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 Attention-deficit hyperactivity disorder, which affects about 3% to 5% of school-aged children, diagnosed according to the DSM-IV criteria, is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsive behaviour (1). ADHD is one of the most common causes of behaviour problems and poor school performance among school-aged children, and clinicians pay particular attention to this disorder because it is followed by various comorbid psychiatric disorders and can act as a source of continuous impairment in affected children (2–4). There are various instruments that assist in the diagnosis of ADHD. One of them is the CBCL (5), which was developed for the purpose of evaluating various aspects of a child’s behaviour. This checklist is also known to be a valuable screening instrument in the assessment of ADHD (6,7). The ARS (8), which is a behaviour-rating scale based on the DSM-IV criteria for ADHD, is another instrument that several studies have confirmed to be effective for identifying ADHD (9,10). To the best of our knowledge, there have not been any studies that made combined use of the CBCL and the ARS scales to constitute an epidemiologic case definition of ADHD. Thus the purpose of this study is to examine the clinical validities and efficiencies of the CBCL and the ARS in identifying children with ADHD in community-based samples. MethodsSubjects With guidance from the school administration, 2 elementary schools from Gunsan, an urban community in Korea with a population of 300 000, were selected as representative schools with community mental health services for children. All the children attending these 2 schools (n = 1668) from the first grade to the third grade participated in the study. Informed consent was obtained from the parents, and assent was obtained from the participating children prior to inclusion. The procedures used in this study involved 2 phases. Phase I The parents completed the parent versions of the CBCL and the ARS. The class teachers completed the teacher version of the ARS. The Korean versions of the CBCL and the ARS are known to have good validity and reliability (10,11). We obtained 1380 of the above-mentioned screening questionnaires (82.7%) from the initial 1668 subjects. Subjects included 702 boys and 678 girls. Those subjects, with a T score above 63 with regard to the Total Problems profile or a T score above 60 with regard to the Attention Problems profile of the CBCL were identified as potential candidates for participation in the next phase. There were significant correlations between the parent and teacher reports of inattention, hyperactivity-impulsivity, and total ARS scores. The cases in which the total scores of ARS were above the 90th percentile cut-off point in both the parent and teacher reports were identified as potential candidates for participation in the next phase. After having evaluated all the questionnaires according to the above-mentioned standards, we selected 98 cases (7.1%) as participants in the next phase. Phase II We asked the parents of these 98 potential cases to participate in the detailed assessment of their children. We obtained agreement to take part in this phase of the study in 46 cases (46.9%). There were no significant differences in demographic characteristics between the participants and the nonparticipants of this phase. The children, together with their parents, underwent a detailed psychiatric interview, which was conducted by an experienced child and adolescent psychiatrist. The interview was performed blind to the child’s CBCL and ARS results. Diagnostic assessments of psychiatric disorders, including ADHD, were made according to the DSM-IV criteria, with the K-SADS-PL (12). The Korean version of the K-SADS-PL was standardized by Kim and colleagues (13). Statistical Analysis To evaluate the discriminant power of the CBCL and the ARS in the diagnosis of ADHD, we examined the sensitivity, specificity, positive predictive value, and negative predictive value. ResultsPsychiatric Diagnoses Of the 46 subjects (33 boys and 13 girls), 33 (71.7%) were diagnosed as having ADHD. Eleven of these had comorbid psychiatric disorders, among which ODD had the highest proportion (8 cases). Psychiatric diagnoses other than ADHD included ODD, separation anxiety disorder, posttraumatic stress disorder, tic disorder, and social phobia. Eight subjects (17.4%) were not diagnosed as having any psychiatric disorders. Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value of the CBCL and the ARS for the Diagnosis of ADHD A T score of 60 with regard to the Attention Problems profile of CBCL resulted in a reasonable level of sensitivity (0.727) or positive predictive value (0.750) in the diagnosis of ADHD (Table 1). The 90th percentile cut-off points in both the parent and teacher reports of the ARS resulted in a high level of predictive value (0.846). The highest level of specificity and positive predictive value were obtained when we combined the CBCL (T ≥ 60 in Attention Problems) and the ARS (parent–teacher total ≥ 90th percentile) reports, with the values being 0.923 and 0.933, respectively.
DiscussionWith regard to the association between the Attention Problems subscale of the CBCL and the symptoms of ADHD, some researchers reported that a T score of 60 was associated with the optimal level of diagnostic discrimination in psychiatric samples (14,15), whereas Doyle and others reported that a T score of 65 maximized both sensitivity and specificity in a school sample (16). Conversely, Achenbach considered a T score of 70 to be the best cut-off score for the clinical range (5). In our study, a T score of 60 resulted in a reasonable level of sensitivity or positive predictive value in the diagnosis of ADHD. However, a T score of 70 as the cut-off score resulted in a low level of sensitivity (0.182). We can infer from these results that a cut-off score of 70 can result in many children with ADHD not being identified. In analyzing the results of the ARS, DuPaul suggested that the 80th and 90th percentile cut-off points could be used for screening ADHD and that the 93rd and 98th percentile cut-off points could be used for identifying ADHD (8). In our study, the 90th percentile cut-off points in both the parent and teacher reports of the ARS resulted in a high level of predictive value of 0.846. However, the sensitivity was only 0.667. The highest level of positive predictive value and specificity for the diagnosis of ADHD were obtained when we combined the CBCL (T ≥ 60 in Attention Problems) and the ARS (parent–teacher total ≥ 90th percentile) reports, with these values being 0.933 and 0.923, respectively. We can infer from these results that clinicians or researchers can predict or even diagnose ADHD based only on the results of the CBCL and the ARS, especially when the 2 reports are considered together. In countries such as ours, where structural diagnostic interviews cannot be performed in community-based approaches owing to limitations in human resources and economic support, the above-mentioned criteria provide a clinically useful guideline for identifying ADHD. The results of our study suggest that a combination of the CBCL and the ARS could serve as a rapid and useful instrument for predicting, or even diagnosing, ADHD in epidemiologic case definitions. References1. American Psychiatric Association. Attention-deficit and disruptive behavior disorders. Washington (DC): American Psychiatric Association Press; 1994. 2. Biederman J. Attention-deficit/hyperactivity disorder: a life-span perspectives. J Clin Psychiatry 1998;59:S4–S15. 3. Biederman J, Newcorn J, Sprich S. Comorbidity of attention deficit hyperactivity disorder with conduct, depressive, anxiety, and other disorders. Am J Psychiatry 1991;148:564–77. 4. Goldman LS, Genel M, Bezman RJ, Slanetz PJ. Diagnosis and treatment of attention-deficit/hyperactive disorder in children and adolescents. JAMA 1998;279:1100–7. 5. Achenbach TM. Manual for the Child Behavior Checklist/4-18 and 1991 Profile. Burlington: University of Vermont; 1991. 6. Biederman J, Monuteaux MC, Greene RW, Braaten E, Doyle AE, Faraone SV. Long-term stability of the Child Behavior Checklist in a clinical sample of youth with attention deficit hyperactivity disorder. J Clin Child Psychol 2001;30:492–502. 7. DuPaul GJ, Stoner GD. ADHD in the schools: assessment and intervention strategies. New York: Guilford; 1994. 8. DuPaul GJ. Parent and teacher ratings of ADHD symptoms: psychometric properties in a community-based sample. J Clin Child Psychol 1991;20:245–53. 9. DuPaul GJ, Power TJ, Anastopoulos AD, Reid R, McGoey KE, Ikeda MJ. Teacher ratings of attention-deficit/hyperactivity disorder: factor structure and normative data. Psychol Assess 1997;9:436–44. 10. So YK, Noh JS, Kim YS, Ko SG, Koh SJ. The reliability and validity of Korean parent and teacher ADHD Rating Scale. Journal of Korean Neuropsychiatric Association 2002;41:283–9. 11. Oh KJ, Lee HR. Development of Korean version of Child Behavior Checklist (K-CBCL). Seoul: Korean Research Foundation Report; 1990. 12. Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, and others. Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Life Time Version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry 1997;36:980–8. 13. Kim YS, Cheon KA, Kim BN, Chang SA, Yoo HJ, Kim JW, and others. The reliability and validity of Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version-Korean Version (K-SADS-PL-K). Yonsei Med J 2004;45:81–9. 14. Biederman J, Faraone SV, Doyle A, Lehman BK, Kraus I, Perrin J, and others. Convergence of the Child Behavior Checklist with structured interview-based psychiatric diagnoses of ADHD children with and without comorbidity. J Child Psychol Psychiatr 1993;34:1241–51. 15. Steingard R, Biederman J, Doyle A, Sprich-Buckminster S. Psychiatric comorbidity in attention deficit disorder: impact on the interpretation of Child Behavior Checklist results. J Am Acad Child Adolesc Psychiatry 1992;31:449–54. 16. Doyle A, Ostrander R, Skare S, Crosby RD, August GJ. Convergent and criterion-related validity of the Behavior Assessment System for Children-Parent Rating Scale. J Clin Child Psychol 1997;26:276–84. Authors1. Staff Physician, Maeumsarang Hospital, 496-28 Haewol-Li, Soyang-Myun, Wanju-Gun, Jeonbuk, Korea. 2. Director, Gunsan Mental Health Center, Gunsan, Korea. 3. Assistant Professor, Department of Psychiatry, College of Medicine, Kwandong University, Kyunggi, Korea. 4. Professor, Department of Child and Adolescent Psychiatry, College of Medicine, Seoul National University Hospital, Seoul, Korea Address for correspondence: Dr Jae-won Kim, Maeumsarang Hospital, 496-28 Haewol-Li, Soyang-Myun, Wanju-Gun, Jeonbuk, Republic of Korea e-mail: jaewon412@korea.com
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