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The diagnostic criteria for posttraumatic stress disorder (PTSD) in the DSM-5 have become the most inherently complex to date, with 20 possible symptoms, four factors (with some studies recommending seven factors), and 636,120 different symptom combinations (Armour et al., 2016; Galatzer-Levy & Bryant, 2013). In addition to this complexity and heterogeneity, issues of comorbidity have become more common with PTSD than with any other psychiatric disorder (Koenen et al., 2008). For example, approximately half of those with PTSD have a comorbid diagnosis of a depressive disorder (Elhai et al., 2008; Flory & Yehuda, 2015). This diagnostic murkiness raises sobering questions, ranging from the internal coherence, structure, and dimensionality of PTSD to broader nosological issues regarding the logic and methods by which psychiatric disorders are identified, differentiated, and classified. Many categorical diagnostic criteria were constructed to maximize clinical utility. Nevertheless, their relative utility for other research applications, including theory-building; measurement; nosology; and investigations into the etiology, clinical course of, and discriminability between diagnostic constructs, remain questionable as diagnostic classifications often do little to “carve nature at the joints” (Zachar & Kendler, 2017). The release of both DSM-5-TR and ICD-11 this year, including the introduction of a new prolonged grief disorder (PGD) in each, underscores the need to clarify clinically important distinctions between related diagnostic entities (e.g., PTSD vs. PGD), as well as to ensure that their internal structures (i.e., dimensionality) and resulting complexity (think diagnostic permutations) does not expand beyond what is truly useful.

The original intent of the DSM-III (APA, 1980) was to serve as a “best effort” in indicating clinically useful diagnostic criteria of what a psychiatric disorder may include rather than an “ultimate authority” of what a disorder is (Andreasen, 2007). Nevertheless, the aim of measuring what is in the DSM, rather than what a psychiatric disorder may be, has seemingly become standard research practice (Berenbaum, 2013).

Measures of mental illness have increasingly utilized a one-to-one ratio of test items to DSM symptoms – meaning for every DSM symptom there is one “best performing” test item. Although this is the intended construction of screening measures, and measures like these do well to identify the possible presence of DSM disorders, they have become commonly used beyond their intended scope when employed to measure psychopathology in a broad range of research contexts—an apparently commonplace practice. For example, a 2004 survey of members of a major trauma society indicated that the PTSD Checklist (PCL) was administered over seven times more in the previous year for research purposes (n = 10,785) than for clinical purposes (n = 1,483; Elhai et al., 2005). This heavy reliance in research on measures specifically designed to maximize clinical utility may be worrisome, as the meaning of any subsequent research findings relies on the assumption that the content and organization of these 1:1 measures necessarily and sufficiently describes what PTSD is, “carves PTSD at its joints,” which was not the intended purpose of many of these measures.

Alternative multidimensional measures that extend beyond traditional DSM symptoms, as well as improved research methods that extend beyond variable-centered statistical approaches like confirmatory factor analysis, are both needed to produce more meaningful diagnostic constructs. To be truly useful for applied clinical research applications, the resulting measures should be capable of describing both the individual’s phenomenological experience as well as contextual variables that surround and inform those experiences (i.e., person and variable-centered approaches). Put another way, research methods that prioritize finding out what diagnostic constructs could be, and that seek out meaningful distinctions between dimensions within constructs and distinctions between constructs, carry considerable promise for advancing the field. By drawing distinctions that make a difference (i.e., carving nature at its joints), such methods could help to improve classifications of psychopathology, reduce comorbidity, and reduce within-construct heterogeneity. Because they are not wedded to 1:1 ratios of symptoms to test items, they also hold promise for increasing construct and content validity by more wholly characterizing individuals’ varying experiences across multiple domains and identifying cultural, developmental, and other contextually dependent features.

One of these alternative classification methods is the Hierarchical Taxonomy of Psychopathology (HiTOP; Conway et al., 2019; Kotov et al., 2017). The HiTOP model organizes psychopathology on a dimensional hierarchy of lower-order traits and symptoms, middle-order syndromes and disorders, and higher-order classifications of disorders (Conway et al., 2019; Kotov et al., 2017). Although it has not become standard practice, the HiTOP model carries promise in clinical research and practice as an alternative method for conceptualizing psychopathology. Although HiTOP describes the theoretical and practical benefits of hierarchical organizations well, it does not adequately describe how to implement such a model, particularly as it relates to trauma- and stressor-related disorders.

The Middle-Out Approach is first presented here as a new analytical and organizational method that compliments existing models like the HiTOP model and network theories of psychopathology that can be applied to trauma- and stressor-related disorders (Borsboom, 2017; Conway et al., 2019). Middle-Out is a term borrowed from computer programming practices (and HBO’s “Silicon Valley”) to describe a form of error checking. Rather than searching for errors from the beginning or ending of code, programmers can start their search from the middle and work their way out in both directions, thereby improving efficiency. Within psychology, the Middle-Out Approach would implement a more efficient and integrative method than either previous top down (person-centered) or bottom-up (variable-centered) analytical approaches used alone.

Middle-Out does not present new methods, but rather, a new approach to organizing existing methods. This organization reduces latent constructs to unique middle-order phenotypes that describe what an individual is experiencing following trauma and then differentiates these experiences from others. Phenotypes are key to improved measurements and classifications of traumatic stress, as they describe clinically meaningful experiences by restricting the number of latent indicators to those that uniquely and parsimoniously comprise the phenotype (see Bollen, 2002's concept of local independence). Phenotypic indicators can include contextual variables, unique etiologies, cultural nuances, gender and racial nuances, mediators/moderators, treatment/health outcomes, functional limitations, causal relationships, etc. that help describe what this outcome looks like, thereby describing what is fundamental to the experience of traumatic stress. Within the Middle-Out Approach, people are analyzed first and associated factors second, rather than the other way around, which is often traditional practice. Using Middle-Out, the researcher casts a broad multidimensional and multiculturally sensitive net of measures/items, identifies potentially unobserved latent constructs based on people’s experiences, and then works backwards to identify which lower-order items are most salient to unique phenotypes. This method works to identify and differentiate heterogeneous and complex outcomes that are particularly vexing to traumatic stress research. Alternative theoretical and methodological conceptualizations like this have the potential to identify meaningful subtypes and specifiers of traumatic stress that could improve clinically useful diagnostic classifications and result in improved psychodiagnostic assessment and treatment efficacy among heterogeneous and diverse populations of trauma survivors.

About the Theoretical Concepts and Mechanisms of Traumatic Stress (TCM) SIG

The mission of the Theoretical Concepts and Mechanisms of Traumatic Stress (TCM) SIG is to advance theoretical knowledge concerning both the nature of diagnostic constructs, such as PTSD, as well as factors theorized to influence their causal origin, causal pathways, naturalistic course, causal consequences, and response to intervention. If you have an interest in joining us and in discussing prospects for collaboration, please feel free to contact us.

How to Join This SIG

If you are interested in joining the TCM SIG:

  1. Log in and go to your ISTSS member profile.
  2. Go to the Listserves/Communities tab and select the SIGs you want to join from the dropdown.
  3. Scroll down and click “next,” then “save changes.”

About the Authors

Shane W. Adams is the Student Co-Chair of the TCM SIG. He is a PhD candidate in clinical psychology at John Jay College of the City University of New York, current extern of the Program for Anxiety and Traumatic Stress Studies at Weill Cornell Medicine and New York Presbyterian, and will be a 2022-23 intern at the Palo Alto VA. The opinions in this article reflect his own and not these institutions.

Christopher M. Layne is Co-Chair of the TCM SIG and of the Traumatic Loss and Grief SIG. He is an Associate Professor of Psychology, Department of Clinical and School Psychology, and Director, Child and Adolescent Traumatic Stress Program (CATSP) Specialty Clinic, at Nova Southeastern University. He is also a Research Psychologist and Principal Investigator of the NCTSN Category II National Child Trauma Workforce Institute at the UCCS Lyda Hill Institute for Human Resilience. 


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