Rethinking trauma-related psychopathology in the Hierarchical Taxonomy of Psychopathology (HiTOP).

Research on trauma exposure and its consequences has made tremendous progress in elucidating the role of traumatic life events in the development and maintenance of psychopathology as well as in evaluating interventions aimed at addressing the personal and public burden of trauma-related psychopathology. However, there is growing concern that problems with predominant definitions of posttraumatic syndrome (e.g., content coverage and scope, within-category heterogeneity, excessive diagnostic comorbidity) limit further efforts to fully conceptualize trauma-related psychopathology and deliver appropriate, personalized interventions. As demonstrated by an impressive body of research over the past several years, the Hierarchical Taxonomy of Psychopathology (HiTOP) presents a compelling alternative to traditional nosologies in terms of empirically based characterizations of psychopathology phenotypes, with evidence of strong utility for research and clinical applications. However, HiTOP's primary focus on descriptive psychopathology has resulted in an unacceptable gap regarding the conceptualization of trauma-related psychopathology from a dimensional, transdiagnostic perspective. We see an important opportunity to clarify what HiTOP can offer the field of traumatic stress research and articulate a future for trauma-related psychopathology within HiTOP. We argue for disaggregating psychopathology symptoms from their purported causes and, instead, developing a detailed taxonomy of traumatic events alongside an ever-evolving HiTOP model. Doing so will help identify empirically based phenotypes of trauma-related psychopathology that (a) go beyond the traditional PTSD criterion sets and (b) allow for the possibility that different features of traumatic experiences (e.g., type, duration, subjective meaning) may be associated with different symptom sequelae across different psychopathology spectra.

Supporting servicemembers and veterans during their transition to civilian life using certified sponsors: A three-arm randomized controlled trial.

Transitioning servicemembers and veterans (TSMVs) face difficulties throughout their reintegration to civilian life, including challenges with employment, poor social connection, and elevated risk for suicide. To meet the needs of this high-risk population, national initiatives have leveraged community-based interventions. Authors conducted a three-arm randomized controlled trial (n = 200) to evaluate two community-based interventions. The first, Team Red, White, and Blue (RWB), connects TSMVs to their community through physical/social activities. The second, Expiration Term of Service Sponsorship Program (ETS-SP) provides one-on-one certified sponsors to TSMVs who provide support during the reintegration process. TSMVs were assessed at baseline, 3, 6, and 12 months. The primary hypothesis was not supported as reintegration difficulties and social support were not significantly different for participants randomly assigned to the two community-based interventions (Arm-2/RWB and Arm-3/RWB + ETS-SP), when the data from the separate arms were collapsed and combined, compared to the waitlist. The results did support the secondary hypothesis as Arm-3/RWB + ETS-SP had less reintegration difficulties over 12 months and initially had more social support compared to Arm-2/RWB, which suggest that augmenting interventions with sponsors outperforms participation in community-based interventions alone. Overall, the results show some limitations of the studied community-based interventions, as implemented and researched within this study. The authors identified factors that may have contributed to the null findings for the primary hypothesis, which can be addressed in future studies, such as addressing the unique needs of TSMVs, enrolling TSMVs into interventions prior to military discharge, measuring and improving participation levels, and providing stepped-care interventions based on risk levels. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Military experiences, connection to military identity, and time since military discharge as predictors of United States veteran suicide risk.

Veterans navigating the military-to-civilian transition appear at elevated risk for suicide. However, research on the transition-suicide association often fails to consider co-occurring risk factors. The independent association of time since military discharge and suicide among veterans therefore remains unclear. Data from 1,495 post-Vietnam community veterans provided estimates of suicide risk, military-based stressful experiences, connection to military identity, and recency of military discharge. Hierarchical regression analyses examined independent, incremental utility of factors associated with suicide risk after controlling for quality of life, age, and duration of military service among the total veteran sample and a subsample discharged from military service within five years prior. The resulting model explained 41% of variance in suicide risk in the total veteran sample and 51% of variance in suicide risk in the recently discharged subsample. Recency of discharge, combat exposure, moral injury, poor quality of life, and poor psychological wellness showed statistically significant, independent associations with suicide risk, whereas connection to military identity did not show significant, independent associations. Results highlight the salience of the military-to-civilian transition as an independent risk factor for veteran suicide even after controlling for military-based stressful experiences, military identity, quality of life, age, and service duration.

An open trial of VA CONNECT: Caring for Our Nation's Needs Electronically during the COVID-19 Transition.

The COVID-19 pandemic impacted emotional well-being due to safety concerns, grief, employment impacts, and social interaction limitations. Face-to-face mental health treatment restrictions were especially impactful to veterans who often gain social enrichment from Veterans Health Administration (VHA) care. We present results from a novel group-based telehealth intervention, VA Caring for Our Nation's Needs Electronically during the COVID-19 Transition (VA CONNECT), which integrates skills training and social support to develop a COVID-19 Safety & Resilience Plan. Veterans (n â€‹= â€‹29) experiencing COVID-related stress participated in an open trial of this 10-session, manualized group VHA telehealth intervention. We examined whether COVID-19-related stress, adjustment disorder symptoms, and loneliness decreased, and coping strategy use increased after participation in VA CONNECT. Between baseline and two-month follow-up, participants reported a significant reduction in perceived stress and adjustment disorder symptoms, and an increase in planning coping skills use. Significant changes were not observed in loneliness or other specific coping strategies. Findings may support the utility of VA CONNECT as an intervention for pandemic-related stress and improving certain coping skills. Future research should explore group-based telehealth interventions like VA CONNECT with other populations within and outside of the VA, which have value during major disruptions to face-to-face mental healthcare access.

Factor analysis in personality disorders research: Modern issues and illustrations of practical recommendations.

The development of factor analysis is uniquely situated within psychology, and the development of many psychological theories and measures are likewise tethered to the common use of factor analysis. In this article, we review modern methodological controversies and developments of factor analytic techniques through concrete demonstrations that span the exploratory-confirmatory continuum. Also, we provide recommendations for working through common challenges in personality disorders research. To help researchers conduct riskier tests of their theory-implied models, we review what factor analysis is and is not, as well as some dos and don'ts for engaging in the process of model evaluation and selection. Throughout, we also emphasize the need for closer alignment between factor models and our theories, as well as clearer statements about which criteria would support or refute the theories being tested. Consideration of these themes appears promising in terms of advances in theory, research, and treatment surrounding the nature and impact of personality disorders. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Is the Window of Learning Only Cracked Open? Parents' Perspectives on Virtual Learning for Deaf and Hard of Hearing Students.

During the COVID-19 pandemic, parents quickly assumed the role of teachers to support their children's learning at home. Deaf and hard of hearing (DHH) students often rely on additional accommodations to access their education. The authors investigated the perspectives of 40 parents of K-12 DHH students on the use of virtual learning during the pandemic. An electronic survey was distributed through Qualtrics to gain an understanding of the new learning environment of remote instruction. The participants' responses revealed that they felt that challenges occurred in the areas of time management, language access, technology, motivation, and children's ability to function independently. The respondents were almost evenly split between satisfaction and dissatisfaction with their child's overall educational experience during the pandemic. The results indicated that degree of access significantly influenced the children's experiences of education in virtual learning settings.

Model fit is a fallible indicator of model quality in quantitative psychopathology research: A reply to Bader and Moshagen.

As evidenced by our exchange with Bader and Moshagen (2022), the degree to which model fit indices can and should be used for the purpose of model selection remains a contentious topic. Here, we make three core points. First, we discuss the common misconception about fit statistics' abilities to identify the "best model," arguing that mechanical application of model fit indices contributes to faulty inferences in the field of quantitative psychopathology. We illustrate the consequences of this practice through examples in the literature. Second, we highlight the parsimony-adjacent concept of fitting propensity, which is not accounted for by commonly used fit statistics. Finally, we present specific strategies to overcome interpretative bias and increase generalizability of study results and stress the importance of carefully balancing substantive and statistical criteria in model selection scenarios. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Partnered implementation of the veteran sponsorship initiative: protocol for a randomized hybrid type 2 effectiveness-implementation trial.

BACKGROUND: The USA is undergoing a suicide epidemic for its youngest Veterans (18-to-34-years-old) as their suicide rate has almost doubled since 2001. Veterans are at the highest risk during their first-year post-discharge, thus creating a "deadly gap." In response, the nation has developed strategies that emphasize a preventive, universal, and public health approach and embrace the value of community interventions. The three-step theory of suicide suggests that community interventions that reduce reintegration difficulties and promote connectedness for Veterans as they transition to civilian life have the greatest likelihood of reducing suicide. Recent research shows that the effectiveness of community interventions can be enhanced when augmented by volunteer and certified sponsors (1-on-1) who actively engage with Veterans, as part of the Veteran Sponsorship Initiative (VSI). METHOD/DESIGN: The purpose of this randomized hybrid type 2 effectiveness-implementation trial is to evaluate the implementation of the VSI in six cities in Texas in collaboration with the US Departments of Defense, Labor and Veterans Affairs, Texas government, and local stakeholders. Texas is an optimal location for this large-scale implementation as it has the second largest population of these young Veterans and is home to the largest US military installation, Fort Hood. The first aim is to determine the effectiveness of the VSI, as evidenced by measures of reintegration difficulties, health/psychological distress, VA healthcare utilization, connectedness, and suicidal risk. The second aim is to determine the feasibility and potential utility of a stakeholder-engaged plan for implementing the VSI in Texas with the intent of future expansion in more states. The evaluators will use a stepped wedge design with a sequential roll-out to participating cities over time. Participants (n=630) will be enrolled on military installations six months prior to discharge. Implementation efforts will draw upon a bundled implementation strategy that includes strategies such as ongoing training, implementation facilitation, and audit and feedback. Formative and summative evaluations will be guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework and will include interviews with participants and periodic reflections with key stakeholders to longitudinally identify barriers and facilitators to implementation. DISCUSSION: This evaluation will have important implications for the national implementation of community interventions that address the epidemic of Veteran suicide. Aligned with the Evidence Act, it is the first large-scale implementation of an evidence-based practice that conducts a thorough assessment of TSMVs during the "deadly gap." TRIAL REGISTRATION: ClinicalTrials.gov ID number: NCT05224440 . Registered on 04 February 2022.

Misbegotten methodologies and forgotten lessons from Tom Swift's electric factor analysis machine: A demonstration with competing structural models of psychopathology.

Confirmatory factor analysis (CFA) and its bifactor models are popular in empirical investigations of the factor structure of psychological constructs. CFA offers straightforward hypothesis testing but has notable pitfalls, such as the imposition of strict assumptions (i.e., simple structure) that obscure unmodeled complexity. Due to the limitations of bifactor CFAs, they have yielded anomalous results across samples and studies that suggest model misspecification (e.g., evaporating specific factors and unexpected loadings). We propose the use of exploratory factor analysis (EFA) to evaluate the structural validity of CFA solutions-either before or after the estimation of more restrictive CFA models-to (a) identify model misspecifications that may drive anomalous estimates and (b) confirm CFA models by examining whether hypothesized structures emerge with limited researcher input. We evaluated the degree to which predominant factor structures were invariant across contexts along the exploratory-confirmatory continuum and demonstrate how poor methodological choices can distort results and impede theory development. All CFA models fit well, but there were numerous differences in replicability and substantive interpretability. Several similarities emerged between bifactor CFA and EFA models, including evidence of overextraction, the collapse of specific factors onto the general factor, and subsequent shifts in how the general factor was defined. We situate these methodological shortcomings within the broader literature on structural models of psychopathology, articulate implications for theories (such as the p-factor) that are borne out of factor analysis, outline several remedies for problems encountered when performing exploratory bifactor analysis, and propose alternative specifications for confirmatory bifactor models. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

An Assessment of Mobile Applications Designed to Address Physical Activity During Pregnancy and Postpartum.

Only 15% of women meet physical activity guidelines during and after pregnancy despite the well-established positive impacts on both the mother and the neonate. There is a clear lack of guidance on this topic, and mobile health interventions are a promising direction for future interventions to facilitate a necessary increase in physical activity during pregnancy and postpartum. The purpose of the study was to objectively assess the quality and perceived impact of existing free mobile apps that are designed to cover physical activity during and after pregnancy. The Mobile Application Rating Scale (MARS) was used by two independent reviewers to determine overall quality of mobile apps freely available in the U.S. iTunes store. The initial search for pregnancy and postpartum physical activity apps yielded 732 results. After careful screening, 567 apps were excluded, leaving 165 that went under further screening procedures. Upon further screening, 54 apps were downloaded and scored using the MARS system. Of the 54 apps included in the analyses, 20 apps contained physical activity information for pregnant women (37.0%), 11 apps contained information for postpartum women (20.4%), and 23 apps contained information pertaining to both pregnant and postpartum women (42.6%). Of note, 33 (61.1%) of the apps required hidden costs in the form of in-app purchases. The mean overall MARS score was 3.06 ± 0.94 out of 5 (1-inadequate and 5-excellent). Overall, the quality of existing apps appears low, and none of the existing apps had specific goal setting based on current recommendations for pregnant women. Due to low quality and perceived impact, existing mobile apps are insufficient to enable women to achieve recommended levels of physical activity during pregnancy and postpartum.

The deadly gap: Understanding suicide among veterans transitioning out of the military.

In the period following separation from the military, service members face the challenge of transitioning to a post-military civilian life. Some evidence suggests these transitioning Veterans are at higher risk for suicide compared with both the broader Veteran population and the United States public, yet they often do not receive adequate support and resources. In this review, we use the Three-Step Theory of suicide to outline characteristics of transitioning Veterans and the transition process that may affect suicide risk. We then highlight relevant services available to this specific subgroup of Veterans and make recommendations that address barriers to care. Cumulatively, this literature suggests transitioning Veterans fall within a "deadly gap" between the end of their military service and transition into civilian life. This "deadly gap" consists of limited psychiatric services and increased suicide risk factors which together may explain the increase in suicide during this transition period.

Substance use in a sexual context: The association of sex-related substance use motives with substance choice and use behaviors.

BACKGROUND: Substance use before sex is associated with riskier behaviors. Sex-related substance use motives may explain pre-sex substance use. We explored what sex-related motives are associated with alcohol versus drug use, and which motives underlie heavier use. METHODS: A sample of 936 participants (50% male, 80% White) completed an Internet survey about sexuality. Those who drank before sex (n=657) reported on six sex-related drinking motives; those who used drugs before sex (n=271) reported on six (parallel) sex-related drug use motives. The frequency of endorsement of each motive between drinkers and drug users was compared with z-distributions. Logistic regressions assessed whether motives were associated with substance use frequency and intoxication before sex. RESULTS: Substance use to relax and to get a sex partner to use were more commonly endorsed for alcohol than drugs; substance use to improve performance and enhance experience were more commonly endorsed for drugs. Most motives were associated with alcohol frequency and intoxication before sex. None were associated with drug frequency; some were associated with drug intoxication. CONCLUSIONS: Alcohol was generally used to facilitate sex, and drugs to enhance sex. Sex-related drinking motives were associated with drinking before sex; sex-related drug use motives were less predictive.

Three recommendations based on a comparison of the reliability and validity of the predominant models used in research on the empirical structure of psychopathology.

The present study compared the primary models used in research on the structure of psychopathology (i.e., correlated factor, higher-order, and bifactor models) in terms of structural validity (model fit and factor reliability), longitudinal measurement invariance, concurrent and prospective predictive validity in relation to important outcomes, and longitudinal consistency in individuals' factor score profiles. Two simpler operationalizations of a general factor of psychopathology were also examined-a single-factor model and a count of diagnoses. Models were estimated based on structured clinical interview diagnoses in two longitudinal waves of nationally representative data from the United States (n = 43,093 and n = 34,653). Models that included narrower factors (fear, distress, and externalizing) were needed to capture the observed multidimensionality of the data. In the correlated factor and higher-order models these narrower factors were reliable, largely invariant over time, had consistent associations with indicators of adaptive functioning, and had moderate stability within individuals over time. By contrast, the fear- and distress-specific factors in the bifactor model did not show good reliability or validity throughout the analyses. Notably, the general factor of psychopathology (p factor) performed similarly well across tests of reliability and validity regardless of whether the higher-order or bifactor model was used; the simplest (single factor) model was also comparable across most tests, with the exception of model fit. Given the limitations of categorical diagnoses, it will be important to repeat these analyses using dimensional measures. We conclude that when aiming to understand the structure and correlates of psychopathology it is important to (a) look beyond model fit indices to choose between different models, (b) examine the reliability of latent variables directly, and (c) be cautious when isolating and interpreting the unique effects of specific psychopathology factors, regardless of which model is used. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Mr. Kim et al. Reply.

We write to respond to an erudite letter to the editor by Zachary J. Williams.1 that extended analyses presented in our recent publication2 investigating the latent structure of autism phenotypic symptoms. The letter by Williams reported results of a bifactor analysis using the standardized loadings and interfactor correlations derived from a Schmid-Leiman orthogonalization of the optimal correlated factor model that we identified. Williams examined the relative contributions of the general and three specific autism symptom factors (ie, social interaction [SI], communication [COM], and restrictive and repetitive behavior [RRB]) to the autism symptom indicators. Those analyses indicated that the majority of autism spectrum disorder (ASD) symptom covariation could be explained by a single general autism factor, whereas the three specific autism symptom factors accounted for minimal covariation among indicators. To pursue the intriguing points raised in the letter, we performed additional analyses using the original raw data.

Are fit indices used to test psychopathology structure biased? A simulation study.

Structural models of psychopathology provide dimensional alternatives to traditional categorical classification systems. Competing models, such as the bifactor and correlated factors models, are typically compared via statistical indices to assess how well each model fits the same data. However, simulation studies have found evidence for probifactor fit index bias in several psychological research domains. The present study sought to extend this research to models of psychopathology, wherein the bifactor model has received much attention, but its susceptibility to bias is not well characterized. We used Monte Carlo simulations to examine how various model misspecifications produced fit index bias for 2 commonly used estimators, WLSMV and MLR. We simulated binary indicators to represent psychiatric diagnoses and positively skewed continuous indicators to represent symptom counts. Across combinations of estimators, indicator distributions, and misspecifications, complex patterns of bias emerged, with fit indices more often than not failing to correctly identify the correlated factors model as the data-generating model. No fit index emerged as reliably unbiased across all misspecification scenarios. Although, tests of model equivalence indicated that in one instance fit indices were not biased-they favored the bifactor model, albeit not unfairly. Overall, results suggest that comparisons of bifactor models to alternatives using fit indices may be misleading and call into question the evidentiary meaning of previous studies that identified the bifactor model as superior based on fit. We highlight the importance of comparing models based on substantive interpretability and their utility for addressing study aims, the methodological significance of model equivalence, as well as the need for implementation of statistical metrics that evaluate model quality. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Personality disorders: community prevalence and socio-demographic correlates.

Multiple studies have reported community prevalence rates of personality disorders (PDs), but these studies differed in terms of diagnostic criteria, assessment instruments, communities sampled, and size, producing widely ranging estimates. We take a meta-analytic approach to characterizing PD community prevalence rates by comparing results from two reviews that pooled previous studies. Overall, particular PD rates are low in community samples, but the presence of any PD is relatively high, with approximately one person in seven experiencing personality psychopathology. High congruence of prevalence estimates, but low rank-order agreement of rates, was observed. We discuss how the presence of PD is associated with socio-demographic correlates such as gender, race/ethnicity, and age and highlight areas for further study.

The temporal stability of the bifactor model of comorbidity: An examination of moderated continuity pathways.

BACKGROUND: Structural models of psychopathology indicate that common mental disorder comorbidity reflects latent transdiagnostic factors. Multiple studies have replicated transdiagnostic internalizing (mood and anxiety disorders) and externalizing (substance use, antisociality-, and impulsivity-related disorders) factors; other studies support distress and fear sub-factors of internalizing. These factors show a high degree of temporal stability. Recently, a bifactor conceptualization of multivariate comorbidity has emerged, positing the existence of an orthogonal general psychopathology factor that saturates all diagnoses in addition to internalizing/distress/fear and externalizing, although no studies have examined the temporal stability of the factors in this competing model over time among adults. METHOD: In a large, two-wave nationally representative sample (N=43,093), we investigated the structure of the bifactor model and examined all potential within- and between-factor stability pathways in a structural equation modeling framework. RESULTS: In general, within-domain stability (e.g., Wave 1 general factor predicting Wave 2 general factor) was high, while between-domain pathways (e.g., Wave 1 general factor predicting the Wave 2 externalizing factor) did not differ significantly from zero. We then tested possible age and gender moderation of factor stability, finding that the stability for all factors, except fear, significantly differed across demographic sub-groups. However, these differences were not clinically meaningful. CONCLUSIONS: Results indicated that bifactor model factors show varying degrees of temporal stability, with lowest comorbidity continuity over time reflecting distress stability. Findings are discussed with regard to recent evidence that the general factor may, to some extent, represent the negative emotionality captured by internalizing/distress in correlated two- and three-factor solutions.

An investigation of habit learning in Anorexia Nervosa.

Anorexia Nervosa (AN) is a disorder characterised by compulsive behaviour, such as self-starvation and excessive exercise, which develop in the pursuit of weight-loss. Recent theory suggests that once established, compulsive weight-loss behaviours in AN may become habitual. In two parallel studies, we measured whether individuals with AN showed a bias toward habits using two outcome-devaluation tasks. In Study 1, 23 women with AN (restrictive and binge/purge subtypes), and 18 healthy controls (HC) completed the slips-of-action paradigm, designed to assess reward-based habits. In Study 2, 13 women with restrictive AN, 14 women recovered from restrictive AN, and 17 female HC participants completed the slips-of-action paradigm, and an avoidance paradigm, designed to assess aversive habits. AN participants showed no deficit relative to HCs in the ability to use feedback to respond correctly to stimuli. Following devaluation of outcomes, all groups in both studies were equally able to withhold inappropriate responses, suggesting no deficit in the balance between goal-directed and habitual control of behaviour in these tasks in AN. These results suggest that individuals with AN do not show a generalised tendency to rely on habits in two outcome-devaluation tasks. Future research is needed to investigate the potential role of disorder-specific habits in the maintenance of behaviour in AN.

Panic disorder and agoraphobia: A direct comparison of their multivariate comorbidity patterns.

BACKGROUND: Scientific debate has long surrounded whether agoraphobia is a severe consequence of panic disorder or a frequently comorbid diagnosis. Multivariate comorbidity investigations typically treat these diagnoses as fungible in structural models, assuming both are manifestations of the fear-subfactor in the internalizing-externalizing model. No studies have directly compared these disorders' multivariate associations, which could clarify their conceptualization in classification and comorbidity research. METHODS: In a nationally representative sample (N=43,093), we examined the multivariate comorbidity of panic disorder (1) without agoraphobia, (2) with agoraphobia, and (3) regardless of agoraphobia; and (4) agoraphobia without panic. We conducted exploratory and confirmatory factor analyses of these and 10 other lifetime DSM-IV diagnoses in a nationally representative sample (N=43,093). RESULTS: Differing bivariate and multivariate relations were found. Panic disorder without agoraphobia was largely a distress disorder, related to emotional disorders. Agoraphobia without panic was largely a fear disorder, related to phobias. When considered jointly, concomitant agoraphobia and panic was a fear disorder, and when panic was assessed without regard to agoraphobia (some individuals had agoraphobia while others did not) it was a mixed distress and fear disorder. LIMITATIONS: Diagnoses were obtained from comprehensively trained lay interviewers, not clinicians and analyses used DSM-IV diagnoses (rather than DSM-5). CONCLUSIONS: These findings support the conceptualization of agoraphobia as a distinct diagnostic entity and the independent classification of both disorders in DSM-5, suggesting future multivariate comorbidity studies should not assume various panic/agoraphobia diagnoses are invariably fear disorders.