Work

Applications of Latent Growth Mixture Modeling and allied methods to posttraumatic stress response data

Year: 2015

Type: article

Abstract: BackgroundScientific research into mental health outcomes following trauma is undergoing a revolution as scientists refocus their efforts to identify underlying dimensions of health and psychopathology. This effort is in stark contrast to the previous focus which was to characterize individuals based on Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic status (Insel et al., 2010 Insel T., Cuthbert B., Garvey M., Heinssen R., Pine D. S., Quinn K., etal. Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. The American Journal of Psychiatry. 2010; 167(7): 748–751. [PubMed Abstract].[Crossref] , [Google Scholar]). A significant unresolved issue underlying this shift is how to characterize clinically relevant populations without reliance on the categorical definitions provided by the DSM. Classifying individuals based on their pattern of stress adaptation over time holds significant promise for capturing inherent inter-individual heterogeneity as responses including chronicity, recovery, delayed onset, and resilience can only be determined longitudinally (Galatzer-Levy & Bryant, 2013 Galatzer-Levy I. R., Bryant R. A. 636,120 ways to have posttraumatic stress disorder. Perspectives on Psychological Science. 2013; 8(6): 651–662.[Crossref], [Web of Science ®] , [Google Scholar]) and then characterizing these patterns for future research (Depaoli, Van de Schoot, Van Loey, & Sijbrandij, 2015 Depaoli S., Van de Schoot R., Van Loey N., Sijbrandij M. Using Bayesian statistics for modeling PTSD through latent growth mixture modeling: implementation and discussion. European Journal of Psychotraumatology. 2015; 6: 27516. http://dx.doi.org/10.3402/ejpt.v6.27516.[Taylor & Francis Online] , [Google Scholar]). Such an approach allows for the identification of phenominologically similar patterns of response to diverse extreme environmental stressors (Bonanno, Kennedy, Galatzer-Levy, Lude, & Elfstom, 2012 Bonanno G. A., Kennedy P., Galatzer-Levy I. R., Lude P., Elfstom M. L. Trajectories of resilience, depression, and anxiety following spinal cord injury. Rehabilitation Psychology. 2012; 57: 236–247.[Crossref] , [Google Scholar]; Galatzer-Levy & Bonanno, 2012 Galatzer-Levy I. R., Bonanno G. A. Beyond normality in the study of bereavement: Heterogeneity in depression outcomes following loss in older adults. Social Science Medicine. 2012; 74(12): 1987–1994. [PubMed Abstract].[Crossref] , [Google Scholar]; Galatzer-Levy, Brown, et al., 2013 Galatzer-Levy I. R., Brown A. D., Henn-Haase C., Metzler T. J., Neylan T. C., Marmar C. R. Positive and negative emotion prospectively predict trajectories of resilience and distress among high-exposure police officers. Emotion. 2013; 13(3): 545.[Crossref] , [Google Scholar]; Galatzer-Levy, Burton, & Bonanno, 2012 Galatzer-Levy I. R., Burton C. L., Bonanno G. A. Coping flexibility, potentially traumatic life events, and resilience: A prospective study of college student adjustment. Journal of Social and Clinical Psychology. 2012; 31(6): 542–567.[Crossref], [Web of Science ®] , [Google Scholar]) including translational animal models of stress adaptation (Galatzer-Levy, Bonanno, Bush, & LeDoux, 2013 Galatzer-Levy I. R., Bonanno G. A., Bush D. E., LeDoux J. E. Heterogeneity in threat extinction learning: Substantive and methodological considerations for identifying individual difference in response to stress. Frontiers in Behavioral Neuroscience. 2013; 7: 55.[Crossref] , [Google Scholar]; Galatzer-Levy, Moscarello, et al., 2014 Galatzer-Levy I. R., Moscarello J., Blessing E. M., Klein J., Cain C. K., LeDoux J. E. Heterogeneity in signaled active avoidance learning: Substantive and methodological relevance of diversity in instrumental defensive responses to threat cues. Frontiers in Systems Neuroscience. 2014; 8: 179.[Crossref] , [Google Scholar]). The empirical identification of heterogeneous stress response patterns can increase the identification of mechanisms (Galatzer-Levy, Steenkamp, et al., 2014 Galatzer-Levy I. R., Steenkamp M. M., Qian M., Inslicht S., Henn-Haase C., Otte C., etal. Cortisol response to an experimental stress paradigm prospectively predicts long-term distress and resilience trajectories in response to active police service. Journal of Psychiatric Research. 2014; 56: 36–42.[Crossref] , [Google Scholar]), consequences (Galatzer-Levy & Bonanno, 2014 Galatzer-Levy I. R., Bonanno G. A. Optimism and death predicting the course and consequences of depression trajectories in response to heart attack. Psychological Science. 2014; 25: 2177–2188.[Crossref] , [Google Scholar]), treatment effects (Galatzer-Levy, Ankri, et al., 2013 Galatzer-Levy I. R., Ankri Y., Freedman S., Israeli-Shalev Y., Roitman P., Gilad M., etal. Early PTSD symptom trajectories: persistence, recovery, and response to treatment: results from the Jerusalem trauma outreach and prevention study (J-TOPS). PLoS One. 2013; 8(8): e70084.[Crossref] , [Google Scholar]), and prediction (Galatzer-Levy, Karstoft, Statnikov, & Shalev, 2014 Galatzer-Levy I. R., Karstoft K.-I., Statnikov A., Shalev A. Y. Quantitative forecasting of PTSD from early trauma responses: A machine learning application. Journal of Psychiatric Research. 2014; 59: 68–76.[Crossref] , [Google Scholar]) of individual differences in response to trauma.MethodMethodological and theoretical considerations for the application of Latent Growth Mixture Modeling (LGMM) and allied methods such as Latent Class Growth Analysis (LCGA) for the identification of heterogeneous populations defined by their pattern of change over time will be presented (Van De Schoot, 2015 Van de Schoot R. Latent trajectory studies: The basics, how to interpret the results and what to report. European Journal of Psychotraumatology. 2015; 6: 27514. http://dx.doi.org/10.3402/ejpt.v6.27514.[Taylor & Francis Online] , [Google Scholar]). Common pitfalls including non-identification, over identification, and issues related to model specification will be discussed as well as the benefits of applying such methods along with the theoretical grounding of such approaches.ConclusionsLGMM and allied methods have significant potential for improving the science of stress pathology as well as our understanding of healthy adaptation (resilience).

Source: European Journal of Psychotraumatology

DOI: 10.3402/ejpt.v6.27515

Author: Isaac R. Galatzer-Levy

Institutions: NYU Langone Health, New York University

Language: English

Topic: Posttraumatic Stress Disorder Research

Subfield: Clinical Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,704