- Email: [email protected]
Disruptive Mood Dysregulation Disorder in A Primary School Sample
Journal Pre-proof Disruptive Mood Dysregulation Disorder in A Primary School Sample ˘ Leyla Ezgi Tu¨ gen
PII:
S1876-2018(19)30825-1
DOI:
https://doi.org/10.1016/j.ajp.2019.101858
Reference:
AJP 101858
To appear in:
Asian Journal of Psychiatry
Received Date:
27 August 2019
Revised Date:
12 October 2019
Accepted Date:
13 October 2019
˘ Please cite this article as: Tu¨ gen LE, Disruptive Mood Dysregulation Disorder in A Primary School Sample, Asian Journal of Psychiatry (2019), doi: https://doi.org/10.1016/j.ajp.2019.101858
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.
Disruptive Mood Dysregulation Disorder in A Primary School Sample Leyla Ezgi Tüğen [email protected]
Introduction
In children, irritability can be seen as part of the normal developmental process or accompanying many psychiatric conditions, such as oppositional defiant disorder (ODD),
ro of
bipolar disorder (BD), depression, attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (Evans et al. 2017). In literature, it is reported that the prevalence of bipolar disorder in children with severe irritability increased significantly between 1990 and 2006 (Blader et al. 2007). However, the position of severe irritability which cannot be explained by any psychiatric disorder in classification and nomenclature is controversial. As a result of
-p
studies conducted in this area, a definition for severe irritability with chronic abnormal mood, hyperarousal symptoms, and anger attacks was required, and Severe Mood Dysregulation
re
(SMD) was identified as a broad phenotype of pediatric bipolar disorder (Leibenluft et al. 2003). Subsequent longitudinal studies reported that SMD and BD had different symptom
lP
clusters and that they differ from each other in terms of comorbid diagnoses and outcomes (Leibenluft et al. 2013). Chronic irritability, which is the main feature of SMD, has been found to be related to ODD, ADHD and depressive disorders, while the key feature of BD, episodic
ur na
irritability, is related to anxiety and mania (Leibenluft et al 2006). For this new form of chronic irritability, hyper-excitability symptoms and intelligence criteria were excluded in DSM-V, and the definition of Disruptive Mood Dysregulation Disorder (DMDD) was introduced as a new diagnostic group that included frequent and severe episodes of anger accompanied by chronic irritability in children and adolescents (Evans and et al. 2017).
Jo
Since DMDD was included as a new diagnosis in the DSM-V, it was observed that mostly SMD data were used in the studies (Evans et al. 2017). SMD and DMDD resemble each other but have different diagnostic criteria. Thus, the applicability of the previous results of SMD studies for DMDD is controversial. Although there are a wide range of prevalence rates for DMDD ranging from 26-31% in the clinical samples to 0.8-8.1% in the community samples (Axelson et al. 2012, Freeman et al. 2016; Copeland et al. 2013), when prevalence rates are evaluated according to frequency and intensity criteria of chronic irritability, decrease in the prevalence is typical (Althoff et al. 2016). Also, the incidence of DMDD decreases with increasing age. In
a longitudinal study, the prevalence of DMDD at the age of 6 was 8%, but at nine years of age, this rate decreased to 1% (Dougherty et al. 2014). Similarly, the prevalence of DMDD was found 9% in an 8-year longitudinal study in a population of 6 to 12 years, but it was reported that only 29% of these children continued to be diagnosed with DMDD after eight years (Mayes et al. 2016). In community-based studies, it is seen that DMDD is accompanied by other psychiatric disorders, especially depression and ODD, between 60.5% and 92%, although DMDD and ODD cannot co-exist according to DSM-5 (Copeland et al. 2013). In addition, Dougherty et al. suggested that having a diagnosis of DMDD at six years of age, predicted depressive disorder,
ro of
ADHD, and worse psychosocial functioning (Dougherty et al. 2016). Similarly, chronic irritability is reported to indicate internalizing disorders, such as depression and anxiety, rather than subsequent externalizing disorders (Whelan et al. 2013).
It is seen that chronic irritability and DMDD have recently begun to find a place in child
-p
psychiatry literature. However, its clinical significance is better understood when its high incidence and high comorbid diagnosis rates are considered. In our study, we aimed to 1)
re
determine the frequency of DMDD in a community-based sample in Turkey, Istanbul, Pendik
Methods
ur na
Sample and Procedures
lP
2) identify comorbid diagnoses in children with DMDD.
Our study is a cross-sectional population-based study applied to all students in the first, second, third and fourth grades, that’s supposed to have the highest DMDD rates, in a primary school in Istanbul, Pendik. Approval to perform the study was obtained from the Marmara
Jo
University Ethics Committee (09.2018.167). Before the data collection, researchers gave information about the purpose, method, and course of the study to the principal and teachers of the school. At the end of the study, necessary referrals to child psychiatry were made. At the beginning of the study, the Child Behavior Checklist, which also includes an informed consent on the first page, was given to the counselor in primary school to be distributed to all students (650 children). One week later, 463 out of 650 forms were filled by the parents of students and collected by the counselor. Ten of the forms collected from the children were excluded because they were incomplete. Four hundred fifty-three children (70% of the total sample) constituted
the sample of the study. Of the children who participated in the study, 83 children with a total score between 180 and 210 in CBCL attention, anxious / depression and aggression subscale scores (18.3% of the study sample) were evaluated in moderate-risk group in terms of DMDD and 14 children with a total score of 210 and higher (3.1% of the study sample) were considered as high-risk group (HRG). Both groups were invited to the hospital by a phone call of a child and adolescent psychiatrist. Of the children invited, 30 (6.62% of the study sample) agreed to participate in the study. : Child and adolescent psychiatrists applied Kiddie-Schedule for Affective Disorders and Schizophrenia for School-Age Children, Present and Lifetime Version, K-SADS-PL (KSADS) to children who agreed to participate in the study, considering the
ro of
changes based on DSM-5. Comorbid diagnoses were determined with KD-SADS-PL, plus a semi-structured interview involving the DSM-V criterias in the interviewed children. Four children (0.88% of the study sample) were diagnosed with DMDD.
-p
Follow-up Form
In our study, age and gender of the child were questioned with the follow-up form. There was
lP
The Child Behavior Checklist (CBCL)
re
an informed consent form in the front of each form.
The Child Behavior Checklist developed by Achenbach and Edenbrock in 1983 was translated
ur na
into Turkish by Erol and Kılıç in 1991, and translations were revised in 1998 (Erol and Şimşek 1998). Test-retest reliability of the scale was found to be 0.70 and 0.84. Internal consistency values were found to be 0,39 and 0,86 (Erol et al. 1995). The questions in the scale are answered by mother and father on the four-point Likert scale. “not correct”, “sometimes or slightly correct” and “absolutely correct or often correct” are scored as “0”, “1”, “2”, respectively. The
Jo
cut-off point for the subscale scores in the CBCL is 60 and above; the cut-off score for the internalizing, externalizing and total scores were taken as 65 and above (Achenbach 1991). DMDD is closely related to emotion dysregulation, aggression, irritability, anxiety and depression. also, CBCL is a scale that can be used for screening of psychopatology of children in Turkey. In the previous studies, because of a lack of diagnostic instruments, the dysregulation profile (DP) of the Child Behavior Checklist (CBCL) was used to assess prevalence rates of DMDD (Freeman et al., 2016). The total score of CBCL attention, anxiety/depression, and aggression subscale scores were evaluated as DMDD panel score, and points below 179 were
considered as non-risk group, points between 180 and 209 were considered as moderate risk group (MRG), and 210 and above points were considered as high-risk group (HRG) for DMDD (Biederman et al. 2012). Kiddie-Schedule for Affective Disorders and Schizophrenia for School-Age Children, Present and Lifetime Version (K-SADS-PL)
K-SADS-PL, which is a semi structured interview was developed by Kauffman et al (Kauffman et al., 1997) Schedule for affective disorders and schizophrenia for schoolage children-present and lifetime version (K-SADS-PL): initial reliability and validity data and its reliabillity and
ro of
validity study in Turkey was carried out by Gökler et al (Gökler et al., 2004).
Clinical Interview for DSM-V Axis I Disorders
It has been used to determine the diagnosis of DMDD and comorbid psychiatric diagnoses in
-p
children (APA 2013).
re
Clinical Significance
lP
Our study is one of the few studies evaluating the frequency of DMDD in Turkey. Although the prevalence of DMDD is low, comorbid diagnosis rates require detailed examination and
ur na
multifaceted perspectives in the follow-up and treatment process.
Statistical Analysis
Data were analyzed using the Statistical Program for Social Sciences (SPSS for Windows,
Jo
20.0). Chi-square (χ²) was used for comparison of numerical variables, and Student t-test and ANOVA were used for comparison of continuous variables. The significance level for all analyzes was accepted as p <0.05.
Results
A total of 453 children, 209 (46,1%) of whom were male, participated in our study. The mean age of the study group was 8.81 ± 1.25 (min: 6.72, max: 11.8).
356 (78.6%) children who participated in the study received a score below 179 in the DMDD panel and were evaluated as non-risk group for DMDD, 83 (18.3%) children received a score between 180 and 210 in the DMDD panel and were evaluated as moderate-risk group (MRG) for DMDD. 44.6% (n=37) of the MRG received a score of 65 and above in CBCL total, 41.0% (n=34) in CBCL internalizing and 16.9% (n=14) in CBCL externalizing. 41.0% (n=34) of the MRG and 46.6% (n=166) of the non-risk group were male (χ²=0.871, p=0.351). The mean age of the MRG was 8.64 ± 1.15, and the non-risk group was 8.84 ± 1.27 (t = 1.283, p = 0.200). When the effect of age was controlled in MRG, no significant difference was found between
ro of
male (mean ±%95 CI; 189.703 ± 187.00-192.39) and female (mean ± %95 CI; 189.044 ± 186.775-191.312) in terms of DMDD panel (F (1, 79); 0.102, p= 0.71) (Ancova).
Of the 453 children participating in the study, 14 (3.1%) scored 210 and higher in the DMDD panel and were considered as high-risk group (HRG). 92.9% (n=13) of the HRG received a
-p
score of 65 and above in CBCL total, 85.7% (n=12) in CBCL internalizing and 50% (n=7) in CBCL externalizing. 50% (n=7) of the HRG and 46.6% (n=166) of the non-risk group were
re
male (χ²=0.061, p=0.804). The mean age of the HRG was 9.22±1.08, and the mean age of the non-risk group was 8.84±1.27 (t=-1.102, p=0.271).
lP
Eight (26.7%) of 30 children who underwent psychiatric interview (PI) were within the HRG, and 4 (13.3%) of these children were diagnosed with DMDD. The children diagnosed with DMDD accounted for 28.57% of the HRG and 0.88% of the whole school group. There was at
ur na
least one comorbid diagnosis in all four children diagnosed with DMDD.
Thirteen of the 30 children (43.3%) who underwent psychiatric interview had ADHD, 7 (23.3%) had enuresis nocturna, 5 (16.7%) had separation anxiety disorder, 5 (16.7%) had social phobia, 4 (13.3%) had oppositional defiant disorder, 3 (10%) specific phobia, 2 (6.7%) had
Jo
generalized anxiety disorder, 2 (6.7%) had obsessive-compulsive disorder, 2 (6.7%) had depression, 1 (3,3%) had mild mental retardation, 1 (3.3%) had atypical autism and 2 (6.7%) had dislexia.
There was at least one mood disorder in 6.7% (n=2), at least one anxiety disorder in 36.7% (n=11), at least one disruptive behavior disorder in 50% (n = 15) and at least one comorbid diagnosis in 76.7% (n = 23) of PI group. 70% (n=21) of the PI group received a score of 65 and
above in the CBCL total, 56.7% (n=17) in CBCL internalizing and 33.3% (n=10) in externalizing. A brief sociodemographic information and CBCL subscale scores in total sample, MRG, HRG, and PI group is demonstrated in Table I.
Discussion
In this study, the prevalence of DMDD and comorbid psychiatric diagnoses were evaluated in a community sample of 6-11 years old primary school students with a clinical interview based
ro of
on DSM-V. While Mayes et al. (2016) found the frequency of DMDD symptoms as 9% in the general population between the ages of 6 and 12, when “very often” criteria was added, the frequency of DMDD was reduced to 1%. Similarly, the prevalence of DMDD was 5.26% among adolescents 13-18 years of age, and this ratio decreased to 0.12% when the frequency
-p
and mania exclusion criteria were added (Althoff et al. 2016). In studies which DSM-V DMDD criteria and clinical examination were evaluated; the frequency of diagnosis in the community
re
sample was 8% (Dougherty et al. 2016), and this rate increased to 26% - 31% in the clinical sample (Axelson et al. 2012, Freeman et al. 2016). Another factor that affects the frequency of
lP
DMDD is the age of the child. Studies show that the prevalence of DMDD is 8%, especially in preschool period, this rate decreases to 1% in 9 years of age, and continuity of diagnosis decreases as the duration of follow-up period increases (Dougherty et al. 2014, Mayes et al.,
ur na
2016). In a large sample study, it was reported that the prevalence of DMDD was between 0.8% and 3.3%, and the highest rates were seen in pre-school children (Copeland et al. 2013). The results of these studies suggest that factors such as age, community/clinical sample, and scale/clinical examination might make a difference in the frequency of diagnosis of DMDD (Mayes et al. 2016, Althoff et al. 2016, Dougherty et al. 2016, Axelson et al. 2012). In our
Jo
study, the frequency of diagnosis of DMDD was decreased because the sample was communitybased, in the primary school period; evaluation was two staged, as scale and clinical examination; the evaluation of frequency, severity, and mania exclusion criteria was considered.
In studies with adolescents, it was reported that approximately 90% of cases with DMDD were accompanied by any psychiatric diagnosis, mood disorders and disruptive behavior disorders are the most common comorbid diagnoses, and comorbidities showed high rates of persistence
at follow-up. (Althoof et al. 2016, Copeland et al. 2013, Doughtery et al. 2016). In our study, similar to the results of previous studies, approximately 76% of cases in PI group and all cases with DMDD had at least one comorbid diagnosis; and 44.6% of the MRG and 92.9% of the HRG had a total score of CBCL above the clinical level. Also, it was found that the MRG, HRG and PI group showed high rates of externalization and internalization symptoms. In the PI group, the overall rates of mood and anxiety disorders and the rates of disruptive behavior disorders were similar. These rates suggest that, although DMDD is classified as an internalizing problem, it has internalizing and externalizing components. High rates of comorbidities in DMDD, emphasizes the need for careful consideration of DMDD during
ro of
diagnosis, treatment, and follow-up procedures.
In literature, DMDD has been reported to be almost always accompanied by ODD (Freeman et al., 2016; Mayes et al., 2016). DSM-V indicates that the diagnosis of ODD cannot be made in patients with DMDD diagnostic criteria (DSM-V), but, as in many studies and our study, the
-p
majority of patients with a diagnosis of DMDD meet the diagnostic criteria for ODD (Althoff et al. 2012; Mayes et al. 2016; Doughtry et al. 2014). Also, Freeman et al. (2016) reported that
re
DMDD did not differ significantly from ODD in terms of diagnostical and dimensional comorbidity and impaired functioning. Both homotypic (comorbidity with ADHD and conduct
lP
disorder) and heterotypic (comorbidity with anxiety and depression) structure of ODD, and the developmental continuity of ODD with many other disorders, provide a diagnostical resemblance of ODD to DMDD (Boylan et al. 2007; Burke and Loeber, 2010; Burke et al 2005;
ur na
Copeland et al 2009; Kim-Cohen et al. 2003). These data give rise to the need for reinterrogation of DMDD as a primary diagnosis in subsequent studies.
Disclosure
Jo
All authors declare that there is no competing financial interests.
Limitations
Although our study has strengths, such as being a community-based study, using DSM-V based clinical assessment and being one of the few studies in Turkey, various limitations are present. First, clinical evaluation was not applied to all children in the sample group; however, children
who were considered to be at moderate risk according to the CBCL were invited. Approximately one-third of children invited to the study accepted clinical evaluation. This makes it difficult to generalize the results of the study. Our second limitation is that Pendik, Istanbul, where we have taken the sample group, is a region in the middle-lower class socioeconomic level. Expanding the study to cover all socioeconomic levels might prevent this limitation. Another limitation was that the number of children diagnosed with DMDD was very few (n=4), which hinders detailed statistical evaluation on the diagnosis of DMDD. The results of our study should be evaluated considering these limitations.
ro of
Conclusions
In our study, 4 children (0.88% of the total sample) was diagnosed with DMDD in 7-12 aged primary school sample and the comorbidity rate was relatively high (76.7%) in the PI group. Longitudinal studies with larger samples are needed to generalize the results of our study.
-p
Conflict of Interest
re
The authors declare that they have no conflicts of interest.
lP
Acknowledgments
There are no sources of support for this study. The authors thank all the children and their
Jo
ur na
families whose participation made this study possible.
References Achenbach T.M. Manual for the Child Behaviour Checklist/4-18 and 1991 profile. Burlington, University of Vermont, 1991. Althoff, R. R., Crehan, E. T., He, J. P., Burstein, M., Hudziak, J. J., & Merikangas, K. R. (2016). Disruptive Mood Dysregulation Disorder at Ages 13–18: Results from the National Comorbidity Survey—Adolescent Supplement. Journal of child and adolescent psychopharmacology, 26
ro of
Axelson, D., Findling, R. L., Fristad, M. A., Kowatch, R. A., Youngstrom, E. A., Horwitz, S. M.,Birmaher, B. (2012). Examining the proposed disruptive mood dysregulation disorder diagnosis in children in the longitudinal assessment of manic symptoms study. Journal of Clinical Psychiatry, 73, 1342–1350.
-p
Biederman, J., Petty, C. R., Day, H., Goldin, R. L., Spencer, T., Faraone, S. V., Surman C.B. & Wozniak, J. (2012). Severity of the aggression/anxiety-depression/attention (AAA) CBCL profile discriminates between different levels of deficits in emotional regulation in youth with ADHD. Journal of developmental and behavioral pediatrics, 33(3), 236.
re
Blader, Joseph C., and Gabrielle A. Carlson. "Increased rates of bipolar disorder diagnoses among US child, adolescent, and adult inpatients, 1996–2004." Biological psychiatry 62.2 (2007): 107-114.
lP
Boylan, K., Vaillancourt, T., Boyle, M., & Szatmari, P. (2007). Comorbidity of internalizing disorders in children with oppositional defiant disorder. European child & adolescent psychiatry, 16(8), 484-494.
ur na
Burke, J. D., Loeber, R., Lahey, B. B., & Rathouz, P. J. (2005). Developmental transitions among affective and behavioral disorders in adolescent boys. Journal of Child Psychology and Psychiatry, 46(11), 1200-1210. Burke, Jeffrey, and Rolf Loeber. "Oppositional defiant disorder and the explanation of the comorbidity between behavioral disorders and depression." Clinical Psychology: Science and Practice 17.4 (2010): 319-326.
Jo
Copeland, W. E., Shanahan, L., Costello, E. J., & Angold, A. (2009). Childhood and adolescent psychiatric disorders as predictors of young adult disorders. Archives of general psychiatry, 66(7), 764-772. Copeland, W. E., Angold, A., Costello, E. J., & Egger, H. (2013). Prevalence, comorbidity, and correlates of DSM-5 proposed disruptive mood dysregulation disorder. American Journal of Psychiatry, 170(2), 173-179. Dougherty, L. R., Smith, V. C., Bufferd, S. J., Kessel, E. M., Carlson, G. A., & Klein, D. N. (2016). Disruptive mood dysregulation disorder at the age of 6 years and clinical and functional outcomes 3 years later. Psychological medicine, 46(5), 1103-1114.
Erol N, Arslan L.B, Akçakın M. The adaptation and standardization of the Child Behaviour Checklist among 6-18 year old Turkish children. In Eunothydis European Approaches to Hyperkinetic Disorders (Ed A Sergeant):109-113. Amsterdam, Klinische Psychologie Universiteit van Amsterdam, 1995. Erol, N. ve Şimşek, Z. (1998). Türkiye Ruh Sağlığı Profili: Çocuk ve Gençlerde Ruh Sağlığı: Yeterlik alanları, davranış ve duygusal sorunların dağılımı. N. Erol, C. Kılıç, , M. Ulusoy, M. Keçeci, ve Z. Şimşek (ed.). Türkiye Ruh Sağlığı Profili Raporu, T.C. Sağlık Bakanlığı Temel Sağlık Hizmetleri Genel Müdürlüğü, Eksen Tanıtım Ltd.Şti., 25-75, Ankara. Evans, S. C., Burke, J. D., Roberts, M. C., Fite, P. J., Lochman, J. E., Francisco, R., & Reed, G. M. (2017). Irritability in child and adolescent psychopathology: An integrative review for ICD-11. Clinical Psychology Review, 53, 29-45.
ro of
Freeman, A. J., Youngstrom, E. A., Youngstrom, J. K., & Findling, R. L. (2016). Disruptive mood dysregulation disorder in a community mental health clinic: prevalence, comorbidity and correlates. Journal of child and adolescent psychopharmacology, 26(2), 123.
-p
Gökler, B., Ünal, F., Pehlivantürk, B., Kültür, E. Ç., Akdemir, D., & Taner, Y. (2004). Okul Çaği Çocuklari İçin Duygulanim Bozukluklari ve Şizofreni Görüşme Çizelgesi-Şimdi ve Yaşam Boyu Şekli-Türkçe Uyarlamasinin Geçerlik ve Güvenirliği. Çocuk ve gençlik Ruh sağliği dergisi.
re
Kaufman, J., Birmaher, B., Brent, D., Rao, U. M. A., Flynn, C., Moreci, P., ... & Ryan, N. (1997). Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data. Journal of the American Academy of Child & Adolescent Psychiatry, 36(7), 980-988.
lP
Kim-Cohen, J., Caspi, A., Moffitt, T. E., Harrington, H., Milne, B. J., & Poulton, R. (2003). Prior juvenile diagnoses in adults with mental disorder: developmental follow-back of a prospective-longitudinal cohort. Archives of general psychiatry, 60(7), 709-717.
ur na
Leibenluft, E., Charney, D. S., Towbin, K. E., Bhangoo, R. K., & Pine, D. S. (2003). Defining clinical phenotypes of juvenile mania. American Journal of Psychiatry, 160, 430–437. Leibenluft, E., & Stoddard, J. (2013). The developmental psychopathology of irritability. Development and Psychopathology, 25, 1473–1487.
Jo
Mayes, S. D., Waxmonsky, J. D., Calhoun, S. L., & Bixler, E. O. (2016). Disruptive mood dysregulation disorder symptoms and association with oppositional defiant and other disorders in a general population child sample. Journal of child and adolescent psychopharmacology, 26(2), 101-106. Whelan, Y. M., Stringaris, A., Maughan, B., & Barker, E. D. (2013). Developmental continuity of oppositional defiant disorder subdimensions at ages 8, 10, and 13 years and their distinct psychiatric outcomes at age 16 years. Journal of the American Academy of Child & Adolescent Psychiatry, 52(9), 961-969.
Table I. A brief sociodemographic information and CBCL subscale scores in total sample, MRG, HRG, and PI group.
Gender (male) Diagnosis
Total Sample
MRG
HRG
PI Group
(n=453)
(n=83)
(n=14)
(n=30)
46.1%
41%
50%
40%
0%
28.57%
13.33%
of 0.88%
DMDD mean (above clinical range %) 8,81
8,64
9,22
8,48
Withdrawal
53,88 (16.6%)
57.73 (36.1%)
70,50 (78.6%)
61,00 (50%)
Somatic
54,40 (18.1%)
57.39 (34.9%)
67,50 (71.4%)
60,03 (46.7%)
Anxiety
57,97 (40.4%)
65.60 (85.5%)
78,21 (100%)
69,53 (100%)
Social
54,76 (17.7%)
59.98 (48.2%)
69,36 (85.7%)
64,10 (66.7%)
Thought
56,74 (26.7%)
62.84 (56.6%)
70,07 (85.7%)
63,27 (63.3%)
Attention
55,60 (26.7%)
62.20 (73.5%)
75,36 (100%)
66,70 (93.3%)
Delinquent
52,21 (7.9%)
55.56 (22.9%)
60,71 (50%)
56,73 (26.7%)
Aggressive
54,22 (19.0%)
61.49 (66.3%)
68,71 (100%)
63,73 (73.3%)
Total
53,25 (12.1%)
64.32 (44.6%)
74,71 (92.9%)
67,17 (70%)
Internal
54,79 (13.2%)
63.16 (41.0%)
75,93 (85.7%)
67,23 (56.7%)
External
49,61 (4.9%)
60.44 (16.9%)
67,00 (50%)
62,60 (33.3%)
DMDD Panel
167,80
189.30
222,28
199,97
lP
re
-p
ro of
Age
Jo
ur na
MRG; Moderate Risk Group, HRG; High Risk Group, PI; Psychiatric Interview, DMDD; Distruptive Mood Dysregulation Disorder, CBCL; Child Behavior Checklist.
PII:
S1876-2018(19)30825-1
DOI:
https://doi.org/10.1016/j.ajp.2019.101858
Reference:
AJP 101858
To appear in:
Asian Journal of Psychiatry
Received Date:
27 August 2019
Revised Date:
12 October 2019
Accepted Date:
13 October 2019
˘ Please cite this article as: Tu¨ gen LE, Disruptive Mood Dysregulation Disorder in A Primary School Sample, Asian Journal of Psychiatry (2019), doi: https://doi.org/10.1016/j.ajp.2019.101858
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.
Disruptive Mood Dysregulation Disorder in A Primary School Sample Leyla Ezgi Tüğen [email protected]
Introduction
In children, irritability can be seen as part of the normal developmental process or accompanying many psychiatric conditions, such as oppositional defiant disorder (ODD),
ro of
bipolar disorder (BD), depression, attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (Evans et al. 2017). In literature, it is reported that the prevalence of bipolar disorder in children with severe irritability increased significantly between 1990 and 2006 (Blader et al. 2007). However, the position of severe irritability which cannot be explained by any psychiatric disorder in classification and nomenclature is controversial. As a result of
-p
studies conducted in this area, a definition for severe irritability with chronic abnormal mood, hyperarousal symptoms, and anger attacks was required, and Severe Mood Dysregulation
re
(SMD) was identified as a broad phenotype of pediatric bipolar disorder (Leibenluft et al. 2003). Subsequent longitudinal studies reported that SMD and BD had different symptom
lP
clusters and that they differ from each other in terms of comorbid diagnoses and outcomes (Leibenluft et al. 2013). Chronic irritability, which is the main feature of SMD, has been found to be related to ODD, ADHD and depressive disorders, while the key feature of BD, episodic
ur na
irritability, is related to anxiety and mania (Leibenluft et al 2006). For this new form of chronic irritability, hyper-excitability symptoms and intelligence criteria were excluded in DSM-V, and the definition of Disruptive Mood Dysregulation Disorder (DMDD) was introduced as a new diagnostic group that included frequent and severe episodes of anger accompanied by chronic irritability in children and adolescents (Evans and et al. 2017).
Jo
Since DMDD was included as a new diagnosis in the DSM-V, it was observed that mostly SMD data were used in the studies (Evans et al. 2017). SMD and DMDD resemble each other but have different diagnostic criteria. Thus, the applicability of the previous results of SMD studies for DMDD is controversial. Although there are a wide range of prevalence rates for DMDD ranging from 26-31% in the clinical samples to 0.8-8.1% in the community samples (Axelson et al. 2012, Freeman et al. 2016; Copeland et al. 2013), when prevalence rates are evaluated according to frequency and intensity criteria of chronic irritability, decrease in the prevalence is typical (Althoff et al. 2016). Also, the incidence of DMDD decreases with increasing age. In
a longitudinal study, the prevalence of DMDD at the age of 6 was 8%, but at nine years of age, this rate decreased to 1% (Dougherty et al. 2014). Similarly, the prevalence of DMDD was found 9% in an 8-year longitudinal study in a population of 6 to 12 years, but it was reported that only 29% of these children continued to be diagnosed with DMDD after eight years (Mayes et al. 2016). In community-based studies, it is seen that DMDD is accompanied by other psychiatric disorders, especially depression and ODD, between 60.5% and 92%, although DMDD and ODD cannot co-exist according to DSM-5 (Copeland et al. 2013). In addition, Dougherty et al. suggested that having a diagnosis of DMDD at six years of age, predicted depressive disorder,
ro of
ADHD, and worse psychosocial functioning (Dougherty et al. 2016). Similarly, chronic irritability is reported to indicate internalizing disorders, such as depression and anxiety, rather than subsequent externalizing disorders (Whelan et al. 2013).
It is seen that chronic irritability and DMDD have recently begun to find a place in child
-p
psychiatry literature. However, its clinical significance is better understood when its high incidence and high comorbid diagnosis rates are considered. In our study, we aimed to 1)
re
determine the frequency of DMDD in a community-based sample in Turkey, Istanbul, Pendik
Methods
ur na
Sample and Procedures
lP
2) identify comorbid diagnoses in children with DMDD.
Our study is a cross-sectional population-based study applied to all students in the first, second, third and fourth grades, that’s supposed to have the highest DMDD rates, in a primary school in Istanbul, Pendik. Approval to perform the study was obtained from the Marmara
Jo
University Ethics Committee (09.2018.167). Before the data collection, researchers gave information about the purpose, method, and course of the study to the principal and teachers of the school. At the end of the study, necessary referrals to child psychiatry were made. At the beginning of the study, the Child Behavior Checklist, which also includes an informed consent on the first page, was given to the counselor in primary school to be distributed to all students (650 children). One week later, 463 out of 650 forms were filled by the parents of students and collected by the counselor. Ten of the forms collected from the children were excluded because they were incomplete. Four hundred fifty-three children (70% of the total sample) constituted
the sample of the study. Of the children who participated in the study, 83 children with a total score between 180 and 210 in CBCL attention, anxious / depression and aggression subscale scores (18.3% of the study sample) were evaluated in moderate-risk group in terms of DMDD and 14 children with a total score of 210 and higher (3.1% of the study sample) were considered as high-risk group (HRG). Both groups were invited to the hospital by a phone call of a child and adolescent psychiatrist. Of the children invited, 30 (6.62% of the study sample) agreed to participate in the study. : Child and adolescent psychiatrists applied Kiddie-Schedule for Affective Disorders and Schizophrenia for School-Age Children, Present and Lifetime Version, K-SADS-PL (KSADS) to children who agreed to participate in the study, considering the
ro of
changes based on DSM-5. Comorbid diagnoses were determined with KD-SADS-PL, plus a semi-structured interview involving the DSM-V criterias in the interviewed children. Four children (0.88% of the study sample) were diagnosed with DMDD.
-p
Follow-up Form
In our study, age and gender of the child were questioned with the follow-up form. There was
lP
The Child Behavior Checklist (CBCL)
re
an informed consent form in the front of each form.
The Child Behavior Checklist developed by Achenbach and Edenbrock in 1983 was translated
ur na
into Turkish by Erol and Kılıç in 1991, and translations were revised in 1998 (Erol and Şimşek 1998). Test-retest reliability of the scale was found to be 0.70 and 0.84. Internal consistency values were found to be 0,39 and 0,86 (Erol et al. 1995). The questions in the scale are answered by mother and father on the four-point Likert scale. “not correct”, “sometimes or slightly correct” and “absolutely correct or often correct” are scored as “0”, “1”, “2”, respectively. The
Jo
cut-off point for the subscale scores in the CBCL is 60 and above; the cut-off score for the internalizing, externalizing and total scores were taken as 65 and above (Achenbach 1991). DMDD is closely related to emotion dysregulation, aggression, irritability, anxiety and depression. also, CBCL is a scale that can be used for screening of psychopatology of children in Turkey. In the previous studies, because of a lack of diagnostic instruments, the dysregulation profile (DP) of the Child Behavior Checklist (CBCL) was used to assess prevalence rates of DMDD (Freeman et al., 2016). The total score of CBCL attention, anxiety/depression, and aggression subscale scores were evaluated as DMDD panel score, and points below 179 were
considered as non-risk group, points between 180 and 209 were considered as moderate risk group (MRG), and 210 and above points were considered as high-risk group (HRG) for DMDD (Biederman et al. 2012). Kiddie-Schedule for Affective Disorders and Schizophrenia for School-Age Children, Present and Lifetime Version (K-SADS-PL)
K-SADS-PL, which is a semi structured interview was developed by Kauffman et al (Kauffman et al., 1997) Schedule for affective disorders and schizophrenia for schoolage children-present and lifetime version (K-SADS-PL): initial reliability and validity data and its reliabillity and
ro of
validity study in Turkey was carried out by Gökler et al (Gökler et al., 2004).
Clinical Interview for DSM-V Axis I Disorders
It has been used to determine the diagnosis of DMDD and comorbid psychiatric diagnoses in
-p
children (APA 2013).
re
Clinical Significance
lP
Our study is one of the few studies evaluating the frequency of DMDD in Turkey. Although the prevalence of DMDD is low, comorbid diagnosis rates require detailed examination and
ur na
multifaceted perspectives in the follow-up and treatment process.
Statistical Analysis
Data were analyzed using the Statistical Program for Social Sciences (SPSS for Windows,
Jo
20.0). Chi-square (χ²) was used for comparison of numerical variables, and Student t-test and ANOVA were used for comparison of continuous variables. The significance level for all analyzes was accepted as p <0.05.
Results
A total of 453 children, 209 (46,1%) of whom were male, participated in our study. The mean age of the study group was 8.81 ± 1.25 (min: 6.72, max: 11.8).
356 (78.6%) children who participated in the study received a score below 179 in the DMDD panel and were evaluated as non-risk group for DMDD, 83 (18.3%) children received a score between 180 and 210 in the DMDD panel and were evaluated as moderate-risk group (MRG) for DMDD. 44.6% (n=37) of the MRG received a score of 65 and above in CBCL total, 41.0% (n=34) in CBCL internalizing and 16.9% (n=14) in CBCL externalizing. 41.0% (n=34) of the MRG and 46.6% (n=166) of the non-risk group were male (χ²=0.871, p=0.351). The mean age of the MRG was 8.64 ± 1.15, and the non-risk group was 8.84 ± 1.27 (t = 1.283, p = 0.200). When the effect of age was controlled in MRG, no significant difference was found between
ro of
male (mean ±%95 CI; 189.703 ± 187.00-192.39) and female (mean ± %95 CI; 189.044 ± 186.775-191.312) in terms of DMDD panel (F (1, 79); 0.102, p= 0.71) (Ancova).
Of the 453 children participating in the study, 14 (3.1%) scored 210 and higher in the DMDD panel and were considered as high-risk group (HRG). 92.9% (n=13) of the HRG received a
-p
score of 65 and above in CBCL total, 85.7% (n=12) in CBCL internalizing and 50% (n=7) in CBCL externalizing. 50% (n=7) of the HRG and 46.6% (n=166) of the non-risk group were
re
male (χ²=0.061, p=0.804). The mean age of the HRG was 9.22±1.08, and the mean age of the non-risk group was 8.84±1.27 (t=-1.102, p=0.271).
lP
Eight (26.7%) of 30 children who underwent psychiatric interview (PI) were within the HRG, and 4 (13.3%) of these children were diagnosed with DMDD. The children diagnosed with DMDD accounted for 28.57% of the HRG and 0.88% of the whole school group. There was at
ur na
least one comorbid diagnosis in all four children diagnosed with DMDD.
Thirteen of the 30 children (43.3%) who underwent psychiatric interview had ADHD, 7 (23.3%) had enuresis nocturna, 5 (16.7%) had separation anxiety disorder, 5 (16.7%) had social phobia, 4 (13.3%) had oppositional defiant disorder, 3 (10%) specific phobia, 2 (6.7%) had
Jo
generalized anxiety disorder, 2 (6.7%) had obsessive-compulsive disorder, 2 (6.7%) had depression, 1 (3,3%) had mild mental retardation, 1 (3.3%) had atypical autism and 2 (6.7%) had dislexia.
There was at least one mood disorder in 6.7% (n=2), at least one anxiety disorder in 36.7% (n=11), at least one disruptive behavior disorder in 50% (n = 15) and at least one comorbid diagnosis in 76.7% (n = 23) of PI group. 70% (n=21) of the PI group received a score of 65 and
above in the CBCL total, 56.7% (n=17) in CBCL internalizing and 33.3% (n=10) in externalizing. A brief sociodemographic information and CBCL subscale scores in total sample, MRG, HRG, and PI group is demonstrated in Table I.
Discussion
In this study, the prevalence of DMDD and comorbid psychiatric diagnoses were evaluated in a community sample of 6-11 years old primary school students with a clinical interview based
ro of
on DSM-V. While Mayes et al. (2016) found the frequency of DMDD symptoms as 9% in the general population between the ages of 6 and 12, when “very often” criteria was added, the frequency of DMDD was reduced to 1%. Similarly, the prevalence of DMDD was 5.26% among adolescents 13-18 years of age, and this ratio decreased to 0.12% when the frequency
-p
and mania exclusion criteria were added (Althoff et al. 2016). In studies which DSM-V DMDD criteria and clinical examination were evaluated; the frequency of diagnosis in the community
re
sample was 8% (Dougherty et al. 2016), and this rate increased to 26% - 31% in the clinical sample (Axelson et al. 2012, Freeman et al. 2016). Another factor that affects the frequency of
lP
DMDD is the age of the child. Studies show that the prevalence of DMDD is 8%, especially in preschool period, this rate decreases to 1% in 9 years of age, and continuity of diagnosis decreases as the duration of follow-up period increases (Dougherty et al. 2014, Mayes et al.,
ur na
2016). In a large sample study, it was reported that the prevalence of DMDD was between 0.8% and 3.3%, and the highest rates were seen in pre-school children (Copeland et al. 2013). The results of these studies suggest that factors such as age, community/clinical sample, and scale/clinical examination might make a difference in the frequency of diagnosis of DMDD (Mayes et al. 2016, Althoff et al. 2016, Dougherty et al. 2016, Axelson et al. 2012). In our
Jo
study, the frequency of diagnosis of DMDD was decreased because the sample was communitybased, in the primary school period; evaluation was two staged, as scale and clinical examination; the evaluation of frequency, severity, and mania exclusion criteria was considered.
In studies with adolescents, it was reported that approximately 90% of cases with DMDD were accompanied by any psychiatric diagnosis, mood disorders and disruptive behavior disorders are the most common comorbid diagnoses, and comorbidities showed high rates of persistence
at follow-up. (Althoof et al. 2016, Copeland et al. 2013, Doughtery et al. 2016). In our study, similar to the results of previous studies, approximately 76% of cases in PI group and all cases with DMDD had at least one comorbid diagnosis; and 44.6% of the MRG and 92.9% of the HRG had a total score of CBCL above the clinical level. Also, it was found that the MRG, HRG and PI group showed high rates of externalization and internalization symptoms. In the PI group, the overall rates of mood and anxiety disorders and the rates of disruptive behavior disorders were similar. These rates suggest that, although DMDD is classified as an internalizing problem, it has internalizing and externalizing components. High rates of comorbidities in DMDD, emphasizes the need for careful consideration of DMDD during
ro of
diagnosis, treatment, and follow-up procedures.
In literature, DMDD has been reported to be almost always accompanied by ODD (Freeman et al., 2016; Mayes et al., 2016). DSM-V indicates that the diagnosis of ODD cannot be made in patients with DMDD diagnostic criteria (DSM-V), but, as in many studies and our study, the
-p
majority of patients with a diagnosis of DMDD meet the diagnostic criteria for ODD (Althoff et al. 2012; Mayes et al. 2016; Doughtry et al. 2014). Also, Freeman et al. (2016) reported that
re
DMDD did not differ significantly from ODD in terms of diagnostical and dimensional comorbidity and impaired functioning. Both homotypic (comorbidity with ADHD and conduct
lP
disorder) and heterotypic (comorbidity with anxiety and depression) structure of ODD, and the developmental continuity of ODD with many other disorders, provide a diagnostical resemblance of ODD to DMDD (Boylan et al. 2007; Burke and Loeber, 2010; Burke et al 2005;
ur na
Copeland et al 2009; Kim-Cohen et al. 2003). These data give rise to the need for reinterrogation of DMDD as a primary diagnosis in subsequent studies.
Disclosure
Jo
All authors declare that there is no competing financial interests.
Limitations
Although our study has strengths, such as being a community-based study, using DSM-V based clinical assessment and being one of the few studies in Turkey, various limitations are present. First, clinical evaluation was not applied to all children in the sample group; however, children
who were considered to be at moderate risk according to the CBCL were invited. Approximately one-third of children invited to the study accepted clinical evaluation. This makes it difficult to generalize the results of the study. Our second limitation is that Pendik, Istanbul, where we have taken the sample group, is a region in the middle-lower class socioeconomic level. Expanding the study to cover all socioeconomic levels might prevent this limitation. Another limitation was that the number of children diagnosed with DMDD was very few (n=4), which hinders detailed statistical evaluation on the diagnosis of DMDD. The results of our study should be evaluated considering these limitations.
ro of
Conclusions
In our study, 4 children (0.88% of the total sample) was diagnosed with DMDD in 7-12 aged primary school sample and the comorbidity rate was relatively high (76.7%) in the PI group. Longitudinal studies with larger samples are needed to generalize the results of our study.
-p
Conflict of Interest
re
The authors declare that they have no conflicts of interest.
lP
Acknowledgments
There are no sources of support for this study. The authors thank all the children and their
Jo
ur na
families whose participation made this study possible.
References Achenbach T.M. Manual for the Child Behaviour Checklist/4-18 and 1991 profile. Burlington, University of Vermont, 1991. Althoff, R. R., Crehan, E. T., He, J. P., Burstein, M., Hudziak, J. J., & Merikangas, K. R. (2016). Disruptive Mood Dysregulation Disorder at Ages 13–18: Results from the National Comorbidity Survey—Adolescent Supplement. Journal of child and adolescent psychopharmacology, 26
ro of
Axelson, D., Findling, R. L., Fristad, M. A., Kowatch, R. A., Youngstrom, E. A., Horwitz, S. M.,Birmaher, B. (2012). Examining the proposed disruptive mood dysregulation disorder diagnosis in children in the longitudinal assessment of manic symptoms study. Journal of Clinical Psychiatry, 73, 1342–1350.
-p
Biederman, J., Petty, C. R., Day, H., Goldin, R. L., Spencer, T., Faraone, S. V., Surman C.B. & Wozniak, J. (2012). Severity of the aggression/anxiety-depression/attention (AAA) CBCL profile discriminates between different levels of deficits in emotional regulation in youth with ADHD. Journal of developmental and behavioral pediatrics, 33(3), 236.
re
Blader, Joseph C., and Gabrielle A. Carlson. "Increased rates of bipolar disorder diagnoses among US child, adolescent, and adult inpatients, 1996–2004." Biological psychiatry 62.2 (2007): 107-114.
lP
Boylan, K., Vaillancourt, T., Boyle, M., & Szatmari, P. (2007). Comorbidity of internalizing disorders in children with oppositional defiant disorder. European child & adolescent psychiatry, 16(8), 484-494.
ur na
Burke, J. D., Loeber, R., Lahey, B. B., & Rathouz, P. J. (2005). Developmental transitions among affective and behavioral disorders in adolescent boys. Journal of Child Psychology and Psychiatry, 46(11), 1200-1210. Burke, Jeffrey, and Rolf Loeber. "Oppositional defiant disorder and the explanation of the comorbidity between behavioral disorders and depression." Clinical Psychology: Science and Practice 17.4 (2010): 319-326.
Jo
Copeland, W. E., Shanahan, L., Costello, E. J., & Angold, A. (2009). Childhood and adolescent psychiatric disorders as predictors of young adult disorders. Archives of general psychiatry, 66(7), 764-772. Copeland, W. E., Angold, A., Costello, E. J., & Egger, H. (2013). Prevalence, comorbidity, and correlates of DSM-5 proposed disruptive mood dysregulation disorder. American Journal of Psychiatry, 170(2), 173-179. Dougherty, L. R., Smith, V. C., Bufferd, S. J., Kessel, E. M., Carlson, G. A., & Klein, D. N. (2016). Disruptive mood dysregulation disorder at the age of 6 years and clinical and functional outcomes 3 years later. Psychological medicine, 46(5), 1103-1114.
Erol N, Arslan L.B, Akçakın M. The adaptation and standardization of the Child Behaviour Checklist among 6-18 year old Turkish children. In Eunothydis European Approaches to Hyperkinetic Disorders (Ed A Sergeant):109-113. Amsterdam, Klinische Psychologie Universiteit van Amsterdam, 1995. Erol, N. ve Şimşek, Z. (1998). Türkiye Ruh Sağlığı Profili: Çocuk ve Gençlerde Ruh Sağlığı: Yeterlik alanları, davranış ve duygusal sorunların dağılımı. N. Erol, C. Kılıç, , M. Ulusoy, M. Keçeci, ve Z. Şimşek (ed.). Türkiye Ruh Sağlığı Profili Raporu, T.C. Sağlık Bakanlığı Temel Sağlık Hizmetleri Genel Müdürlüğü, Eksen Tanıtım Ltd.Şti., 25-75, Ankara. Evans, S. C., Burke, J. D., Roberts, M. C., Fite, P. J., Lochman, J. E., Francisco, R., & Reed, G. M. (2017). Irritability in child and adolescent psychopathology: An integrative review for ICD-11. Clinical Psychology Review, 53, 29-45.
ro of
Freeman, A. J., Youngstrom, E. A., Youngstrom, J. K., & Findling, R. L. (2016). Disruptive mood dysregulation disorder in a community mental health clinic: prevalence, comorbidity and correlates. Journal of child and adolescent psychopharmacology, 26(2), 123.
-p
Gökler, B., Ünal, F., Pehlivantürk, B., Kültür, E. Ç., Akdemir, D., & Taner, Y. (2004). Okul Çaği Çocuklari İçin Duygulanim Bozukluklari ve Şizofreni Görüşme Çizelgesi-Şimdi ve Yaşam Boyu Şekli-Türkçe Uyarlamasinin Geçerlik ve Güvenirliği. Çocuk ve gençlik Ruh sağliği dergisi.
re
Kaufman, J., Birmaher, B., Brent, D., Rao, U. M. A., Flynn, C., Moreci, P., ... & Ryan, N. (1997). Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data. Journal of the American Academy of Child & Adolescent Psychiatry, 36(7), 980-988.
lP
Kim-Cohen, J., Caspi, A., Moffitt, T. E., Harrington, H., Milne, B. J., & Poulton, R. (2003). Prior juvenile diagnoses in adults with mental disorder: developmental follow-back of a prospective-longitudinal cohort. Archives of general psychiatry, 60(7), 709-717.
ur na
Leibenluft, E., Charney, D. S., Towbin, K. E., Bhangoo, R. K., & Pine, D. S. (2003). Defining clinical phenotypes of juvenile mania. American Journal of Psychiatry, 160, 430–437. Leibenluft, E., & Stoddard, J. (2013). The developmental psychopathology of irritability. Development and Psychopathology, 25, 1473–1487.
Jo
Mayes, S. D., Waxmonsky, J. D., Calhoun, S. L., & Bixler, E. O. (2016). Disruptive mood dysregulation disorder symptoms and association with oppositional defiant and other disorders in a general population child sample. Journal of child and adolescent psychopharmacology, 26(2), 101-106. Whelan, Y. M., Stringaris, A., Maughan, B., & Barker, E. D. (2013). Developmental continuity of oppositional defiant disorder subdimensions at ages 8, 10, and 13 years and their distinct psychiatric outcomes at age 16 years. Journal of the American Academy of Child & Adolescent Psychiatry, 52(9), 961-969.
Table I. A brief sociodemographic information and CBCL subscale scores in total sample, MRG, HRG, and PI group.
Gender (male) Diagnosis
Total Sample
MRG
HRG
PI Group
(n=453)
(n=83)
(n=14)
(n=30)
46.1%
41%
50%
40%
0%
28.57%
13.33%
of 0.88%
DMDD mean (above clinical range %) 8,81
8,64
9,22
8,48
Withdrawal
53,88 (16.6%)
57.73 (36.1%)
70,50 (78.6%)
61,00 (50%)
Somatic
54,40 (18.1%)
57.39 (34.9%)
67,50 (71.4%)
60,03 (46.7%)
Anxiety
57,97 (40.4%)
65.60 (85.5%)
78,21 (100%)
69,53 (100%)
Social
54,76 (17.7%)
59.98 (48.2%)
69,36 (85.7%)
64,10 (66.7%)
Thought
56,74 (26.7%)
62.84 (56.6%)
70,07 (85.7%)
63,27 (63.3%)
Attention
55,60 (26.7%)
62.20 (73.5%)
75,36 (100%)
66,70 (93.3%)
Delinquent
52,21 (7.9%)
55.56 (22.9%)
60,71 (50%)
56,73 (26.7%)
Aggressive
54,22 (19.0%)
61.49 (66.3%)
68,71 (100%)
63,73 (73.3%)
Total
53,25 (12.1%)
64.32 (44.6%)
74,71 (92.9%)
67,17 (70%)
Internal
54,79 (13.2%)
63.16 (41.0%)
75,93 (85.7%)
67,23 (56.7%)
External
49,61 (4.9%)
60.44 (16.9%)
67,00 (50%)
62,60 (33.3%)
DMDD Panel
167,80
189.30
222,28
199,97
lP
re
-p
ro of
Age
Jo
ur na
MRG; Moderate Risk Group, HRG; High Risk Group, PI; Psychiatric Interview, DMDD; Distruptive Mood Dysregulation Disorder, CBCL; Child Behavior Checklist.