Attention-related disorders like attention deficit hyperactivity disorder (ADHD) and sluggish cognitive tempo (SCT) are primarily conceptualized as neuropsychological problems in attentional dysfunction (Bauermeister et al., 2012). However, individuals with (vs. without) ADHD/SCT experience problems in many areas of daily life, including academic, occupational, and social functioning (Becker & Langberg, 2013; Holst & Thorell, 2020; Smith & Langberg, 2017), and emotional processing (Hartman et al., 2019). Despite ADHD and SCT appearing similar on the surface, they result in different consequences. For example, SCT has been identified as an independent predictor of internalizing symptoms, such as shyness or poor reading achievement, whereas ADHD has been associated more with externalizing symptoms, such as poor mathematics achievement and slow processing speed (Becker, Burns, Leopold, et al., 2018).

The differences between the consequences of these disorders may arise because the two conditions have different properties. Previous studies have suggested SCT and ADHD are separate disorders that have discriminant factor structures (e.g., Becker et al., 2016). Therefore, a valid and reliable scale distinguishing SCT from ADHD is essential for proper assessment and treatment (Lovett et al., 2021). Scales such as the Adult Concentration Inventory (Becker, Burns, Garner, et al., 2018a) and the Barkley Adult ADHD Rating Scale-IV (BAARS-IV; Barkley, 2011) are widely used to evaluate SCT as a distinct symptom from ADHD in adult populations (Becker et al., 2015; Penny et al., 2009).

The BAARS-IV enables measurement of ADHD symptoms based on the Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM-V]; American Psychiatric Association, 2013) and SCT symptoms in adults within a single measure, and its validity and reliability have been verified in various samples (Becker, 2021; Nitta, 2018). The BAARS-IV comprises four dimensions covering three ADHD symptom domains (inattention, hyperactivity, impulsivity), and three SCT symptom domains (hypoactivity, lethargy, slow movement; Becker et al., 2011). Although the BAARS-IV is useful to discriminate ADHD from SCT, it yields mixed results in terms of psychometric properties. For example, there is no consensus about whether SCT is a unidimensional or multidimensional factor (Becker, 2021). Early works conceptualized SCT as a single factor (e.g., Becker et al., 2014; Willcutt et al., 2014), but there is incremental evidence supporting the multidimensional perspective. For example, Lunsford-Avery et al. (2021) proposed three SCT dimensions of slow/daydreamy, sleepy/sluggish, and low initiation/persistence, and Smith and Suhr (2021) used the dimensions of daydreaming/bored, lethargic, and cognitive complaints.

Moreover, the psychometric properties of the BAARS-IV differ across cultures. In North American samples the scale has shown a good fit on the basis of confirmatory factor analysis with a four-factor solution comprising ADHD inattention, ADHD hyperactivity, ADHD impulsivity, and SCT (Becker et al., 2014), whereas Loong (2015) found that the four-factor solution did not fit a Hong Kong population. In a Turkish population, when the SCT items of the BAARS-IV were separated into two domains (daydreaming and sluggishness) the results differed from those for the North American population (Gul & Gul, 2022). Further, Takeda et al. (2019) found only five of nine SCT domains were valid in a Japanese population. The aforementioned studies demonstrate the necessity of further exploration of the psychometric properties of the BAARS-IV to identify appropriate factor structures in various cultures.

In addition, despite SCT being reported as having a considerable influence on treatment response (Froehlich et al., 2018), it has been disregarded in psychiatric assessment and in the treatment of attention-related disorders in Korea (Bahn et al., 2020). Since the BAARS-IV has not been validated for the Korean population there is not yet a measurement tool that can evaluate and discriminate between attention-related symptoms for Korean people, hindering the development of appropriate interventions. Thus, we investigated the factor structure and verified the reliability and validity of the BAARS-IV in a Korean adult population.

Method

Participants

This study was part of a larger project aimed at developing an attention training program for young adults with SCT (K. Kim et al., 2020). We recruited 1,098 participants with attentional problems via online communities, psychiatric clinics, and university bulletin boards in Seoul, South Korea. Of the 771 participants who completed all questionnaires and were eligible for this study, 429 (55.64%) were women, 330 (10.80%) were men, and 12 (1.56%) did not specify their gender. Their ages ranged from 18 to 58 years (M = 21.73, SD = 4.00). The institutional review board of Chung-Ang University (No. 1041078-202001-HR-010-01) approved the procedure for this study, and we obtained the informed consent of participants.

Measures

The Barkley Adult Attention Deficit Hyperactivity Disorder Rating Scale-IV
We measured ADHD and SCT symptoms using the BAARS-IV, which is a 27-item self-report questionnaire that consists of 18 items measuring ADHD symptoms and nine items for SCT symptoms (Barkley, 2011). Each item is rated on a 4-point Likert scale ranging from 1 (not at all) to 4 (very often). The total score ranges from 27 to 108. A higher score means that participants experience more severe ADHD/SCT symptoms.

World Health Organization Adult Attention Deficit Hyperactivity Disorder Self-Report Scale
The 18-item World Health Organization Adult Attention Deficit Hyperactivity Disorder Self-Report Scale (ASRS) is a self-report questionnaire that measures adult ADHD symptoms and was developed based on the DSM-V criteria (Kessler et al., 2005). Each item is rated on a 5-point Likert scale from 0 (never) to 4 (very often). The total score ranges from 0 to 72. A higher score means that participants experience more severe ADHD symptoms. In this study the internal consistency of the ASRS was good (Cronbach’s α = .87).

The Beck Depression Inventory – Second Edition
Severity of depression was measured with the Beck Depression Inventory – Second Edition (BDI-II; Beck et al., 1996), which is a self-report questionnaire that consists of 21 items. Each item is rated on a 4-point Likert scale from 0 (not at all) to 3 (severely). The total score ranges from 0 to 63. A higher score means that participants experience a higher level of depression. In this study the internal consistency of the BDI was excellent (Cronbach’s α = .94).

The Beck Anxiety Inventory
The Beck Anxiety Inventory (BAI; Beck et al., 1988) is a self-report questionnaire that consists of 21 items measuring the severity of anxiety. Each item is rated on a 4-point Likert scale from 0 (not at all) to 3 (severely). The total score ranges from 0 to 63. A higher score means that participants experience a higher level of anxiety. In this study the internal consistency of the BAI was excellent (Cronbach’s α = .93).

Translation

Two bilingual individuals fluent in both English and Korean translated the BAARS-IV. One of the translators was a graduate student majoring in clinical psychology, whereas the other had no background in psychology. First, the English version of the BAARS-IV was forward-translated into Korean by one translator (T1). Second, the translated version was back-translated by another translator (T2). Last, a licensed clinical psychologist and one translator (T1) reviewed the final Korean version of the BAARS-IV.

Data Analysis

We performed statistical analyses using SPSS 26 and Amos 26, and evaluated the construct validity of the BAARS-IV using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). We split the data in half; one set of data each was used for EFA (N = 386) and CFA (N = 385). EFA using principal axis factoring with Promax rotation was performed to ascertain the factor structure of the BAARS-IV in the Korean population. To ensure the adequacy of factor analysis, we used the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity. KMO > .60 was considered acceptable (Kaiser, 1970). We determined the number of factors based on Kaiser’s rule (eigenvalues > 1.0), scree plots, and parallel analysis. Items with factor loadings below .40 or those that loaded on multiple factors were deleted. To validate the factor structure found in EFA we used CFA with maximum-likelihood estimation. Comparative fit index (CFI) > .90, Tucker–Lewis Index (TLI) > .90, and root mean square error of approximation (RMSEA) < .80 were considered as acceptable model fit indices (Browne & Cudeck, 1992). Concurrent validity was assessed by Pearson correlation analysis.

Results

Factor Analysis

We performed an EFA to explore the factor structure of the BAARS-IV with a Korean sample. The KMO measure of sampling adequacy of .93 and Bartlett’s test of sphericity result of χ²(351) = 4491.41 were significant at p < .001; thus, our sample was suitable for EFA. On the basis of Kaiser’s rule, we extracted five eigenvalues. Contrary to Kaiser’s rule, the results of the scree plot (see Figure 1) and parallel analysis supported the two-factor model. Previous research has suggested that more than just eigenvalues be used when deciding on the number of factors (Reise et al., 2000). However, underextraction of factors can cause considerably greater error bias compared to overextraction (Wood et al., 1996). Loong (2015) found support for the five-factor structure of the BAARS-IV (ADHD inattention, ADHD hyperactivity, ADHD impulsivity, SCT sluggishness, SCT ennui) via EFA with a sample from Hong Kong. Therefore, we adopted the five-factor model in consideration of the eigenvalues.

The EFA results showed a different factor structure from that of the original BAARS-IV, except for the impulsivity domain (ADHD impulsivity, e.g., “I blurt out answers before questions have been completed”). The first factor (SCT) consisted of six SCT items (e.g., “I am spacey or in a fog”). We loaded four inattention items (e.g., “I fail to give close attention to details or make careless mistakes in my work or other activities”) on the second factor (ADHD inattention). Items 8, 10, 19, 20, and 22 formed a new factor (sustained attention; e.g., “I have trouble staying alert or awake in boring situations”) that was not in the original factor structure. We named this factor sustained attention because the content of these items was related to problems with maintaining attention over time, rather than carelessness or sluggishness. The fifth factor (ADHD hyperactivity) included three hyperactivity items and one inattention item (e.g., “Shift around excessively or feel restless or hemmed in”). We excluded four items due to their low factor loadings (< .40; Items 2 and 14) or loading on more than one factor (Items 3 and 6). The five-factor solution accounted for 57.78% of the total variance. The results of the EFA are summarized in Table 1.

A CFA was performed to examine the adequacy of the five-factor model identified in the EFA with the Korean population. The five-factor model showed a poor model fit, CFI = .87, TLI = .85, RMSEA = .072, 90% confidence interval (CI) [.066, .078]. On the basis of these modification indices and a theoretical background search, we added three correlated residuals to the measurement model: Item 19 (“I am prone to daydreaming when I should be concentrating on something or working”) correlated with Item 23 (“I am spacey or in a fog”); Item 24 (“I am lethargic or more tired than others”) correlated with Item 25 (“I am underactive or have less energy than others”); and Item 26 (“I am slow moving”) correlated with Item 27 (“I don’t seem to process information as quickly or as accurately as others”). The measurement model provided an acceptable fit to the data, CFI = .92, TLI = .90, RMSEA = .059, 90% CI [.052, .065]. This finding suggests that the BAARS-IV showed a distinctive factor structure in the Korean population that differed from the original four-factor model.

Reliability

We measured the reliability of the BAARS-IV using Cronbach’s alpha internal consistency coefficient. For the entire scale, internal consistency was excellent (α = .93). Each dimension also showed good-to-acceptable internal consistency: ADHD inattention = .78, SCT = .84, ADHD hyperactivity = .78, sustained attention = .78, ADHD impulsivity = .74.

Concurrent Validity

To investigate the association between the BAARS-IV and other variables, we conducted a Pearson correlation analysis. We found the BAARS-IV was positively correlated with the ASRS (r = .76, p < .001) and that it showed a moderate positive correlation with the BDI-II (r = .65, p < .001) and the BAI (r = .62, p < .001). All the BAARS-IV factors were positively correlated with the ASRS, the BDI-II, and the BAI. The results of Pearson correlation analysis are presented in Table 2.

Discussion

We identified a five-factor model of the BAARS-IV and verified the translated scale’s validity and reliability in a Korean sample. The results demonstrate that the original four-factor model of the BAARS-IV was not adequate for the Korean population. Our findings are consistent with those of a study conducted with a Hong Kong population, which also reported on the inadequacy of the four-factor solution in an Eastern culture (Loong, 2015). However, the factor structure identified in this study differed from that of the Hong Kong population, which implies that the BAARS-IV shows different psychometric properties depending on cultural background. Specifically, in the Korean population, only four of the original inattention items clustered on the ADHD inattention factor, contrariwise to all nine ADHD inattention items maintained in the Hong Kong population. Loong (2015) also suggested SCT ennui as a fifth factor of the BAARS-IV that was not identified in other cultures. Thus, a cautious approach is recommended when applying the BAARS-IV to populations from different cultures.

A recent systematic review by Becker (2021) suggested that some SCT items are not optimal for distinguishing SCT from ADHD, and there is a need to eliminate them. In line with this argument, our results demonstrate that in the Korean population the SCT factor consists only of items capturing sluggishness/sleepy behavior and mental confusion. To advance the discriminant validity of the BAARS-IV it would be helpful to consider removing confounding items. In addition, a new factor, sustained attention, was found in an EFA. Willcutt et al. (2014) referred to a poor ability to sustain attention as a potential underlying mechanism of SCT symptoms. This provides evidence for an exclusive association between SCT and sustained attention, but other ADHD symptoms did not provide evidence of such a link. One possible explanation for this newfound factor is that Korea’s unique cultural features contribute to sustained attention. Korean culture puts a high value on academic performance (Jung, 2018) and on diligence and hard work (S. Kim et al., 2018), which may lead to a differential perception of problems in maintaining an attentive state at work or for academic tasks, resulting in classification of sustained attention as separate from other factors.

The original (Becker et al., 2014) and Korean versions of the BAARS-IV show comparable internal consistency. The correlation between the BAARS-IV and the ASRS was high and supported the scale’s concurrent validity. Further, the BAARS-IV was positively correlated with BDI-II and the BAI. These results reflect a high risk of comorbidity between depression, anxiety, and attention-related disorders (Katzman et al., 2017).

This study has several limitations. First, since we focused only on adult participants, the results may not be generalizable to children or adolescents. Further research could examine the validity of the BAARS-IV in other age populations (e.g., those aged 10–18 years). Second, we did not collect demographic characteristics like socioeconomic status and medication use. Controlling for these demographic variables may allow for a more profound understanding of the BAARS-IV.

Despite these limitations, this study is the first to investigate the psychometric properties of the BAARS-IV in the Korean population. Our findings provide evidence in favor of the clinical application of this translated scale to facilitate the accurate diagnosis of attention-related disorders.

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This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A5A8063980).

Kiho Kim, Department of Psychology of Counseling, Sejong Cyber University, Cheonho-daero 680, Gwangjin-gu, Seoul 04992, Republic of Korea. Email: [email protected]