The psychometric network structure of mental health in eating disorder patients

Exploring mental health dynamics during eating disorder treatment: A psychometric network study with panel data

To explore mental health associations during eating disorder (ED) treatment. Based on the dual-continua model of mental health, general and ED-specific psychopathology, as well as emotional, psychological, and social well-being were considered as mental health domains.

Network analyses with panel data were applied to explore within- (temporal and contemporaneous networks) and between-person effects in a sample of 1250 female ED patients during 12 months of outpatient treatment. The associations between the domains and their centrality were examined. Autoregressive and cross-lagged effects were also estimated.

ED psychopathology was the most central domain in the temporal network. ED psychopathology changes predicted further ED psychopathology changes and small changes in the other domains. Weak bi-directional associations were found between changes in the well-being domains and general psychopathology. In contrast to the temporal network, ED psychopathology was the least central and psychological well-being the most central domain in the contemporaneous and between-subjects networks. This suggests a central role of psychological well-being for experiencing mental health within time points.

ED psychopathology may change relatively independent from other mental health domains. Well-being domains may be considered as more stable aspects of mental health.

A new network analysis model in anorexia nervosa patients based on self-reported eating disorder symptoms, psychological distress, and cognitive flexibility

OBJECTIVES

Cognitive flexibility and psychological distress, such as depression and anxiety, have been implicated in the aetiology of Anorexia Nervosa (AN). Despite the known associations between eating disorder (ED) symptoms, depression, anxiety, and cognitive flexibility, the specific pathways that connect these constructs are unclear. We therefore used network analysis to examine the relationship between these symptoms in an AN sample.

METHODS

One hundred and ninety-three treatment-seeking individuals diagnosed with AN (95.6% female, M = 26.89 [SD = 9.45] years old) completed self-report measures assessing depression, anxiety, cognitive flexibility, and ED symptoms. To determine each symptom's influence in the network, we calculated the expected influence.

RESULTS

The two relationships with the greatest edges were those between (1) weight/shape concerns and eating/dietary restraint and (2) weight/shape concerns and psychological distress (a measure that combined depression and anxiety). Cognitive flexibility was not connected to weight/shape concerns but had negative partial associations with eating concerns/dietary restraint and psychological distress. There was also a slight, non-zero connection between eating concerns/dietary restraint and psychological distress.

CONCLUSIONS

The findings underscore the importance of weight/shape, eating/dietary concerns, and psychological distress in the AN network and suggest that addressing cognitive flexibility may be a useful target for eating concerns/dietary restraint and psychological distress. Future studies assessing the longitudinal course of psychopathology within the AN network structure may help in identifying whether specific symptoms function as risk factors or maintaining factors for this co-occurrence.

Outcomes in people with eating disorders: a transdiagnostic and disorder-specific systematic review, meta-analysis and multivariable meta-regression analysis

Eating disorders (EDs) are known to be associated with high mortality and often chronic and severe course, but a recent comprehensive systematic review of their outcomes is currently missing. In the present systematic review and meta-analysis, we examined cohort studies and clinical trials published between 1980 and 2021 that reported, for DSM/ICD-defined EDs, overall ED outcomes (i.e., recovery, improvement and relapse, all-cause and ED-related hospitalization, and chronicity); the same outcomes related to purging, binge eating and body weight status; as well as mortality. We included 415 studies (N=88,372, mean age: 25.7±6.9 years, females: 72.4%, mean follow-up: 38.3±76.5 months), conducted in persons with anorexia nervosa (AN), bulimia nervosa (BN), binge eating disorder (BED), other specified feeding and eating disorders (OSFED), and/or mixed EDs, from all continents except Africa. In all EDs pooled together, overall recovery occurred in 46% of patients (95% CI: 44-49, n=283, mean follow-up: 44.9±62.8 months, no significant ED-group difference). The recovery rate was 42% at <2 years, 43% at 2 to <4 years, 54% at 4 to <6 years, 59% at 6 to <8 years, 64% at 8 to <10 years, and 67% at ≥10 years. Overall chronicity occurred in 25% of patients (95% CI: 23-29, n=170, mean follow-up: 59.3±71.2 months, no significant ED-group difference). The chronicity rate was 33% at <2 years, 40% at 2 to <4 years, 23% at 4 to <6 years, 25% at 6 to <8 years, 12% at 8 to <10 years, and 18% at ≥10 years. Mortality occurred in 0.4% of patients (95% CI: 0.2-0.7, n=214, mean follow-up: 72.2±117.7 months, no significant ED-group difference). Considering observational studies, the mortality rate was 5.2 deaths/1,000 person-years (95% CI: 4.4-6.1, n=167, mean follow-up: 88.7±120.5 months; significant difference among EDs: p<0.01, range: from 8.2 for mixed ED to 3.4 for BN). Hospitalization occurred in 26% of patients (95% CI: 18-36, n=18, mean follow-up: 43.2±41.6 months; significant difference among EDs: p<0.001, range: from 32% for AN to 4% for BN). Regarding diagnostic migration, 8% of patients with AN migrated to BN and 16% to OSFED; 2% of patients with BN migrated to AN, 5% to BED, and 19% to OSFED; 9% of patients with BED migrated to BN and 19% to OSFED; 7% of patients with OSFED migrated to AN and 10% to BN. Children/adolescents had more favorable outcomes across and within EDs than adults. Self-injurious behaviors were associated with lower recovery rates in pooled EDs. A higher socio-demographic index moderated lower recovery and higher chronicity in AN across countries. Specific treatments associated with higher recovery rates were family-based therapy, cognitive-behavioral therapy (CBT), psychodynamic therapy, and nutritional interventions for AN; self-help, CBT, dialectical behavioral therapy (DBT), psychodynamic therapy, nutritional and pharmacological treatments for BN; CBT, nutritional and pharmacological interventions, and DBT for BED; and CBT and psychodynamic therapy for OSFED. In AN, pharmacological treatment was associated with lower recovery, and waiting list with higher mortality. These results should inform future research, clinical practice and health service organization for persons with EDs.

Eating disorders symptoms and depressive symptoms in Chinese Tibetan University students: a network analysis

BACKGROUND

Depression is being increasingly acknowledged as a global public health concern, and following this trend, attention towards eating disorders (EDs) has surged within China's national consciousness. EDs symptoms frequently coexist with various mental health conditions, including depression. However, research focusing on EDs symptoms and depressive symptoms among Tibetan students in China remains scant. This study employs network analysis to estimate the relational network between EDs and depressive symptoms.

METHODS

Tibetan (n = 2,582) and Han (n = 1,743) students from two universities in the Xizang Autonomous Region, China, completed the Eating Attitude Test-26 (EAT-26) and the Patient Health Questionnaire-9 (PHQ-9). We estimated the network structure of EDs symptoms and depressive symptoms, identified central and bridge symptoms, and examined whether network characteristics differed by gender and ethnic.

RESULTS

The core symptoms identified within this study were Calorie_awareness, Desire_to_thin and Fatigue. Conversely, bridge symptoms included Appetite, Suicide, Anhedonia, Guilty, Body_fat_awareness, and Food_preoccupation. The study also revealed no significant gender differences within the network model. However, disparities among ethnic groups were observed within the network structure.

CONCLUSIONS

Our study examined the correlation between EDs symptoms and depressive symptoms in Tibetan college students. Focusing on the individual's quest for the perfect body shape and some Tibetan students' appetite problems - potentially stemming from transitioning to a new university environment, adapting to the school canteen's diet, or being away from their hometown - could aid in the prevention and management of EDs and depression symptoms. It could reduce the incidence of complications by helping students maintain good physical and mental health. Concurrently, our research provides insights into the relatively higher levels of depression triggered by the unique plateau environment.

An investigation of the dual continua model of mental health in the context of eating disorder symptomatology using latent profile analysis

OBJECTIVE

The dual continua model of mental health suggests that mental well-being and mental illness are two distinct continua that are interrelated in their contributions to overall mental health. This study investigated the dual continua model in individuals with eating disorder symptoms.

METHOD

Female university students (N = 346) completed measures of mental well-being, eating disorder symptomatology, clinical impairment and psychological distress. Confirmatory factor and latent profile analyses were used to derive underlying mental health profiles.

RESULTS

Results revealed two oblique factors representing the mental well-being and eating disorder symptomatology constructs and four unique mental health profiles that were partially consistent with the dual continua model emerged: 'flourishing', 'vulnerable', 'partially symptomatic and content', and 'languishing'. The derived mental health profiles had unique characteristics described by psychological distress and clinical impairment.

CONCLUSIONS

The results did not provide conclusive evidence for the dual continua model as they could also be interpreted in a manner consistent with the unidimensional approach. While the dual continua model is a promising avenue to understand mental health in a way that looks beyond symptoms, these results caution against its rapid adoption and encourage future research to understand how eating disorder symptomatology and positive mental health assets contribute to overall mental health.

A roadmap for applying machine learning when working with privacy-sensitive data: predicting non-response to treatment for eating disorders

OBJECTIVES

Applying machine-learning methodology to clinical data could present a promising avenue for predicting outcomes in patients receiving treatment for psychiatric disorders. However, preserving privacy when working with patient data remains a critical concern.

METHODS

In showcasing how machine-learning can be used to build a clinically relevant prediction model on clinical data, we apply two commonly used machine-learning algorithms (Random Forest and least absolute shrinkage and selection operator) to routine outcome monitoring data collected from 593 patients with eating disorders to predict absence of reliable improvement 12 months after entering outpatient treatment.

RESULTS

An RF model trained on data collected at baseline and after three months made 31.3% fewer errors in predicting lack of reliable improvement at 12 months, in comparison with chance. Adding data from a six-month follow-up resulted in only marginal improvements to accuracy.

CONCLUSION

We were able to build and validate a model that could aid clinicians and researchers in more accurately predicting treatment response in patients with EDs. We also demonstrated how this could be done without compromising privacy. ML presents a promising approach to developing accurate prediction models for psychiatric disorders such as ED.

Network analysis of eating disorder and depression symptoms among university students in the late stage of COVID-19 pandemic in China

Background

Eating disorders (EDs) and depression are common in university students, especially during the COVID-19 pandemic. The aim of this study was to elucidate characteristics of EDs and depression symptoms networks among Chinese university students in the later stage of the COVID-19 pandemic in China.

Methods

A total of 929 university students completed the SCOFF questionnaire measuring EDs and Patient Health Questionnaire with 9 items (PHQ-9) measuring depression in Guangzhou, China. The network model was applied to identify central symptoms, bridge symptoms, and important connections between SCOFF and PHQ-9 using R studio. The subgroup analyses of both genders in medical and non-medical students were further explored.

Results

In the networks of the whole sample, central symptoms included "Loss of control over eating" (EDs) and "Appetite changes" (depression). The bridge connections were between "Loss of control over eating" (EDs) and "Appetite changes" (depression), between "Deliberate vomiting" (EDs) and "Thoughts of death" (depression). "Appetite changes" (depression) and "Feeling of worthlessness" (depression) were central symptoms in both subgroups of medical and non-medical students. "Fatigue" (depression) was the central symptom in the female and medical students group. The edge between "Loss of control over eating" (EDs) and "Appetite changes" (depression) acted as a bridge in all subgroups.

Conclusion

Social network approaches offered promising ways of further understanding the association between EDs and depression among university students during the pandemic of COVID-19 in China. Investigations targeting central and bridge symptoms would help to develop effective treatments for both EDs and depression for this population.

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.

Integral definition and conceptual model of mental health: Proposal from a systematic review of different paradigms

Global society presents a mental health scenario characterized by the prevalence of mental disorders and the limited existence of formal care services. Faced with such a context, it is necessary to review what is understood and done in favor of mental health. This implies, in the first instance, analyzing the concept of mental health from a comprehensive approach that takes into account different perspectives from the social and natural sciences, related factors, and care options. Therefore, the present work aimed to propose an integral definition and a conceptual model of mental health based on the Systematic Literature Review, with the PRISMA approach, of the theoretical frameworks of 52 articles related to mental health published up to February 2022. A qualitative approach was used, with a Grounded Theory design, which allowed comparing different paradigms and identifying gaps in conceptual notions to build an explanatory model of mental health. The results showed three dominant paradigms that circumscribe the concept of mental health. Mental health is understood as the absence of illness, positive mental health, and a state of equilibrium. In addition, the need to propose a definition that integrates these dominant paradigms was mainly identified, and that would allow a broader understanding of the state of equilibrium as the basic process through which the individual must pass in the search for personal recovery. From the comparative analysis of the categories designated according to the Grounded Theory approach, an explanatory model was proposed to define mental health as the internal process of self-care, centered on the self-awareness and self-regulation of the human being, in which the person seeks to balance their feelings, thoughts, and behaviors, intrapersonal and interpersonal ones, to approach an optimal state of wellbeing and absence of mental disorders according to universal values and symptoms, and biological, social, psychological, and environmental factors.

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.