Has growth mixture modeling improved our understanding of how early change predicts psychotherapy outcome?

References

• Aderka, I. M., Nickerson, A., Bøe, H. J., & Hofmann, S. G. (2012). Sudden gains during psychological treatments of anxiety and depression: A meta-analysis. Journal of Consulting and Clinical Psychology, 80, 93–101. doi:10.1037/a0026455
   PubMed Web of Science ®Google Scholar
• Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52, 317–332. doi:10.1007/BF02294359
   Web of Science ®Google Scholar
• American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text revision). Washington, DC: Author.
   Google Scholar
• Barkham, M., Connell, J., Stiles, W. B., Miles, J. N. V., Margison, F., Evans, C., & Mellor-Clark, J. (2006). Dose-effect relations and responsive regulation of treatment duration: The good enough level. Journal of Consulting and Clinical Psychology, 74, 160–167. doi:10.1037/0022-006X.74.1.160
   PubMed Web of Science ®Google Scholar
• Beck, A. T., Ward, C. H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4, 561–571. doi:10.1001/archpsyc.1961.01710120031004
   PubMed Web of Science ®Google Scholar
• Cahill, J., Barkham, M., Stiles, W. B., Twigg, E., Rees, A., Hardy, G. E., & Evans, C. (2006). Convergent validity of the CORE measures with measures of depression for clients in brief cognitive therapy for depression. Journal of Counseling Psychology, 53, 253–259. doi:10.1037/0022-0167.53.2.253
   Web of Science ®Google Scholar
• Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427–431. doi:10.1080/01621459.1979.10482531
   Web of Science ®Google Scholar
• Flückiger, C., Regli, D., Zwahlen, D., Hostettler, S., & Caspar, F. (2010). Der Berner Patienten- und Therapeutenstundenbogen/The Bern Patient and Therapist Session Report. Zeitschrift für klinische Psychologie und Psychotherapie, 39, 71–79. doi:10.1026/1616-3443/a000015.
   Web of Science ®Google Scholar
• Haas, E., Hill, R. D., Lambert, M. J., & Morrell, B. (2002). Do early responders to psychotherapy maintain treatment gains?Journal of Clinical Psychology, 58, 1157–1172. doi:10.1002/jclp.10044
   PubMed Web of Science ®Google Scholar
• Hardy, G. E., Cahill, J., Stiles, W. B., Ispan, C., Macaskill, N., & Barkham, M. (2005). Sudden gains in cognitive therapy for depression: A replication and extension. Journal of Consulting and Clinical Psychology, 73, 59–67. doi:10.1037/0022-006X.73.1.59
   PubMed Web of Science ®Google Scholar
• Hautzinger, M. (2003). Kognitive Verhaltenstherapie bei Depressionen/Cognitive behavior therapy for depression (6th ed.). Weinheim: Beltz.
   Google Scholar
• Im, K. S., Peseran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115, 53–74. doi:10.1016/S0304-4076(03)00092-7
   Web of Science ®Google Scholar
• Jacobson, N. S., & Truax, P. (1991). Clinical significance: A statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59, 12–19. doi:10.1037/0022-006X.59.1.12
   PubMed Web of Science ®Google Scholar
• Keller, F., & Hautzinger, M. (2007). Klassifikation von Verlaufskurven in der Depressionsbehandlung. Ein methodischer Beitrag/Classification of change processes in depression treatment. Zeitschrift für klinische Psychologie und Psychotherapie, 36, 83–92. doi:10.1026/1616-3443.36.2.83
   Web of Science ®Google Scholar
• Kopta, S. M., Howard, K. I., Lowry, J. L., & Beutler, L. E. (1994). Patterns of symptomatic recovery in psychotherapy. Journal of Consulting and Clinical Psychology, 62, 1009–1016. doi:10.1037/0022-006X.62.5.1009
   PubMed Web of Science ®Google Scholar
• Kopta, S. M., & Lowry, J. L. (2002). Psychometric evaluation of the Behavioral Health Questionnaire-20: A brief instrument for assessing global mental health and the three phases of psychotherapy outcome. Psychotherapy Research, 12, 413–426. doi:10.1093/ptr/12.4.413
   Web of Science ®Google Scholar
• Kuljanin, G., Braun, M. T., & DeShon, R. P. (2011). A cautionary note on modeling growth trends in longitudinal data. Psychological Methods, 16, 249–264. doi:10.1037/a0023348
   PubMed Web of Science ®Google Scholar
• Lambert, M. J., Hansen, N. B., Umphress, V., Lunnen, K., Okiishi, J., Burlingame, G., … Reisinger, C. W. (1996). Administration and scoring manual for the Outcome Questionnaire (OQ 45.2). Wilmington, DE: American Professional Credentialing Services.
   Google Scholar
• Lambert, M. J., Hatfield, D. R., Vermeersch, D. A., & Burlingame, G. M. (2001). Administration and scoring manual for the life status questionnaire (LSQ) [draft version]. Orem, UT: American Professional Credentialing Services, LLC.
   Google Scholar
• Liu, M., & Hancock, G. R. (2014). Unrestricted mixture models for class identification in growth mixture modeling. Educational and Psychological Measurement, 74, 557–584. doi:10.1177/0013164413519798
   Web of Science ®Google Scholar
• Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767–778. doi: 10.1093/biomet/88.3.767
   Web of Science ®Google Scholar
• Lutz, W., Ehrlich, T., Rubel, J., Hallwachs, N., Röttiger, M.-A., Jorasz, C., … Tschitsaz-Stucki, A. (2013). The ups and downs of psychotherapy: Sudden gains and sudden losses identified with session reports. Psychotherapy Research, 23, 14–24. doi:10.1080/10503307.2012.693837
   PubMed Web of Science ®Google Scholar
• Lutz, W., Hofmann, S. G., Rubel, J., Boswell, J. F., Shear, M. K., Gorman, J. M., … Barlow, D. H. (2014). Patterns of early change and their relationship to outcome and early treatment termination in patients with panic disorder. Journal of Consulting and Clinical Psychology, 82, 287–297. doi:10.137/a0035535
   PubMed Web of Science ®Google Scholar
• Lutz, W., Stulz, N., & Köck, K. (2009). Patterns of early change and their relationship to outcome and follow-up among patients with major depressive disorders. Journal of Affective Disorders, 118, 60–68. doi:10.1016/j.jad.2009.01.019
   PubMed Web of Science ®Google Scholar
• Lutz, W., Stulz, N., Smart, D. W., & Lambert, M. J. (2007). Die Identifikation früher Veränderungsmuster in der ambulanten Psychotherapie/Patterns of early change in outpatient therapy. Zeitschrift für klinische Psychologie und Psychotherapie, 36, 93–104. doi:10.1026/1616-3443.36.2.93
   Web of Science ®Google Scholar
• Lutz, W., & Tschitsaz, A. (2007). Plötzliche Gewinne und Verluste im Behandlungsverlauf von Angststörungen, depressiven und komorbiden Störungen/Sudden Gains and Losses in the treatment of patients with anxiety, depressive and comorbid disorders. Zeitschrift für klinische Psychologie und Psychotherapie, 36, 298–308. doi:10.1026/1616-3443.36.4.298
   Web of Science ®Google Scholar
• McLachlan, G., & Peel, D. (2000). Finite mixture models. New York, NY: Wiley.
   Google Scholar
• Muthén, B. (2003). Statistical and substantive checking in growth mixture modeling: Comment on Bauer and Curran (2003). Psychological Methods, 8, 369–377. doi:10.1037/1082-989X.8.3.369
   PubMed Web of Science ®Google Scholar
• Muthén, B., & Asparouhov, T. (2015). Growth mixture modeling with non-normal distributions. Statistics in Medicine, 34, 1041–1058. doi: 10.1002/sim.6388.
   PubMed Web of Science ®Google Scholar
• Muthén, B. (2001). Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class-latent growth modeling. In L. M. Collins&A. G. Sawyers (Eds.), New methods for the analysis of change (pp. 291–322). Washington, DC: American Psychological Association.
   Google Scholar
• Muthén, L. K., & Muthén, B. O. (1998–2015). MPlus user’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.
   Google Scholar
• Nagin, D. S. (1999). Analyzing developmental trajectories: A semiparametric, group-based approach. Psychological Methods, 4, 139–157. doi:10.1037/1082-989X.4.2.139
   Web of Science ®Google Scholar
• 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: A Multidisciplinary Journal, 14, 535–569. doi:10.1080/10705510701575396
   Web of Science ®Google Scholar
• Peugh, J., & Fan, X. (2015). Enumeration index performance in generalized growth mixture models: A Monte Carlo test of Muthén’s (2003) hypothesis. Structural Equation Modeling: A Multidisciplinary Journal, 22, 115–131. doi:10.1080/10705511.2014.919823
   Web of Science ®Google Scholar
• Ramaswamy, V., DeSabro, W., Reibstein, D., & Robinson, W. (1993). An empirical pooling approach for estimating marketing mix elasticities with PIM data. Marketing Science, 12, 103–124. doi:10.1287/mksc.12.1.103
   Web of Science ®Google Scholar
• Rubel, J., Lutz, W., Kopta, S. M., Köck, K., Minami, T., Zimmermann, D., & Saunders, S. M. (2015). Defining early positive response to psychotherapy: An empirical comparison between significant change criteria and growth mixture modeling. Psychological Assessment, 27, 478–488. doi:10.1037/pas0000060
   PubMed Web of Science ®Google Scholar
• Rubel, J., Lutz, W., & Schulte, D. (2015). Patterns of change in different phases of outpatient psychotherapy: A stage-sequential pattern analysis of change in session reports. Clinical Psychology and Psychotherapy, 22, 1–14. doi:10.1002/cpp.1868
   PubMed Web of Science ®Google Scholar
• Schwarz, G. (1978). Estimating dimensions of a model. The Annals of Statistics, 6, 461–464. doi:10.1214/aos/1176344136
   Web of Science ®Google Scholar
• Shear, M. K., Brown, T. A., Barlow, D. H., Money, R., Sholomskas, D. E., Woods, S. W., … Papp, L. A. (1997). Multicenter collaborative panic disorder severity scale. American Journal of Psychiatry, 154, 1571–1575. doi:10.1176/ajp.154.11.1571
   PubMed Web of Science ®Google Scholar
• Shimokawa, K., Lambert, M. J., & Smart, D. W. (2010). Enhancing treatment outcome of patients at risk of treatment failure: Meta-analytic and mega-analytic review of a psychotherapy quality assurance system. Journal of Consulting and Clinical Psychology, 78, 298–311. doi:10.1037/a0019247
   PubMed Web of Science ®Google Scholar
• Stulz, N., Lutz, W., Leach, C., Lucock, M., & Barkham, M. (2007). Shapes of early change in psychotherapy under routine outpatient conditions. Journal of Consulting and Clinical Psychology, 75, 864–874. doi:10.1037/002-006X.75.6.864
   PubMed Web of Science ®Google Scholar
• Swift, J. K., & Greenberg, R. P. (2012). Premature discontinuation in adult psychotherapy: A meta-analysis. Journal of Consulting and Clinical Psychology, 80, 547–559. doi:10.1037/a0028226
   PubMed Web of Science ®Google Scholar
• Theodossiou, P. (1998). Financial data and the skewed generalized t distribution. Management Science, 44, 1650–1661. doi:10.1287/mnsc.44.12.1650
   Web of Science ®Google Scholar
• Thomas, C., & Persons, J. B. (2013). Sudden gains can occur in psychotherapy even when the pattern of change is gradual. Clinical Psychology: Science and Practice, 20, 127–142. doi:10.1111/cpsp.12029
   Web of Science ®Google Scholar
• Vermeersch, D. A., Whipple, J. L., Lambert, M. J., Hawkins, E. J., Burchfield, C. M., & Okiishi, J. C. (2004). Outcome Questionnaire: Is it sensitive to changes in counseling center clients?. Journal of Counseling Psychology, 51, 38–49. doi:10.1037/0022-0167.51.1.38.
   Web of Science ®Google Scholar
• Wampold, B. E., & Imel, Z. E. (2015). The great psychotherapy debate: The evidence for what makes psychotherapy work (2d ed.). New York, NY: Routledge.
   Google Scholar