Abstract
Objectives
This study examined the neurocognitive profiles of early adulthood attention-deficit/hyperactivity disorder (ADHD) patients using the Korean version of the Wechsler Adult Intelligence Scale, 4th Edition (K-WAIS-IV) and Continuous Performance Test 3rd Edition (CPT-3) assessment results.
Methods
A total of 105 individuals underwent the K-WAIS-IV assessment, and 68 participants completed the CPT-3. We examined the differences between intelligence subindex scores using paired t-tests and applied Pearson’s correlation analysis to determine the correlation between the K-WAIS-IV and CPT-3 scores.
Results
Working Memory Index scores were significantly lower than Verbal Comprehension Index scores, whereas Processing Speed Index (PSI) scores were significantly lower than all three other subindex scores. Significant negative correlations were found between all four K-WAIS-IV subindex scores and the CPT-3 scores for Detectability, Omissions, Commissions, Perseverations, Hit Reaction Time, Hit Reaction Time Standard Deviation, and Variability.
Conclusion
The PSI of the K-WAIS-IV can be considered a useful predictor in early adulthood ADHD patients combined with the CPT-3 examination.
Keywords: Attention-deficit/hyperactivity disorder, Neurocognitive tests, Wechsler Intelligence Scales, Continuous Performance Task, Working memory, Processing speed
INTRODUCTION
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder typically detected in childhood. It is characterized by a persistent pattern of attention deficit, hyperactivity, and impulsivity, resulting in various degrees of functional impairment in social, academic or occupational settings [1]. Decades of research have shown that many individuals continue to experience performance difficulties well into adulthood [2,3], and the onset of symptoms should present before 12 years of age. However, diagnosing ADHD in adults remains challenging because of the lack of available informants from childhood and the potential presence of coexisting psychiatric disorders. This highlights the need for more reliable tools to support ADHD diagnosis in adults, with a high degree of specificity to differentiate it from other comorbidities [4,5].
The overall worldwide prevalence of ADHD is 5%, with a 2.5% prevalence in adults [6]. According to previous research, approximately 50% of cases detected in childhood persist into adulthood [3,7,8]. In South Korea, the prevalence of ADHD is estimated to be 0.192% in the general Korean population [9]. Among the groups diagnosed with ADHD in South Korea, 61.84% of the children/adolescent group and 78.72% of the adult group had at least one psychiatric comorbidity [9].
Further, ADHD groups showed significantly lower Full Scale Intelligence Quotient (FSIQ) scores than control groups [10], and a meta-analysis of 123 studies assumed that the difference is equivalent to 9 points in FSIQ [11], in which Verbal IQ and Performance IQ derived from the Wechsler scales showed significant decrement. Other studies that analyzed profiles of children with ADHD using the Wechsler Intelligence Scale for Children, 3rd and 4th Editions (WISC-III and WISC-IV), reported significantly lower mean scores in the Working Memory Index (WMI) and Processing Speed Index (PSI) compared to the Verbal Comprehension Index (VCI) and Perceptual Reasoning Index (PRI) [12,13]. These findings support the notion that ADHD patients exhibit weaknesses in attention and processing speed.
The relationship between working memory and ADHD has attracted considerable scholarly attention [14]. Impairment in working memory is associated with prefrontal cortex dysfunction [15], and improvements in ADHD symptoms occasionally accompany the enhancement of working memory due to pharmacological treatment [16]. Moreover, improvements in ADHD symptoms following working memory training have been reported [17,18]. While the neurological mechanisms linking processing speed and ADHD are less clear than those for working memory, studies using the WISC-IV have shown lower WMI and PSI scores in children with ADHD [12,19]. However, the findings using the WISCIII indicated less prominent reductions in WMI or PSI scores among children with ADHD [12], suggesting that this may be dependent on the assessment tool used. Interestingly, studies involving German children with ADHD have shown significant reductions, specifically in PSI scores [20-22]. Given the need for an updated standardization of the WISC for different populations, further investigation into the relationship between ADHD and lower WMI and PSI scores in the Korean population is warranted.
This study focuses on the association between adult ADHD and low WMI and PSI scores. The relationship between working memory and adult ADHD has been reported in functional neuroimaging and neuropsychological testing [15,23]. Furthermore, a link between processing speed and adult ADHD has been reported [24]. Nevertheless, the association between working memory or processing speed scores, as measured using various tools, and ADHD may not be reproducible when using standardized intelligence tests. Given the frequent use of the Wechsler Adult Intelligence Scale (WAIS) in clinical settings, identifying ADHD-related findings on the WAIS may aid in the efficient diagnosis of ADHD. Nonetheless, there is limited research on the association between WMI or PSI scores and ADHD in adults compared with findings in youth. A study on Norwegian adults with ADHD (aged 18–65 years) using the WAIS, 3rd Edition (WAIS-III) observed reductions in WMI and PSI scores, but only PSI scores were associated with self-reported attention deficits [25]. In Japanese adults with ADHD (aged 19–54 years), although reductions in WMI and PSI scores were observed using the WAIS-III, these were more likely related to comorbid depression and autism spectrum disorder rather than to ADHD [26]. Conversely, a study of German adults with ADHD (aged 16–71 years) using the WAIS, 4th Edition (WAIS-IV) reported more robust reductions in WMI and PSI scores [13]. Although limited in number, the findings suggest that, as in children, the reduction in WMI and PSI scores is more pronounced when measured by the WAIS-IV than using the WAIS-III. However, while the reductions in PSI scores were more prominent in German children with ADHD, the reduction in WMI scores was more significant in German adults with ADHD.
Therefore, this study investigates the relationship between adult ADHD and the WAIS-IV scores in a Korean population. While impairments in working memory and processing speed are relatively well-documented in ADHD, further investigation of the association between WMI and PSI scores, as measured by the WAIS-IV and ADHD, is necessary. As previously mentioned, existing studies conducted overseas are limited in number and lack consistent findings. Moreover, the Korean version of the Wechsler Adult Intelligence Scale, 4th Edition (K-WAIS-IV), which has been standardized for the Korean population, requires further investigation. Additionally, previous studies typically included participants with a wide age range [13,25,26], suggesting the need for followup research with a narrower age range. Finally, few studies have examined whether the observed reductions in WMI or PSI scores are associated with ADHD symptoms [13]. When examined, the associations were often absent or only partially related to ADHD symptoms [25,26]. Therefore, this study seeks to confirm the reduction in WMI and PSI scores in ADHD and examine the relationship between these scores and continuous performance test results. Thus, we investigate whether the possible reductions in WMI and PSI observed in the K-WAIS-IV are genuinely related to ADHD. Furthermore, this study explores cognitive differences based on medication treatment for ADHD.
METHODS
Participants
We retrospectively collected data from patients diagnosed with ADHD who underwent the Wechsler Intelligence Scale assessments and Continuous Performance Tests between 2014 and 2022. These patients were examined by the principal investigator (S.-B.H.), and their data were sourced from the electronic medical record system at Seoul National University Hospital. A total of 105 individuals underwent the KWAIS-IV assessment during the study period, and 68 completed the Conners Continuous Performance Test, 3rd Edition (CPT-3). Therefore, our main analysis, which focused solely on the K-WAIS-IV scores, included 105 participants, whereas the analysis incorporating the CPT-3 results targeted a subset of 68 participants (Table 1).
Table 1.
Demographic and clinical characteristics of participants with ADHD
| Characteristics | Value |
|---|---|
| Age (yr) | 19.1±2.2 |
| Sex, male | 85 (81.0) |
| K-WAIS-IV | |
| VCI | 88.8±20.6 |
| PRI | 84.6±21.5 |
| WMI | 85.7±22.0 |
| PSI | 79.3±19.8 |
| FSIQ | 80.7±22.8 |
| CPT-3 (T-score) | |
| Detectability | 48.3±13.2 |
| Omissions | 51.6±13.2 |
| Commissions | 47.7±10.4 |
| HRT | 53.0±12.6 |
| HRT SD | 47.8±13.8 |
| Variability | 48.1±12.1 |
| Perseverations | 49.9±10.6 |
| HRT Block Change | 47.1±11.3 |
| HRT ISI Change | 49.0±10.1 |
| Medication, yes | 46 (43.8) |
Values are presented as mean±standard deviation or n (%). n=105 for age, sex, K-WAIS-IV scores, and medication. n=68 for CPT-3 scores, except for Inattentiveness Variability (n=67) and Sustained Attention HRT Block Change (n=67). ADHD, attentiondeficit/hyperactivity disorder; CPT-3, The Conners Continuous Performance Test 3rd Edition; FSIQ, Full Scale Intelligence Quotient; HRT, Hit Reaction Time; HRT Block Change, Hit Reaction Time Block Change; HRT ISI Change, Hit Reaction Time Inter-Stimulus Intervals Change; HRT SD, Hit Reaction Time Standard Deviation; K-WAIS-IV, Korean version of Wechsler Adult Intelligence Scale 4th Edition; PRI, Perceptual Reasoning Index; PSI, Processing Speed Index; VCI, Verbal Comprehension Index; WMI, Working Memory Index
Measures
Korean version of Wechsler Adult Intelligence Scale, 4th Edition
The K-WAIS-IV [27] is a widely used tool for assessing overall cognitive function in individuals aged 16 and older. We used the K-WAIS-IV to evaluate overall the cognitive ability and differences and correlations among the sub-indices. The K-WAIS-IV was introduced in South Korea in 2012 as a revised version of the WAIS-IV originally published in 2008 [28]. The results of the K-WAIS-IV include the FSIQ and four standardized sub-indices: the VCI, the PRI, the WMI, and the PSI. Each of these scores, including the FSIQ, was standardized to have a mean of 100 and a standard deviation of 15.
Conners Continuous Performance Test 3rd Edition
The CPT-3 [29] is a standardized computer-based assessment used to evaluate attention-related difficulties in individuals aged eight and older [30]. It measures four key attention domains: inattentiveness, impulsivity, sustained attention, and vigilance. This assessment is achieved by analyzing participants’ response patterns to specific target stimuli while ignoring non-target stimuli. The CPT-3 produces T-scores for the following measures: Detectability, Omissions, Commissions, Hit Reaction Time (HRT), Hit Reaction Time Standard Deviation (HRT SD), Variability, Perseverations, HRT Block Change, and HRT Inter-Stimulus Interval Change (HRT ISI Change). These scores collectively structure the four domains of attention.
Statistical analysis
Statistical analyses were performed using SPSS (version 19.0; IBM Corp., Armonk, NY, USA). Paired t-tests were conducted to assess differences among intelligence subindex scores, specifically examining whether the WMI and PSI scores were lower than the VCI or PRI scores. Pearson’s correlation analysis was used to determine the relationship between K-WAIS-IV and CPT-3 scores. Additionally, participants were stratified into groups based on whether they were prescribed medication during the outpatient visit prior to the neuropsychological test.
Ethical approval and consent to participate
Ethical approval for this study was obtained from the Institutional Review Board of Seoul National University Hospital, which waived the requirement for informed consent (IRB Number: H-2211-155-1382).
RESULTS
Participant characteristics
A total of 105 participants (81% male) aged 16–27 years (mean age=19.1±2.2 years) diagnosed with ADHD completed the K-WAIS-IV assessment (Table 1). Results from the KWAIS-IV showed the following scores: FSIQ=80.7±22.8, VCI=88.8± 20.6, PRI=84.6±21.5, WMI=85.7±22.0, and PSI=79.3±19.8. Among them, 46 (43.8%) were taking medications for ADHD. Moreover, 68 participants underwent CPT-3 testing, with T-scores for each subindex as follows: Detectability=48.3±13.2, Omissions=51.6±13.2, Commissions=47.7±10.4, HRT=53.0±12.6, HRT SD=47.8±13.8, Variability=48.1±12.1, Perseverations=49.9±10.6, HRT Block Change=47.1±11.3, and HRT ISI Change=49.0±10.1. Our primary analysis centered on the K-WAIS-IV scores for all 105 participants, with a subset analysis including the CPT-3 results conducted on 68 participants.
Differences in intelligence subindex scores
We conducted paired t-tests to analyze the differences between the K-WAIS-IV sub-indices. The results indicated that the WMI scores were significantly lower than the VCI scores, whereas the PSI scores were significantly lower than all three other subindex scores (Table 2).
Table 2.
Difference between intelligence subindex scores
| Measures | Paired differences | t | df | p | |
|---|---|---|---|---|---|
| Mean±SD | 95% CI | ||||
| VCI minus PRI | 4.219±13.523 | 1.602-6.836 | 3.197 | 104 | 0.002** |
| VCI minus WMI | 3.162±14.044 | 0.444-5.880 | 2.307 | 104 | 0.023* |
| VCI minus PSI | 9.581±16.766 | 6.336-12.826 | 5.856 | 104 | <0.001*** |
| PRI minus WMI | -1.057±14.042 | -3.775-1.660 | -0.771 | 104 | 0.442 |
| PRI minus PSI | 5.362±15.498 | 2.363-8.361 | 3.545 | 104 | 0.001** |
| WMI minus PSI | 6.419±16.632 | 3.200-9.638 | 3.955 | 104 | <0.001*** |
*p<0.05; **p<0.01; ***p<0.001. CI, confidence interval; PRI, Perceptual Reasoning Index; PSI, Processing Speed Index; SD, standard deviation; VCI, Verbal Comprehension Index; WMI, Working Memory Index
Relationship between intelligence subindex scores and CPT-3
We analyzed the correlation between the K-WAIS-IV subindex scores and CPT-3 measures. Significant negative correlations were identified between all four K-WAIS-IV subindex scores and CPT-3 scores, including Detectability, Omissions, Commissions, Perseverations, HRT, HRT SD, and Variability. However, no significant correlations were found with the other two CPT-3 measures—HRT Block Change and ISI Change—which exhibited no statistical significance (Table 3).
Table 3.
Relationship between intelligence subindex scores and CPT-3
| Measures | K-WAIS-IV | ||||
|---|---|---|---|---|---|
| VCI | PRI | WMI | PSI | FSIQ | |
| Detectability | -0.630*** | -0.407** | -0.523*** | -0.557*** | -0.591*** |
| Omissions | -0.649*** | -0.479*** | -0.483*** | -0.495*** | -0.592*** |
| Commissions | -0.501*** | -0.325** | -0.486*** | -0.484*** | -0.500*** |
| HRT | -0.310* | -0.292* | -0.265* | -0.346** | -0.336** |
| HRT SD | -0.529*** | -0.373** | -0.454*** | -0.474*** | -0.509*** |
| Variability | -0.535*** | -0.357** | -0.511*** | -0.398** | -0.497*** |
| Perseverations | -0.515*** | -0.424*** | -0.399** | -0.448*** | -0.496*** |
| HRT Block Change | -0.076 | -0.062 | -0.050 | -0.070 | -0.079 |
| HRT ISI Change | -0.072 | -0.077 | -0.082 | -0.073 | -0.086 |
*p<0.05; **p<0.01; ***p<0.001. CPT-3, The Conners Continuous Performance Test 3rd Edition; FSIQ, Full Scale Intelligence Quotient; HRT, Hit Reaction Time; HRT Block Change, Hit Reaction Time Block Change; HRT ISI Change, Hit Reaction Time Inter-Stimulus Intervals Change; HRT SD, Hit Reaction Time Standard Deviation; K-WAIS-IV, Korean version of Wechsler Adult Intelligence Scale 4th Edition; PRI, Perceptual Reasoning Index; PSI, Processing Speed Index; VCI, Verbal Comprehension Index; WMI, Working Memory Index
Additional analysis based on medication prescription
We investigated the cognitive differences among ADHD patients based on medication prescriptions. The criteria for prescribing medications focused on ADHD treatment, specifically methylphenidate or atomoxetine. Patients who did not take any of these medications were classified as ADHD patients not on medication. Based on this criterion, 46 subjects who underwent the K-WAIS-IV and 32 subjects who underwent the CPT-3 were classified as patients on medication. Participants who did not receive medication during the outpatient visit preceding the neuropsychological test tended to have higher intelligence scores than those who were prescribed medication. Statistically significant differences were observed only in the PSI scores, not in the FSIQ or other indices. Additionally, no significant differences were found in CPT-3 scores between the two groups (Table 4).
Table 4.
Additional analysis based on medication prescription
| Characteristics | Prescription before the test | p | |
|---|---|---|---|
| Yes | No | ||
| Age (yr) | 19.3±2.2 | 19.0±2.3 | 0.568 |
| Sex, male | 41 (89.1) | 44 (74.6) | 0.060 |
| K-WAIS-IV | |||
| VCI | 88.1±19.1 | 89.4±21.8 | 0.736 |
| PRI | 82.5±21.9 | 86.3±21.2 | 0.370 |
| WMI | 81.5±21.7 | 88.9±21.8 | 0.086 |
| PSI | 74.9±18.9 | 82.6±20.0 | 0.048* |
| FSIQ | 77.6±22.3 | 83.1±23.1 | 0.227 |
| CPT-3 (T-score) | |||
| Detectability | 48.0±11.5 | 48.4±14.7 | 0.899 |
| Omissions | 50.2±9.5 | 52.8±15.9 | 0.407 |
| Commissions | 48.0±10.1 | 47.3±10.7 | 0.776 |
| HRT | 53.7±11.9 | 52.4±13.3 | 0.679 |
| HRT SD | 46.0±12.0 | 49.4±15.2 | 0.311 |
| Variability | 46.3±10.9 | 49.7±13.1 | 0.263 |
| Perseverations | 48.2±6.7 | 51.4±13.1 | 0.200 |
| HRT Block Change | 47.8±11.2 | 46.3±11.5 | 0.591 |
| HRT ISI Change | 49.1±11.3 | 49.0±9.0 | 0.961 |
Values are presented as mean±standard deviation or n (%). n=46 (age, sex, and K-WAIS-IV scores) and 32 (CPT-3 scores) for participants who were prescribed medication before the test. n=59 (age, sex, and K-WAIS-IV scores) and 36 (CPT-3 scores) for participants who were not prescribed medication before the test, except for CPT-3 Inattentiveness Variability (n=35) and Sustained Attention HRT Block Change (n=35). *p<0.05. CPT-3, The Conners Continuous Performance Test 3rd Edition; FSIQ, Full Scale Intelligence Quotient; HRT, Hit Reaction Time; HRT Block Change, Hit Reaction Time Block Change; HRT ISI Change, Hit Reaction Time Inter-Stimulus Intervals Change; HRT SD, Hit Reaction Time Standard Deviation; K-WAIS-IV, Korean version of Wechsler Adult Intelligence Scale 4th Edition; PRI, Perceptual Reasoning Index; PSI, Processing Speed Index; VCI, Verbal Comprehension Index; WMI, Working Memory Index
Participants who were prescribed medication before the test demonstrated similar results in the comparison of KWAIS-IV subindex scores with those observed in the full sample (Table 5). Specifically, the WMI scores were significantly lower than the VCI scores, whereas the PSI scores were significantly lower than all three other subindex scores. Conversely, participants who were not prescribed medication before the test showed a significant decline in PSI scores compared with VCI and WMI.
Table 5.
Difference between intelligence subindex scores based on medication prescription
| Measures | Paired differences | t | df | p | |
|---|---|---|---|---|---|
| Mean±SD | 95% CI | ||||
| Prescription before the test, yes (n=46) | |||||
| VCI minus PRI | 5.587±13.077 | 1.704-9.470 | 2.898 | 45 | 0.006** |
| VCI minus WMI | 6.565±13.502 | 2.556-10.575 | 3.298 | 45 | 0.002** |
| VCI minus PSI | 13.130±13.875 | 9.010-17.251 | 6.418 | 45 | <0.001*** |
| PRI minus WMI | 0.978±12.461 | -2.722-4.679 | 0.532 | 45 | 0.597 |
| PRI minus PSI | 7.543±14.031 | 3.377-11.710 | 3.646 | 45 | 0.001** |
| WMI minus PSI | 6.565±14.826 | 2.162-10.968 | 3.003 | 45 | 0.004** |
| Prescription before the test, no (n=59) | |||||
| VCI minus PRI | 3.153±13.879 | -0.464-6.769 | 1.745 | 58 | 0.086 |
| VCI minus WMI | 0.508±13.996 | -3.139-4.156 | 0.279 | 58 | 0.781 |
| VCI minus PSI | 6.814±18.355 | 2.030-11.597 | 2.851 | 58 | 0.006** |
| PRI minus WMI | -2.644±15.074 | -6.572-1.284 | -1.347 | 58 | 0.183 |
| PRI minus PSI | 3.661±16.469 | -0.631-7.953 | 1.707 | 58 | 0.093 |
| WMI minus PSI | 6.305±18.039 | 1.604-11.006 | 2.685 | 58 | 0.009** |
**p<0.01; ***p<0.001. CI, confidence interval; PRI, Perceptual Reasoning Index; PSI, Processing Speed Index; SD, standard deviation; VCI, Verbal Comprehension Index; WMI, Working Memory Index
In terms of the correlation between the K-WAIS-IV subindex scores and CPT-3, significant negative correlations were found between all four K-WAIS-IV subindex scores and CPT-3 scores, except for the HRT Block Change and HRT ISI Change measures, in both groups. However, stronger correlations were observed among participants who did not receive medication prescriptions before the test (Table 6).
Table 6.
Relationship between intelligence subindex scores and CPT-3 based on medication prescription
| Measures | K-WAIS-IV | ||||
|---|---|---|---|---|---|
| VCI | PRI | WMI | PSI | FSIQ | |
| Prescription before the test, yes (n=32) | |||||
| Detectability | -0.531** | -0.231 | -0.406* | -0.421* | -0.413* |
| Omissions | -0.535** | -0.288 | -0.265 | -0.273 | -0.363* |
| Commissions | -0.441* | -0.276 | -0.449** | -0.487** | -0.433* |
| HRT | -0.270 | -0.285 | -0.186 | -0.227 | -0.284 |
| HRT SD | -0.538** | -0.327 | -0.432* | -0.379* | -0.453** |
| Variability | -0.529** | -0.358* | -0.495** | -0.397* | -0.472** |
| Perseverations | -0.609*** | -0.432* | -0.476** | -0.358* | -0.489** |
| HRT Block Change | -0.222 | -0.219 | -0.181 | -0.120 | -0.206 |
| HRT ISI Change | -0.111 | -0.033 | -0.097 | -0.040 | -0.076 |
| Prescription before the test, no (n=36) | |||||
| Detectability | -0.691*** | -0.548** | -0.617*** | -0.666*** | -0.725*** |
| Omissions | -0.725*** | -0.630*** | -0.644*** | -0.661*** | -0.760*** |
| Commissions | -0.543** | -0.368* | -0.516** | -0.485** | -0.553*** |
| HRT | -0.333* | -0.295 | -0.317 | -0.425** | -0.371* |
| HRT SD | -0.543** | -0.435** | -0.516** | -0.596*** | -0.588*** |
| Variability | -0.567*** | -0.386* | -0.583*** | -0.476** | -0.567*** |
| Perseverations | -0.518** | -0.482** | -0.436** | -0.568*** | -0.571*** |
| HRT Block Change | 0.036 | 0.091 | 0.075 | -0.010 | 0.040 |
| HRT ISI Change | -0.039 | -0.128 | -0.066 | -0.108 | -0.099 |
*p<0.05; **p<0.01; ***p<0.001. CPT-3, The Conners Continuous Performance Test 3rd Edition; FSIQ, Full Scale Intelligence Quotient; HRT, Hit Reaction Time; HRT Block Change, Hit Reaction Time Block Change; HRT ISI Change, Hit Reaction Time Inter-Stimulus Intervals Change; HRT SD, Hit Reaction Time Standard Deviation; K-WAIS-IV, Korean version of Wechsler Adult Intelligence Scale 4th Edition; PRI, Perceptual Reasoning Index; PSI, Processing Speed Index; VCI, Verbal Comprehension Index; WMI, Working Memory Index
To mitigate the potential confounding effects of age and sex, we conducted a correlation analysis between the K-WAISIV subindex scores and the CPT-3, controlling for these variables (Table 7). Significant associations were found between the K-WAIS-IV subindex scores and CPT-3, except for the HRT Block Change and HRT ISI Change measures, which aligned with the findings from the analysis without adjustment for age and sex, as shown in Table 3.
Table 7.
Correlation between intelligence subindex scores and CPT-3 adjusted for age and sex
| Measures | B | SE | p | 95% CI |
|---|---|---|---|---|
| Detectability | ||||
| VCI | -0.825 | 0.127 | <0.001*** | -1.079 to -0.570 |
| PRI | -0.638 | 0.171 | <0.001*** | -0.979 to -0.297 |
| WMI | -0.835 | 0.170 | <0.001*** | -1.174 to -0.496 |
| PSI | -0.767 | 0.144 | <0.001*** | -1.055 to -0.480 |
| FSIQ | -0.925 | 0.157 | <0.001*** | -1.240 to -0.611 |
| Omissions | ||||
| VCI | -0.861 | 0.125 | <0.001*** | -1.111 to -0.612 |
| PRI | -0.735 | 0.166 | <0.001*** | -1.066 to -0.403 |
| WMI | -0.762 | 0.176 | <0.001*** | -1.114 to -0.409 |
| PSI | -0.694 | 0.151 | <0.001*** | -0.995 to -0.392 |
| FSIQ | -0.930 | 0.159 | <0.001*** | -1.246 to -0.613 |
| Commissions | ||||
| VCI | -0.845 | 0.182 | <0.001*** | -1.207 to -0.482 |
| PRI | -0.682 | 0.226 | 0.004** | -1.133 to -0.231 |
| WMI | -1.009 | 0.222 | <0.001*** | -1.452 to -0.566 |
| PSI | -0.852 | 0.194 | <0.001*** | -1.240 to -0.463 |
| FSIQ | -1.104 | 0.216 | <0.001*** | -1.445 to -0.583 |
| HRT | ||||
| VCI | -0.460 | 0.172 | 0.009** | -0.804 to -0.117 |
| PRI | -0.492 | 0.199 | 0.016* | -0.890 to -0.094 |
| WMI | -0.430 | 0.214 | 0.048* | -0.858 to -0.003 |
| PSI | -0.548 | 0.179 | 0.003** | -0.905 to -0.191 |
| FSIQ | -0.586 | 0.203 | 0.005** | -0.992 to -0.179 |
| HRT SD | ||||
| VCI | -0.678 | 0.134 | <0.001*** | -0.947 to -0.410 |
| PRI | -0.544 | 0.170 | 0.002** | -0.883 to -0.205 |
| WMI | -0.690 | 0.173 | <0.001*** | -1.035 to -0.344 |
| PSI | -0.645 | 0.147 | <0.001*** | -0.939 to -0.352 |
| FSIQ | -0.771 | 0.163 | <0.001*** | -1.096 to -0.445 |
| Variability | ||||
| VCI | -0.770 | 0.152 | <0.001*** | -1.074 to -0.466 |
| PRI | -0.588 | 0.194 | 0.004** | -0.975 to -0.200 |
| WMI | -0.893 | 0.188 | <0.001*** | -1.270 to -0.517 |
| PSI | -0.601 | 0.171 | 0.001** | -0.942 to -0.260 |
| FSIQ | -0.845 | 0.186 | <0.001*** | -1.217 to -0.474 |
| Perseverations | ||||
| VCI | -0.868 | 0.177 | <0.001*** | -1.223 to -0.514 |
| PRI | -0.821 | 0.216 | <0.001*** | -1.253 to -0.390 |
| WMI | -0.783 | 0.233 | 0.001** | -1.248 to -0.317 |
| PSI | -0.799 | 0.195 | <0.001*** | -1.189 to -0.409 |
| FSIQ | -0.987 | 0.215 | <0.001*** | -1.417 to -0.558 |
| HRT Block Change | ||||
| VCI | -0.116 | 0.193 | 0.548 | -0.502 to 0.269 |
| PRI | -0.118 | 0.222 | 0.596 | -0.562 to 0.325 |
| WMI | -0.099 | 0.235 | 0.674 | -0.569 to 0.370 |
| PSI | -0.113 | 0.204 | 0.583 | -0.521 to 0.295 |
| FSIQ | -0.148 | 0.230 | 0.521 | -0.607 to 0.311 |
| HRT ISI Change | ||||
| VCI | -0.131 | 0.214 | 0.543 | -0.559 to 0.297 |
| PRI | -0.134 | 0.246 | 0.587 | -0.626 to 0.358 |
| WMI | -0.184 | 0.260 | 0.482 | -0.703 to 0.335 |
| PSI | -0.147 | 0.226 | 0.519 | -0.598 to 0.305 |
| FSIQ | -0.180 | 0.255 | 0.483 | -0.689 to 0.329 |
The analyses were adjusted for age and sexes. *p<0.05; **p<0.01; ***p<0.001. B, unstandardized regression coefficient; CI, confidence interval; CPT-3, The Conners Continuous Performance Test 3rd Edition; FSIQ, Full Scale Intelligence Quotient; HRT, Hit Reaction Time; HRT Block Change, Hit Reaction Time Block Change; HRT ISI Change, Hit Reaction Time Inter-Stimulus Intervals Change; HRT SD, Hit Reaction Time Standard Deviation; PRI, Perceptual Reasoning Index; PSI, Processing Speed Index; SE, standard error; VCI, Verbal Comprehension Index; WMI, Working Memory Index
DISCUSSION
In our study, participants diagnosed with ADHD exhibited a mean FSIQ score of 80.7±22.8—notably lower than the average for their age group. Specifically, among the K-WAISIV subindex scores, the PSI showed the lowest mean score, followed by the PRI, WMI, and VCI, in ascending order. When comparing each index, we observed a statistically significant decrease in PSI scores compared to the other sub-indices. Nevertheless, contrary to our initial hypothesis, the decline in working memory scores was not statistically significant compared to the other indices.
This result aligns with previous studies demonstrating that the PSI is associated with inattentiveness [19,31] and is significantly reduced in patients with ADHD [32]. From this perspective, our study confirms that participants with ADHD exhibit inattentiveness problems, as reflected in the PSI. However, the WMI was not significantly reduced compared to other indices, contrary to previous studies that emphasized PSI and WMI as key contributors to overall cognitive impairment in the ADHD population [12,13,33,34].
These results suggest that the PSI may be more specific to ADHD than the WMI. This interpretation is supported by a study by Anker et al. [25], where only the PSI was significantly correlated with ADHD severity among other WAISIII indices, including the WMI. While working memory is considered one of the core symptoms [35] of ADHD, the results of WMI reduction in ADHD vary [36]. This variability has been attributed to the limited discriminant power of the WMI and methodological variability [37].
In our study, regarding the correlations between K-WAISIV and CPT-3 scores, all four indices of K-WAIS-IV were negatively correlated with CPT-3 scores, except for the HRT Block Change and HRT ISI Change measures. This finding deviated from our a priori hypothesis, which anticipated that only the WMI and PSI from the K-WAIS-IV would exhibit significant negative correlations with CPT-3 scores. This could be explained by the dual vulnerability arising from potential comorbidities in participants with ADHD, such as borderline intellectual functioning or intellectual disabilities, given the low average FSIQ score of the study group. Notably, individuals with intellectual disabilities are more likely to have ADHD as a comorbid condition [38-40], and several studies have shown that those with intellectual disability and ADHD tend to experience greater impairments in attentional processes [41,42].
Interestingly, a meta-analysis by Callan et al. [43] highlighted that the HRT Block Change and HRT ISI Change variables were among the least reported to be statistically significant in ADHD populations across all ages, which is consistent with these measures showing the least correlation with K-WAIS-IV scores in ADHD patients in our study. The underlying reasons for these findings warrant further investigation.
Regardless of medication intake, our study found similar results on the CPT-3. However, individuals who did not take any medications had higher intelligence scores. This could be attributed to the severity of ADHD symptoms and the resulting impairment in functioning, which might influence the decision to use medications. Moreover, those not taking medication might compensate with relatively higher intelligence to achieve comparable functional improvements.
The relationship between working memory and ADHD has been attributed to prefrontal cortex dysfunction [15]. However, neurological mechanisms underlying the association between processing speed and ADHD remain inadequately understood. Some researchers argue that processing speed may act as an underlying variable influencing various cognitive abilities or functions [44]. According to Kail and Salthouse [45], processing speed is a fundamental cognitive resource that underpins a range of higher-order functions, including executive functions. They proposed that improvements in processing speed during development and declines in processing speed with age could explain the changes in working memory during these periods [45]. This may be relevant to the consistent reductions in WMI and PSI scores observed in individuals with ADHD in this study and previous research.
More recently, Clark et al. [46] suggested that impaired processing speed can limit the amount of information perceived because the cognitive effort is directed toward processing prior information, leading to missed information. Thus, processing speed may have a cascading effect on overarching executive function domains such as attentional shifting/cognitive flexibility, updating/working memory, and inhibition [46]. As these executive function domains are frequently impaired in ADHD, this hypothesis aligns well with the findings of this study, in which PSI scores played a pivotal role compared with other indices of the K-WAIS-IV in individuals with ADHD.
Neurologically, evidence suggests that the cerebellum may play a significant role in mediating processing speed [47,48]. Although cerebellar abnormalities have been reported in individuals with ADHD [49], more research is necessary to explore the direct link between these abnormalities and processing speed.
This study has several limitations. First, it lacked a control group to differentiate participants with ADHD, relying solely on the age-adjusted mean scales of the K-WAIS-IV and CPT-3. This limitation suggests that the observed results may have been influenced by factors unrelated to ADHD symptoms. Moreover, the average FSIQ scores of 80.7 among all participants and 77.6 for those on ADHD medications were lower than the cognitive decline observed in previous studies of ADHD participants [11,50]. This study collected data from patients at a tertiary medical institution, which may indicate characteristics that differ from those of the general ADHD population. This discrepancy raises concerns about the representativeness of the study’s findings, suggesting that they may not accurately reflect the cognitive abilities of the broader ADHD population within this age group. Second, the analysis included only the most recent follow-up examinations, which may not have adequately captured the developmental or aging aspects of ADHD. Further longitudinal studies are necessary to confirm this hypothesis. Third, the study contained insufficient information regarding medication use—dosage information was not collected because the appropriate dosage of ADHD medications varies according to the patient’s weight, which is often not recorded in medical records. Additionally, medication use data were collected only at the time of testing, without capturing the total duration of medication use for each patient. Furthermore, for patients who were prescribed medication during their most recent visit before testing, it was unclear whether they continued to take the medication during the test or if they had temporarily discontinued it to assess their cognitive abilities without the influence of medication. These limitations, including the heterogeneity of medicated and non-medicated subjects in our analysis, inhibit the interpretation of our findings.
Despite these limitations, this study has several notable strengths. First, it employed the K-WAIS-IV and CPT-3, both widely used and up-to-date neurocognitive assessment tools in clinical settings. While many previous studies have examined the neurocognitive profiles of ADHD patients, they have often relied on earlier versions of these assessments or tools primarily designed for research, which are less applicable to clinical practice. Second, this study confirmed reductions in WMI and PSI scores in ADHD patients and elucidated the relationship between these scores and continuous performance test results. Third, unlike similar international studies that included a wide age range from adolescents to older adults, this study focused on a narrower age range, yielding more age-specific insights. Finally, our study is one of the few naturalistic, retrospective observational studies conducted within the Korean population to examine the neurocognitive profiles of ADHD patients. As previous research has reported somewhat divergent results across different countries, this study contributes to greater cultural and ethnic diversity in ADHD studies, enhancing our understanding of ADHD in a broader context.
CONCLUSION
The PSI score was notably lower than the other indices of the K-WAIS-IV in ADHD patients. Our study also identified a statistically significant negative correlation between the KWAIS-IV sub-indices and CPT-3 subtest measures, excluding HRT Block Change and HRT ISI Change, among participants with ADHD. This suggests that the PSI may be a useful predictor of ADHD in early adulthood. However, for a comprehensive assessment, clinicians should consider incorporating self-report measures and background questionnaires along with neurocognitive profiles to enhance the diagnostic accuracy and understanding of ADHD.
Acknowledgments
None
Footnotes
Availability of Data and Material
The data may be available upon reasonable request after approval from the institutional review board.
Conflicts of Interest
The authors have no potential conflicts of interest to disclose.
Author Contributions
Conceptualization: Heesung So, Soon-Beom Hong. Data curation: Heesung So, Soon-Beom Hong. Formal analysis: Heesung So, Soon-Beom Hong. Investigation: Heesung So, Soon-Beom Hong. Methodology: Heesung So, Soon-Beom Hong. Project administration: Heesung So, Soon-Beom Hong. Resources: Heesung So, Soon-Beom Hong. Software: Heesung So, Soon-Beom Hong. Supervision: Soon-Beom Hong. Validation: Heesung So, Soon-Beom Hong. Visualization: Heesung So, Soon-Beom Hong. Writing—original draft: Heesung So, Soon-Beom Hong. Writing—review & editing: Heesung So, Soon-Beom Hong.
Funding Statement
None
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