Neuropsychological performance in adult attention-deficit hyperactivity disorder: Meta-analysis of empirical data

Archives of Clinical Neuropsychology 20 (2005) 727–744

Neuropsychological performance in adult attention-deficit hyperactivity disorder: Meta-analysis of empirical data Claudia Schoechlin ∗ , Rolf R. Engel Ludwig-Maximilians-University, Munich, Germany Accepted 9 April 2005

Abstract Attention-deficit hyperactivity disorder (ADHD) is increasingly recognized not only in children but also in adults. Neuropsychological tests are important tools to quantify the attentional and/or cognitive deficits of patients compared to controls. The present meta-analysis integrates 24 empirical studies reporting results of at least one of 50 standard neuropsychological tests comparing adult ADHD patients with controls. The 50 tests were categorized into the following 10 functional domains: verbal ability, figural problem solving, abstract problem solving, executive function, fluency, simple attention, sustained attention, focused attention, verbal memory, figural memory. For each domain a pooled effect size d was calculated. Complex attention variables and verbal memory discriminated best between ADHD patients and controls. Effect sizes for these domains were homogeneous and of moderate size (d between 0.5 and 0.6). In contrast to results reported in children, executive functions were not generally reduced in adult ADHD patients. © 2005 National Academy of Neuropsychology. Published by Elsevier Ltd. All rights reserved.

1. ADHD in adults The diagnosis of attention-deficit hyperactivity disorder (ADHD) is attracting more and more attention in adult psychiatry (National Academy for the Advancement of ADHD Care, ∗ Corresponding author. Present address: Department of Clinical Psychology and Psychophysiology, Psychiatric and Psychotherapeutic Hospital, University of Munich, Nussbaumstr. 7, D-80336 M¨unchen, Germany. Tel.: +49 89 5160 5561; fax: +49 89 5160 5562. E-mail address: [email protected] (C. Schoechlin).

0887-6177/$ – see front matter © 2005 National Academy of Neuropsychology. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.acn.2005.04.005

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2003). Long-term studies have shown that there is a rather high persistence of ADHD symptoms into adulthood (Biederman, 1998; Hill & Schoener, 1996; Mannuzza, Klein, Bessler, Malloy, & LaPadula, 1998; Yan, 1998). Epidemiological studies have suggested ADHD prevalence rates higher than supposed before (Barkley, Fischer, Smallish, & Fletcher, 2002) and state a high comorbidity with other psychiatric disorders (Hornig, 1998; Weiss & Hechtman, 1993, p. 408). ADHD in adults is accompanied by an increased risk of substance abuse, anxiety and mood disorders (Biederman, Newcorn, & Sprich, 1991; Biederman et al., 1993; Marks, Newcorn, & Halperin, 2001), as well as a disruptive family environment, which may impair offspring development (Biederman, Faraone, & Monuteaux, 2002). It accounts for social and economic problems and impairs academic achievement and work performance. In consequence, health costs increase (Barkley, 2002; Trollor, 1999). Specific medical treatments have been proposed and scientifically investigated (Wilens, Spencer, & Biederman, 2002). Adult ADHD is more difficult to diagnose than childhood ADHD because symptoms are less obvious and more unspecific. Lack of concentration, unhappiness due to emotional and organizational overload, and disinhibition-deficit as well as difficulties in affect integration may be the result or the core symptoms of ADHD, but they also occur as unspecific symptoms in depression, anxiety disorders, and personality disorders, to mention only a few. Childhood ADHD as a necessary condition for the diagnosis of adult ADHD is sometimes difficult to assess retrospectively (Mannuzza, Klein, Klein, Bessler, & Shrout, 2002; Murphy, 2003), although one study by Murphy and Schachar (2000) reported high validity figures. As a whole, adult ADHD today is judged as being a valid distinct clinical diagnosis (Spencer, Biederman, Wilens, & Faraone, 1998). The pivotal instruments most often used in the diagnostic process are observer- and self-rating scales for both children and adults. These rating instruments focus on patients’ attention, hyperactivity and other behavioral categories. Based on natural observations such as in classrooms or at home, they are easy to use with children, but less easy to implement with adults. Moreover the spectrum of behavior and complaints covered by the instruments has a large overlap with behavior sampled in other diagnostic categories. The core symptoms of ADHD are of neurocognitive nature. Neurocognitive symptoms in general can be assessed not only by observer- or self-ratings, but also by objective neuropsychological tests. In the literature on ADHD, a few studies have reported neuropsychological test results of ADHD patients compared to control groups. The studies were usually conducted with small samples of patients, and each used a different set of neuropsychological standard tests. Individual studies could therefore not establish the significance and value of neuropsychological tests in the diagnostic process; nevertheless, usefulness of neuropsychological evaluation is supported by the reviews of Woods, Lovejoy, and Ball (2002) and Gallagher and Blader (2001). The present paper reviews quantitatively the existing data by categorizing each neuropsychological measure into one of 10 neuropsychological functional domains. Published studies reporting neuropsychological test results comparing ADHD patients with a control group are analyzed by means of a meta-analysis. The aim is to review the empirical evidence that patients’ subjective complaints of cognitive deficits are reflected in objective measures of such deficits. Further, it is intended to describe the quality and extent of specific cognitive deficits of ADHD patients.

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2. Methods of meta-analysis 2.1. Studies English-, German-, and French-language literature published before December 2002 was searched for empirical studies on neuropsychological test results of ADHD patients by using Medline, Current Contents, and manual cross-referencing in existing reviews. Studies were included if they compared the neurocognitive performance, measured by neuropsychological standard tests, of clinically diagnosed ADHD patients aged 16 years or older to a control group. Thirty-seven studies were identified. Twenty-four studies were suitable for inclusion in the statistical meta-analysis. Thirteen studies had to be excluded: Eight used uncommon neuropsychological tests or experimental designs that were not comparable with other tests, and five did not present their data in enough detail. In a few studies, some but not all of the variables were uncommon (e.g. smell identification or time estimation); in these cases, only the common variables were entered into the meta-analysis. 2.2. Data reduction The 24 studies reported 104 measures using 50 standard neuropsychological tests. For each measure of each study an effect size d was calculated as a standardized performance difference between ADHD and control subjects (see below). In a first step, we assigned each measure to a functional domain, to reduce the number of measures to a manageable and interpretable size. Table 1 gives an overview of the domains, a short description and samples of the test scores allocated to them. In selecting and naming the domains our main goal was to stay with the neuropsychological nomenclature used in the studies included. Thus, the domains reflect the common concepts of the authors of the original studies as far as possible. Not all studies included the same measures, and authors’ integration of different measures mostly took place only in the discussion, were measures were discussed concerning their different functional aspects. For statistical reasons, we preferred to assign each measure to only one category, even if there might be a second category that also could fit. This especially concerns some of the measures of executive functions, which we preferred to assign to more specific categories. As a consequence of the heuristic approach used the list includes domains with a varying degree of specificity. Not unexpectedly, almost all studies included several tests of attention. We could therefore break down the attentional domain into several subdomains (simple attention, focused attention and sustained attention), where each subdomain still included many tests. On the other hand, we had to use “verbal intelligence” as a broad category to summarize the few tests measuring different verbal abilities. Thus, the domain names used should be seen as heuristic concepts reflecting what has been measured in the studies with a narrow focus in areas widely measured and a broad focus elsewhere. Secondly, for each study, single effect sizes of all test results belonging to one functional domain were averaged to obtain the domain effect sizes of the individual study. Thirdly, these domain-specific effect sizes were pooled across studies.

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Table 1 Functional neuropsychological domains and corresponding test instruments Functional domain

Description

Tests

Verbal intelligence

Verbal abilities; education-mediated knowledge

WAIS-R Similarities, information, vocabulary; reading

Executive functions

Wisconsin Card Sorting Test; Tower of Hanoi

Fluency

Planning and controlling of actions Productivity; creativity

Visual-figural problem solving

Logical structuring, problem solving, visual

WAIS-R Block Design, picture completion, picture arrangement; Rey-Osterrieth Complex Figure (accuracy; organization); Embedded Figures Test

Abstract problem solving; working memory

Logical problem solving without action

WAIS-R arithmetic; Auditory Consonant Trigrams

Simple attention

Simple attention tasks; mostly visual-motor processing; mostly speed measures

Digit span (forwards); freedom-from-distractibility (WAIS-R); Stroop Word, Color; Trail Making Test A; Visual CPT reaction time; 3RT Simple; Wechsler Memory Scale-Attention, Target Orientation Test

Sustained attention

Attention tasks that require attention over a longer period of time

CPT, different versions (MHS, X, A, Auditory); quality measures (false positives; false negatives; d’)

Focused attention

Complex attention tasks

WAIS-R digit Symbol; Digit span backwards; Stroop interference; Trail Making Test B; 3RT complex, conditional; reaction time pattern comparison, GDS distractibility, TOAD

Verbal memory

Learning and reproduction of verbally presented material

California Verbal Learning Test; Wechsler Memory Scale

Figural memory

Learning and reproduction of figural material

Rey-Osterrieth Complex Figure Test; Kimura Recurring Figures Test

Controlled Oral Word Association Test; design fluency

2.3. Effect size calculation The standard meta-analytical techniques for continuous data were used as described by Hedges and Olkin (1985) and DerSimonian and Laird (1986). Effect size d (Eq. (1)) was calculated from the statistics given in the papers, mostly means and standard deviations (S.D.s).
d = 1−




3 4N − 9

 

AMADHD − AMctrl (NADHD −1)S.D.2ctrl +(Nctrl −1)S.D.2ADHD NADHD +Nctrl −2

with AM, mean, S.D., standard deviation and N, number of patients (total).

(1)

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In mathematical terms, d represents the difference between patient and control means calibrated in pooled S.D. units. If d = 1, the magnitude of study and control group difference equals one (pooled) S.D.; d = 0.5 reflects half of a S.D. The mean effect size d reflects the average individual effect size across studies in the synthesis. As we assume a heterogeneous data set over k studies, the random effects model was applied to yield the pooled effect size d by weighting each d of study i with its standard error, corrected for possible heterogeneity by τ 2 (see Eqs. (2)–(8): k di w∗i (d)  , (2) d = i=1 k ∗ w (d) i i=1 with the weight w∗ (d) =

w(d) 1 + w(d)τ 2

(3)

and w(d) =

1 S.E.(d)2

(4)

with a standard error of d: 
 N d2 S.E.(d) = + NADHD × Nctrls 2(N − 3.94)

(5)

and τ 2 = max (T, 0)

(6)

with χ2 − k + 1  k  2 i=1 wi (d)  w (d) − k i=1 i w (d)

T = k

i=1

(7)

i

and 2 χk−1

=

k 

(di − d  ) w(d)i 2

(8)

i=1

Homogeneity of study effect sizes was assessed by the usual χ2 -test for homogeneity of d (Eq. (8); Mantel & Haenszel, 1957). As an indicator for the extent of heterogeneity I was computed as proposed by Higgins, Thompson, Deeks, and Altman (2003) and Higgins and Thompson (2002):
2  χ − (k − 1) I = max ,0 (9) χ2 

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The usual confidence intervals (CI, Eq. (10)) give information on the statistical weight of the studies. CI = d  − (1.96 × S.E.(d  ))

(10)

Fail-safe N is the number of unpublished, non-significant studies which would be necessary to render the results of a meta-analysis non-significant (P < = .05). It was calculated by: Nfs =

k(kz2 − 2.706) 2.706

(11)

with k, number of studies in the meta-analysis and z, combined z-value, as described by ClarkCarter (1997). The critical number of studies, i.e. the number of unpublished studies one could expect, is: Crit No = 5k+10

(12)

Rosenthal (1991, p. 106) argues that is unlikely that file drawers have more than five times as many studies as the reviewers. The minimum number of studies filed away is set to 15 by this formula.

3. Results 3.1. Study details and patient characteristics The 24 studies included a total of 867 ADHD patients and 806 controls. Patient characteristics are described in Table 2, the main study characteristics in Table 3. References are given in the literature. Patients were young (unweighted mean 31 years); the ADHD group was predominantly male (70%), whereas the control group comprised fewer males (57%). Level of education and intelligence of the samples were high. Most studies compared ADHD patients to healthy controls; in six cases, an outpatient group served as the control group or was established as an additional control group. Most controls were healthy persons recruited by advertisement. Some studies included controls who referred themselves to counseling but who did not receive a psychiatric diagnosis. Nearly all patients fulfilled the criteria for attentiondeficit hyperactivity disorder according to DSM-III-R or DSM-IV. Subtyping of the ADHD patients into predominantly inattentive versus predominantly hyperactive–impulsive group was seldom considered. The majority of studies excluded ADHD patients with a comorbid major psychiatric disorder. Exceptions were Corbett and Stanczak (1999), who also included patients with comorbid depression, Gansler et al. (1998), who reported a substance abuse comorbidity of 30% in their ADHD group, and Oie and Rund (1999), 9% of whose patients were suffering from comorbid obsessive compulsive disorder. Most of the studies did not allow patients to take any psychotropic drugs, at least not prior to testing. In eight studies, the groups were explicitly matched, mostly by education, age and sex.

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Table 2 Patient characteristics First author Published year

N

Age

% Male

Education (years)

ADHD Ctrl

ADHD Ctrl

ADHD Ctrl

ADHD Ctrl ADHD 13 14 n.a. n.a.; ns 15 n.a. n.a.; ns 14 n.a.; ns 15 n.a.; ns k.A. 14 14 n.a. 14 16

Arcia Barkley Biederman Bush Corbett Epstein Epstein Gansler Himelstein Holdnack Hopkins Jenkins Johnson Katz Klee Kovner Lovejoy

1994 1996 1993 1999 1999 1998 2001 1998 2000 1995 1979 1998 2001 1998 1986 1998 1999

23 25 84 8 27 25 60 30 9 25 70 22 56 58 12 19 26

25 23 142 8 15 30 72 10 23 30 42 18 38 20 12 10 26

23 23 39 37 37 35 34 29 35 31 19 34 33 29 20 31 41

27 22 39 37 40 25 33 35 23 27 19 32 41 35 29 31 41

65 64 65 60 50 67 40 93 85 60 n.a. 54 71 87 100 66 50

60 61 47 60 33 62 50 70 23 63 22 63 44 100 66 50

Murphy Murphy Oie Rapport Seidman Silverstein Walker

2001 2002 1999 2001 1998 1995 2000

18 105 20 35 64 16 30 867

18 64 30 32 73 17 30 808

21 40 14 33 36 36 26 31

21 40 16 33 40 31 26 31

75 100 100 66 52 50 83 70

69 100 50 55 45 50 63 57

13 n.a. n.a. 15 high n.a.; ns 11

14 14

16

14 14 99 17 15 14 16 14

15

11

IQ

n.a. 107a 110b 107 n.a. n.a. n.a. 108d n.a.; ns 57e 105 106 57f 109 n.a. 110 115 104a 94–125 n.a. 105c 111b 32g n.a.

Ctrl 108 113 111

105 60 108 58 111 110 115 111 94–125 108 112 33

n.a., not availiable; ns, non significant; Ed, education; Soc, socioeconomic status. a Kaufman Brief Intelligence Test. b Estimated from WAIS-R Vocabulary and Block Design. c Estimated from WAIS-R Similarities, Block Design, Picture Arrangement, Picture Completion. d Estimated from WAIS-R Block Design and Vocabulary. e Sum of age corrected subscale scores on WAIS-R Information, Digit Span, Vocabulary, Block Design, Digit Symbol. f Shipley Institute of Living Scale—Vocabulary and Abstract Reasoning. g Shipley Intelligence Scale.

3.2. Effects Table 4 shows effect sizes for the 10 functional domains, with negative d values indicating lower performance in the ADHD group. In all functional domains ADHD patients scored lower than the combined control groups. The deficits were most pronounced in verbal memory, focused attention, sustained attention and abstract problem solving requiring working memory. In these four domains the ADHD patients scored about one half of a S.D. lower than the control

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First author

Published year

Design

Recruitment Controls

ADHD

Comorbidity

Subtype

Control

Arcia Barkley

1994 1996

ADHD/crl/neu ADHD/ctrl

Neuropsych. outp Clinic

Ad

DSM-III-R DSM-IV

– Comb

Healthy Healthy

Biederman

1993

ADHD/ctrl

Genetic study

Genetic study

7 DSM-III-R-Crit.

–

Healthy

None Stim. (4); AD (1); 24 h WO ?

Bush Corbett

1999 1999

ADHD/ctrl ADHD/ctrl

Outp clinic Private practices

Ad

DSM-IV-R DSM-IV-R

None No psychosis, no neuro Yes (67% ADHD; 0% contr.) No axis I diagnosis 50% depression

Healthy

48 h wo None

Epstein

1998

ADHD/ctrl

Outp clinic

Study

Healthy

?

Epstein

2001

ADHD/ctr/anx

Professionals; ad

Newspaper ad

DSM-IV; current sympt. DSM-IV

Healthy; Axiety

12 h wo

Gansler

1998

ADHD/ctrl

SR

Ad; rebursed

DSM IV

?

Himelstein

2000

ADHD/ctrl

Queens College

DSM-IV

Holdnack

1995

ADHD/ctrl

Ad, practice, groups Referral

Healthy (40% alcoholism) No ADHD

Project

DSM-III-R

Healthy

None

Hopkins

1979

CADHD/ctrl

Long-term study

Long-term study

n. a.

“Hyperactive”

Healthy

?

Jenkins

1998

CADHD/ctrl

SR

SR

DSM-III-R (childhood)

Multiple diagnoses

?

Johnson

2001

ADHD/ctrl

SR

Ad

DSM-IV

15 current ADD; 7 res; comorbidity –

Healthy

None

Katz

1998

ADHD/outp.

SR

SR

DSM-III-R

–

Depression

None

Klee Kovner

1986 1998

CADHD/ctrl ADHD/ctrl

Formerly treated SR

Staff SR

CADHD DSM-IV

– –

None for 1 year 12 h wo

Lovejoy

1999

ADHD/ctrl

SR; stimulant responder

SR; parents; friends

DSM-IV

Healthy (?) Yes (Depr.; LD; Anx) Healthy or substance abuse

ADHD

Diagnosis

Medication

? ? No psychosis, no neuro ? No neuro; no psychia. No psychia.; no neuro No neuro; no psychia. No mood disorder; no substance use LD (40 ADHS; 6 crtls) 4 LD; 4 Depression/Anx Substance abuse/depend.

Healthy 24 full crit.; 3 ina 39 ina; 7 hyp; 14 comb 14 ina; 1 hyp; 10 comb 16 ina; 14 hyp 6 ina; 1 hyper; 2 comb, ?

–

None

12 h wo

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Table 3 Study characteristics

2001

ADHD/Ctrl

Clinic referral

Newspaper ad

DSM-IV

No axis I diagnosis

No axis I diagnosis

55% comb; 34% ina; 2% hyp; 9% res Com

Murphy

2002

ADHD/Ctrl

Staff

DSM-IV-R

Oie

1999

ADHD/Ctrl/Sz

Fathers of ADHD-children Outp

Schools; hospitals

Rapport

2001

ADHD/Ctrl

University center

Seidman

1998

ADHD/Ctrl

Silverstein

1995

Walker

2000

?

Healthy

DSM-III-R

OCD 9%

?

Healthy

University ad

DSM-IV

?

Healthy

SR

Studies

–

ADHD/Ctrl/ GdT

Outp groups

Straff; students

DSM-III-R (5 crit.+CADHD) DSM-III-R

No neurological or subst. abuse 66% ADHD; 8% ctrls. No psy. treatment

–

Normals; 8% ysychia. dia. Controls

ADHD/ctrl/outp

SR; outp clinic

Community sample

DSM-III-R

None

–

Healthy

Stim. (17); AD (4); wo 12 h/2 weeks ? Stim. (32); 24 h wo; AP (29 sz) Stim. (3); 12 h wo None Stim. (5); AD (2), both (1) None

Neu, neurological patients; Anx, anxiety; Sz, schizophrenia; GdT, Gilles de la Tourette; Outp, outpatients; CADHD, childhood ADHD; SR, self referral; LD, learning disabilities; Ina, inattentive; Hyp, hyperactive; Comb, combined; Res, residual type; Psychia., psychiatric; Stim, stimulants; AD, antidepressants; WO, wash out; AP, antipsychotics; h, hours; crit, criteria.

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Murphy

735

736

Verbal intelligence Executive functions Visual/verbal fluency Visual/figural problem solving Abstract problem solving; working memory Simple attention Sustained attention Focused attention Verbal memory Figural memory

N studies

N patients

d

CI low

CI upper

z (d)

P (z)

χ2

P (χ2 )

TAU

I2

12 7 7 8 12 22 13 22 8 8

863 464 527 762 952 1537 963 1493 546 541

−.27 −.21 −.52 −.26 −.51 −.38 −.52 −.55 −.56 −.18

−.43 −.46 −.83 −.40 −.64 −.55 −.65 −.68 −.79 −.35

−.11 .03 −.20 −.11 −.37 −.22 −.39 −.42 −.37 .00

−3.34 −1.70 −3.23 −3.45 −7.40 −4.50 −7.79 −8.31 −6.14 −1.93

.00 .09 .00 .00 .00 .00 .00 .00 .00 .05

13.5 9.5 17.4 4.0 10.8 47.6 11.1 28.3 6.2 7.5

.26 .14 .00 .78 .46 .00 .52 .13 .52 .38

.014 .039 .113 .000 .000 .080 .000 .023 .000 .005

19 37 65 0 0 56 0 26 0 7

d, pooled weighted effect size; CI low/upper, confidence interval (d); z, z-value; χ2 , χ2 for heterogeneity; TAU, heterogeneity correction for random effects model; I2 , percentage of heterogeneity due to study differences. See Formulas 1–10 for all parameters.

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Table 4 Pooled effect sizes and meta-analytic parameters

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Table 5 Fail-safe N and critical number of studies

Verbal intelligence Executive functions Fluency Visual/figural problem solving Abstract problem solving; working memory Simple attention Sustained attention Focused attention Verbal memory Figural memory

Fail-safe N

Critical number

578 43 182 269 2863 3592 875 12393 863 79

70 45 45 50 70 120 75 120 50 50

persons. Across all domains, pooled effect sizes d ranged from small (−.18) to moderate (−.54) effects, in eight of the ten domains, difference in performance was significant. χ2 values of homogeneity indicate that the differences between ADHD patients and controls in verbal memory, focused attention, sustained attention, and abstract problem solving were homogeneous across studies. This was not the case with simple attention and fluency, where the difference between single studies (or test instruments) was obviously large, as indicated by significant χ2 values. Table 4 also reports the new heterogeneity index I2 (Higgins & Thompson, 2003), which corresponds to the percentage of total variation across studies due to heterogeneity, i.e. the variation of effect sizes that is probably due to study differences and not to chance (Higgins et al., 2003). For visual/verbal fluency, a high degree of heterogeneity was found (65%), the second highest value was found for simple attention (56%). No heterogeneity whatsoever was found for visual/figural problem solving, abstract problem solving/working memory, sustained attention or verbal memory. 3.3. Fail-safe N Fail-safe N is the number of unpublished, non-significant studies that could render the significant result of meta-analysis non-significant. It serves as an indicator of the stability of a meta-analytic result. In the present data, fail-safe N for those functional domains that show effect sizes of d = 0.5 or above and an acceptable homogeneity across studies (verbal memory, focused attention, sustained attention and abstract problem solving) reached well above 100. The theoretical possibility of a falsification of our results by unpublished non-significant studies is therefore highly unlikely (Table 5).

4. Discussion The present meta-analysis of published empirical studies of neuropsychological performance of ADHD patients summarizes the evidence on performance deficits of ADHD patients compared to controls by analyzing 1675 patients from 24 studies. In eight of 10 neuropsycho-

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logical functional domains ADHD patients showed significant performance deficits. In most of the domains, the homogeneity between studies was very acceptable, indicating reliability of the results. There are, however, numerical differences in the extent of deficits of ADHD patients across the cognitive functions. Small effect sizes were found for the domains visual memory, visual problem solving, and, surprisingly, for executive functions. In children, ADHD is supposed to be primarily characterized by impaired function of the frontal lobe, which regulates executive functions such as planning, inhibition and action (Barkley, Grodzinsky, & DuPaul, 1992; Spencer et al., 2002). Gallagher and Blader (2001), in a qualitative research review on adults, also emphasizes the role of impaired executive functions. In this meta-analysis, the highest effect sizes for adults were found for verbal memory, focused attention, sustained attention and abstract verbal problem solving with working memory. Simple alertness tasks, which are highly dependent on basic psychomotor reaction time, were less impaired than more complex attention tasks. These results fit well with clinical reports of high distractibility in patients, which has been reported to occur in more complex attention tasks (Weiss & Murray, 2003). It also supports recommendations in ADHD self-help books emphasizing the importance of presenting knowledge in multimodal, visual, and auditory form and in a well-structured and highly interesting way (e.g. Hallowell & Ratey, 2001), in order to arouse interest, avoid a decrease of attention, and to enhance encoding and consolidating memory processes. The results of the published studies may be confounded by the existence of diagnostic subgroups, mainly the hyperactive versus the inattentive type. One hypothesis, advanced by Barkley (1997), supports the view that (mainly) hyperactive patients perform worse on executive tasks such as delay of reaction, problem solving, flexibility, and sustained attention, whereas the inattentive type would be more impaired in tasks of memory, focused attention, and speed of information processing. Lockwood, Marcotte, and Stern (2001) review neurobiological studies on subtyping children and state that results are inconsistent. They propose the application of a neuropsychological model of attention (Cohen, 1993), and found in inattentive type children more problems with selective attention and slow processing, whereas hyperactive type children had more difficulties in executive and inhibitory functions. Results on adults’ subtyping are limited in number. Gansler et al. (1998) and Dinn, Robbins, Robbins, and Harris (2002) refer to Petrides (1994) who proposes two separate frontal subsystems of frontal functions, a dorsolateral prefrontal system and a inferior frontal/limbic system. Both systems are supposed to generate specific functional deficits that are thought to be reflected by the hyperactive versus the inattentive subtype. Barkley (1990, p. 89) postulates different neuroanatomic loci and different neurotransmitter systems. According to Barkley, hyperactivity is connected to dopaminergic dysfunction, whereas hypoactivity is a norepinephrine phenomenon. These changes are to be accompanied by different neuropsychological profiles. Other authors, however, do not find any influence of subtyping in their data on cognitive functioning (Murphy, Barkley, & Bush, 2001), or they emphasize the difficulty of correctly subtyping, especially in adults (Fisher, 1998, p. 145). Moreover, the diagnostic relevance of hyperactivity has changed over time (Wender, Wolf, & Wasserstein, 2001); it is probable that studies that were conducted more recently include more patients of the inattentive type (Baumgaertel, Wolraich, & Dietrich, 1995; Morgan, Hynd, Riccio, & Hall, 1996). In the present study, it was not possible to evaluate the influence of subtypes, as information given in the publications was insufficient. If neuropsychological profiles differ between subtypes, smaller effects will result by mix-

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ing subtypes. Our finding that effects are of moderate size and are highest in verbal memory tasks, followed by focused attention, refers to the undifferentiated group of ADHD-patients. In future, selection of patients for neuropsychological studies should be based on more detailed clinical differentiation. Another possible confounding factor is comorbidity. High comorbidity of ADHD with various psychiatric conditions is known in both children (Biederman et al., 1991) and adults (Tzelepis, Schubiner, & Warbasse, 1995). Neuropsychological deficits are described and empirically validated in a variety of psychiatric diseases. Most of the data have been presented for schizophrenia (Aleman, Hijman, de Haan, & Kahn, 1999; Heinrichs & Zakzanis, 1998; Johnson-Selfridge & Zalewski, 2001) and affective disorders (Burt, Zembar, & Niederehe, 1995; Christensen, Griffiths, Mackinnon, & Jacomb, 1997; Lachner & Engel, 1994; Zakzanis, Leach, & Kaplan, 1998). Neuropsychological profiles of obsessive compulsive disorder (Harting & Markowitsch, 1997), post-traumatic stress disorder (Golier & Yehuda, 2002), and personality disorders, mainly borderline (O’Leary, 2000) and antisocial personalities (Morgan & Lilienfeld, 2000), have also been investigated. Various deficits in memory, attention, speed, fluency, and executive functions and other higher functions are described, with effect sizes reaching d = 1 and higher, especially in depression and schizophrenia. Frequently, mood and anxiety disorders as well as substance abuse and personality disorders co-occur with ADHD, although there are still some questions about prevalence rates in adults (Marks et al., 2001). These comorbid disorders could be responsible for neuropsychological deficits found in ADHD patients. Taylor and Miller (2002) report a decline in neuropsychological performance with increasing severity in diagnosis in their data of a rather large but heterogeneous ADHD sample. However, in most of the studies that were included in this meta-analysis, major psychiatric disorders were excluded. Murphy et al. (2001), as well as Seidman, Biederman, Weber, Hatch, and Faraone (1998) and Biederman et al. (1993), also found no associations between psychiatric comorbidity (mostly depression, OCD, anxiety) and neuropsychological performance. Our finding that higher executive functions, as measured by planning and flexibility tasks, are not the strongest predictors of the distinction between ADHD and normal controls is inconsistent with the current view that ADHD is the result of a deficit in behavioral inhibition that secondarily leads to deficits in executive function (Barkley, 1997; Ossmann & Mulligan, 2003), or of a diminished capacity to switch between executive and inhibitory engagements (Rubia et al., 2001). One possible explanation for this finding might be the hypothesis advanced by Rubia et al. (2000) that ADHD symptomatology in children is partly caused by anomalies of frontal-lobe maturation, which lose importance in adulthood. Another explanation could be a population bias. It is probable that the patients included in adult studies represent only a specific part of the former child samples, as in nearly all studies adult patients are intelligent outpatients with a relatively good outcome. ADHD children with poor outcome, such as criminality, chronic drug abuse or severe psychiatric disorders, are usually not included in the studies analyzed here. These patients, who are excluded from the present studies possibly show more problems on tasks measuring executive and inhibitory functions. This implies that children without or with only minimal executive dysfunction have better prognosis than children with clear executive dysfunction. A further explanation might be that the tests used in the present studies might be subject to ceiling effects that mask differences in highly educated

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samples. Besides, there is no commonly accepted definition on executive functions (Barkley, 2001). We chose to separate more basic aspects of executive functions such as working memory and inhibition from higher level functioning. It might also that ADHD impacts some aspects of executive functions more than others. If we had included all measures that are discussed as measures of executive functioning, effect size would have reached a much higher value. The question whether neuropsychological tests may serve as diagnostic tools cannot be answered by this meta-analysis, as there is no way to compute sensitivity-specifity analyses. Some authors of primary studies (Epstein, Conners, Sitarenious, & Erhardt, 1998; Katz, Wood, Goldstein, Auchenbach, & Geckle, 1998; Lovejoy et al., 1999; Rapport, Van Voorhis, Tzelepis, & Friedman, 2001; Walker, Shores, Trollor, Lee, & Sachdev, 2000) found in their sensitivity analysis and/or discriminant analysis that about 70% of patients/controls are correctly classified, with rather high specifity and low sensitivity. A meta-analysis is subject to methodological restrictions that need to be discussed. The most obvious source of error is publication bias, which means that a number of (unpublished) studies exist where no differences between ADHD patients and controls could be found. Fail-safe N offers the possibility to estimate these chances. For the main results of this meta-analysis, fail-safe N indicates that these results would remain significant even if a number of negative results were to be published. Another problematic aspect is the variety of studies integrated in this meta-analysis. Our effect sizes came from studies with various designs using different approaches to diagnosis and a variety of neuropsychological test instruments. Nevertheless, the integration of the effect sizes (between instruments within studies as well as between studies within domains) showed sufficient homogeneity for nearly all calculations. Therefore, it is quite clear that a significant deficit in neurocognitive functions is measurable in adult ADHD patients. This deficit is mainly characterized by impaired verbal memory and low scores on tasks requiring focused and/or sustained attention. Clinical evaluation of ADHD patients should include a comprehensive test battery of standard tests, as single test measures do not have sufficient diagnostic value. In future studies a promising approach might be to focus on clinical variables of adults, especially hypo- versus hyperactivity, which may correlate with different profiles of neuropsychological deficits.

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