Skip to main content
Search
Search
    Quick Search anywhere
    Quick search in Citations
Advanced Search
Skip main navigationClose Drawer MenuOpen Drawer Menu
Previous article
Next article
Originalarbeit

Die Diagnostik von Angst und Depression mit dem Mehrdimensionalen Angstinventar für Kinder und Jugendliche (MAI-KJ)

Published Online:August 27, 2019https://doi.org/10.1026/0012-1924/a000234

Abstract

Zusammenfassung. Das allgemeine Modul des „Mehrdimensionalen Angstinventars für Kinder und Jugendliche“ (MAI-KJ) dient der Messung von dispositioneller Angst (indiziert durch Aufgeregtheit und Besorgnis) und Depression (indiziert durch hohe Traurigkeit und niedrige Freude). Der Aufbau des Fragebogens wird vorgestellt. Überprüft werden Faktorenstruktur, psychometrische Eigenschaften und Validität des Verfahrens. Die Analysen basieren vorwiegend auf 2 Stichproben von Kindern und Jugendlichen der Klassenstufen 3 bis 10 (Stichprobe 1: N = 2 594, Stichprobe 2: N = 7 339). Die angenommene Struktur konnte mittels explorativer und konfirmatorischer Faktorenanalysen bestätigt werden. Struktur und Messeigenschaften des MAI-KJ waren weitgehend invariant gegenüber Geschlecht und Alter der Kinder. Die Reliabilitäten der Skalen fielen zufriedenstellend bis gut aus (Cronbachs α zwischen .70 und .88). Die Stabilitäten erwiesen sich als hoch (Korrelationen zwischen .61 und .76, Zeitabstand: 2 bis 4 Wochen). Zahlreiche Hinweise auf die Validität konnten durch Korrelationen mit Fragebogenverfahren zur Diagnostik von Angst und Depression gewonnen werden.


The Assessment of Anxiety and Depression With the Multidimensional Anxiety Inventory for Children and Adolescents (MAICA)

Abstract. The general module of the Multidimensional Anxiety Inventory for Children and Adolescents (MAICA) is designed to measure dispositional anxiety (indexed by emotionality and worry) and depression (indexed by high dysthymia and low joy). This article describes the construction, the factor structure, the psychometric properties, and the validity of the general module of the MAICA. Analyses are based mainly on two samples of children and adolescents attending class levels 3 – 10 (Sample 1: N = 2,594, Sample 2: N = 7,339). The expected factor structure was substantiated with both exploratory and confirmatory factor analyses, respectively. The structure and the measurement properties of the MAICA proved to be largely invariant with respect to the gender and age of the children. The reliabilities of all subscales were satisfactory (Cronbach’s α between .70 and .88). In addition, all subscales were moderately to highly stable over a period of 2 – 4 weeks (correlations between .61 and .76). Convergent and discriminant validity was established with respect to other anxiety and depression scales.

Literatur

  • American Psychiatric Association (APA). (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed., DSM-5). Washington, DC: APA. First citation in articleCrossref, Google Scholar

  • Anderson, E. R. & Hope, D. A. (2008). A review of the tripartite model for understanding the link between anxiety and depression in youth. Clinical Psychology Review, 28, 275 – 287. https://doi.org/10.1016/j.cpr.2007.05.004 First citation in articleCrossref, Google Scholar

  • Beauducel, A. & Wittmann, W. W. (2005). Simulation study on fit indices in confirmatory factor analysis based on data with slightly distorted simple structure. Structural Equation Modeling: A Multidisciplinary Journal, 12 (1), 41 – 75. https://doi.org/10.1207/s15328007sem1201_3 First citation in articleCrossref, Google Scholar

  • Brodbeck, J., Abbott, R. A., Goodyer, I. M. & Croudace, T. J. (2011). General and specific components of depression and anxiety in an adolescent population. BMC Psychiatry, 11, 191. https://doi.org/10.1186/1471-244X-11-191 First citation in articleCrossref, Google Scholar

  • Chalmers, R. P., Counsell, A. & Flora, D. B. (2016). It might not make a big DIF: Improved differential test functioning statistics that account for sampling variability. Educational and Psychological Measurement, 76 (1), 114 – 140. https://doi.org/10.1177/0013164415584576 First citation in articleCrossref, Google Scholar

  • Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14, 464 – 504. https://doi.org/10.1080/10705510701301834 First citation in articleCrossref, Google Scholar

  • Cheung, G. W. & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9, 233 – 255. https://doi.org/10.1207/S15328007SEM0902_5 First citation in articleCrossref, Google Scholar

  • Clark, L. A. & Watson, D. (1991). Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. Journal of Abnormal Psychology, 100, 316 – 336. https://doi.org/10.1037/0021-843X.100.3.316 First citation in articleCrossref, Google Scholar

  • Costa Jr., P. T., Terracciano, A. & McCrae, R. R. (2001). Gender differences in personality traits across cultures: Robust and surprising findings. Journal of Personality and Social Psychology, 81, 322 – 331. https://doi.org/10.1037//0022-3514.81.2.322 First citation in articleCrossref, Google Scholar

  • Cummings, C. M., Caporino, N. E. & Kendall, P. C. (2014). Comorbidity of anxiety and depression in children and adolescents: 20 years after. Psychological Bulletin, 140, 816 – 845. https://doi.org/10.1037/a0034733 First citation in articleCrossref, Google Scholar

  • Eschenbeck, H., Heim-Dreger, U., Hock, M. & Kohlmann, C.-W. (2019). Mehrdimensionales Angstinventar für Kinder und Jugendliche (MAI-KJ). Manuskript in Vorbereitung. Göttingen: Hogrefe. First citation in articleGoogle Scholar

  • Esser, G., Laucht, M., Drews, S. & Ihle, W. (2013). Depressionstest für Kinder im Grundschulalter (DTGA). Göttingen: Hogrefe. First citation in articleGoogle Scholar

  • Fehm, L. & Fydrich, T. (2011). Prüfungsangst (Fortschritte der Psychotherapie, Band 44). Göttingen: Hogrefe. First citation in articleGoogle Scholar

  • Hofmann, R. J. (1978). Complexity and simplicity as objective indices descriptive of factor solutions. Multivariate Behavioral Research, 13, 247 – 250. https://doi.org/10.1207/s15327906mbr1302_9 First citation in articleCrossref, Google Scholar

  • Hu, L. & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6 (1), 1 – 55. First citation in articleCrossref, Google Scholar

  • Krohne, H. W. (2010). Psychologie der Angst. Stuttgart: Kohlhammer. First citation in articleGoogle Scholar

  • Laux, L., Hock, M., Bergner-Köther, R., Hodapp, V. & Renner, K.-H. (2013). Das State-Trait-Angst-Depressions-Inventar (STADI). Göttingen: Hogrefe. First citation in articleGoogle Scholar

  • Liebert, R. M. & Morris, L. W. (1967). Cognitive and emotional components of test anxiety: A distinction and some initial data. Psychological Reports, 20, 975 – 978. https://doi.org/10.2466/pr0.1967.20.3.975 First citation in articleCrossref, Google Scholar

  • Lonigan, C. J., Phillips, B. M. & Hooe, E. S. (2003). Relations of positive and negative affectivity to anxiety and depression in children: Evidence from a latent variable longitudinal study. Journal of Consulting and Clinical Psychology, 71, 465 – 481. https://doi.org/10.1037/0022-006X.71.3.465 First citation in articleCrossref, Google Scholar

  • McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, NJ: Lawrence Erlbaum Associates. First citation in articleGoogle Scholar

  • Meade, A. W., Johnson, E. C. & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in tests of measurement invariance. Journal of Applied Psychology, 93, 568 – 592. https://doi.org/10.1037/0021-9010.93.3.568 First citation in articleCrossref, Google Scholar

  • Melfsen, S. (1998). Die deutsche Fassung der Social Anxiety Scale for Children – Revised (SASC-R-D): Psychometrische Eigenschaften und Normierung. Diagnostica, 44, 1 – 11. First citation in articleGoogle Scholar

  • Millsap, R. E. & Yun-Tein, J. (2004). Assessing factorial invariance in ordered-categorical measures. Multivariate Behavioral Research, 39, 479 – 515. https://doi.org/10.1207/S15327906MBR3903_4 First citation in articleCrossref, Google Scholar

  • Mineka, S., Watson, D. & Clark, L. A. (1998). Comorbidity of anxiety and unipolar mood disorders. Annual Review of Psychology, 49, 377 – 412. https://doi.org/10.1146/annurev.psych.49.1.377 First citation in articleCrossref, Google Scholar

  • Muthén, B. O. & Asparouhov, T. (2002). Latent variable analysis with categorical outcomes: Multiple-group and growth modeling in Mplus. Verfügbar unter https://www.statmodel.com/download/webnotes/CatMGLong.pdf First citation in articleGoogle Scholar

  • Nolen-Hoeksema, S., Wisco, B. E. & Lyubomirsky, S. (2008). Rethinking rumination. Perspectives on Psychological Science, 3, 400 – 424. https://doi.org/10.1111/j.1745-6924.2008.00088.x First citation in articleCrossref, Google Scholar

  • Plück, J., Döpfner, M. & Lehmkuhl, G. (2000). Internalisierende Auffälligkeiten bei Kindern und Jugendlichen in Deutschland – Ergebnisse der PAK-KID-Studie. Kindheit und Entwicklung, 9, 133 – 142. https://doi.org/10.1026//0942-5403.9.3.133 First citation in articleLink, Google Scholar

  • Ravens-Sieberer, U., Wille, N., Bettge, S. & Erhart, M. (2007). Psychische Gesundheit von Kindern und Jugendlichen in Deutschland: Ergebnisse aus der BELLA-Studie im Kinder- und Jugendgesundheitssurvey (KiGGS). Bundesgesundheitsblatt, 50, 871 – 878. https://doi.org/10.1007/s00103-007-0250-6 First citation in articleCrossref, Google Scholar

  • Renner, K.-H., Hock, M., Bergner-Köther, R. & Laux, L. (2018). Differentiating anxiety and depression: The State-Trait Anxiety-Depression Inventory. Cognition and Emotion, 32, 1409 – 1423. https://doi.org/10.1080/02699931.2016.1266306 First citation in articleCrossref, Google Scholar

  • Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48 (2), 1 – 36. https://doi.org/10.18637/jss.v048.i02 First citation in articleCrossref, Google Scholar

  • Rossmann, P. (2014). Depressionstest für Kinder (DTK-II). Göttingen: Hogrefe. First citation in articleGoogle Scholar

  • Rost, D. H. & Haferkamp, W. (1979). Zur Brauchbarkeit des AFS (Angstfragebogen für Schüler). Zeitschrift für Empirische Pädagogik, 3, 183 – 210. First citation in articleGoogle Scholar

  • Sass, D. A., Schmitt, T. A. & Marsh, H. W. (2014). Evaluating model fit with ordered categorical data within a measurement invariance framework: A comparison of estimators. Structural Equation Modeling: A Multidisciplinary Journal, 21, 167 – 180. https://doi.org/10.1080/10705511.2014.882658 First citation in articleCrossref, Google Scholar

  • Satorra, A. & Bentler, P. M. (2010). Ensuring postiveness of the scaled difference chi-square test statistic. Psychometrika, 75, 243 – 248. https://doi.org/10.1007/s11336-009-9135-y First citation in articleCrossref, Google Scholar

  • Spence, S. H. (2017). Review – Measurement Issues: Assessing anxiety disorders in children and adolescents. Child and Adolescent Mental Health [Vorab-Onlinepublikation] https://doi.org/10.1111/camh.12251 First citation in articleGoogle Scholar

  • Spinath, B. (2005). Akkuratheit der Einschätzung von Schülermerkmalen durch Lehrer und das Konstrukt der diagnostischen Kompetenz. Zeitschrift für Pädagogische Psychologie, 19, 85 – 95. First citation in articleLink, Google Scholar

  • Steiger, J. H. (1980). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87, 245 – 251. https://doi.org/10.1037/0033-2909.87.2.245 First citation in articleCrossref, Google Scholar

  • Steyer, R., Mayer, A., Geiser, C. & Cole, D. A. (2015). A theory of states and traits – revised. Annual Review of Clinical Psychology, 11 (1), 71 – 98. https://doi.org/10.1146/annurev-clinpsy-032813-153719 First citation in articleCrossref, Google Scholar

  • Thurner, F. & Tewes, U. (2000). Kinder-Angst-Test-II (KAT II). Göttingen: Hogrefe. First citation in articleGoogle Scholar

  • Watson, D. (2009). Differentiating the mood and anxiety disorders: A quadripartite model. Annual Review of Clinical Psychology, 5, 221 – 247. https://doi.org/10.1146/annurev.clinpsy.032408.153510 First citation in articleCrossref, Google Scholar

  • Watson, D., Clark, L. A. & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063 – 1070. https://doi.org/10.1037/0022-3514.54.6.1063 First citation in articleCrossref, Google Scholar

  • World Health Organization (WHO). (1993). The ICD-10 classification of mental and behavioural disorders. Diagnostic criteria for research (10th rev.). Genf, Schweiz: WHO. First citation in articleGoogle Scholar

  • Wieczerkowski, W., Nickel, H., Janowski, A., Fittkau, B. & Rauer, W. (1974). Angstfragebogen für Schüler (AFS) (1. Aufl.). Göttingen: Hogrefe. First citation in articleGoogle Scholar

  • Wieczerkowski, W., Nickel, H., Janowski, A., Fittkau, B. & Rauer, W. (1981). Angstfragebogen für Schüler (AFS) (2. Aufl.). Göttingen: Hogrefe. First citation in articleGoogle Scholar

  • Wieczerkowski, W., Nickel, H., Janowski, A., Fittkau, B., Rauer, W. & Petermann, F. (2016). Angstfragebogen für Schüler (AFS) (7., überarb. und norm. Aufl.). Göttingen: Hogrefe. First citation in articleGoogle Scholar

  • Zavaglia, E. & Bergeron, L. (2017). Systematic review of comorbidity between DSM disorders and depression according to age and sex in youth. Canadian Psychology, 58 (2), 124 – 139. https://doi.org/10.1037/cap0000085 First citation in articleCrossref, Google Scholar

  • Zeidner, M. (1998). Test anxiety: The state of the art. New York, NY: Plenum Press. First citation in articleGoogle Scholar