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Abstract
This study examined the hypothesis that individuals with attention deficit hyperactivity disorder, predominantly inattentive type (ADHD-I), show both executive function (EF) deficits and non-EF deficits. A group with ADHD-I (n = 16) and a paired control group (n = 21) completed a battery of tasks covering the major domains of EF (planning, working memory, flexibility and inhibition) and non-EF (alertness, divided attention, flexibility, sustained attention, visual field and visual scanning). EF impairments in planning, spatial working memory, flexibility, and inhibition as well as non-EF impairments in divided attention, flexibility, sustained attention and visual scanning were observed in the ADHD-I group. Our results do not support Barkley’s (1997) view of ADHD which postulated that only ADHD-C and ADHD-H, but not ADHD-I, are associated with EF deficits. It suggests that ADHD-I and ADHD-C children had similar profiles of cognitive impairment, and the deficits in cognition are not good markers for the classification of ADHD subtypes in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V).
Keywords
- ADHD-I
- Executive function
- Non-executive function
- Cognitive profile
1. Introduction
Executive function (EF) is an umbrella term that refers to processes that control other cognitive processes [1]. Researchers have identified four distinct domains of EF: planning, working memory, flexibility, and response inhibition [2-6]. The role of EF is debated, but most researchers agree that EF is involved in deliberately managing an appropriate problem solving set to attain a future goal [7-8].
A deficit in EF is postulated to account for core symptoms in psychiatric patients with no focal frontal lesions, such as those diagnosed with attention deficit hyperactivity disorder (ADHD). The evidence supporting a deficiency in EF domains in ADHD comes from a number of sources [8, 9-14].
Clarification of the neuropsychological similarities and differences in ADHD subtypes can contribute to understanding their etiological relationship.
Now, nearly all of the neuropsychological literature on ADHD pertains to the group designated as ADHD combined type (ADHD-C), while the primarily inattentive subtype of ADHD (ADHD-I) remains relatively under-investigated with regard to potentially relevant cognitive functions [17-19]. Nigg (2005) suggested that further studies of children with ADHD-C versus control children on many executive measures might no longer be needed [18]. Instead, studies to examine issues such as neuropsychological process theories of ADHD-I have been proposed.
Previous research has found many non-EF cognitive deficits in ADHD-I, such as the inconsistent alertness and orientation [20], Sluggish cognitive tempo [21], and the poor attention shifting [22]. And many non-EF symptoms rather than EF symptoms were described in DSM-V, such as often fails to give close attention to details or often loses things necessary for tasks or activities. For a long time, we failed to give much attention to the EF domain in ADHD-I, thus it is still unknown whether the EF domain are impaired in ADHD-I. Combining the hypothesis that EF weaknesses are neither necessary nor sufficient to cause all cases of ADHD [8], we predict that individuals with ADHD-I encounter not just difficulties with EF, but also show deficits in other cognitive domains (hereafter termed non-EF).
Thus, the first goal of the present study was to examine the EF weaknesses hypothesis in ADHD-I by comparing children with ADHD-I versus typically developing children in the four distinct EF domains of planning, working memory, flexibility, and inhibition. The second goal was to examine the non-EF deficit hypothesis in children with ADHD-I by comparing them with a control group on six non-EF domains: alertness, divided attention, flexibility, sustained attention, visual field and visual scanning.
2. Methods
2.1. Participants
Children diagnosed with ADHD were recruited from several child psychiatry outpatient services across the Zabei district of Shanghai. Each sample was referred from the Shanghai Pediatric Hospital where the participants were diagnosed with ADHD, primarily inattentive type.
Before testing, we obtain written consent from participants and their parents. Each family completed an unstructured screening interview based on the Child and Adolescent Psychiatric Assessment [23]. We recorded information regarding the children’s medical history, developmental history and general symptoms. We excluded children with any significant comorbid psychiatric or neurological conditions, such as epilepsy, severe attention deficit hyperactivity disorder or schizophrenia. We also confirmed that the children had not been on medication for at least 3 months.
All children met DSM-V diagnostic criteria for ADHD. Any child with ADHD-H or ADHD-C was excluded. Furthermore, a 27 items version of Conners’ Teacher Rating Scale (CTRS-S) [24] was completed for each child to confirm the pervasiveness of symptoms. Scoring was performed according to the test manual [25] and established cutoff points for possible and likely ADHD, primarily inattentive type were imposed. Furthermore, all children were administered the Raven’s Progressive Matrices IQ test. Children exhibiting intellectual disability (IQ scores below 75) were excluded from further experiment. Finally, a total of 16 children with ADHD-I participated in the experiment.
Twenty-one children without ADHD were paired with the ADHD group by gender and age. We administered an unstructured screening interview based on the Child and Adolescent Psychiatric Assessment [23] for the controls and did not find any psychiatric or neurological symptoms. All children did not meet DSM-V diagnostic criteria for ADHD. Furthermore, a teacher completed the CTRS-S [24] for the control group, with t scores below 50 used to confirm the children’s non-ADHD status. In addition, the non-ADHD group was administered the IQ test (CRT) to confirm that they did not have intellectual disability. Information on participants is shown in Table 1.
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N | 16 | 21 | |
Sex ratio (F/M) | 12/4 | 14/7 | Ns |
Age | 12 (1.43) | 12 (1.41) | Ns |
Range of age | 9-14 | 9-14 | |
IQ(CRT-C) | 89 (11.3) | 92 (12) |
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Range of IQ | 75-122 | 80-123 |
2.2. EF tests
We chose EF tests according to distinct domains of EF: planning, working memory, flexibility, and response inhibition [2-6]. Four EF tests were conducted in this study: the Spatial Working Memory Test (SWM), Stockings of Cambridge Test (SOC), Wisconsin Card Sorting Test (WCST), and Stroop/reverse-Stroop Test. With regard to response inhibition, Barkley (1997) proposed a model suggesting that a deficit in behavioral inhibition, considered a key process in EF, accounts for central impairment of ADHD [16]. In the model, Barkley distinguished three interrelated processes believed to constitute behavioral inhibition: (1) inhibition of a prepotent response; (2) cessation of an ongoing response; and (3) interference control. Researchers have long used Stroop/reverse-Stroop interference as the main paradigm to study interference control. Thus, in this study, we used the Stroop/reverse-Stroop Test [26, 27] to evaluate the level of response inhibition.
In the original SWM, there were four types of trials with either three, four, six, or eight boxes in each. Several previous studies showed that children with ADHD made significantly more errors compared with controls only on the eight-box problems [30, 31]. Given that between-search errors may appear as a function of the number of boxes in pediatric clinical populations [32], it is possible that children with ADHD also make significantly more errors compared with controls on seven-box problems. Thus, we made a few changes to the original task, in which the independent variable of box consisted of five uninterrupted levels with three, four, five, six, or seven boxes. There were four test trials each with three, four, five, six, and seven boxes. The order of the trials was randomized, with the constraint that the same number of boxes did not occur consecutively. The dependent measure for the SWM test was the number of between-search errors on three-, four-, five-, six-, and seven-box problems.
In the original SOC task, there were four test trials each with two, three, four, and five moves. However, some studies failed to find that children with ADHD made significantly more extra moves than typically developing children on this task (For example, see [30,31,34]). It is possible that the short range of the minimum moves to goal state can account for the above conclusion. Thus, we made a few changes to the original task, such that the minimum moves to goal state ranged from three to seven moves. There were four test trials each with of three, four, five, six, and seven moves, and the order of the trials was randomized. The dependent measure for the SWM test was response times on three-, four-, five-, six-, and seven-move problems.
Continued matching to a category that is no longer correct is considered a perseverative error (PE). Other errors that occur when a participant is required to switch to another sorting principle are referred to as non-perseverative errors (NPE). The variables of interest were the number of categories achieved, percentage of perseverative errors and percentage of non-perseverative errors.
Test 1 was control condition for the Stroop test, in which the color patch was shown on the left side of the test sheet, requiring participants to make a choice from the five matching color–words(written in black ink) corresponding to the color of the color patch. Test 2 was the Stroop test, in which incongruent color–words were shown on the left side of the test sheet, requiring participants to make a choice from the five matching color–words (printed with black ink) according to the ink color of the color–word in the center. If the semantic content of the incongruent color–word does not affect the processing of ink color, the response to Test 1 and Test 2 should not differ. Test 3 was control condition for the Reverse-Stroop test, in which all the color–word combinations were written in black ink, requiring participants to make a choice from the five matching color patches corresponding to the color–words. Test 4 was the RI test, in which all the color–word combinations were written in incongruent ink (e.g., the word blue printed in green ink) on the left side of the test sheet, requiring participants to make a choice from the five matching color patches corresponding to the semantic meaning of the word. Similarly, if the ink color does not affect semantic processing, the responses to Test 3 and Test 4 should not differ. Thus, we can evaluate the Stroop interference ratio and the reverse-Stroop interference ratio by comparing the responses in the four tests.
Each test consisted of 10 practice trials and 100 test trials. On the basis of the number of correct responses in each subtest (C1, C2, C3, C4), two interference ratios were calculated using the following formulas: Stroop interference ratio, (SI) = (C3–C4)/C3, and reverse-Stroop interference ratio, (RI) = (C1–C2)/C1.
2.3. Non-EF tests
To fully assess non-EF in this study, performance was assessed by a set of computer-assisted psychological tests, the Test for Attentional Performance (TAP), version 2.2, published by Zimmermann and Fimm [39]. The six subtests of alertness, divided attention, flexibility, sustained attention, visual field, and visual scanning were administered. The dependent measure for the TAP was the reaction times.
2.4. Procedure
Testing took place on four different occasions and was administered in a fixed order for both groups. During the first session, the Stroop/reverse-Stroop Test was administered. In the second testing session, the TAP battery was administered individually. In the third testing session, the WCST and SOC were administered individually. Finally, the SWM was administered individually.
3. Results
In this section, we briefly provide the statistical analyses, focusing on the performance on the EF tests (working memory, planning, flexibility and inhibition) and non-EF tests (alertness, divided attention, flexibility, sustained attention, visual field and visual scanning) between children with ADHD-I and typically developing children.
3.1. EF tests
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Working Memory | SWM | |||
BSE on 3-box problems | .13(.34) | .01(.22) | Ns | |
BSE on 4-box problems | 1.31(1.85) | .43(1.03) | Ns | |
BSE on 5-box problems | .88(1.41) | .71(1.82) | Ns | |
BSE on 6-box problems | 4.38(4.56) | 1.81(2.52) | ADHD-I>NC | |
BSE on 7-box problems | 9.83(7.95) | 2.79(4.15) | ADHD-I>NC | |
Planning | SOC | |||
TT on 3-move problems | 17.27(6.71) | 14.20(3.41) | Ns | |
TT on 4-move problems | 27.76(15.18) | 33.14(11.80) | Ns | |
TT on 5-move problems | 62.81(38.92) | 37.05(31.08) | ADHD-I>NC | |
TT on 6-move problems | 70.68(30.00) | 49.24(20.64) | ADHD-I>NC | |
TT on 7-move problems | 73.20(39.23) | 48.32(37.85) | ADHD-I>NC | |
Flexibility | WCST | |||
C | 6.50(2.00) | 8.29(1.55) | ADHD-I<NC | |
PE | 13.94(9.47) | 6.76(8.31) | ADHD-I>NC | |
NPE | 25.44(5.97) | 23.10(5.88) | Ns | |
Inhibition | Stroop/reverse-Stroop Test | |||
SI | .23(.21) | .19(.13) | Ns | |
RI | .30(.15) | .17(.11) | ADHD-I>NC |
3.2. Non-EF tests
We performed multivariate analysis (Pillai's trace) with group type (ADHD group or non-ADHD group) as a fixed factor and reaction times on the six subtests as a dependent factor. Results showed that the effect of group type,
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Alertness | TAP, subtest 1 | 350.67(54.44) | 345.17(64.88) | Ns |
Divided attention | TAP, subtest 4 | 1434.17 (432.73) | 1097.09 (265.93) | ADHD-I>NC |
Flexibility | TAP, subtest 6 | 560.75(92.43) | 480.00(74.42) | ADHD-I>NC |
Sustained attention | TAP, subtest 9 | 560.56(59.50) | 515.96(61.07) | ADHD-I>NC |
Visual field | TAP, subtest 11 | 503.97(107.96) | 496.36(90.83) | Ns |
Visual scanning | TAP, subtest 12 | 5454.91(1270.07) | 4114.94 (898.77) | ADHD-I>NC |
4. Discussion
4.1. EF domains
4.2. Non-EF domains
Deficits in divided attention, flexibility, sustained attention, and visual scanning relative to controls indicate that individuals with ADHD-I also exhibited impairment on the non-EF domains. We know that the cognitive and behavioral characters (the attention trait, hyperactivity and impulsivity) are the main criterion for the subtypes of ADHD in DSM-V. However, the DSM-V does not provide specific examples of the cognitive difference between ADHD-C and ADHD-I.
With regard to non-EF domains, previous studies have suggested that ADHD-I shows a deficit in speed of information processing, generally, and in focused or selective attention, specifically [54, 55], while deficits in ADHD-C are characterized as sustained persistence [16]. However, one recent study has shown that ADHD-I and ADHD-C children had similar profiles of vigilance impairment indexing a lack of sustained attention [56]. Furthermore, in the present research, we found that ADHD-I is also associated with a sustained attention deficit. Moreover, Geurts, Vert´ec, Oosterlaana, Roeyersc, and Sergeanta (2005) found no differences between inattentive and combined ADHD subtypes on non-EF tasks, such as response execution, short-term memory, visual-motor integration and categorization [57]. Based on combined results of the current research and previous studies, we wonder whether the deficits in non-EF cognitive abilities can be used as good markers for the validation of ADHD subtypes in DSM-V.
5. General discussion
The present study was designed to investigate the hypothesis that those with ADHD-I exhibit both EF deficits and non-EF deficits by comparing typically developing controls with boys carefully diagnosed with ADHD-I on an extensive battery of tasks that cover the major EF and non-EF domains.
With regard to the EF domains, results are consistent with findings in previous studies of EF and ADHD. That is, ADHD is associated with weaknesses in several key EF domains, but the strongest and most consistent effects are obtained on measures of response inhibition, vigilance, spatial working memory and some measures of planning [8, 41, 56-58]. The deficits on EF domains revealed in ADHD-I also suggest that the pathology of ADHD-I is related to deficits in managing an appropriate problem or attaining a future goal. Furthermore, results did not yield evidence for the model of ADHD in which only ADHD-C and ADHD-H, but not ADHD-I, are associated with EF deficits.
With regard to non-EF domains, findings revealed that the children with ADHD-I also demonstrated deficits in these domains, such as, divided attention, flexibility, sustained attention and visual scanning. This suggests that children with ADHD-I not only show deficits in EF, but also experience deficits in other non-EF domains.
Discriminating among disorders is particularly important. However, there are no objective diagnostic tests for ADHD-I [59]. Considering the fact that neither EF nor non-EF domains distinguish ADHD-I from ADHD-C, examination of other factors, such social, emotional and behavioral characteristics [60, 61] may be needed to support the validity of ADHD subtypes in the DSM-V.
6. Limitations
A limitation of our study findings is the small sample size and potential response bias from those who agreed to participate. To gather more reliable data and validate the results of the present study, future research should focus on selecting larger samples to engage in the same tasks. Furthermore, to examine whether EF and non-EF tests can distinguish ADHD-I from ADHD-C, it would be useful to make a direct comparison between ADHD-C and ADHD-I in the battery of EF and non-EF tests used in the study. Future studies should be conducted using the same tasks with an ADHD-C group.
Acknowledgments
The authors wish to thank all the participants in this experiment. Special thanks go to Yu Jia for her invaluable help. This work was also supported by National Natural Foundation of China (31300839), Grant-in-Aid for JSPS Postdoctoral Fellowship For Foreign Researchers (P13311), Shanghai Pujiang Program (12PJC034), and MOE (Ministry of Education in China) Project of Humanities and Social Sciences (13YJC190020).
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