The class-dimensional structure of PTSD before and after deployment to Iraq: Evidence from direct comparison of dimensional, categorical, and hybrid models

Assessing posttraumatic stress disorder symptom clusters with the Minnesota Multiphasic Personality Inventory-3 in a forensic disability sample

OBJECTIVE

Previous evidence indicates that scales from the Minnesota Multiphasic Personality Inventory (MMPI) family of instruments can measure self-reported posttraumatic stress disorder (PTSD) symptomology and differentiate symptom clusters, including in forensic disability assessments. However, limited research has examined assessment of PTSD symptoms with the MMPI-3, the most recent MMPI instrument. The goal of the current study was to identify the strongest MMPI-3 scale predictors of individual PTSD symptom clusters, measured via self-report.

METHODS

Using a sample of 716 disability claimants (54.2% men; Mage  = 42.98, SD = 10.87; 81.8% White), correlation, regression, and dominance analyses were performed to examine associations between scores on MMPI-3 scales and latent PTSD symptom cluster factors derived using confirmatory factor analyses from items of the Detailed Assessment of Posttraumatic Stress (DAPS), and to identify the strongest predictor of each symptom cluster when MMPI-3 scales were concurrently considered.

RESULTS

Results indicate that conceptually expected MMPI-3 scale scores were meaningfully associated with PTSD symptom cluster factors, with the MMPI-3 Anxiety-Related Experiences (ARX) scale demonstrating the strongest and most consistent associations across symptom clusters.

CONCLUSIONS

Results of the current study largely converge with previous empirical studies of self-reported PTSD symptoms in disability claimant settings with the MMPI instruments. Interpretive implications for the MMPI-3, limitations, and future research directions are discussed.

Longitudinal Associations Among Service Members' PTSD Symptoms, Partner Accommodation, and Partner Distress

Romantic partners' accommodation of trauma survivors' posttraumatic stress disorder (PTSD) symptoms (e.g., participating in avoidance and safety behaviors, not expressing one's thoughts and feelings) is a putative mechanism linking PTSD symptoms and partner distress, but this hypothesis has never been empirically tested. The current study investigated this proposed within-couple mediation process from service members' PTSD symptoms to partners' depressive symptoms and relationship satisfaction through partner accommodation, as well as between-couple associations among these constructs and the possible moderating role of partners' conflict avoidance and helplessness (CAH) motivations for accommodating service members' PTSD symptoms. We examined these questions in 272 male service member/female civilian couples assessed four times over an 18-month period using the multiple-group version of the random intercept cross-lagged panel model. Within couples, service members' higher levels of PTSD symptoms at one time point significantly predicted partners being more accommodating at the next time point (βs = .14-.19), which, in turn, significantly predicted higher levels of partner depressive symptoms at the subsequent time point (βs = .09-.19) but did not predict partners' subsequent relationship satisfaction. At the between-couple level, partner accommodation was significantly positively associated with partners' depressive symptoms only among those endorsing high CAH motivations for accommodation (r = .50). In addition, accommodation was significantly negatively associated with partners' relationship satisfaction regardless of CAH motivation level (rs = -.43 to -.49). These findings are discussed in light of the potential for couple-based treatments for PTSD to enhance partner individual and relational well-being.

Robustness of Latent Profile Analysis to Measurement Noninvariance Between Profiles

Latent profile analysis (LPA) identifies heterogeneous subgroups based on continuous indicators that represent different dimensions. It is a common practice to measure each dimension using items, create composite or factor scores for each dimension, and use these scores as indicators of profiles in LPA. In this case, measurement models for dimensions are not included and potential noninvariance across latent profiles is not modeled in LPA. This simulation study examined the robustness of LPA in terms of class enumeration and parameter recovery when the noninvariance was unmodeled by using composite or factor scores as profile indicators. Results showed that correct class enumeration rates of LPA were relatively high with small degree of noninvariance, large class separation, large sample size, and equal proportions. Severe bias in profile indicator mean difference was observed with intercept and loading noninvariance, respectively. Implications for applied researchers are discussed.

COVID Stress Syndrome: Clinical and Nosological Considerations

PURPOSE OF REVIEW

To review the current state of knowledge on the newly proposed COVID Stress Syndrome.

RECENT FINDINGS

The syndrome consists of five inter-correlated elements: (a) fear of SARSCoV2 infection and fear of coming into contact with objects or surfaces contaminated with the coronavirus; (b) fear of socio-economic impacts of the pandemic; (c) fear of foreigners for fear that they are infected; (d) pandemic-related compulsive checking and reassurance-seeking; and (e) pandemic-related traumatic stress symptoms. A severe form of the syndrome, characterized by clinically significant distress and impairment in functioning, is the COVID Stress Disorder, which is regarded as a pandemic-related adjustment disorder. Several treatment options exist but further research is needed. Research during the COVID-19 pandemic has identified a pandemic-related adjustment disorder. The diagnosis of COVID Stress Syndrome should be made only after ruling out other disorders that could potentially account for the pattern of symptoms, such as obsessive-compulsive disorder and posttraumatic stress disorder. Further studies are needed to investigate the long-term course of the syndrome. Similar adjustment disorders may arise in future pandemics. Accordingly, understanding the COVID Stress Syndrome may facilitate efforts to understand and treat psychopathology in future pandemics.

Les progrès dans la réalisation de la classification quantitative de la psychopathologie☆

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.

Using Latent Class Analysis to Support the ICD-11 Complex Posttraumatic Stress Disorder Diagnosis in a Sample of Homeless Adults

The 11th revision of the International Classification of Diseases (ICD-11), ratified at the World Health Assembly in May 2019, introduced revised diagnostic guidelines for posttraumatic stress disorder (PTSD) as well as a separate diagnosis of complex PTSD (CPTSD). We aimed to test the new ICD-11 symptom structure for PTSD and CPTSD in a sample of individuals who have experienced homelessness. Experiences of trauma exposure and the associated mental health outcomes have been underresearched in this population. A sample of adults experiencing homelessness (N = 206) completed structured and semi-structured interviews that collected information about trauma exposure and symptoms of PTSD and CPTSD. We conducted a latent class analysis (LCA) using six symptom clusters (three PTSD symptom clusters that are components of CPTSD and three CPTSD symptom clusters). All participants reported trauma exposure, with 88.6% having experienced at least one event before 16 years of age. Four distinct classes of participants emerged in relation to the potential to meet the diagnosis: LCA CPTSD (n = 122, 59.8%), LCA no diagnosis (n = 27: 13.2%), LCA PTSD (n = 33; 16.2%), and LCA disturbance in self-organization (DSO; n = 22; 10.8%). Of note, participants with an ICD-11 CPTSD as well as those with an ICD-11 PTSD diagnosis fell into the LCA CPTSD class. Our findings provide some support for the distinction between CPTSD and PTSD within this population specifically but potentially have broader implications. Clear diagnoses will allow targeted PTSD and CPTSD treatment development.

Comparison of latent typologies of posttraumatic stress disorder and depression symptoms across military personnel from India and the US

Research has identified heterogeneous subgroups of individuals based on posttraumatic stress disorder (PTSD) and depression symptoms. Using data collected from military personnel in India (N = 146) and U.S. (N = 194), we examined (1) the best-fitting latent class solution; (2) multi-group invariance of the class solution; and (3) construct validity of optimal class solution. Results indicated that the optimal 4-class solution differed in severity and severity/type in the India and U.S. samples respectively. With similarity in the optimal number of classes across cultural samples, the meaning/nature of classes differed. In the India sample, anxiety severity predicted the Low Severity Class vs. all other classes, and the Moderately High Severity/High Severity Classes vs. the Moderately Low Severity Class; number of traumas predicted the High Severity Class vs. other classes; and resilience predicted the Moderately Low Severity Class vs. the Moderately High Severity Class. In the U.S. sample, alcohol use predicted the High Severity Class vs. all other classes, and the High Depression-Low PTSD Class vs. the Low Severity Class; rumination significantly predicted the High Severity and High Depression-Low PTSD Classes vs. each of the High PTSD-Low Depression and Low Severity Classes. Thus, meaning and nature of PTSD-depression subgroups may vary culturally; hence, culturally-sensitive interventions need to account for this heterogeneity.

Progress in achieving quantitative classification of psychopathology

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.

Spontaneous neural activity differences in posttraumatic stress disorder: A quantitative resting-state meta-analysis and fMRI validation

Identifying the pathophysiology of posttraumatic stress disorder (PTSD) is a critical step toward reducing its debilitating impact. Spontaneous neural activity, measured at rest using various neuroimaging techniques (e.g., regional homogeneity [ReHo], amplitude of low frequency fluctuations [ALFF]), can provide insight about baseline neurobiological factors influencing sensory, cognitive, or behavioral processes associated with PTSD. The present study used activation likelihood estimation (ALE) to conduct the largest-to-date quantitative meta-analysis of spontaneous neural activity in PTSD, including 457 PTSD cases, 292 trauma-exposed controls (TECs), and 293 non-traumatized controls (NTCs) across 22 published studies. Five regions-of-interest (ROIs) were identified where activity differed between PTSD cases and controls: one when compared to all controls (left globus pallidus), two when compared to TECs (left inferior parietal lobule [IPL] and right lingual gyrus), and two when compared to NTCs (left amygdala and right caudate head). To corroborate these results, a second analysis was conducted using resting-state functional magnetic resonance imaging on an independent sample of 205 previously-deployed US military veterans. In this analysis, converging evidence from ReHo and ALFF showed that spontaneous neural activity in the left IPL alone was positively correlated with PTSD symptom severity. This result is consistent with theoretical accounts that link left IPL activity with PTSD-relevant processes such as processing of emotional stimuli (e.g., fearful faces) and the extent that attention is captured by salient autobiographical memories. By modeling the neurobiological correlates of PTSD, we can increase our understanding of this debilitating disorder and guide the development of future clinical innovations.