Change in eating-disorder psychopathology network structure in patients with anorexia nervosa treated with intensive cognitive behavior therapy

Using network analysis to characterize clinical improvement during cognitive processing therapy

OBJECTIVE

Cross-sectional network studies find mixed results regarding changes in network structure as a response to treatment across disorders. This study characterized improvement in mental health following Cognitive Processing Therapy (CPT) for PTSD in veterans from the perspective of network psychometrics and explored how cross-sectional networks inform our understanding of PTSD recovery.

METHODS

Veterans with PTSD participated in CPT-based intensive treatment programs (ITPs), offered in two-week (N = 635) or three-week (N = 457) formats. PTSD symptoms were self-reported on the PTSD Checklist for DSM-5 (PCL-5) at pre-, mid-, and post-treatment. Cross-sectional networks for each time point were compared using network comparison tests. Linear regression tested if the relationship of initial treatment gains from admission to mid-treatment with overall outcomes was associated with the expected influence centrality of a node.

RESULTS

Substantial improvement in PTSD symptoms were found, but network structure remained largely unaffected, with global edge strength increasing from pre-to post-treatment. Initial treatment gains in nodes with high expected influence were associated with overall treatment outcomes. A post-hoc simulation based on a common-cause model produced similar regression results, indicating that while our findings align with spreading activation, they are not exclusive to this mechanism.

CONCLUSION

The indiscernibility of cross-sectional networks between pre- and post-treatment raises questions about whether cross-sectional networks can illuminate PTSD recovery beyond traditional measures of treatment response.

Investigating change in network structure of eating disorder symptoms after delivery of a smartphone app-based intervention

BACKGROUND

Eating disorder (ED) research has embraced a network perspective of psychopathology, which proposes that psychiatric disorders can be conceptualized as a complex system of interacting symptoms. However, existing intervention studies using the network perspective have failed to find that symptom reductions coincide with reductions in strength of associations among these symptoms. We propose that this may reflect failure of alignment between network theory and study design and analysis. We offer hypotheses for specific symptom associations expected to be disrupted by an app-based intervention, and test sensitivity of a range of statistical metrics for identifying this intervention-induced disruption.

METHODS

Data were analyzed from individuals with recurrent binge eating who participated in a randomized controlled trial of a cognitive-behavioral smartphone application. Participants were categorized into one of three groups: waitlist (n = 155), intervention responder (n = 49), and intervention non-responder (n = 77). Several statistical tests (bivariate associations, network-derived strength statistics, network invariance tests) were compared in ability to identify change in network structure.

RESULTS

Hypothesized disruption to specific symptom associations was observed through change in bivariate correlations from baseline to post-intervention among the responder group but were not evident from symptom and whole-of-network based network analysis statistics. Effects were masked when the intervention group was assessed together, ignoring heterogeneity in treatment responsiveness.

CONCLUSION

Findings are consistent with our contention that study design and analytic approach influence the ability to test network theory predictions with fidelity. We conclude by offering key recommendations for future network theory-driven interventional studies.

Emotion dysregulation links pathological eating styles and psychopathological traits in bariatric surgery candidates

Objectives

Approximately one-third of bariatric surgery patients experience weight regain or suboptimal weight loss within five years post-surgery. Pathological eating styles and psychopathological traits (e.g., emotion dysregulation) are recognized as potential hindrances to sustain weight loss efforts and are implicated in obesity development. A comprehensive understanding of these variables and their interplays is still lacking, despite their potential significance in developing more effective clinical interventions for bariatric patients. We investigate the prevalence of and interactions between pathological eating styles and psychopathological traits in this population.

Materials and methods

110 bariatric surgery candidates were characterized using the Binge Eating Scale (BES), Hamilton Depression/Anxiety Scales (HAM-D/A), Barratt Impulsiveness Scale (BIS-11), Experiences in Close Relationships (ECR), Difficulties in Emotion Regulation Scale (DERS). We analyzed these variables with multiple logistic regression analyses and network analysis.

Results

Patients with pathological eating styles showed more pronounced anxiety/depressive symptoms and emotion dysregulation. Network analysis revealed strong connections between BES and DERS, with DERS also displaying robust connections with HAM-A/D and ECR scales. DERS and attention impulsivity (BIS-11-A) emerged as the strongest nodes in the network.

Discussion

Our findings demonstrate the mediating role of emotion dysregulation between pathological eating styles and psychopathological traits, supporting existing literature on the association between psychopathological traits, insecure attachment styles, and pathological eating behaviors. This research emphasizes the significance of emotion regulation in the complex network of variables contributing to obesity, and its potential impact on bariatric surgery outcomes. Interventions focusing on emotion regulation may thus lead to improved clinical outcomes for bariatric patients.

Structure and factorial invariance of a brief version of the Eating Attitudes Test in Peruvian university students

Background

University students often experience significant changes in their eating habits, which can increase the risk of developing eating disorders (ED). This situation calls for the creation of brief assessment tools to identify college students who may be most at risk. The aim of the study was to determine the psychometric properties of the Eating Attitudes Test-8 (EAT-8) in a Peruvian university population; additionally, the possible differences in the scores of the instrument according to sociodemographic variables, such as gender and age, were examined.

Methods

A psychometric study was conducted on 610 participants (M = 24.3, SD = 2.16, and 61.5% female), aged 19 to 31 years, belonging to four universities of different professional careers.

Results

The unidimensional eight-item model was found to have fit indices that confirm acceptable factorial validity (X2/df = 3.23, CFI = 0.984, TLI = 0.977, RMSEA = 0.061, SRMR = 0.049) and an internal consistency of 0.833 for the Cronbach's alpha coefficient and 0.838 for the McDonald's omega coefficient. In addition, the EAT-8 was reported to be invariant according to gender and age; likewise, there were no significant differences in the age and gender categories.

Conclusion

The EAT-8 has solid psychometric properties, including validity, reliability, and invariance, in the Peruvian university population, which supports its ability to assess the risk of developing ED in this specific group.

A systematic review and meta-analysis of intensive treatment options for adults with eating disorders

Eating disorders (EDs) are complex conditions with one of the highest mortality rates among psychiatric illnesses. While outpatient evidence-based treatments for EDs in adults exist, there is often utilisation of more intensive interventions as part of treatment. However, a comprehensive analysis of the impacts of intensive treatment (inpatient, residential and day program) on physical and psychosocial outcomes is lacking. Thus, the current systematic review and meta-analysis aimed to investigate the effectiveness of intensive treatments in adults with EDs for the outcomes of body mass index (BMI), disordered eating, depression, and quality of life, as well as a moderation analysis investigating a range of clinical characteristics. Overall, 62 studies were included in the meta-analysis. The results revealed that intensive treatment in adults yielded significant improvements in BMI (for underweight patients), disordered eating, depression, and quality of life. Treatment setting, length of stay and geographical region of the study all served as moderators for disordered eating and depression. Nevertheless, given the high heterogeneity in the meta- and moderation analyses, these results should be interpreted with caution. Future high-quality research is needed to determine the most beneficial elements of intensive treatment (compared to outpatient) in adults with EDs.

Psychotherapies for eating disorders: findings from a rapid review

BACKGROUND

Psychotherapy is considered central to the effective treatment of eating disorders-focusing on behavioural, psychological, and social factors that contribute to the illness. Research indicates psychotherapeutic interventions out-perform placebo, waitlist, and/or other treatments; but, outcomes vary with room for major improvement. Thus, this review aims to (1) establish and consolidate knowledge on efficacious eating disorder psychotherapies; (2) highlight select emerging psychotherapeutic interventions; and (3) identify knowledge gaps to better inform future treatment research and development.

METHODS

The current review forms part of a series of Rapid Reviews published in a special issue in the Journal of Eating Disorders to inform the development of the Australian-government-funded National Eating Disorder Research and Translation Strategy 2021-2031. Three databases were searched for studies published between 2009 and 2023, published in English, and comprising high-level evidence studies (meta-analyses, systematic reviews, moderately sized randomised controlled studies, moderately sized controlled-cohort studies, and population studies). Data pertaining to psychotherapies for eating disorders were synthesised and outlined in the current paper.

RESULTS

281 studies met inclusion criteria. Behavioural therapies were most commonly studied, with cognitive-behavioural and family-based therapies being the most researched; and thus, having the largest evidence-base for treating anorexia nervosa, bulimia nervosa, and binge eating disorder. Other therapies, such as interpersonal and dialectical behaviour therapies also demonstrated positive treatment outcomes. Emerging evidence supports specific use of Acceptance and Commitment; Integrative Cognitive Affective; Exposure; Mindfulness; and Emotionally-Focused therapies; however further research is needed to determine their efficacy. Similarly, growing support for self-help, group, and computer/internet-based therapeutic modalities was noted. Psychotherapies for avoidant/restrictive food intake disorder; other, and unspecified feeding and eating disorders were lacking evidence.

CONCLUSIONS

Currently, clinical practice is largely supported by research indicating that behavioural and cognitive-behavioural psychotherapies are most effective for the treatment of eating disorders. However, the efficacy of psychotherapeutic interventions varies across studies, highlighting the need for investment and expansion of research into enhanced variants and novel psychotherapies to improve illness outcomes. There is also a pressing need for investigation into the whole range of eating disorder presentations and populations, to determine the most effective interventions.

Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders

Assessing the validity of a psychometric test is fundamental to ensure a reliable interpretation of its outcomes. Few attempts have been made recently to complement classical approaches (e.g., factor models) with a novel technique based on network analysis. The objective of the current study is to carry out a network-based validation of the Eating Disorder Inventory 3 (EDI-3), a questionnaire designed for the assessment of eating disorders. Exploiting a reliable, open source sample of 1206 patients diagnosed with an eating disorder, we set up a robust validation process encompassing detection and handling of redundant EDI-3 items, estimation of the cross-sample psychometric network, resampling bootstrap procedure and computation of the median network of the replica samples. We then employed a community detection algorithm to identify the topological clusters, evaluated their coherence with the EDI-3 subscales and replicated the full validation analysis on the subpopulations corresponding to patients diagnosed with either anorexia nervosa or bulimia nervosa. Results of the network-based analysis, and particularly the topological community structures, provided support for almost all the composite scores of the EDI-3 and for 2 single subscales: Bulimia and Maturity Fear. A moderate instability of some dimensions led to the identification of a few multidimensional items that should be better located in the intersection of multiple psychological scales. We also found that, besides symptoms typically attributed to eating disorders, such as drive for thinness, also non-specific symptoms like low self-esteem and interoceptive deficits play a central role in both the cross-sample and the diagnosis-specific networks. Our work adds insights into the complex and multidimensional structure of EDI-3 by providing support to its network-based validity on both mixed and diagnosis-specific samples. Moreover, we replicated previous results that reinforce the transdiagnostic theory of eating disorders.

Network analysis studies in patients with eating disorders: A systematic review and methodological quality assessment

INTRODUCTION

Network psychometrics has been enthusiastically embraced by researchers studying eating disorders (ED), but a rigorous evaluation of the methodological quality of works is still missing. This systematic review aims to assess the methodological quality of cross-sectional network analysis (NA) studies conducted on ED clinical populations.

METHODS

PRISMA and PICOS criteria were used to retrieve NA studies on ED. Methodological quality was evaluated based on five criteria: variable-selection procedure, network estimation method, stability checks, topological overlap checks, and handling of missing data.

RESULTS

Thirty-three cross-sectional NA studies were included. Most studies focused on populations that were female, white and, with an anorexia nervosa (AN) diagnosis. Depending on how many criteria were satisfied, 27.3% of studies (n = 9) were strictly adherent, 30.3% (n = 10) moderately adherent, 33.3% (n = 11) sufficiently adherent, and 9.1% (n = 3) poorly adherent. Missing topological overlap checks and not reporting missing data represented most unreported criteria, lacking, respectively, in 63.6% and 48.5% of studies.

CONCLUSIONS

Almost all reviewed cross-sectional NA studies on ED report those methodological procedures (variable-selection procedure, network estimation method, stability checks) necessary for a network study to provide reliable results. Nonetheless these minimum reporting data require further improvement. Moreover, elements closely related to the validity of an NA study (controls for topological overlap and management of missing data) are lacking in most studies. Recommendations to overcome such methodological weaknesses in future NA studies on ED are discussed together with the need to conduct NA studies with longitudinal design, to address diversity issues in study samples and heterogeneity of assessment tools.

PUBLIC SIGNIFICANCE

The present work aims to evaluate the quality of ED NA studies to support applications of this approach in ED research. Results show that most studies adopted basic procedures to produce reliable results; however, other important procedures linked to NA study validity were mostly neglected. Network methodology in ED is extremely promising, but future studies should consistently include topological overlap control procedures and provide information on missing data.

Network-based methods for psychometric data of eating disorders: A systematic review

BACKGROUND

Network science represents a powerful and increasingly promising method for studying complex real-world problems. In the last decade, it has been applied to psychometric data in the attempt to explain psychopathologies as complex systems of causally interconnected symptoms. One category of mental disorders, relevant for their severity, incidence and multifaceted structure, is that of eating disorders (EDs), serious disturbances that negatively affect a person's eating behavior.

AIMS

We aimed to review the corpus of psychometric network analysis methods by scrutinizing a large sample of network-based studies that exploit psychometric data related to EDs. A particular focus is given to the description of the methodologies for network estimation, network description and network stability analysis providing also a review of the statistical software packages currently used to carry out each phase of the network estimation and analysis workflow. Moreover, we try to highlight aspects with potential clinical impact such as core symptoms, influences of external factors, comorbidities, and related changes in network structure and connectivity across both time and subpopulations.

METHODS

A systematic search was conducted (February 2022) on three different literature databases to identify 57 relevant research articles. The exclusion criteria comprehended studies not based on psychometric data, studies not using network analysis, studies with different aims or not focused on ED, and review articles.

RESULTS

Almost all the selected 57 papers employed the same analytical procedures implemented in a collection of R packages specifically designed for psychometric network analysis and are mostly based on cross-sectional data retrieved from structured psychometric questionnaires, with just few exemptions of panel data. Most of them used the same techniques for all phases of their analysis. In particular, a pervasive use of the Gaussian Graphical Model with LASSO regularization was registered for in network estimation step. Among the clinically relevant results, we can include the fact that all papers found strong symptom interconnections between specific and nonspecific ED symptoms, suggesting that both types should therefore be addressed by clinical treatment.

CONCLUSIONS

We here presented the largest and most comprehensive review to date about psychometric network analysis methods. Although these methods still need solid validation in the clinical setting, they have already been able to show many strengths and important results, as well as great potentials and perspectives, which have been analyzed here to provide suggestions on their use and their possible improvement.

Changes in specific and nonspecific psychopathology network structure after intensive cognitive behavior therapy in patients with anorexia nervosa

OBJECTIVE

This study aimed to compare eating disorder-specific and nonspecific clinical features in patients with anorexia nervosa before and after intensive enhanced cognitive behavior therapy (CBT-E) via network analysis.

METHODS

All consecutive patients admitted to intensive CBT-E were eligible, and the sample comprised patients aged ≥16 years who completed a 20-week intensive CBT-E program. Body mass index (BMI), Eating Disorder Examination Questionnaire and Brief Symptoms Inventory responses were gathered at baseline and end of treatment, and used to generate statistical networks of the connections between symptoms (nodes) and the strength and centrality thereof.

RESULTS

A total of 214 patients were included. Most nodes had relatively similar centrality compared to other nodes in the networks. "Eating concern" and "phobic anxiety" showed the greatest bridge centrality at both time points. No differences were found between baseline and the end of treatment in either global network or individual connection strengths.

CONCLUSION

These findings suggest that some clinical expressions not specific to eating-disorder psychopathology remain strongly connected in the generalized network of patients with anorexia nervosa after CBT-E. Future research should examine whether additional procedures specifically designed to target these symptoms should be integrated into this and other treatments.