Insecure Attachment, Temperament, and Character Traits Associated With Cognitive Disengagement Syndrome and Attention Deficit Hyperactivity Disorder Symptoms in Children

Article information

Psychiatry Investig. 2025;22(6):632-640
Publication date (electronic) : 2025 June 16
doi : https://doi.org/10.30773/pi.2025.0027
1Department of Child and Adolescent Psychiatry, Dr. Ismail Fehmi Cumalioglu City Hospital, Tekirdag, Turkey
2Department of Child and Adolescent Psychiatry, Istinye University, Istanbul, Turkey
3Department of Child and Adolescent Psychiatry, Yalova University, Yalova, Turkey
4Department of Child and Adolescent Psychiatry, Tinaztepe University, Izmir, Turkey
Correspondence: Hasan Can Özbay, MD Department of Child and Adolescent Psychiatry, Dr. Ismail Fehmi Cumalioglu City Hospital, Istiklal Mahallesi, Yemen Caddesi, No:13 Suleymanpasa, Tekirdag 59700, Turkey Tel: +90-543-494-14 04, E-mail: ozbayhasancan@gmail.com
Received 2025 January 17; Revised 2025 March 13; Accepted 2025 March 23.

Abstract

Objective

Based on the view that cognitive disengagement syndrome (CDS) and attention-deficit/hyperactivity disorder (ADHD) are distinct clinical conditions, we aimed to investigate differences between CDS and ADHD symptoms in terms of insecure attachment, temperament, and character traits in children.

Methods

We assessed 80 children with ADHD (24 girls and 56 boys, aged 9–12 years) through Turgay’s DSM-IV Based ADHD and Disruptive Behavior Disorders Screening Scale, Barkley Child Attention Scale, Kerns Security Scale, and the Junior Temperament and Character Inventory. Exclusion criteria included the presence of other psychiatric disorders or neurological diseases.

Results

CDS was significantly correlated with age (r=0.280, p=0.012), ADHD-inattention (r=0.435, p<0.001), harm avoidance (HA) (r=0.302, p=0.006), and insecure attachment (r=-0.280, p=0.012). Hierarchical multiple regression analysis indicated that age (beta=1.459, p=0.031), ADHD-inattention (beta=0.528, p=0.001), and HA (beta=0.306, p=0.044) were significant predictors of CDS severity. ADHD-inattention was significantly associated with delayed speech onset (r=-0.252, p=0.024), CDS (r=0.435, p<0.001), and novelty seeking (r=0.250, p=0.025), whereas ADHD-hyperactivity/impulsivity had an inversely significant correlation with self-directedness (r=-0.233, p=0.038). Only CDS significantly predicted the severity of ADHD-inattention (beta=0.252, p<0.001).

Conclusion

Our findings may suggest that examining CDS and ADHD in terms of attachment styles, temperament and character traits may improve our understanding of the distinctions between these two constructs.

INTRODUCTION

Attention-deficit/hyperactivity disorder (ADHD) is considered a neurodevelopmental disorder that emerges in early childhood and is characterized by symptoms of inattention, hyperactivity, and impulsivity [1]. Formerly known as sluggish cognitive tempo, cognitive disengagement syndrome (CDS), is characterized by slowing in behavior and cognitive processes, excessive daydreaming, confusion, drowsiness, absent-mindedness, being lost in one’s own thoughts [2,3]. Although CDS symptoms were initially considered part of ADHD [4,5], later studies suggest that CDS is a separate construct from ADHD, and that the relationship between CDS and ADHD is better understood as a comorbidity between two different disorders [6-8].

Many studies of children with and without ADHD show a greater association between CDS and increased internalizing symptoms (depression, anxiety, and withdrawal) than ADHD symptoms [2,5,7,9]. When symptoms of ADHD-inattention are controlled for, CDS is either not associated or negatively associated with externalizing behaviors. Some findings suggest that CDS is associated with poorer social skills, social isolation, loneliness, difficulties in cognitive processess and emotional regulation, reduced self-esteem, social anxiety, poorer academic functioning, higher suicide risk, self-reported rumination and mind wandering, even when comorbid conditions such as ADHD, anxiety, and depression are accounted for [4,7,10-12].

Although many studies have examined the differences and similarities between CDS and ADHD in terms of behavioral, emotional, and cognitive factors, no study to date has compared CDS and ADHD in terms of attachment styles and Cloninger’s temperament and character traits. Therefore, improving our understanding of the relationship of these traits to CDS and ADHD symptoms will contribute to a better conceptualization of possible developmental pathways, associated comorbidities and impairments, and treatment considerations for both CDS and ADHD.

Cloninger [13] and Cloninger et al. [14] developed a psychobiological model that suggests that personality consists of both temperament and character traits. Temperament emerges early in development and endures throughout life, shaping how individuals react to sensory stimuli due to innate individual differences. Character includes an individual’s objectively observable behaviors and subjectively reported experiences. Temperament encompasses four basic dimensions: novelty seeking (NS), reward dependence (RD), harm avoidance (HA), and persistence (P). These temperament dimensions can also manifest as anger, fear, and dominance in early development. In addition, Cloninger’s model includes three-character traits that are hypothesized to regulate basic temperament: self-directedness (SD), cooperativeness (C), and self-transcendence (ST). Several studies, involving both clinical and non-clinical samples, have examined the associations of Cloninger’s temperament and character dimensions with ADHD in children and adolescents [15-18]. These studies reveal that HA and NS are positively associated with ADHD, while P, RD, C, and SD are negatively associated with both ADHD-inattention and hyperactivity symptoms. These studies confirm that the NS trait in particular plays an important role in the diagnosis of ADHD [19].

Certain temperament characteristics in children may be associated with CDS because of their associations with withdrawal, emotional dysregulation, social isolation, behavioral inhibition (BI), and avoidance. A study among university students examining correlations between CDS and personality traits found that higher levels of CDS symptoms were associated with lower extraversion and conscientiousness [20]. Individuals with CDS may have greater susceptibility to introverted tendencies and internalizing issues, potentially due to their lower levels of extraversion and conscientiousness compared to those with ADHD.

Attachment is defined as the emotional bond that develops between a child and their primary caregiver, and is often observed in stressful situations, especially when the child tends to seek closeness to the caregiver. Ainsworth proposed that attachment can be categorized as either secure or insecure, depending on the nature of the infant’s relationship with the caregiver, usually the mother [21]. Insecurely attached children tend to have difficulty solving problems in social contexts and have difficulty forming and maintaining friendships [22]. In addition, insecurely attached children often exhibit lower self-regulatory capacities, reflected in reduced ego-control and ego-resilience [23]. Insecure attachment in children is broadly recognized as a nonspecific risk factor for psychopathology and predicts both internalizing and externalizing symptoms [24,25]. Some studies have suggested an association between clinical ADHD and insecure attachment [26,27]. One study reported that ADHD children had more insecure attachment with difficulty expressing fear or anger during separation, compared to typically developing children [28]. In middle childhood, some studies found that insecure attachment was associated with more symptoms of inattention and hyperactivity [29].

Various measures allow a comprehensive assessment of the attachment construct. Kerns Security Scale (KSS) is one of the most commonly used measures of attachment in middle childhood and early adolescence [30]. The instrument was originally designed to assess children’s perceptions of attachment security with a specific attachment figure. Items assess the extent to which children perceive attachment figure as available and responsive, trust them during times of stress, and exhibit ease and interest in communicating with them. A meta-analysis has provided evidence that the KSS is a robust measure of attachment in middle childhood and early adolescence. A recent study using the KSS found that maternal negative cognition and depression, mediated by the children’s relationships with their mothers, negatively predicted their cognition and mental health problems [31].

Insecure attachment and certain temperament characteristics in children may be associated with CDS because of their associations with withdrawal, emotional dysregulation, social isolation, BI, and avoidance. Thus, examining CDS and ADHD in relation to insecure attachment styles, temperament, and character traits may advance the distinctions between CDS and ADHD, and also inform how these two constructs should be conceptualized in broader models of psychopathology. In the current study, we examined the insecure attachment, temperament, and character traits associated with CDS and ADHD symptoms in a sample of children with ADHD. Based on the view that CDS and ADHD are distinct clinical conditions, we hypothesized that there would be differences in insecure attachment, temperament, and character traits between CDS and ADHD symptoms in children. We also hypothesized that CDS would be specifically associated with HA and insecure attachment, whereas inattention and hyperactivity symptoms would be associated with NS, RD, and P.

METHODS

Subjects and assessment

The study sample comprised 80 participants, consisting of 24 girls and 56 boys, aged 9–12 years, who presented at a university clinic with a primary diagnosis of ADHD between October 2020 and September 2021. Each participant underwent an assessment using the Turkish Adaptation 32 of the DSM-5-Based Schedule for Affective Disorders and Schizophrenia for School-Aged Children (6–18 years)-Present and Lifetime Version (K-SADS-PL) [33]. Exclusion criteria included the presence of other psychiatric disorders and neurological diseases. It is noteworthy that none of the ADHD patients had a history of lifetime psychotropic medication use. Detailed information about the participants, such as age, gender, education level, and various developmental characteristics, was collected through a sociodemographic form. This study was conducted in compliance with the Declaration of Helsinki, and the research protocol (2020/189) received approval from the Ethics Committee of the Aydin Adnan Menderes University ethics committee. Subsequently, written informed consent was obtained from all participants following a comprehensive explanation of the study procedures.

Assessment instruments employed in the study included the followings

Turgay’s DSM-IV Based ADHD and Disruptive Behavior Disorders Screening Scale Parent Form

This scale, developed by Turgay [34], serves as a screening tool for disruptive behavior disorders based on DSM-IV diagnostic criteria It was validated for use in Turkey by Ercan et al. [35] This scale consists of 9 items assessing attention deficit, 6 items on hyperactivity, 3 items for impulsivity, 8 items related to oppositional defiant disorder, and 15 items addressing conduct disorder. The Cronbach’s alpha coefficients for subscales are as follows: 0.88 for attention deficit, 0.95 for hyperactivity, 0.89 for oppositional defiant disorder, and 0.85 for conduct disorder.

Barkley Child Attention Scale

Developed by Barkley, 4 this scale comprises 12 items organized into two subdimensions: sluggishness and daydreaming. In this scale, which can be completed by teachers or parents, a score of three or more on any item is considered significant. Additionally, in Barkley’s study [4], a score of three or more of the 12 CDS symptoms was considered significant for the diagnosis of CDS. The Turkish reliability study of Barkley Child Attention Scale (BCAS), conducted by Firat et al. [36], yielded a Cronbach’s alpha coefficient of 0.86. Specifically, the Cronbach’s alpha coefficients for the daydreaming and sluggishness dimensions were 0.83 and 0.80, respectively. Screen positive scores are defined as a total score greater than 23. Normative scores represent values above the 93rd percentile or greater than 1.5 standart deviations in the US sample. In the current study, we used total scores from parent-reported BCAS to explore the relationship between the severity of CDS and attachment and temperament.

The Junior Temperament and Character Inventory

Developed by Luby et al. [37], the Junior Temperament and Character Inventory (J-TCI-R) measures Cloninger’s personality model in children aged 8–13. The scale includes 125 items, and children provide responses on a 5-point Likert scale. The Turkish reliability and validity study conducted by Kose et al. [38], reported Cronbach’s alpha values ranging from 0.60 to 0.79 for the temperament and character subscales in total sample. Alpha coefficient was 0.60 for NS (mean: 12.90±5.78), 0.61 for HA (mean: 15.44±5.78), 0.60 for RD (mean: 20.82±5.67), 0.66 for PS (mean: 18.98±5.90), 0.79 for SD (mean: 28.66±8.86), and 0.75 for C (mean: 23.95±6.71).

KSS

In this study, the mother–child relationship was assessed using Turkish version [39] of KSS, originally developed by Kerns et al. [30] It is widely validated for assessing attachment quality [31,40]. This scale is a 15-item self-report questionnaire, with participants providing responses separately for both mothers and fathers. Factor analysis results indicate that the KSS measures the level of secure attachment to parents for both maternal and paternal forms. Each item is graded on a four-point scale. The scores on the items are combined to obtain a single score on a security dimension, with higher scores indicating a more secure attachment. There are two subscales in this scale. Subscales measure maternal dependability (with 9 items) and maternal availability (with 6 items). The Turkish version of KSS demonstrated satisfactory internal consistency, with Cronbach’s alpha values of 0.84 and 0.88 for the mother and father subscales, respectively.

Statistical analyses

Data analysis was performed using SPSS 22.0 (IBM Corp.).

Descriptive statistics, percentages, and standard deviations were calculated, as appropriate. The normal distribution of the data was assessed using skewness-kurtosis measures and histogram graphs. The variable was determined as normally distributed if both measures have confirmed the assumption. In examining the relationships between numerical variables, the Pearson correlation test was employed for variables conforming to a normal distribution (BCAS, age, birth weight, duration of breast feeding, ADHD-inattention, ADHD-hyperactivity/impulsivity, HA, NS, RD, P, SD, C, KSS), while the Spearman correlation coefficient was used for those that did not meet the normality assumption (walking onset, speech onset). We also analyzed whether the study parameters differed between the high CDS and low CDS groups using Student’s t-test, and we presented the results in Supplementary Table 1. As Barkley [6] suggested, a score of three or more of the 12 CDS symptoms was considered significant for high CDS. Because of the exploratory nature of our study, we did not apply correction analyses for multiple comparisons since our primary aim was to investigate possible associations between the study variables.

In the hierarchical multiple regression analysis performed in three stages, the errors between the observed and predicted values were normally distributed. First, we aimed to determine the total effect of KSS scores on CDS without considering the effects of temperament or ADHD symptoms, as examining the relationship between KSS and BCAS was one of the main aims of this study. After confirming this hypothesis, we included KSS and HA as independent variables in the second model to test the main hypothesis. Age and ADHD-inattention, which are indicated to be associated with CDS, were then included in the model as controlling variables. Thus, by controlling for age and ADHD-inattention, we were able to understand the relationships of CDS with insecure attachment and HA. We performed a multiple regression analysis using enter method to identify variables associated with ADHD-inattention. The errors between the observed and predicted values were normally distributed.

RESULTS

Descriptive statistics and correlations

The results of the descriptive analysis are presented in Table 1. The majority of the sample consists of boys (boys=56, girls=24). Additionally, 81.3% of the parents in the sample are married. The type of delivery was Caesarean for 70% of the participants. There was no significant difference between boys and girls in terms of age, ADHD-inattention, BCAS, J-TCI-R, and KSS scores. However, the mean hyperactivity/impulsivity score in boys (17.67±6.87) was significantly higher than in girls (10.45±5.82) (p<0.001). As demonstrated in Supplementary Table 1, the high and low CDS groups showed significant differences in terms of inattention, KSS, HA, and NS.

Sociodemographic and clinical characteristics of the sample (N=80)

The bivariate analysis revealed that there were significant relationships between CDS and age (r=0.280, p=0.012), ADHD-inattention (r=0.435, p<0.001), HA (r=0.302, p=0.006), and KSS (r=-0.280, p=0.012) (Table 2). ADHD-inattention was significantly associated with delayed speech (r=-0.252, p=0.024), and NS (r=0.250, p=0.025). ADHD-hyperactivity/impulsivity displayed a negative relationship with SD (r=-0.233, p=0.038) (Table 3).

Correlations between CDS and the other study variables (N=80)

Correlations between ADHD symptoms and other study variables (N=80)

Hierarchical multiple regression analysis

Model 1

KSS was introduced as the independent variable. The results indicated that insecure attachment was significantly associated with CDS severity (beta=-0.314, p=0.012).

Model 2

The addition of HA to the model changed the results, and the significant relationship between insecure attachment and CDS severity disappeared. Instead, HA was significantly associated with CDS severity (beta=0.358, p=0.03).

Model 3

The final model incorporated age and ADHD-inattention as variables. In this model, age (beta=1.459, p=0.031), ADHD-inattention (beta=0.528, p=0.001), and HA (beta=0.306, p=0.044) were identified as significant predictors of CDS severity. This model produced a significant regression equation (F=8.561, p<0.001). The assumptions of error independence were met for the analysis, as evidenced by a Durbin–Watson value of 1.372. The adjusted R-squared value for the model was 0.277, indicating that the predictors explained a considerable portion of the variation in CDS severity. The variance inflation factor (VIF) values for the model were low, with the highest value being 1.130, indicating an absence of multicollinearity (Table 4).

Hierarchical regression analysis for variables predicting CDS (N=80)

Multiple linear regression analysis

The multiple regression analysis indicated that CDS was the only predictor of ADHD-intattention (beta=0.252, p<0.001). This model produced a significant regression equation (F=8.091, p<0.001). The assumptions of error independence were met for the analysis, as evidenced by a Durbin–Watson value of 1.644. The adjusted R-squared value for the model was 0.212, indicating that the predictors explained a considerable portion of the variation in CDS severity. The VIF values for the model were low, with the highest value being 1.033, indicating an absence of multicollinearity (Table 5).

Multiple regression analysis for variables predicting ADHD-inattention (N=80)

DISCUSSION

To the best of our knowledge, this is the first study to examine CDS and ADHD symptoms in children diagnosed with ADHD in terms of insecure attachment, temparament and character traits. In congruence with prior research [3,5], we identified a significant association between the severity of CDS and ADHD-inattention symptoms. Moreover, we observed a positive correlation between age and CDS severity, consistent with previous findings that children with CDS tend to be older than their ADHD peers [41].

Our main finding in this study was that, as expected, CDS and ADHD symptoms differed across insecure attachment, temperament, and character traits. Importantly, the previously noted significant association between insecure attachment and CDS in Model 1 became non-significant when additional variables were included in subsequent models. This finding may indicate the weakness of the significant association between CDS and insecure attachment. The strong relationship between CDS and inattention may have contributed to the attenuation of the CDS-insecure attachment relationship after controlling for inattention and age. Our findings substantiate that HA serves as a strong predictor of CDS in a sample of children diagnosed with ADHD, even after controlling for age and ADHD-inattention symptoms. Our findings demonstrated that ADHD-inattention was significantly associated with NS. However, this relationship did not remain significant after controlling for CDS. Moreover, ADHD-hyperactivity had an inverse relationship with SD.

Insecure attachment, CDS, and ADHD

Our findings demonstrated that CDS symptoms, but not ADHD symptoms, were significantly associated with insecure attachment. This finding contradicts previous findings that inattention and hyperactivity symptoms are significantly associated with insecure attachment in children with ADHD [26-29,42,43]. The lack of a relationship between attachment and ADHD symptoms may be due in part to the method used to assess attachment. These associations persist even when comorbid conditions such as ADHD, anxiety, and depression are accounted for [44]. The presentation of CDS symptoms has been associated with heightened activation of the BIS [6,20,45], conflicted shyness [45], and social withdrawal [5,20]. Therefore, the withdrawn behavior and social problems observed in children with CDS may be due to their inability to select appropriate social information during interactions that may be related to insecure attachment [46]. Barkley [47] hypothesized that the absent-mindedness feature of CDS contributes to social difficulties and increased self-consciousness. Willcutt et al. [7] suggested that emotion regulation (ER) problems may mediate the relationship among CDS and avoidance of social situations.

Temperament and character traits associated with CDS and ADHD symptoms

In this study, we found that HA was significantly associated with the severity of CDS symptoms in children diagnosed with ADHD, even after controlling for age and ADHD inattention symptoms. Additionally, ADHD-inattention was significantly associated with NS, whereas ADHD-hyperactivity had an inverse relationship with SD.

CDS is characterized by a range of symptoms, including difficulties in sustained alertness and slowing of cognitive and behavioral processes [10,11,41]. CDS has been found to be associated with heightened activation of the Behavioral Inhibition System [6,20,45] and social withdrawal [5,20]. In addition to BI, HA is associated with a range of personality traits, including fearfulness, shyness, harm prediction, cautiousness, discouragement, passivity, and pessimism [13,48]. Research has indicated that HA is a significant predictor of withdrawn behavior in children [49] and adolescents with higher HA levels often use strategies such as rumination, self-blame, and catastrophizing to cope with anxiety, uncertainty, or shyness [50,51]. Therefore, HA may contribute to deficiencies in emotional regulation, BI, hypoactivity, and reduced engagement in social contexts in individuals with CDS. Avoidance of social contact may hinder the development of adaptive coping strategies to manage affective arousal in social situations and limit exposure to perceived threats. When coupled with temperamental susceptibility to sympathetic arousal, this avoidance may further intensify the severity of CDS. Furthermore, behaviorally inhibited children may display strong negative reactions to unfamiliar, novel, or ambiguous stimuli or situations. This physiological predisposition may lead to avoidance of uncertain situations, aligning with CDS characteristics. Adolescents with high HA may develop internalizing symptoms as a result of their reactions to worries, fear-inducing situations, uncertainty, or shyness which are characteristics of CDS. In the context of HA, characteristics such as attentional bias towards threat and anticipatory worries may contribute to an increased disengagement bias towards threatening information, which may require extra regulatory effort and facilitate maladaptive ER. Previous studies have reported associations between ADHD and TCI dimensions in children and adolescents [15-18]. In general, these studies reveal that HA and NS temperament dimensions are positively related to ADHD, while P, RD, C, and SD are negatively related to inattention and hyperactivity. These studies confirm that NS traits in particular play an important role in the diagnosis of ADHD [19].

High NS is characterized by impulsivity, a quick-temper and a tendency to break rules. Individuals with high NS are often impulsive, unorganized and impatient. They may be more easily agitated and improvisatory in their speech. In addition, high NS has been associated with externalizing problems such as early-onset antisocial behaviour and conduct disorder [52] and impulsivity [53]. Some studies [54] show that NS has a mediating role in the relationship between ADHD and personality disorders, such as borderline personality disorder. The possible association between NS and ADHD-inattention in our sample may be related to the persistence of ADHD in later developmental stages. High NS scores may be a risk factor for ADHD persisting into adulthood. It is also well-known that high NS levels are associated with bipolar disorder [55,56]. Therefore, assuming a continuum, ADHD with NS traits may be a risk factor for the development of personality disorder or bipolar disorder later in life. However, future studies are required to confirm these hypotheses. SD involves the level of understanding and identification of a person’s ability to self-regulate his/her behaviour according to specific goals and values [14]. Low SD is related to personality disorders and is found in a wide range of psychopathological conditions [57-59]. Low SD has been associated with ADHD in children and adolescents. It is also expected to be found among externalizing disorders, impulsiveness, inattention, and non-recognition of rules in youth [15]. Consistent with these findings, we found that ADHD-hyperactivity was associated with lower levels of SD.

Study limitations and further directions

It is important to acknowledge several limitations in this study. First, the size of our sample was relatively small, which restricts the generalizability of our findings to a broader population. Additionally, the entire sample consisted of children diagnosed with ADHD which could affect the generalizability of the results to non-ADHD populations. Future research should examine these associations in non-ADHD populations. Secondly, the use of a cross-sectional design in this study precludes the establishment of a causal relationship among the variables investigated. Thirdly, we did not evaluate the severity of anxiety and depression in this study, as we had excluded all diagnoses other than ADHD. Additionally, we did not collect data on parental psychopathology, which could encompass factors related to temperament and character, CDS, and ADHD in the children. Future studies should investigate whether attachment styles, different temperament, and character profiles reflect distinct developmental pathways in relation to CDS and ADHD.

Clinical implications

In summary, our findings suggest that CDS and ADHD symptoms may display different relationships with insecure attachment, temperament, and character dimensions in children with ADHD. Evaluating attachment styles, temperament, and character dimensions in relation to CDS and ADHD may improve our understanding of the developmental trajectories of psychopathology.

Supplementary Materials

The Supplement is available with this article at https://doi.org/10.30773/pi.2025.0027.

Supplementary Table 1.

Comparison of clinical characteristics between high CDS and low CDS

pi-2025-0027-Supplementary-Table-1.pdf

Notes

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Hasan Can Özbay, Hatice Aksu. Data curation: Hasan Can Özbay. Formal analysis: Doğa Sevinçok. Investigation: Hasan Can Özbay, Muhammed Mutlu Özbek, Doğa Sevinçok. Methodology: Muhammed Mutlu Özbek, Hasan Can Özbay. Project administration: Hatice Aksu. Resources: Hasan Can Özbay, Muhammed Mutlu Özbek, Doğa Sevinçok. Supervision: Hatice Aksu. Validation: Doğa Sevinçok. Visualization: Hasan Can Özbay, Doğa Sevinçok. Writing—original draft: Hasan Can Özbay, Doğa Sevinçok. Writing—review & editing: Hatice Aksu.

Funding Statement

None

Acknowledgments

We would like to thank all patients and their parents who agreed to participate in the study.

References

1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5) (5th ed) Arlington: American Psychiatric Association; 2013.
2. Becker SP, Webb KL, Dvorsky MR. Initial examination of the bidirectional associations between sluggish cognitive tempo and internalizing symptoms in children. J Clin Child Adolesc Psychol 2021;50:258–266.
3. Becker SP, Willcutt EG, Leopold DR, Fredrick JW, Smith ZR, Jacobson LA, et al. Report of a work group on sluggish cognitive tempo: key research directions and a consensus change in terminology to cognitive disengagement syndrome. J Am Acad Child Adolesc Psychiatry 2023;62:629–645.
4. Barkley RA. Distinguishing sluggish cognitive tempo from attention-deficit/hyperactivity disorder in adults. J Abnorm Psychol 2012;121:978–990.
5. Garner AA, Marceaux JC, Mrug S, Patterson C, Hodgens B. Dimensions and correlates of attention deficit/hyperactivity disorder and sluggish cognitive tempo. J Abnorm Child Psychol 2010;38:1097–1107.
6. Barkley RA. Distinguishing sluggish cognitive tempo from ADHD in children and adolescents: executive functioning, impairment, and comorbidity. J Clin Child Adolesc Psychol 2013;42:161–173.
7. Willcutt EG, Chhabildas N, Kinnear M, DeFries JC, Olson RK, Leopold DR, et al. The internal and external validity of sluggish cognitive tempo and its relation with DSM-IV ADHD. J Abnorm Child Psychol 2014;42:21–35.
8. Becker SP, Langberg JM. Sluggish cognitive tempo among young adolescents with ADHD: relations to mental health, academic, and social functioning. J Atten Disord 2013;17:681–689.
9. Burns GL, Servera M, Bernad Mdel M, Carrillo JM, Cardo E. Distinctions between sluggish cognitive tempo, ADHD-IN, and depression symptom dimensions in Spanish first-grade children. J Clin Child Adolesc Psychol 2013;42:796–808.
10. Becker SP, Marshall SA, McBurnett K. Sluggish cognitive tempo in abnormal child psychology: an historical overview and introduction to the special section. J Abnorm Child Psychol 2014;42:1–6.
11. Penny AM, Waschbusch DA, Klein RM, Corkum P, Eskes G. Developing a measure of sluggish cognitive tempo for children: content validity, factor structure, and reliability. Psychol Assess 2009;21:380–389.
12. Becker SP, Vaughn AJ, Zoromski AK, Burns GL, Mikami AY, Fredrick JW, et al. A multi-method examination of peer functioning in children with and without cognitive disengagement syndrome. J Clin Child Adolesc Psychol 2025;54:389–404.
13. Cloninger CR. A systematic method for clinical description and classification of personality variants: a proposal. Arch Gen Psychiatry 1987;44:573–588.
14. Cloninger CR, Svrakic DM, Przybeck TR. A psychobiological model of temperament and character. Arch Gen Psychiatry 1993;50:975–990.
15. Cho SC, Hwang JW, Lyoo IK, Yoo HJ, Kin BN, Kim JW. Patterns of temperament and character in a clinical sample of Korean children with attention-deficit hyperactivity disorder. Psychiatry Clin Neurosci 2008;62:160–166.
16. Rettew DC, Copeland W, Stanger C, Hudziak JJ. Associations between temperament and DSM-IV externalizing disorders in children and adolescents. J Dev Behav Pediatr 2004;25:383–391.
17. Tillman R, Geller B, Craney JL, Bolhofner K, Williams M, Zimerman B, et al. Temperament and character factors in a prepubertal and early adolescent bipolar disorder phenotype compared to attention deficit hyperactive and normal controls. J Child Adolesc Psychopharmacol 2003;13:531–543.
18. Yoo HJ, Kim M, Ha JH, Chung A, Sim ME, Kim SJ, et al. Biogenetic temperament and character and attention deficit hyperactivity disorder in Korean children. Psychopathology 2006;39:25–31.
19. Donfrancesco R, Di Trani M, Porfirio MC, Giana G, Miano S, Andriola E. Might the temperament be a bias in clinical study on attention-deficit hyperactivity disorder (ADHD)?: novelty seeking dimension as a core feature of ADHD. Psychiatry Res 2015;227:333–338.
20. Becker SP, Schmitt AP, Jarrett MA, Luebbe AM, Garner AA, Epstein JN, et al. Sluggish cognitive tempo and personality: links to BIS/BAS sensitivity and the five factor model. J Res Pers 2018;75:103–112.
21. Holmes J. John Bowlby and attachment theory London: Routledge; 1993. p. 61–78.
22. Sroufe LA, Carlson E, Shulman S. Individuals in relationships: development from infancy through adolescence (1st ed) In: Funder DC, Parke RD, Tomlinson-Keasey CE, Widaman KE, editors. Studying lives through time: personality and development. Washington, DC: American Psychological Association, 1993, p.315-342.
23. Stams GJ, Juffer F, van IJzendoorn MH. Maternal sensitivity, infant attachment, and temperament in early childhood predict adjustment in middle childhood: the case of adopted children and their biologically unrelated parents. Dev Psychol 2002;38:806–821.
24. Groh AM, Roisman GI, van Ijzendoorn MH, Bakermans-Kranenburg MJ, Fearon RP. The significance of insecure and disorganized attachment for children’s internalizing symptoms: a meta-analytic study. Child Dev 2012;83:591–610.
25. Madigan S, Atkinson L, Laurin K, Benoit D. Attachment and internalizing behavior in early childhood: a meta-analysis. Dev Psychol 2013;49:672–689.
26. Clarke L, Ungerer J, Chahoud K, Johnson S, Stiefel I. Attention deficit hyperactivity disorder is associated with attachment insecurity. Clin Child Psychol Psychiatry 2002;7:179–198.
27. Green J, Stanley C, Peters S. Disorganized attachment representation and atypical parenting in young school age children with externalizing disorder. Attach Hum Dev 2007;9:207–222.
28. Sempio OL, Fabio RA, Tiezzi P, Cedro C. Parental and teachers attachment in children at risk of ADHD and with ADHD. Life Span Disabil 2016;19:57–77.
29. Niederhofer H. Attachment as a component of attention-deficit hyperactivity disorder. Psychol Rep 2009;104:645–648.
30. Kerns KA, Klepac L, Cole A. Peer relationships and preadolescents’ perceptions of security in the child-mother relationship. Dev Psychol 1996;32:457–466.
31. Kwon B, Lee IH, Lee G. Maternal predictors of children’s mental health in low-income families: a structural equation model. Int J Ment Health Nurs 2023;32:162–171.
32. Ünal F, Öktem F, Çetin Çuhadaroğlu F, Çengel Kültür SE, Akdemir D, Foto Özdemir D. [Reliability and validity of the schedule for affective disorders and schizophrenia for school-age children-present and lifetime version, DSM-5 November 2016-Turkish adaptation (K-SADS-PL-DSM-5-T)]. Turk Psikiyatri Derg 2019;30:42–50. Turkish.
33. Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, et al. Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry 1997;36:980–988.
34. Turgay A. Adult ADHD screening and rating scale and structured interview guidelines Toronto: Integrative Therapy Institute Publication; 1995.
35. Ercan ES, Amado S, Somer O, Cıkoğlu S. Development of A test battery for the assessment of attention deficit hyperactivity disorder. Turk J Child Adolesc Ment Health 2001;8:132–144.
36. Firat S, Bolat GU, Gul H, Baytunca MB, Kardas B, Aysev A, et al. Barkley child attention scale validity and reliability study. Dusunen Adam J Psychiatry Neurol Sci 2018;31:284–293.
37. Luby JL, Svrakic DM, McCallum K, Przybeck TR, Cloninger CR. The junior temperament and character inventory: preliminary validation of a child self-report measure. Psychol Rep 1999;84(3 Pt 2):1127–1138.
38. Kose S, Sayar K, Kalelioglu U, Aydin N, Celikel FC, Gulec H, et al. Normative data and factorial structure of the Turkish version of the temperament and character inventory. Compr Psychiatry 2009;50:361–368.
39. Sümer N, Sendag MA. Attachment to parents during middle childhood, self-perceptions, and anxiety. Turk Psikol Derg 2009;24:86–103.
40. Brumariu LE, Madigan S, Giuseppone KR, Movahed Abtahi M, Kerns KA. The security scale as a measure of attachment: meta-analytic evidence of validity. Attach Hum Dev 2018;20:600–625.
41. Becker SP, Leopold DR, Burns GL, Jarrett MA, Langberg JM, Marshall SA, et al. The internal, external, and diagnostic validity of sluggish cognitive tempo: a meta-analysis and critical review. J Am Acad Child Adolesc Psychiatry 2016;55:163–178.
42. Fearon RM, Belsky J. Attachment and attention: protection in relation to gender and cumulative social-contextual adversity. Child Dev 2004;75:1677–1693.
43. Low JA, Webster L. Attention and executive functions as mediators of attachment and behavior problems. Soc Dev 2016;25:646–664.
44. Shelton CR, Addison WE, Hartung CM. ADHD and SCT symptomatology in relation to college students› use of self-regulated learning strategies. J Atten Disord 2019;23:1719–1728.
45. Becker SP, McQuade JD. Physiological correlates of sluggish cognitive tempo in children: examining autonomic nervous system reactivity during social and cognitive stressor tasks. J Abnorm Child Psychol 2020;48:923–933.
46. Yung TWK, Lai CYY, Chan JYC, Ng SSM, Chan CCH. Examining the role of attention deficits in the social problems and withdrawn behavior of children with sluggish cognitive tempo symptoms. Front Psychiatry 2021;12:585589.
47. Barkley RA. Sluggish cognitive tempo (concentration deficit disorder?): current status, future directions, and a plea to change the name. J Abnorm Child Psychol 2014;42:117–125.
48. Matthews G, Derryberry D, Siegle GJ. Personality and emotion: cognitive science perspectives (1st ed) In : Hampson SE, ed. In: Hampson SE, editor. Advances in personality psychology. London: Psychology Press, 2000, p.199-237.
49. Rubin KH, Chronis-Tuscano A. Perspectives on social withdrawal in childhood: past, present, and prospects. Child Dev Perspect 2021;15:160–167.
50. Carleton RN, Sharpe D, Asmundson GJ. Anxiety sensitivity and intolerance of uncertainty: requisites of the fundamental fears? Behav Res Ther 2007;45:2307–2316.
51. Liao KY, Wei M. Intolerance of uncertainty, depression, and anxiety: the moderating and mediating roles of rumination. J Clin Psychol 2011;67:1220–1239.
52. Schmeck K, Goth K, Poustka F, Cloninger RC. Reliability and validity of the junior temperament and character inventory. Int J Methods Psychiatr Res 2001;10:172–182.
53. Evren C, Alniak I, Karabulut V, Cetin T, Umut G, Agachanli R, et al. Relationship of probable ADHD with novelty seeking, severity of psychopathology and borderline personality disorder in a sample of patients with opioid use disorder. Psychiatry Clin Psychopharmacol 2018;28:48–55.
54. Carlotta D, Borroni S, Maffei C, Fossati A. On the relationship between retrospective childhood ADHD symptoms and adult BPD features: the mediating role of action-oriented personality traits. Compr Psychiatry 2013;54:943–952.
55. Nowakowska C, Strong CM, Santosa CM, Wang PW, Ketter TA. Temperamental commonalities and differences in euthymic mood disorder patients, creative controls, and healthy controls. J Affect Disord 2005;85:207–215.
56. Frye MA, Salloum IM. Bipolar disorder and comorbid alcoholism: prevalence rate and treatment considerations. Bipolar Disord 2006;8:677–685.
57. Nigg JT, Goldsmith HH, Sachek J. Temperament and attention deficit hyperactivity disorder: the development of a multiple pathway model. J Clin Child Adolesc Psychol 2004;33:42–53.
58. Martel MM, Nigg JT, von Eye A. How do trait dimensions map onto ADHD symptom domains? J Abnorm Child Psychol 2009;37:337–348.
59. Purper-Ouakil D, Cortese S, Wohl M, Aubron V, Orejarena S, Michel G, et al. Temperament and character dimensions associated with clinical characteristics and treatment outcome in attention-deficit/hyperactivity disorder boys. Compr Psychiatry 2010;51:286–292.

Article information Continued

Table 1.

Sociodemographic and clinical characteristics of the sample (N=80)

Variables Value
Gender
 Girls 24 (30.0)
 Boys 56 (70.0)
Marital status of family
 Married 65 (81.3)
 Divorced/seperated 15 (18.8)
Type of delivery
 Caesarean 56 (70.0)
 Normal 24 (30.0)
Age (yr) 10.32±1.05
Birth weight (kg) 3.34±0.75
Walking onset (mon) 12.03±1.72
Speech onset (mon) 13.23±3.11
Duration of breast feeding (mon) 15.10±10.07
BCAS 21.18±7.08
ADHD
 Inattention 18.25±4.53
 Hyperactivity/impulsivity 15.51±7.33
J-TCI-R
 Novelty seeking 13.11±7.28
 Harm avoidance 13.76±4.83
 Reward dependence 16.25±5.96
 Persistence 14.36±6.17
 Self-directedness 23.45±8.28
 Cooperativeness 18.85±7.98
KSS 48.10±6.31

Values are presented as number (%) or mean±standard deviation. BCAS, Barkley Child Attention Scale; ADHD, attention-deficit/hyperactivity disorder; J-TCI-R, Junior Temperament and Character Inventory; KSS, Kerns Security Scale

Table 2.

Correlations between CDS and the other study variables (N=80)

CDS
r p
Age (yr) 0.280 0.012
Birth weight (mon) 0.084 0.459
Walking onset (mon) 0.010 0.927*
Speech onset (mon) -0.207 0.066*
Duration of breast feeding (mon) 0.106 0.348
ADHD
 Inattention 0.435 <0.001
 Hyperactivity/impulsivity -0.205 0.068
J-TCI-R
 Novelty seeking -0.134 0.236
 Harm avoidance 0.302 0.006
 Reward dependence -0.169 0.133
 Persistence -0.124 0.272
 Self-directedness -0.154 0.174
 Cooperativeness -0.146 0.197
KSS -0.280 0.012

Pearson correlation test.

*

Spearman correlation coefficient.

CDS, cognitive disengagement syndrome; ADHD, attention-deficit/hyperactivity disorder; J-TCI-R, Junior Temperament and Character Inventory; KSS, Kerns Security Scale

Table 3.

Correlations between ADHD symptoms and other study variables (N=80)

Inattention
Hyperactivity/impulsivity
r p r p
Age (yr) 0.171 0.129 -0.033 0.769
Birth weight (mon) 0.007 0.950 -0.033 0.770
Walking onset (mon) 0.024 0.835* 0.115 0.309*
Speech onset (mon) -0.252 0.024* 0.068 0.546*
Duration of breast feeding (mon) 0.215 0.055 -0.012 0.918
CDS 0.527 <0.001 -0.205 0.068
J-TCI-R
 Novelty seeking 0.250 0.025 0.103 0.363
 Harm avoidance 0.195 0.084 -0.147 0.193
 Reward dependence -0.022 0.843 -0.046 0.683
 Persistence -0.037 0.746 0.032 0.775
 Self-directedness -0.003 0.979 -0.233 0.038
 Cooperativeness -0.039 0.733 -0.136 0.229
KSS -0.130 0.249 -0.103 0.365

Pearson correlation test. *Spearman correlation coefficient. ADHD, attention-deficit/hyperactivity disorder; CDS, cognitive disengagement syndrome; J-TCI-R, Junior Temperament and Character Inventory; KSS, Kerns Security Scale

Table 4.

Hierarchical regression analysis for variables predicting CDS (N=80)

Dependent variable: BCAS B SE β p VIF
Model 1* Constant 36.307 5.918 - <0.001 -
KSS -0.314 0.122 -0.280 0.012 1.000
Model 2 Constant 27.809 6.936 - <0.001 -
KSS -0.240 0.124 -0.214 0.056 1.080
Harm avoidance 0.358 0.162 0.244 0.030 1.080
Model 3 Constant 0.481 10.080 - 0.962 -
Age 1.459 0.663 0.217 0.031 1.060
ADHD-inattention 0.528 0.156 0.338 0.001 1.081
KSS -0.171 0.113 -0.152 0.135 1.107
Harm avoidance 0.306 0.149 0.209 0.044 1.130

Model 1 includes only KSS as a predictor. Model 2 adds harm avoidance to the regression model. Model 3 further includes age and ADHDinattention as additional predictors. Standardized (β) and unstandardized (B) coefficients are reported along with SEs, p-values, and VIF.

Adjusted R2=

*

0.067;

0.111;

0.277.

KSS, Kerns Security Scale; CDS, cognitive disengagement syndrome; BCAS, Barkley Child Attention Scale; ADHD, attention-deficit/hyperactivity disorder; SE, standard error; VIF, variance inflation factor; -, not applicable

Table 5.

Multiple regression analysis for variables predicting ADHD-inattention (N=80)

Dependent variable: ADHD-inattention* B SE β 95% CI p VIF
Consant 13.812 2.700 - 8.435–19.189 <0.001
Speech onset -0.181 0.147 -0.124 -0.474–0.113 0.224 1.029
Novelty seeking 0.114 0.063 0.183 -0.012–0.239 0.076 1.029
CDS 0.252 0.065 0.394 0.123–0.381 <0.001 1.033
*

adjusted R2=0.212.

ADHD, attention-deficit/hyperactivity disorder; CDS, cognitive disengagement syndrome; SE, standard error; CI, confidence interval; VIF, variance ınflation factor; -, not applicable