

39.

Heinrich

Hoegl

Moll

G. H.

Kratz

(2014). A bimodal neurophysiological study of motor control in attention-deficit hyperactivity disorder: A step towards core mechanisms? Brain, 137(Pt. 4), 1156-1166.

40.

Hervey

A. S.

Epstein

J. N.

Curry

J. F.

(2004). Neuropsychology of adults with attention-deficit/hyperactivity disorder: A meta-analytic review. Neuropsychology, 18, 485-503.

41.

A. K.

Sahakian

B. J.

Robbins

T. W.

Barker

R. A.

Rosser

A. E.

Hodges

J. R.

(2002). Verbal fluency in Huntington’s disease: A longitudinal analysis of phonemic and semantic clustering and switching. Neuropsychologia, 40, 1277-1284.

42.

Huang

Y. S.

Wang

L. J.

Chen

C. K.

(2012). Long-term neurocognitive effects of methylphenidate in patients with attention deficit hyperactivity disorder, even at drug-free status. BMC Psychiatry, 12, Article 194.

43.

Kessler

R. C.

Adler

Ames

Demler

Faraone

Hiripi

. . .Walters

E. E.

(2005). The World Health Organization Adult ADHD Self-Report Scale (ASRS). Psychological Medicine, 35, 245-256.

44.

Kessler

R. C.

Adler

Barkley

Biederman

Conners

C. K.

Demler

. . .Zaslavsky

A. M.

(2006). The prevalence and correlates of adult ADHD in the United States: Results from the National Comorbidity Survey Replication. The American Journal of Psychiatry, 163, 716-723.

45.

King

J. A.

Colla

Brass

Heuser

Von Cramon

D. Y.

(2007). Inefficient cognitive control in adult ADHD: Evidence from trial-by-trial Stroop test and cued task switching performance. Behavioral and Brain Functions, 3, Article 42.

46.

Kramer

J. H.

Quitania

Dean

Neuhaus

Rosen

H. J.

Halabi

. . .Miller

B. L.

(2007). Magnetic resonance imaging correlates of set shifting. Journal of the International Neuropsychological Society, 13, 386-392.

47.

Lezak

M. D.

Howieson

D. B.

Loring

D. W.

(2004). Neuropsychological assessment (4th ed.). New York, NY: Oxford University Press.

48.

Logie

R. H.

Cocchini

Della Sala

Baddeley

A. D.

(2004). Is there a specific executive capacity for dual task co-ordination? Evidence from Alzheimer’s disease. Neuropsychology, 18, 504-513.

49.

MacLaren

V. V.

Taukulis

H. K.

Best

L. A.

(2007). Inhibition in adults with attention deficit/hyperactivity disorder: Event-related potentials in the stop task. Applied Psychophysiology and Biofeedback, 32, 155-162.

50.

Marchetta

N. D. J.

Hurks

P. P. M.

Krabbendam

Jolles

(2008). Interference control, working memory, concept shifting, and verbal fluency in adults with attention-deficit/hyperactivity disorder (ADHD). Neuropsychology, 22, 74-84.

51.

Mattos

Segenreich

Saboya

Louzã

Dias

Romano

(2006). Adaptação transcultural da escala ASRS-18 (versão1.1) para avaliação do transtorno de déficit de atenção e hiperatividade em adultos para o português [Transcultural adaptation of the Adult Self-Report Scale into Portuguese for evaluation of adult attention-deficit/hyperactivity disorder]. Revista de Psiquiatria Clínica, 33, 188-194.

52.

Mesquita

Coutinho

Mattos

(2010). Neuropsychological profile of adults with attention deficits: Differences between ADHD and clinical controls. Revista de Psiquiatria Clínica, 37, 212-215.

53.

Michielsen

Comijs

H. C.

Semeijn

E. J.

Beekman

A. T.

Deeg

D. J.

Sandra Kooij

J. J.

(2013). The comorbidity of anxiety and depressive symptoms in older adults with attention-deficit/hyperactivity disorder: A longitudinal study. Journal of Affective Disorders, 148, 220-227.

54.

Miller

Hinshaw

S. P.

(2012). Executive functions in girls with ADHD followed prospectively into young adulthood. Neuropsychology, 26, 278-287.

55.

Miyake

Friedman

N. P.

(2012). The nature and organization of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science, 21, 8-14.

56.

Miyake

Friedman

N. P.

Emerson

M. J.

Witzki

A. H.

Howerter

Wager

T. D.

(2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49-100.

57.

MTA Cooperative Group. (1999). 14-month randomized clinical trial of treatment strategies for attention deficit hyperactivity disorder. Archives of General Psychiatry, 56, 1073-1086.

58.

Murphy

(2002). Cognitive functioning in adults with attention-deficit/hyperactivity disorder. Journal of Attention Disorders, 5, 203-209.

59.

Nigg

Stavro

Ettenhofer

Hambrick

D. Z.

Miller

Henderson

J. M.

(2005). Executive functions and ADHD in adults: Evidence for selective effects on ADHD symptom domains. Journal of Abnormal Psychology, 114, 706-717.

60.

Owen

A. M.

(1997). Cognitive planning in humans: Neuropsychological, neuroanatomical and neuropharmacological perspectives. Progress in Neurobiology, 53, 431-450.

61.

Pazvantoglu

Aker

A. A.

Karabekiroglu

Akbas

Sarısoy

Baykal

. . .Sahin

A. R.

(2012). Neuropsychological weaknesses in adult ADHD: Cognitive functions as core deficit and roles of them in persistence to adulthood. Journal of the International Neuropsychological Society, 18, 819-826.

62.

Polanczyk

de Lima

M. S.

Horta

B. L.

Biederman

Rohde

L. A.

(2007). The worldwide prevalence of ADHD: A systematic review and metaregression analysis. The American Journal of Psychiatry, 164, 942-948.

63.

Raven

J. C.

(1947). Guide to using progressive matrices. London, England: H.K. Lewis.

64.

Reimer

Mehler

D’Ambrosio

L. A.

Fried

(2010). The impact of distractions on young adult drivers with attention deficit hyperactivity disorder (ADHD). Accident Analysis & Prevention, 42, 842-851.

65.

Riccio

C. A.

Wolfe

M. E.

Romine

Davis

Sullivan

J. R.

(2004). The Tower of London and neuropsychological assessment of ADHD in adults. Archives of Clinical Neuropsychology, 19, 661-671.

66.

Rohlf

Jucksch

Gawrilow

Huss

Hein

Lehmkuhl

Salbach-Andrae

(2012). Set shifting and working memory in adults with attention-deficit/hyperactivity disorder. Journal of Neural Transmission, 119, 96-106.

67.

Rösler

Retz

Stieglitz

R. D.

(2010). Psychopathological rating scales as efficacy parameters in adult ADHD treatment investigations—Benchmarking instruments for international multicentre trials. Pharmacopsychiatry, 43(3), 92-98.

68.

Sandra Kooij

J. J.

(2012). Adult ADHD: Diagnostic assessment and treatment. London, England: Springer-Verlag.

69.

Schreiber

H. E.

Javorsky

D. J.

Robinson

J. E.

Stern

R. A.

(1999). Rey-Osterrieth Complex Figure performance in adults with attention deficit hyperactivity disorder: A validation study of the Boston Qualitative Scoring System. The Clinical Neuropsychologist, 13, 509-520.

70.

Seidman

L. J.

(2006). Neuropsychological functioning in people with ADHD across the lifespan. Clinical Psychology Review, 26, 466-485.

71.

Seidman

L. J.

Biederman

Weber

Hatch

Faraone

(1998). Neuropsychological functioning in adults with attention-deficit hyperactivity disorder. Biological Psychiatry, 44, 260-268.

72.

Shallice

(1982). Specific impairments of planning. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 298(1089), 199-209.

73.

Sobanski

(2006). Psychiatric comorbidity in adults with attention-deficit/hyperactivity disorder (ADHD). European Archives of Psychiatry & Clinical Neuroscience, 256(Suppl. 1), i26-i31.

74.

Sonuga-Barke

E. J.

(2010). Disambiguating inhibitory dysfunction in attention-deficit/hyperactivity disorder: Toward the decomposition of developmental brain phenotypes. Biological Psychiatry, 67, 599-601.

75.

Spielberger

C. D.

Gorsuch

R. L.

Lushene

R. E.

(1970). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press.

76.

Towse

J. N.

Neil

(1998). Analyzing human random generation behavior: A review of methods used and a computer program for describing performance. Behavior Research Methods, Instruments, & Computers, 30, 583-591.

77.

Troyer

A. K.

Moscovitch

Winocur

Alexander

M. P.

Stuss

(1998). Clustering and switching on verbal fluency: The effects of focal frontal- and temporal-lobe lesions. Neuropsychologia, 36, 499-504.

78.

Troyer

A. K.

Moscovitch

Winocur

Leach

Freedman

(1998). Clustering and switching on verbal fluency tests in Alzheimer’s and Parkinson’s disease. Journal of the International Neuropsychological Society, 4, 137-143.

79.

Tucha

Mecklinger

Laufkötter

Kaunzinger

Paul

G. M.

Klein

H. E.

Lange

K. W.

(2005). Clustering and switching on verbal and figural fluency functions in adults with attention deficit hyperactivity disorder. Cognitive Neuropsychiatry, 10, 231-248.

80.

Valera

E. M.

Faraone

S. V.

Biederman

Poldrack

R. A.

Seidman

L. J.

(2005). Functional neuroanatomy of working memory in adults with attention-deficit/hyperactivity disorder. Biological Psychiatry, 57, 439-447.

81.

Valera

E. M.

Spencer

R. M. C.

Zeffiro

T. A.

Makris

Spencer

T. J.

Faraone

. . .Seidman

L. J.

(2010). Neural substrates of impaired sensorimotor timing in adult attention-deficit/hyperactivity disorder. Biological Psychiatry, 68, 359-367.

82.

Vaz

Pradella-Hallinan

Bueno

O. F.

Pompéia

(2011). Acute glucocorticoid effects on the multicomponent model of working memory. Human Psychopharmacology, 26, 477-487.

83.

Walker

A. Y.

Shores

A. E.

Trollor

J. N.

Lee

Sachdev

P. S.

(2000). Neuropsychological functioning of adults with attention deficit hyperactivity disorder. Journal of Clinical and Experimental Neuropsychology, 22, 115-124.

84.

White

H. A.

Marks

(2004). Updating memory in list-method directed forgetting: Individual differences related to adult attention-deficit/hyperactivity disorder. Personality and Individual Differences, 37, 1453-1462.

85.

Willcutt

E. G.

Doyle

A. E.

Nigg

J. T.

Faraone

S. V.

Pennington

B. F.

(2005). Validity of the executive function theory of attention-deficit/hyperactivity disorder: A meta-analytic review. Biological Psychiatry, 57, 1336-1346.

86.

Wilson

B. A.

Alderman

Burgess

P. W.

Emslie

Evans

J. J.

(1996). Behavioural Assessment of the Dysexecutive Syndrome. Bury St. Edmunds, UK: Thames Valley Test Company.

87.

Woods

S. P.

Lovejoy

D. W.

Stutts

M. L.

Ball

J. D.

Fals-Stewart

(2002). Comparative efficiency of a discrepancy analysis for the classification of attention-deficit/hyperactivity disorder in adults. Archives of Clinical Neuropsychology, 17, 351-369.

88.

Yang

B. R.

Chan

R. C. K.

Gracia

Cao

X. Y.

Zou

X. B.

. . .Shum

D. Y.

(2011). Cool and hot executive functions in medication-naive attention deficit hyperactivity disorder children. Psychological Medicine, 41, 2593-2602.