An Examination of Idiographic Networks of Posttraumatic Stress Disorder Symptoms

Dynamic symptom associations in posttraumatic stress disorder: a network approach

Background and objective: The current study aimed to investigate the within-day symptom dynamics in PTSD patients, specifically focusing on symptoms that most predict changes in other symptoms. The study included a baseline diagnostic assessment, followed by an assessment using the experience sampling method (ESM) via a smartphone.Method: Participants answered questions related to their PTSD symptoms four times per day for 15 consecutive days (compliance rate 75%). The clinical sample consisted of 48 treatment-seeking individuals: 44 with PTSD as a primary diagnosis, and four patients with subsyndromal PTSD, all of whom had not yet begun trauma-focused treatment. The ESM assessment included the 20 items from the PTSD Checklist for DSM-5, five items from the International Trauma Questionnaire (ITQ) assessing disturbances in relationships and functional impairment, and two items from the Clinician-Administered PTSD Scale for DSM-5 assessing symptoms of depersonalization and derealization.Results: Temporal networks (prospective associations between symptoms) showed that changes in hypervigilance predicted changes in the greatest number of symptoms at the next time point. Furthermore, hypervigilance showed temporal connections with at least one additional symptom from each of the DSM-5 PTSD symptom clusters.Conclusions: Results show that the contemporaneous network (representing the relationship between given symptoms within the same assessment occasion) and the temporal network (representing prospective associations between symptoms) differ and that it is important to estimate both. Some findings from earlier research are replicated, but heterogeneity across studies remains. Future studies should include potential moderators.

Using the experience sampling method to support clinical practice: An illustration with problematic cannabis use

The experience sampling method (ESM) has been frequently used in clinical research; however, there is low translational uptake in clinical practice. This may be due to challenges with interpreting individual-level data at granular intervals. We provide an illustrative example of how ESM can be leveraged to generate personalized cognitive-behavioral strategies for problematic cannabis use.

We conducted a descriptive case series analysis using ESM data from 30 individuals reporting on problematic cannabis use, craving, affect, and coping four times daily for 16-days (t = 64, T = 1,920).

Analyzing ESM data using descriptive statistics and visualizations from individuals with similar clinical and demographic profiles supported a diverse array of personalized clinical insights and recommendations for each case. These recommendations included psychoeducation regarding affect- and boredom-regulation strategies, functional analyses of occasions during which cannabis was not used, and discussions on how cannabis use intersects with one's personal values.

While many clinicians utilize measurement-based care, barriers have limited the incorporation of ESM towards personalized, data-informed approaches to treatment. We provide an illustrative example of how ESM data can be used to generate actionable treatment strategies for problematic cannabis use and highlight continued challenges with interpreting time-series data.

A pilot randomized controlled trial of transdiagnostic network-informed personalized treatment for eating disorders versus enhanced cognitive behavioral therapy

OBJECTIVE

Eating disorders (EDs) are serious mental illnesses with high mortality and relapse rates and carry significant societal and personal costs. Nevertheless, there are few evidence-based treatments available. One aspect that makes treatment difficult is the high heterogeneity in symptom presentation. This heterogeneity makes it challenging for clinicians to identify pertinent treatment targets. Personalized treatment based on idiographic models may be well-suited to address this heterogeneity, and, in turn, presumably improve treatment outcomes.

METHODS

In the current randomized controlled trial, participants will be randomly assigned to either 20 sessions of enhanced cognitive behavioral therapy (CBT-E) or transdiagnostic network-informed personalized treatment for EDs (T-NIPT-ED). Assessment of ED symptoms, clinical impairment, and quality of life will occur at pre-, mid-, posttreatment, and 1-month follow-up.

RESULTS

We will examine the acceptability and feasibility of T-NIPT-ED compared to CBT-E. We also will test the initial clinical efficacy of T-NIPT-ED versus CBT-E on clinical outcomes (i.e., ED symptoms and quality of life). Finally, we will test if the network-identified precision targets are the mechanisms of change.

DISCUSSION

Ultimately, this research may inform the development and dissemination of evidence-based personalized treatments for EDs and serve as an exemplar for personalized treatment development across the broader field of psychiatry.

PUBLIC SIGNIFICANCE

Current evidence-based treatments for eating disorders result in low rates of recovery, especially for adults with AN. Our study aims to test the feasibility, acceptability, and clinical efficacy of a data-driven, individualized approach to ED treatment, network-informed personalized treatment, compared to the current evidence-based treatment for EDs, Enhanced CBT. Findings have the potential to improve treatment outcomes for EDs by identifying and targeting core symptoms maintaining EDs.

Heterogeneity in Individual Network Analysis: Reality or Illusion?

The use of idiographic research techniques has gained popularity within psychological research and network analysis in particular. Idiographic research has been proposed as a promising avenue for future research, with differences between idiographic results highlighting evidence for radical heterogeneity. However, in the quest to address the individual in psychology, some classic statistical problems, such as those arising from sampling variation and power limitations, should not be overlooked. This article aims to determine to what extent current tools to compare idiographic networks are suited to disentangle true from illusory heterogeneity in the presence of sampling error. To this end, we investigate the performance of tools to inspect heterogeneity (visual inspection, comparison of centrality measures, investigating standard deviations of random effects, and GIMME) through simulations. Results show that power limitations hamper the validity of conclusions regarding heterogeneity and that the power required to assess heterogeneity adequately is often not realized in current research practice. Of the tools investigated, inspecting standard deviations of random effects and GIMME proved the most suited. However, all tools evaluated leave the door wide open to misinterpret all observed variability in terms of individual differences. Hence, the current paper calls for caution in the use and interpretation of new time-series techniques when it comes to heterogeneity.

Toward a Developmental Model of Continuity and Change in PTSD Symptoms following Exposure to Traumatic and Adverse Experiences

A developmental understanding of the expression of posttraumatic stress (PTS) symptoms following trauma in childhood requires identifying continuity and change in not just overall symptoms but in the individual symptoms as well. Such models of change also require understanding multiple dimensions of time. That is, longitudinal change-the passage of time-may have different effects on symptom expression depending on when in time an individual entered the study - such as what age they were when first assessed. This paper addresses these ideas with an overview of the developmental differences in the assessment of PTS from the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders, (DSM-5), longitudinal research on posttraumatic stress disorder (PTSD) symptoms, and providing synthesis within a symptom network perspective. We then provide an illustration of how individual PTSD symptoms change over time at different ages (elementary versus middle school) with a secondary analysis of data from a previously reported study (n = 191 youth, aged 8-15, assessed at two time points six months apart). The reanalysis of the data suggests both continuity and change in symptoms over time (i.e., some symptoms were more stable than other symptoms) with differences in symptom rates and their longitudinal change as a function of age (i.e., some symptoms more common or more stable in younger versus older or older versus younger). We close with avenues for future research aimed at better understanding symptom cascades over time and at different ages and potential implications for future iterations of assessment/classification systems.

Clinician Opinions: Perceived Utility of and Barriers to Incorporating Pretreatment Ecological Momentary Assessment Into Clinical Care

Increasingly, clinicians have the option of including technological components into clinical care. However, little research has assessed clinicians' interest in utilizing technology in their clinical work. Here, clinicians reported their opinions related to using a mobile assessment platform (MAP) to collect ecological data from clients before providing clinical care. Practicing and training mental health clinicians (N = 221) reported demographics, characteristics of their clinical work, and confidence in their clinical skill. Participants then read a description of MAP and responded to questions about their perceived benefits of and barriers to its use. Last, participants rated their interest in using MAP in their clinical work. These perceptions were then factor-analyzed and the resulting factor scores were regressed onto clinician characteristics. Interest in using MAP was significantly lower for the group that endorsed a psychodynamic/psychoanalytic orientation and those with greater confidence in their clinical skills. Across scales, we found a pattern that participants who did not identify as male, those with a psychodynamic/psychoanalytic orientation, and those with greater confidence in their clinical skills tended to have lower ratings of the benefits of and higher ratings for the barriers to using MAP. Results revealed that significant differences in opinions about incorporating technology into clinical work exist between different groups of clinicians. This information may be useful in future work that attempts to implement technological tools into clinical settings.

Assessing perceptions of resilience: The understanding from network analysis

Introduction

Previous studies have yet to reach a consensus on the construct of resilience perception, and how to enhance the effect of resilience intervention remains an urgent issue. In this consideration, this study examines the fundamental construct of resilience. It provides insight into the critical prevention goal for resilience intervention by utilizing the latest methods of psychological network analysis.

Methods

The sample is the graduate students enrolled in September 2021. Participants completed (1) the Connor-Davidson Resilience Scale, (2) the University of Washington Resilience Scale-8 Item, (3) the Brief Resilience Scale, and (4) the Resilience Scale for Adults, each representing different orientations of resilience.

Results

The network analysis grants greater clarity to the resilience perception as a dynamic system that interacts between an individual's tendency to intrinsic capacity and response to external resources. This study has shown that a positive perception of external social resources is the most important for individuals' resilience cognition; the effect of resilience intervention can be achieved more quickly by changing the individual's sense of hope.

Discussion

Based on the results, a psychometric instrument that integrates different orientations of resilience concepts and is based on time-varying needs to be developed.

Co-occurring depression and obsessive-compulsive disorder: A dimensional network approach

BACKGROUND

Depressive and obsessive-compulsive (OCD) symptoms often co-occur and a number of possible explanations for this co-occurrence have been explored, including shared biological and psychosocial risk factors. Network approaches have offered a novel hypothesis for the link between depression and OCD: functional inter-relationships across the symptoms of these conditions. The few network studies in this area have relied largely on item, rather than process-level constructs, and have not examined relationships dimensionally.

METHODS

Network analytic methods were applied to data from 463 treatment-seeking adults with OCD. Patients completed self-report measures of OCD and depression. Factor analysis was used to derive processes (i.e., nodes) to include in the network. Networks were computed, and centrality, bridge, and stability statistics examined.

RESULTS

Networks showed positive relations among specific OCD and depressive symptoms. Obsessions (particularly repugnant thoughts), negative affectivity, and cognitive-somatic changes (e.g., difficulty concentrating) were central to the network. Unique relations were observed between symmetry OCD symptoms and cognitive-somatic changes. No direct link between harm-related OCD symptoms and depression was observed.

CONCLUSIONS

Our results bring together prior findings, suggesting that both negative affective and psychomotor changes are important to consider in examining the relationship between OCD and depression. Increased consideration of heterogeneity in the content of OCD symptoms is key to improving clinical conceptualizations, particularly when considering the co-occurrence of OCD with other disorders.

Identifying and predicting posttraumatic stress symptom states in adults with posttraumatic stress disorder

Between-person heterogeneity of posttraumatic stress disorder (PTSD) is well established. Within-person analyses and the DSM-5 suggest that heterogeneity may also be evident within individuals across time as they move through social contexts and biological cycles. Modeling within-person symptom-level fluctuations may confirm such heterogeneity, elucidate mechanisms of disorder maintenance, and inform time- and person-specific interventions. The present study aimed to identify and predict discrete within-person disorder presentations, or symptom states, and explore group-level patterns of these states. Adults (N = 20, 60.0% male, M age = 38.25 years) with PTSD responded to symptom surveys four times per day for 30 days. We subjected each individual's dataset to Gaussian finite mixture modeling (GFMM) to uncover latent, within-person classes of symptom levels (i.e., states) and predicted those states with idiographic elastic net regularized regression using a set of time-based and behavioral predictors. Next, we conducted a GFMM of the within-person GFMM outputs and tested idiographic prediction models of these states. Multiple within-person states were revealed for 19 of 20 participants (Mdn = 4; 66 for the full sample). Prediction models were moderately successful, M AUC = .66 (d = 0.58), range: .50-1.00. The GFMM of the within-person model outputs revealed two states: one with above-average and one with below-average symptom levels. Prediction models were, again, moderately successful, M AUC = .66; range: .50-.89. The findings provide evidence for within-person heterogeneity of PTSD as well as between-person similarities and suggest that future work should incorporate additional contextual variables as symptom state predictors.

Examining the associations between PTSD symptoms and aspects of emotion dysregulation through network analysis

Despite the clearly established link between posttraumatic stress disorder (PTSD) and emotion dysregulation, little is known about how individual symptoms of PTSD and aspects of emotion dysregulation interrelate. The network approach to mental health disorders provides a novel framework for conceptualizing the association between PTSD and emotion dysregulation as a system of interacting nodes. In this study, we estimated the structural relations among PTSD symptoms and aspects of emotion dysregulation within a large sample of women who participated in a multi-site study of sexual revictimization (N = 463). We estimated expected influence to reveal differential associations among PTSD symptoms and aspects of emotion dysregulation. Further, we estimated bridge expected influence to identify influential nodes connecting PTSD symptoms and aspects of emotion dysregulation. Results highlighted the key role of concentration difficulties in expected influence and bridge expected influence. Findings highlight several PTSD symptoms and aspects of emotion dysregulation that may be targets for future intervention.

Using individual networks to identify treatment targets for eating disorder treatment: a proof-of-concept study and initial data

BACKGROUND

Eating disorders (EDs) are severe mental illnesses, with high morbidity, mortality, and societal burden. EDs are extremely heterogenous, and only 50% of patients currently respond to first-line treatments. Personalized and effective treatments for EDs are drastically needed.

METHODS

The current study (N = 34 participants with an ED diagnosis collected throughout the United States) aimed to investigate best methods informing how to select personalized treatment targets utilizing idiographic network analysis, which could then be used for evidence based personalized treatment development. We present initial data collected via experience sampling (i.e., ecological momentary assessment) over the course of 15 days, 5 times a day (75 total measurement points) that were used to select treatment targets for a personalized treatment for EDs.

RESULTS

Overall, we found that treatment targets were highly variable, with less than 50% of individuals endorsing central symptoms related to weight and shape, consistent with current treatment response rates for treatments designed to target those symptoms. We also found that different aspects of selection methods (e.g., number of items, type of centrality measure) impacted treatment target selection.

CONCLUSIONS

We discuss implications of these data, how to use idiographic network analysis to personalize treatment, and identify areas that need future research.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT04183894. Registered 3 December 2019-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04183894 . NCT04183894 (ClinicalTrials.gov identifier).

Posttraumatic stress disorder in daily life among World Trade Center responders: Temporal symptom cascades

BACKGROUND

Posttraumatic stress disorder (PTSD) symptoms are common in the immediate aftermath of a trauma, but it is their persistence over time that leads to a diagnosis. This pattern highlights the critical role of symptom maintenance to understanding and treating the disorder. Relatively few studies have explored whether PTSD symptoms may be interacting or triggering one another to worsen and maintain the disorder, a dynamic we refer to as "symptom cascades." Additionally, little work has tested in real-time how other maintenance factors, such as stress, contribute to such events in daily life.

METHODS

The present study in a group (N = 202) of World Trade Center (WTC) responders oversampled for PTSD tested day-to-day temporal associations among PTSD symptom dimensions (i.e., intrusions, avoidance, numbing, and hyperarousal) and stress across one week.

RESULTS

Longitudinal models found hyperarousal on a given day predicted increased PTSD symptoms the next day, with the effect sizes almost double compared to other symptom dimensions or daily stress. Intrusions, in contrast, showed little prospective predictive effects, but instead were most susceptible to the effects from other symptoms the day before. Avoidance and numbing showed weaker bidirectional effects.

LIMITATIONS

Findings are from a unique population and based on naturalistic observation.

CONCLUSIONS

Results are consistent with the idea of symptom cascades, they underscore hyperarousal's strong role in forecasting short-term increases in PTSD (even more than stress per se) and they raise the prospect of highly specific ecological momentary interventions to potentially disrupt PTSD maintenance in daily life.

Network Analysis of Psychopathology: Controversies and Challenges

Empirical publications inspired by the network approach to psychopathology have increased exponentially in the twenty-first century. The central idea that an episode of mental disorder arises from causal interactions among its symptomatic elements has especially resonated with those clinical scientists whose disenchantment with traditional categorical and dimensional approaches to mental illness has become all too apparent. As the field has matured, conceptual and statistical concerns about the limitations of network approaches to psychopathology have emerged, inspiring the development of novel methods to address these concerns. Rather than reviewing the vast empirical literature, I focus instead on the issues and controversies regarding this approach and sketch directions where the field might go next.

Temporal networks of tobacco withdrawal symptoms during smoking cessation treatment

A recently developed network perspective on tobacco withdrawal posits that withdrawal symptoms causally influence one another across time, rather than simply being indicators of a latent syndrome. Evidence supporting a network perspective would shift the focus of tobacco withdrawal research and intervention toward studying and treating individual withdrawal symptoms and intersymptom associations. Here we construct and examine temporal tobacco withdrawal networks that describe the interplay among withdrawal symptoms across time using experience-sampling data from 1,210 participants (58.35% female, 86.24% White) undergoing smoking cessation treatment. We also construct person-specific withdrawal networks and capture individual differences in the extent to which withdrawal symptom networks promote the spread of symptom activity through the network across time using impulse response analysis. Results indicate substantial moment-to-moment associations among withdrawal symptoms, substantial between-person differences in withdrawal network structure, and reductions in the interplay among withdrawal symptoms during combination smoking cessation treatment. Overall, findings suggest the utility of a network perspective and also highlight challenges associated with the network approach stemming from vast between-person differences in symptom networks. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Commentary on the Special Issue on Network Analysis: Assessment, Intervention, Theory, and the Nature of Reality: Actualizing the Potential of Network Perspectives on Posttraumatic Stress Disorder

This commentary on the Journal of Traumatic Stress special issue on network analysis explores the network perspective on posttraumatic stress disorder (PTSD), emphasizing the advances in research made in this collection of articles. The commentary is organized around the following themes related to actualizing the perspective's methodological, assessment, and intervention potential and the potential shift in the theoretical underpinnings of mental disorders that networks models imply. First, extant data using network analysis suggest that reactions to traumatic stress are more complicated than once thought but that this complexity does not mean efficient, relatively simple heuristics to aid assessment and intervention do not exist. Attention to methodological issues in symptom assessment may help move this aspect of the research forward. Second, the extant research is largely correlational and has not yet established causal linkages, although temporal associations underlying network models are being identified. Prospective and intervention studies employing network analysis are critical. Third, the network perspective of PTSD symptoms may advance research on the mechanisms of risk and resilience (e.g., neurodevelopmental, cognitive behavioral, emotional, and social models) by helping link symptoms to theoretical causal processes. A developmental framework that views the effect of traumatic stress in terms of temporal cascades of reactions with both negative and potentially positive cognitive, behavioral, social, and emotional outcomes fits the network analysis model. Fourth, network models call into question some of the fundamental assumptions underlying the conceptualization of mental disorders, leaving several ontological questions and implications currently unanswered; research examining the implications of the new assumptions is needed.

Introduction to the Special Issue: Network Analysis of Traumatic Stress

Network analysis has emerged as a promising new statistical methodology for traumatic stress studies. The present special issue of the Journal of Traumatic Stress amalgamates the reports of 10 studies that employed network analysis to further the field's understanding of traumatic stress. The current issue includes reports of network analyses that sought to better understand the impact of different kinds of traumatic events, including childhood and gender-based trauma exposure, on PTSD symptomatology as defined under the DSM-5 and ICD-11, and examined the relation between PTSD symptoms and trauma-related dissociative experiences as well as the impact of psychological treatment on trauma recovery. A variety of research designs from a diverse group of international samples were employed, including concurrent, longitudinal, experience-sampling, and treatment outcome studies. Finally, a commentary on the articles included in this special issue was provided by Dr. Carl Weems.