Group and longitudinal intra-individual networks of eating disorder symptoms in adolescents and young adults at-risk for an eating disorder

A network analysis of eating disorder, PTSD, major depression, state-trait anxiety, and quality of life measures in eating disorder patients treated in residential care

BACKGROUND

The network approach in the eating disorder (ED) field has confirmed important links between EDs and posttraumatic stress disorder (PTSD) symptoms. However, studies including comorbid symptoms are scarce, which limits our understanding of potentially important connections. We hypothesised that anxiety, depression and poor quality of life (QOL) would provide a more complete picture of central, maintaining factors.

METHODS

Network analysis using R was performed in 2178 adult ED patients (91% female) admitted to residential treatment. Assessments included the ED Examination Questionnaire (EDEQ), the Eating Disorders Inventory (EDI-2), the PTSD Checklist for DSM-5 (PTSD clusters (PCL-5)), the Patient Health Questionnaire (PHQ-9), the Spielberger State-Trait Anxiety Scale (STAI), and the ED QOL Scale (EDQOL), which measure symptoms of EDs, PTSD, major depression, state-trait anxiety, and QOL, respectively.

RESULTS

EDI-2 ineffectiveness showed the highest centrality (expected influence) followed by EDI-2 interoceptive awareness, STAI state anxiety, EDEQ shape concern, EDQOL psychological subscale, and PTSD cluster D (hyperarousal) symptoms. Eating Disorder Quality of Life psychological and physical-cognitive subscales and PHQ-9 major depressive, STAI state anxiety and PCL-5 PTSD cluster E (negative alterations in mood and cognition) symptoms showed the highest bridge expected influence, suggesting their interactive role in maintaining ED-PTSD comorbidity.

CONCLUSIONS

This is the first network analysis of the interaction between ED and PTSD symptoms to include the comorbid measures of depression, anxiety, and QOL in a large clinical sample of ED patients. Our results indicate that several symptom clusters are likely to maintain ED-PTSD comorbidity and may be important targets of integrated treatment.

Testing the longitudinal relationship between muscle dysmorphia symptoms and suicidality: A network analysis investigation

Research on suicidality in muscle dysmorphia is limited despite the high rates of suicidal thoughts and behaviors in related disorders. This study employed network analysis to examine the longitudinal relationships between muscle dysmorphia symptoms, as well as the relations between MD symptoms and suicide risk factors. Fifty individuals (Mage = 30.6 years, 63 % male) meeting criteria for muscle dysmorphia received four daily surveys for three weeks. Multi-level vector autoregression analysis was used to estimate associations between muscle dysmorphia- and suicide-related thoughts, emotions, and behaviors. The most central nodes in the muscle dysmorphia networks related to assessing muscle size, dieting, using muscle-building supplements, experiencing body dissatisfaction, seeking reassurance, and avoiding others due to concerns about appearance. In the comorbidity networks, the most central suicide-related factors were feelings of burdensomeness, feeling disgusted, and dwelling on the past. Our findings indicated that various intrusive thoughts (body dissatisfaction, dieting), compulsions (seeking reassurance, body checking, supplement use), and beliefs (burden to others, disgust with oneself) predicted future engagement in muscle dysmorphia and suicide-related symptomology. Targeting intrusive thoughts and compulsions, as well as feelings of disgust and burdensomeness, may reduce the severity of these conditions.

Perfectionism and eating disorders in children and adolescents: A systematic review and meta-analysis

There is a consistent link between perfectionism and eating disorders, however no meta-analysis to date has synthesized this literature in children and adolescents. We hypothesized that there would be significant, small pooled correlations between perfectionism dimensions and eating disorder symptoms in children and adolescents. Published, peer-reviewed articles with standardised measures of perfectionism and eating disorder symptoms were included. Articles were excluded if the age range was over 18 years. Overall, 39 studies were included (N = 13,954 participants, M age = 13.7 years). Total perfectionism (r = 0.25), perfectionistic strivings (r = 0.21), and perfectionistic concerns (r = 0.31) had significant positive associations with eating disorder symptoms. Most studies were rated as fair or good quality. Limitations included high heterogeneity, insufficient studies to investigate age as a moderator, the inclusion of only English articles, and predominately cross-sectional studies which precluded causal inference. Higher perfectionism was associated with greater eating disorder symptoms in children and adolescents. Future research should focus on longitudinal studies of eating disorder symptoms in children and adolescents.

A Pilot, Time-Series Investigation of Depression, Anxiety, and Eating Disorder Symptoms in Adults Experiencing Major Depressive Symptoms: The Need for Eating Disorder Assessment and Research in Depression

Major Depressive Disorder (MDD) is a prevalent psychiatric disorder impacting 10-16% of Americans in their lifetime. Approximately 60% of individuals with MDD have comorbid anxiety disorders. Additionally, although scarce research has examined eating disorders (EDs) in depression, a bidirectional association exists between ED and MDD symptoms. The current pilot study (N = 31 individuals with moderate to severe depression) modeled networks of depressive, anxiety, and ED symptoms using intensive time-series data. This study also tested if temporal central symptoms predicted six-month clinical outcomes. The most central symptoms were guilt, self-dislike, lack of energy, and difficulty concentrating. Several anxiety and ED symptoms were also central, including physical anxiety, social anxiety, body dissatisfaction, and desire for thinness. The central symptom crying predicted six-month depression with a medium effect size. These findings suggest anxiety and ED symptoms may influence the day-to-day course of depression in some individuals with comorbid diagnoses, but predictors of symptoms across hours may differ from predictors across longer time scales (i.e., months). Time scale should be considered when conducting and interpreting research on MDD. Research, assessment, and treatment for MDD should continue to explore transdiagnostic approaches including anxiety and ED symptoms to optimize care for individuals with complex presentations.

Auditing the research practices and statistical analyses of the group-level temporal network approach to psychological constructs: A systematic scoping review

Network analyses have become increasingly common within the field of psychology, and temporal network analyses in particular are quickly gaining traction, with many of the initial articles earning substantial interest. However, substantial heterogeneity exists within the study designs and methodology, rendering it difficult to form a comprehensive view of its application in psychology research. Since the field is quickly growing and since there have been many study-to-study variations in terms of choices made by researchers when collecting, processing, and analyzing data, we saw the need to audit this field and formulate a comprehensive view of current temporal network analyses. To systematically chart researchers' practices when conducting temporal network analyses, we reviewed articles conducting temporal network analyses on psychological variables (published until March 2021) in the framework of a scoping review. We identified 43 articles and present the detailed results of how researchers are currently conducting temporal network analyses. A commonality across results concerns the wide variety of data collection and analytical practices, along with a lack of consistency between articles about what is reported. We use these results, along with relevant literature from the fields of ecological momentary assessment and network analysis, to formulate recommendations on what type of data is suited for temporal network analyses as well as optimal methods to preprocess and analyze data. As the field is new, we also discuss key future steps to help usher the field's progress forward and offer a reporting checklist to help researchers navigate conducting and reporting temporal network analyses.

Eating disorder psychopathology and resilience in Iranian college students: A network analysis

OBJECTIVE

Eating disorder (ED) psychopathology is common among Iranian college students. Resilience (i.e., the ability to bounce back and adapt in the face of adverse and stressful conditions) has been found to be a protective factor against ED psychopathology in the West. However, no research to date has examined resilience as a protective factor against ED psychopathology in Iran. The current study used network analysis to examine an ED and resilience network in an Iranian sample.

METHOD

Participants were Iranian college students (N = 478) who completed the Farsi-Eating Disorder Examination-Questionnaire and Farsi-Brief Resilience Scale. We estimated a network of ED symptoms and resilience processes and identified central and bridge symptoms.

RESULTS

Central ED and resilience nodes were discomfort in seeing one's own body, feeling guilty about eating due to shape/weight, and thinking about shape and weight making it difficult to concentrate. Having a hard time making it through stressful events bridged with binge eating and fear of losing control over eating.

CONCLUSION

Processes related to managing stress and binge eating appear to maintain the association between ED symptoms and resilience processes.

Eating disorder psychopathology dimensions based on individual co-occurrence patterns of symptoms over time: a dynamic time warp analysis in a large naturalistic patient cohort

PURPOSE

Most of the network approaches in eating disorders found the highest degree of centrality for symptoms related to weight and shape concerns. However, longitudinal analyses are scarce and may increase our insight of the complex characteristics and dynamics over time. In the current study, an alternative non-linear method to perform longitudinal network analyses, the dynamic time warp approach, was used to examine whether robust dimensions of eating disorder psychopathology symptoms could be found based on the individual dynamic interplay of eating disorder symptoms co-occurrence patterns in time.

METHODS

The study sample included a naturalistic cohort of patients (N = 255) with all eating disorder subtypes who were assessed with the eating disorder examination questionnaire (EDE-Q) at a minimum of four times during treatment. Dynamic time warp analyses yielded distance matrices within each individual patient, which were subsequently aggregated into symptom networks and dimensions at the group level.

RESULTS

Aggregation of the individual distance matrices at the group level yielded four robust symptom dimensions: 1. restraint/rules, 2. secret eating/fasting, 3. worries/preoccupation, and 4. weight and shape concern. The items 'fear of weight gain' and 'guilt' were bridge symptoms between the dimensions 1, 3 and 4.

CONCLUSION

Dynamic time warp could capture the within-person dynamics of eating disorder symptoms. Sumscores of the four dimensions could be used to follow patients over time. This approach could be applied in the future to visualize eating disorder symptom dynamics and signal the central symptoms within an individual and groups of patients.

LEVEL OF EVIDENCE

Level III: evidence obtained from well-designed cohort or case-control analytic studies. .

Integrating clinician and patient case conceptualization with momentary assessment data to construct idiographic networks: Moving toward personalized treatment for eating disorders

Eating disorders are serious psychiatric illnesses with treatments ineffective for about 50% of individuals due to high heterogeneity of symptom presentation even within the same diagnoses, a lack of personalized treatments to address this heterogeneity, and the fact that clinicians are left to rely upon their own judgment to decide how to personalize treatment. Idiographic (personalized) networks can be estimated from ecological momentary assessment data, and have been used to investigate central symptoms, which are theorized to be fruitful treatment targets. However, both efficacy of treatment target selection and implementation with 'real world' clinicians could be maximized if clinician input is integrated into such networks. An emerging line of research is therefore proposing to integrate case conceptualizations and statistical routines, tying together the benefits from clinical expertise as well as patient experience and idiographic networks. The current pilot compares personalized treatment implications from different approaches to constructing idiographic networks. For two patients with a diagnosis of anorexia nervosa, we compared idiographic networks 1) based on the case conceptualization from clinician and patient, 2) estimated from patient EMA data (the current default in the literature), and 3) based on a combination of case conceptualization and patient EMA data networks, drawing on informative priors in Bayesian inference. Centrality-based treatment recommendations differed to varying extent between these approaches for patients. We discuss implications from these findings, as well as how these models may inform clinical practice by pairing evidence-based treatments with identified treatment targets.

Eating disorder psychopathology and negative affect in Iranian college students: a network analysis

BACKGROUND

ED psychopathology is becoming more prevalent in Iran. Negative affect has been found to be an important risk factor in eating disorder (ED) onset in research conducted in Western countries, and is also emerging as a potential vulnerability factor to ED psychopathology in Iran. Network theory offers a novel framework to understand the association between negative affect and ED psychopathology in Iran. The primary aim of the current study was to use network analysis to identify bridge symptoms (i.e., symptoms that activate or weaken symptoms in another cluster) across a negative affect and ED psychopathology network among Iranian college students. We also aimed to identify core symptoms (i.e., nodes that demonstrate the strongest connections to other nodes).

METHOD

Participants were Iranian college students (n = 637; 60.3% women) who completed the Farsi-eating disorder examination-questionnaire and Farsi-negative affect. We estimated a network of ED symptoms and negative affective states and identified bridge and central symptoms.

RESULTS

Hostility and shame emerged as central bridge symptoms across the negative affect and ED psychopathology clusters. The most central nodes were strong desire to lose weight, definite fear of losing control over eating, and binge eating episodes.

CONCLUSION

The negative affective states of hostility and shame may increase vulnerability to ED psychopathology among Iranian college students. Findings have important implications for ED prevention programs that should be examined in future research.

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.

The dynamic network associations of food craving, restrained eating, hunger and negative emotions

OBJECTIVE

Food craving, restrained eating, hunger, and negative emotions may predict and reinforce one another. However, less is known about how they interact together as a complex system in daily life. Therefore, we used a dynamic network approach to examine the associations between food craving, restrained eating, hunger and negative emotions in daily life.

METHODS

Food craving, restrained eating, hunger and negative emotions were measured using ecological momentary assessment three times a day over ten days in a community sample in Israel (n = 123). A two-step multilevel vector auto-regression network analysis was used to estimate temporal, contemporaneous and between-persons networks.

RESULTS

In the temporal network, restrained eating was the most central predictor of eating behaviors and negative emotions, predicting food craving and hunger as well as sadness and loneliness. Food craving was also predicted by hunger and stress, and hunger predicted loneliness. In the contemporaneous network, food craving was associated with hunger and feeling bored, and higher anger was associated with lower restrained eating. Stress and sadness were central negative emotions in the models.

DISCUSSION

This study suggests possible temporal and contemporaneous relationships between food craving, restrained eating, hunger and negative emotions, emphasizing their complex interactions in daily life. Restrained eating and stress should be investigated as potential targets for interventions addressing food craving and overeating.

Cross-sectional and longitudinal AUD symptom networks: They tell different stories

Modern theoretical models of Alcohol Use Disorder (AUD) highlight the different functional roles played by various mechanisms associated with different symptoms. Symptom network models (SNMs) offer one approach to modeling AUD symptomatology in a way that could reflect these processes and provide important information on the progression and persistence of disorder. However, much of the research conducted using SNMs relies on cross-sectional data, which has raised questions regarding the extent they reflect dynamic processes. The current study aimed to (a) examine symptom networks of AUD and (b) compare the extent to which cross-sectional network models had similar structures and interpretations as longitudinal network models. 17,360 participants from Wave 1 (2001-2002) and Wave 2 (2003-2004) of the National Epidemiological Survey on Alcohol and Related Conditions (NESARC) were used to model cross-sectional and longitudinal AUD symptom networks. The cross-sectional analyses demonstrate high replicability across waves and central symptoms consistent with other cross-sectional studies on addiction networks. The longitudinal network shared much less similarity than the cross-sectional networks and had a substantially different structure. Given the increasing attention given to the network perspective in psychopathology research, the results of this study raise concerns about interpreting cross-sectional symptom networks as representative of temporal changes occurring within a psychological disorder. We conclude that the psychological symptom network literature should be bolstered with additional research on longitudinal network models.

A network approach can improve eating disorder conceptualization and treatment

Eating disorders are severe mental illnesses with the second highest mortality rate of all psychiatric illnesses. Eating disorders are exceedingly deadly because of their complexity. Specifically, eating disorders are highly comorbid with other psychiatric illnesses (up to 95% of individuals with an eating disorder have at least one additional psychiatric illness), have extremely heterogeneous presentations, and individuals often migrate from one specific eating disorder diagnosis to another. In this Perspective, we propose that understanding eating disorder comorbidity and heterogeneity via a network theory approach offers substantial benefits for both conceptualization and treatment. Such a conceptualization, strongly based on theory, can identify specific pathways that maintain psychiatric comorbidity, how diagnoses vary across individuals, and how specific symptoms and comorbidities maintain illness for one individual, thereby paving the way for personalized treatment.

Eating disorder and social anxiety symptoms in Iranian preadolescents: a network analysis

PURPOSE

Network studies of eating disorder (ED) symptoms have identified central and bridge symptoms in Western samples, yet few network models of ED symptoms have been tested in non-Western samples, especially among preadolescents. The current study tested a network model of ED symptoms in Iranian preadolescents (ages 9 to 13), as well as a model of co-occurring social anxiety disorder (SAD) and ED symptoms.

METHOD

Preadolescent boys (n = 405) and girls (n = 325) completed the Children Eating Attitudes Test-20 and Social Anxiety Scale for Children. We estimated two network models (ED and ED/SAD networks) and identified central and bridge symptoms, as well as tested if these models differed by sex.

RESULTS

We found that discomfort eating sweets were the most central symptoms in ED networks. Concern over being judged was central in networks including both ED and SAD symptoms. Additionally, concern over being judged was the strongest bridge symptoms. Networks did not differ by sex.

CONCLUSION

Future research is needed to test if interventions focused on bridge symptoms (i.e., concern over being judged) as primary intervention points target comorbid ED-SAD pathology in preadolescents at risk for ED and SAD.

LEVEL OF EVIDENCE

Level III; Evidence obtained from well-designed observational study, including case-control design for relevant aspects of the study.

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).

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

OBJECTIVE

This study was designed to compare the change in eating-disorder feature networks in patients with anorexia nervosa after treatment with intensive enhanced cognitive behavior therapy (CBT-E).

METHODS

Patients seeking treatment for anorexia nervosa were consecutively recruited from January 2016 to September 2020. All patients aged ≥16 years who completed a 20-week intensive CBT-E program (13 weeks of inpatient followed by 7 weeks of day-hospital treatment) were included in the study. Body mass index (BMI) was measured, and the Eating Disorder Examination Questionnaire completed for each patient, both at baseline and the end of treatment.

RESULTS

The sample comprised 214 patients with anorexia nervosa. Treated patients showed significant improvements in BMI and eating-disorder psychopathology. Network analysis revealed a significant reduction in the network global and connection strengths at the end of treatment. The most central and highly interconnected nodes in the network at baseline were related to the drive for thinness, but at the end of treatment to body image concerns. Some edge connections were significantly stronger at baseline than at the end of treatment, while others were significantly stronger at the end of treatment than at baseline.

DISCUSSION

CBT-E reduces the psychopathology network connectivity over time in patients with anorexia nervosa. The differences in central nodes and edge connections between baseline and end of treatment, not detected by classical inferential analysis, may be informative for understanding the centrality of symptoms in the psychopathology network, and how a specific treatment may act to reduce symptoms and change their connections over time.

A systematic review of network analysis studies in eating disorders: Is time to broaden the core psychopathology to non specific symptoms

Objective

Network theory considers mental disorders as the product of symptom interaction. A growing number of studies employing this methodology has been conducted in eating disorders (EDs). We aimed to review those studies to provide evidence and limitations for a novel conceptualisation of EDs.

Methods

According to PRISMA guidelines and PICOS criteria, studies eligible for inclusion were those employing network analysis in people with a clinically defined diagnosis of ED. Twenty‐five studies were included and were analysed in relation to diagnosis, comorbidity, and treatment outcome.

Results

Despite the central role of overvaluation of body shape and weight and cognitive restraint across ED diagnoses, ineffectiveness, interoceptive awareness and affective problems appear central symptoms. Ineffectiveness and interoceptive awareness emerge as bridge symptoms promoting comorbidity in people with anorexia nervosa and in mixed ED samples. Although few studies assessed treatment outcome, there is evidence supporting the predictive role of central network nodes.

Conclusions

Ineffectiveness, interoceptive ability and affective problems may be included in the core ED psychopathology, in addition to ED‐specific symptoms. Network analysis is a promising method to reconceptualize comorbidity. Future studies are recommended to include general psychopathology in ED networks, to assess connections with the external field and clinical meaning of network connectivity.

Overvaluation of body shape and weight and cognitive restraint appear as central nodes across eating disorder diagnoses and ages.

In addition to specific symptoms, ineffectiveness, low interoceptive ability and affective problems also emerge as central nodes in eating disorders.

There is some evidence to point to ineffectiveness and low interoceptive ability as bridge nodes promoting psychiatric comorbidity.

Only few studies assessed treatment outcome through the network analysis approach

Unhealthy life habits associated with self-induced vomiting and laxative misuse in Brazilian adolescents

Adolescence is a stage in life characterized by important social, cognitive, and physical changes. Adolescents are vulnerable to various psychosocial disorders, including eating disorders. We aimed to investigate the association between unhealthy habits, sociodemographic characteristics, and the practice of self-induced vomiting or laxative misuse in a representative sample of Brazilian adolescent girls and boys. Data from 102,072 students who participated in the National Adolescent School-based Health Survey were analyzed using the dependent variable: presence or absence of self-induced vomiting and/or laxative misuse; independent variables: consumption of unhealthy and high-calorie food items, age during first sexual intercourse, and the use of tobacco, alcohol, and/or illicit drugs. Associations between exposure and outcome were estimated using Poisson's regression models stratified by sex, and including region, school, age group, and mother's educational history as adjustment variables. Eating ultra-processed foods and age during first sexual intercourse were associated with self-induced vomiting and laxative misuse only for girls; all other variables (consuming unhealthy foods and using legal or illicit substances) were associated with these behaviors for both sexes after applying adjustment variables. Early interventions focusing on changing unhealthy behaviors may prevent development of eating disorders in adolescents. Our findings demonstrate a strong association of many unhealthy habits with laxative misuse and self-induced vomiting practices in Brazilian adolescents.