Improving the K6 short scale to predict serious emotional disturbance in adolescents in the USA.

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Title: Improving the K6 short scale to predict serious emotional disturbance in adolescents in the USA.
Authors: Green, Jennifer Greif, Gruber, Michael J., Sampson, Nancy A., Zaslavsky, Alan M., Kessler, Ronald C.
Source: International Journal of Methods in Psychiatric Research. 2010 Supplement 1, Vol. 19, p23-35. 13p. 5 Charts, 1 Graph.
Subjects: Behavior Disorders Identification Scale, Psychiatric diagnosis, Anxiety, Teenagers, Psychometrics
Abstract: Effective screening for emotional and behavioral disorders among youth requires brief screening scales with good validity to identify youth requiring further evaluation and to estimate prevalence of target disorders in populations of interest such as schools or neighborhoods. This paper examines the psychometric properties of a very short (six-item) screening scale, the K6, to assess serious emotional disturbance (SED) among youth. The K6, which is made up of symptoms of depression and anxiety, has been shown in previous research to be a strong predictor of serious mental illness (SMI) in adults, but no information is available on the ability of the scale to screen for SED among youth. The current report examines the K6 as a screen for SED in a national survey of US adolescents, the National Comorbidity Survey Replication Adolescent Supplement (NCS-A). The K6 is shown to provide fairly good prediction of SED [area under curve (AUC) = 0.74] that is somewhat higher for internalizing (AUC = 0.80) than behavior (AUC = 0.75) disorders. Based on this result, we augmented the K6 with questions about symptoms of behavior disorders. This improved prediction of SED (from AUC = 0.74 to AUC = 0.83) as well as of SED associated with pure behavior disorders (from AUC = 0.53 to AUC = 0.78). These results show that although the symptoms of depression and anxiety in the K6 are sufficient to detect SMI among adults, high rates of behavior disorders among adolescents require indicators of behavior disorders to be added to the K6 to screen adequately for adolescent SED. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Methods in Psychiatric Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Improving the K6 short scale to predict serious emotional disturbance in adolescents in the USA.
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  Data: <searchLink fieldCode="AR" term="%22Green%2C+Jennifer+Greif%22">Green, Jennifer Greif</searchLink><br /><searchLink fieldCode="AR" term="%22Gruber%2C+Michael+J%2E%22">Gruber, Michael J.</searchLink><br /><searchLink fieldCode="AR" term="%22Sampson%2C+Nancy+A%2E%22">Sampson, Nancy A.</searchLink><br /><searchLink fieldCode="AR" term="%22Zaslavsky%2C+Alan+M%2E%22">Zaslavsky, Alan M.</searchLink><br /><searchLink fieldCode="AR" term="%22Kessler%2C+Ronald+C%2E%22">Kessler, Ronald C.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Methods+in+Psychiatric+Research%22">International Journal of Methods in Psychiatric Research</searchLink>. 2010 Supplement 1, Vol. 19, p23-35. 13p. 5 Charts, 1 Graph.
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  Data: <searchLink fieldCode="DE" term="%22Behavior+Disorders+Identification+Scale%22">Behavior Disorders Identification Scale</searchLink><br /><searchLink fieldCode="DE" term="%22Psychiatric+diagnosis%22">Psychiatric diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Anxiety%22">Anxiety</searchLink><br /><searchLink fieldCode="DE" term="%22Teenagers%22">Teenagers</searchLink><br /><searchLink fieldCode="DE" term="%22Psychometrics%22">Psychometrics</searchLink>
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  Data: Effective screening for emotional and behavioral disorders among youth requires brief screening scales with good validity to identify youth requiring further evaluation and to estimate prevalence of target disorders in populations of interest such as schools or neighborhoods. This paper examines the psychometric properties of a very short (six-item) screening scale, the K6, to assess serious emotional disturbance (SED) among youth. The K6, which is made up of symptoms of depression and anxiety, has been shown in previous research to be a strong predictor of serious mental illness (SMI) in adults, but no information is available on the ability of the scale to screen for SED among youth. The current report examines the K6 as a screen for SED in a national survey of US adolescents, the National Comorbidity Survey Replication Adolescent Supplement (NCS-A). The K6 is shown to provide fairly good prediction of SED [area under curve (AUC) = 0.74] that is somewhat higher for internalizing (AUC = 0.80) than behavior (AUC = 0.75) disorders. Based on this result, we augmented the K6 with questions about symptoms of behavior disorders. This improved prediction of SED (from AUC = 0.74 to AUC = 0.83) as well as of SED associated with pure behavior disorders (from AUC = 0.53 to AUC = 0.78). These results show that although the symptoms of depression and anxiety in the K6 are sufficient to detect SMI among adults, high rates of behavior disorders among adolescents require indicators of behavior disorders to be added to the K6 to screen adequately for adolescent SED. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of International Journal of Methods in Psychiatric Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: 2010 Supplement 1
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