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Longitudinal investigation of anxiety sensitivity growth trajectories and relations with anxiety and depression symptoms in adolescence

  • Nicholas P. Allan (a1), Julia W. Felton (a2), Carl W. Lejuez (a2), Laura MacPherson (a2) and Norman B. Schmidt (a1)...

Abstract

Anxiety sensitivity (AS), the belief that anxious arousal is harmful, is a malleable risk factor that has been implicated in anxiety and depression symptoms in adolescents. Although there is some evidence that adolescents possess distinct developmental trajectories, few studies have explored this topic. This study examined the developmental trajectory of AS in 248 adolescents (M age = 11.0 years, SD = 0.82; 56% male) across 6 years, beginning when children were age 11. This study also examined the influence of AS trajectories on anxiety and depression at age 16. Finally, this study examined the utility of AS classes in identifying anxiety and depression growth. Three AS classes were found, described by normative-stable, high-stable, and high-unstable trajectories. Adolescents in the high-stable and the high-unstable AS classes had higher levels of anxiety and depression at age 16 than did adolescents in the normative-stable AS class. In addition, the anxiety and depression trajectories fit by AS class mirrored the AS class trajectories. These findings suggest three AS trajectories can be identified in adolescents. These trajectories are discussed in relation to a developmental perspective of AS.

Copyright

Corresponding author

Address correspondence and reprint requests to: Nicholas P. Allan or Norman B. Schmidt, Department of Psychology, Florida State University, P.O. Box 3064301, Tallahassee, FL 32306–4301; E-mail: allan@psy.fsu.edu or schmidt@psy.fsu.edu.

References

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Allan, N. P., Capron, D. W., Lejuez, C. W., Reynolds, E. K., MacPherson, L., & Schmidt, N. B. (2014). Developmental trajectories of anxiety symptoms in early adolescence: The influence of anxiety sensitivity. Journal of Abnormal Child Psychology, 42, 589600.
Allan, N. P., Korte, K. J., Capron, D. M., Raines, A. M., & Schmidt, N. B. (2014). Factor mixture modeling of anxiety sensitivity: A three-class structure. Psychological Assessment, 26, 11841195.
Allan, N. P., MacPherson, L., Young, K. C., Lejuez, C. W., & Schmidt, N. B. (2014). Examining the latent structure of anxiety sensitivity in adolescents using factor mixture modeling. Psychological Assessment, 26, 741751.
Allan, N. P., Raines, A. M., Capron, D. W., Norr, A. M., Zvolensky, M. J., & Schmidt, N. B. (2014). Identification of anxiety sensitivity classes and clinical cut-scores: Results from a factor mixture model. Journal of Anxiety Disorders, 28, 696703.
Bakk, Z., & Vermunt, J. K. (2015). Robustness of stepwise latent class modeling with continuous distal outcomes. Structural Equation Modeling. Advance online publication. doi:10.1080/10705511.2014.955104
Bauer, D. J., & Curran, P. J. (2004). The integration of continuous and discrete latent variable models: Potential problems and promising opportunities. Psychological Methods, 9, 329.
Bernstein, A., Stickle, T. R., & Schmidt, N. B. (2013). Factor mixture model of anxiety sensitivity and anxiety psychopathology vulnerability. Journal of Affective Disorders, 149, 406417.
Bernstein, A., Stickle, T. R., Zvolensky, M. J., Taylor, S., Abramowitz, J., & Stewart, S. (2010). Dimensional, categorical, or dimensional-categories: Testing the latent structure of anxiety sensitivity among adults using factor-mixture modeling. Behavior Therapy, 41, 515529.
Bolck, A., Croon, M. A., & Hagenaars, J. A. (2004). Estimating latent structure models with categorical variables: One-step versus three-step estimators. Political Analysis, 12, 327.
Broman-Fulks, J. J., & Storey, K. M. (2008). Evaluation of a brief aerobic exercise intervention for high anxiety sensitivity. Anxiety, Stress, and Coping, 21, 117128.
Chorpita, B. F., Moffitt, C. E., & Gray, J. (2005). Psychometric properties of the Revised Child Anxiety and Depression Scale in a clinical sample. Behaviour Research and Therapy, 43, 309322.
Chorpita, B. F., Yim, L., Moffitt, C., Umemoto, L. A., & Francis, S. E. (2000). Assessment of symptoms of DSM-IV anxiety and depression in children: A revised child anxiety and depression scale. Behaviour Research and Therapy, 38, 835855.
Crocetti, E., Klimstra, T., Keijsers, L., Hale III, W. W., & Meeus, W. (2009). Anxiety trajectories and identity development in adolescence: A five-wave longitudinal study. Journal of Youth and Adolescence, 38, 839849.
Ebesutani, C., Bernstein, A., Nakamura, B. J., Chorpita, B. F., & Weisz, J. R. (2010). A psychometric analysis of the Revised Child Anxiety and Depression Scale—Parent version in a clinical sample. Journal of Abnormal Child Psychology, 38, 249260.
Ebesutani, C., Okamura, K., Higa-McMillan, C., & Chorpita, B. F. (2011). A psychometric analysis of the Positive and Negative Affect Schedule for Children—Parent version in a school sample. Psychological Assessment, 23, 406416.
Ebesutani, C., Reise, S. P., Chorpita, B. F., Ale, C., Regan, J., Young, J., et al. (2012). The Revised Child Anxiety and Depression Scale—Short version: Scale reduction via exploratory bifactor modeling of the broad anxiety factor. Psychological Assessment, 24, 833845.
Feng, X., Shaw, D. S., & Silk, J. S. (2008). Developmental trajectories of anxiety symptoms among boys across early and middle childhood. Journal of Abnormal Psychology, 117, 3247.
Grant, D. M., Beck, J. G., & Davila, J. (2007). Does anxiety sensitivity predict symptoms of panic, depression, and social anxiety? Behaviour Research and Therapy, 45, 22472255.
Henson, J. M., Reise, S. P., & Kim, K. H. (2007). Detecting mixtures from structural model differences using latent variable mixture modeling: A comparison of relative model fit statistics. Structural Equation Modeling, 14, 202226.
Holsen, I., Kraft, P., & Vittersø, J. (2000). Stability in depressed mood in adolescence: Results from a 6-year longitudinal panel study. Journal of Youth and Adolescence, 1, 6178.
Jung, T., & Wickrama, K. A. S. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2, 302317.
Kessler, R. C., Chiu, W. T., Demler, O., & Walters, E. E. (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 617627.
Last, C. G., Perrin, S., Hersen, M., & Kazdin, A. E. (1996). A prospective study of childhood anxiety disorders. Journal of the American Academy of Child & Adolescent Psychiatry, 35, 15021510.
Li, F., Cohen, A. S., Kim, S. H., & Cho, S. J. (2009). Model selection methods for mixture dichotomous IRT models. Applied Psychological Measurement, 33, 353373.
Lubke, G., & Muthén, B. O. (2007). Performance of factor mixture models as a function of model size, covariate effects, and class-specific parameters. Structural Equation Modeling, 14, 2647.
McLachlan, G. J. (1987). On bootstrapping the likelihood ratio test statistic for the number of components in a normal mixture. Applied Statistics, 36, 318324.
McLaughlin, K. A., & Hatzenbuehler, M. L. (2009). Stressful life events, anxiety sensitivity, and internalizing symptoms in adolescents. Journal of Abnormal Psychology, 77, 659669.
Merikangas, K. R., He, J., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., et al. (2010). Lifetime prevalence of mental disorders in U.S. adolescents: Results from the National Comorbidity Survey Replication—Adolescent supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry, 49, 980989.
Morin, A. J., Maïano, C., Nagengast, B., Marsh, H. W., Morizot, J., & Janosz, M. (2011). General growth mixture analysis of adolescents’ developmental trajectories of anxiety: The impact of untested invariance assumptions on substantive interpretations. Structural Equation Modeling, 18, 613648.
Muris, P., Schmidt, H., Merckelbach, H., & Schouten, E. (2001). Anxiety sensitivity in adolescents: Factor structure and relationships to trait anxiety and symptoms of anxiety disorders and depression. Behaviour Research and Therapy, 39, 89100.
Muthén, B. O., & Muthén, L. K. (1998–2012). Mplus (Version 7.3) [Computer software]. Los Angeles: Author.
Muthén, B. O., & Muthén, L. K. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and Experimental Research, 24, 882891.
Nagin, D. S., & Odgers, C. L. (2010). Group-based trajectory modeling in clinical research. Annual Review of Clinical Psychology, 6, 109138.
Naragon-Gainey, K. (2010). Meta-analysis of the relations of anxiety sensitivity to the depressive and anxiety disorders. Psychological Bulletin, 136, 128150.
Newman, D. L., Moffitt, T. E., Caspi, A., Magdol, L., Silva, P. A., & Stanton, W. R. (1996). Psychiatric disorder in a birth cohort of young adults: Prevalence, comorbidity, clinical significance, and new case incidence from ages 11 to 21. Journal of Consulting and Clinical Psychology, 64, 552562.
Noël, V. A., & Francis, S. E. (2011). A meta-analytic review of the role of child anxiety sensitivity in child anxiety. Journal of Abnormal Child Psychology, 39, 721733.
Norr, A. M., Allan, N. P., Macatee, R. J., Keough, M. E., & Schmidt, N. B. (2014). The effects of an anxiety sensitivity intervention on anxiety, depression, and worry: Mediation through affect tolerances. Behaviour Research and Therapy, 59, 1219.
Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14, 535569.
Olatunji, B. O., & Cole, D. A. (2009). The longitudinal structure of general and specific anxiety dimensions in children: Testing a latent trait-state-occasion model. Psychological Assessment, 21, 412421.
Olatunji, B. O., & Wolitzky-Taylor, K. B. (2009). Anxiety sensitivity and the anxiety disorders: A meta-analytic review and synthesis. Psychological Bulletin, 135, 974999.
Rabian, B., Embry, L., & MacIntyre, D. (1999). Behavioral validation of the Childhood Anxiety Sensitivity Index in children. Journal of Clinical Child Psychology, 28, 105112.
Reiss, S. (1991). Expectancy model of fear, anxiety, and panic. Clinical Psychology Review, 11, 141153.
Reiss, S., & Havercamp, S. (1996). The sensitivity theory of motivation: Implications for psychopathology. Behaviour Research and Therapy, 34, 621632.
Robertson, R., & Combs, A. (Eds.). (1995). Chaos theory in psychology and the life sciences. Mahwah, NJ: Erlbaum.
Schmidt, N. B., Capron, D. W., Raines, A. M., & Allan, N. P. (2014). Development and randomized clinical trial evaluating the efficacy of a brief intervention targeting cognitive anxiety sensitivity. Journal of Consulting and Clinical Psychology, 82, 10231033.
Schmidt, N. B., Eggleston, A. M., Woolaway-Bickel, K., Fitzpatrick, K. K., Vasey, M. W., & Richey, J. A. (2007). Anxiety Sensitivity Amelioration Training (ASAT): A longitudinal primary prevention program targeting cognitive vulnerability. Journal of Anxiety Disorders, 21, 302319.
Schmidt, N. B., Kotov, R., Lerew, D. R., Joiner, T. E., & Ialongo, N. S. (2005). Evaluating latent discontinuity in cognitive vulnerability to panic: A taxometric investigation. Cognitive Therapy and Research, 29, 673690.
Schmidt, N. B., Zvolensky, M. J., & Maner, J. K. (2006). Anxiety sensitivity: Prospective prediction of panic attacks and Axis I pathology. Journal of Psychiatric Research, 40, 691699.
Silverman, W. K., Fleisig, W., Rabian, B., & Peterson, R. A. (1991). Childhood anxiety sensitivity index. Journal of Clinical Child and Adolescent Psychology, 20, 162168.
Stein, M. B., Jang, K. L., & Livesley, W. J. (1999). Heritability of anxiety sensitivity: A twin study. American Journal of Psychiatry, 156, 246251.
Sterba, S. K., Prinstein, M. J., & Cox, M. J. (2007). Trajectories of internalizing problems across childhood: Heterogeneity, external validity, and gender differences. Development and Psychopathology, 19, 345366.
Tofighi, D., & Enders, C. K. (2008). Identifying the correct number of classes in a growth mixture model. In Hancock, G. R. (Ed.), Mixture models in latent variable research (pp. 317341). Greenwich, CT: Information Age.
Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18, 450469.
Watson, D. (2005). Rethinking the mood and anxiety disorders: A quantitative hierarchical model for DSM-V. Journal of Abnormal Psychology, 114, 522536.
Weems, C. F. (2008). Developmental trajectories of childhood anxiety: Identifying continuity and change in anxious emotion. Developmental Review, 28, 488502.
Weems, C. F., & Graham, R. A. (2014). Resilience and trajectories of posttraumatic stress among youth exposed to disaster. Journal of Child and Adolescent Psychopharmacology, 24, 28.
Weems, C. F., Hammond-Laurence, K., Silverman, W. K., & Ginsburg, G. S. (1998). Testing the utility of the anxiety sensitivity construct in children and adolescents referred for anxiety disorders. Journal of Clinical Child Psychology, 27, 6977.
Weems, C. F., Hayward, C., Killen, J., & Taylor, C. B. (2002). A longitudinal investigation of anxiety sensitivity in adolescence. Journal of Abnormal Psychology, 111, 471477.
Zavos, H., Rijsdijk, F. V., & Eley, T. C. (2012). A longitudinal genetically informative, study of associations between anxiety sensitivity, anxiety and depression. Behavioral Genetics, 42, 592602.
Zavos, H., Rijsdijk, F. V., Gregory, A. M., & Eley, T. C. (2010). Genetic influences on the cognitive biases associated with anxiety and depression symptoms in adolescents. Journal of Affective Disorders, 124, 4553.
Zinbarg, R. E., Barlow, D. H., & Brown, T. A. (1997). Hierarchical structure and general factor saturation of the Anxiety Sensitivity Index: Evidence and implications. Psychological Assessment, 9, 277284.

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