A new approach to eating‐disorder classification: Using empirical methods to delineate diagnostic dimensions and inform care

Forbush, Kelsie T.; Chen, Po Yi; Hagan, Kelsey E.; Chapa, Danielle A. N.; Gould, Sara R.; Eaton, Nicholas R.; Krueger, Robert F.

doi:10.1002/eat.22891

Cited by 51 publications

(54 citation statements)

References 67 publications

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“…To our knowledge, this is the first ED network study identifying central symptoms among people with and without core ED symptoms. The overall similarity in network structure among people with and without core ED symptoms is in line with dimensional models of EDs (e.g., Forbush et al, 2018).…”

Section: Discussionsupporting

confidence: 73%

“…The overall similarity in network structure among people with and without core ED symptoms is in line with dimensional models of EDs (e.g., Forbush et al, 2018). This may be due to the Core ED Symptom group having a smaller sample size and the LASSO procedure consequently pulling more edge weights to zero.…”

Section: Discussionsupporting

confidence: 70%

“…In contrast, jointly estimating networks among men with and without core ED symptoms overcomes these limitations, through methodological procedures that capitalize on between-network similarities and penalize between-network differences. As such, particularly given the lack of data on traditional categorical (e.g., American Psychiatric Association, 2013) versus contemporary dimensional models (e.g., Forbush et al, 2017Forbush et al, , 2018 of EDs among men, the current approach represents an appropriate middle path for this investigation. Because the analyses were largely exploratory, we did not have specific hypotheses about which symptoms would emerge as most central in the networks.…”

Section: Intoductionmentioning

confidence: 99%

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Using network analysis to identify central eating disorder symptoms among men

Forrest

Perkins

Lavender

et al. 2019

Intl J Eating Disorders

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Objective: The network theory of psychopathology has been described as an "innovative framework" that may "transform" clinical psychological science. Several network studies have identified central eating disorder (ED) symptoms, yet studies have been comprised primarily of women. Using two large samples, we constructed ED symptom networks among men to identify central symptoms.Method: Participants were recruited from three universities and using Amazon's Mechanical Turk. Participants completed the Eating Disorder Examination-Questionnaire (EDE-Q), Male Body Attitudes Scale, and Drive for Muscularity Scale.ED symptom networks were jointly estimated among men with (n = 248) and without core ED symptoms (n = 902). Core ED symptoms were defined by (a) scoring above a suggested male EDE-Q clinical cutoff and (b) reporting symptoms consistent with probable ED diagnoses. Expected influence and predictability (proportion of each node's variance explained by other nodes in the network) were calculated for each node.Results: Shape overvaluation, desiring weight loss, fear of losing control over eating, feeling guilty for missing weight training, and using supplements had the greatest expected influence and predictability. Network structures did not significantly differ between participants with versus without core ED symptoms.Discussion: The centricity of body dissatisfaction items in the networks supports some components of cognitive behavioral theories of EDs. However, the findings also suggest the importance of muscularity-and leanness-oriented concerns, which have been traditionally neglected from leading ED theories that tend to focus on thinness pursuits as a main driver of body dissatisfaction. K E Y W O R D Seating disorder, leanness, men, muscularity, network analysis

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Section: Discussionsupporting

confidence: 73%

Section: Discussionsupporting

confidence: 70%

Section: Intoductionmentioning

confidence: 99%

See 1 more Smart Citation

Using network analysis to identify central eating disorder symptoms among men

Forrest

Perkins

Lavender

et al. 2019

Intl J Eating Disorders

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“…The relative placement of eating disorders within the higher-order structure of psychopathology has been debated. Most recently, structural models of psychopathology suggest that it can be placed within the Internalizing framework (50,51), although some models suggest it is a separate dimension (8). However, in the current analyses, eating disorders loaded most strongly on the Thought Problems factor, perhaps suggesting that this factor is characterized by disturbed cognitions found across disparate psychopathological disorders.…”

Section: Discussionmentioning

confidence: 99%

Testing structural models of psychopathology at the genomic level

Waldman

Poore

Luningham

et al. 2018

Preprint

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Genome-wide association studies (GWAS) have revealed hundreds of genetic loci that underlie major psychiatric disorders, and post-GWAS analyses have discovered substantial genetic correlations among these disorders. This suggests these disorders share a common genetic architecture, implying the presence of a higher-order structure of psychopathology at both the genetic and phenotypic levels. Nonetheless, despite recent efforts at elucidating this structure by collaborative consortia such as HiTOP, the exact structure of psychopathology remains unknown. Herein, in one of the largest genetic studies of psychopathology conducted to date, we tested multiple alternative structural models of psychopathology at the genomic level using the genetic correlations among fourteen psychiatric disorders and related psychological traits estimated from GWAS summary statistics. The best-fitting model includes four correlated higher-order factors -Externalizing, Internalizing, Thought Problems, and Neurodevelopmental Disorders. These higher-order factors were validated by examining their correlations with external criterion variables, which showed distinct patterns of genetic correlations with the 4 higher-order factors. Several model modifications were tested to explore the placement of a few disorders -such as bipolar disorder, OCD, and eating disorders -within the broader psychopathology structure. These findings show support for several of the HiTOP higher-order dimensions and suggest a similar structure of psychopathology at the genomic and phenotypic levels. Our results imply that such higher-order psychopathology dimensions might be better targets for genetic and genomic investigations than individual disorders, and might be more predictive of relevant outcomes of considerable public health and societal concern.

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“…HiTOP may provide clinicians with greater prognostic power (Hasler et al, 2004). When compared to categorical diagnoses, dimensional scores show superior prediction of clinical outcomes such as chronicity (Kim & Eaton, 2015), functional impairment (Forbush et al, 2017(Forbush et al, , 2018Keyes et al, 2013;Morey et al, 2007Morey et al, , 2012, and physical health comorbidities (e.g., Eaton et al, 2013). HiTOP constructs also show notable links with significant non-disorder outcomes.…”

Section: Integrating Hitop Into Clinical Practice 14mentioning

confidence: 99%

Integrating a Dimensional, Hierarchical Taxonomy of Psychopathology into Clinical Practice_

Ruggero¹

2018

Preprint

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Diagnosis is a cornerstone of clinical practice for mental health care providers, yet traditional diagnostic systems have well-known shortcomings, including inadequate reliability in daily practice, high co-morbidity, and marked within-diagnosis heterogeneity. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a data-driven, hierarchically based alternative to traditional classifications that conceptualizes psychopathology as a set of dimensions organized into increasingly broad, transdiagnostic spectra. Prior work has shown that using a dimension-based approach improves reliability and validity, but translating a model like HiTOP into a workable system that is useful for health care providers remains a major challenge. To this end, the present work outlines the HiTOP model and describes the core principles to guide its integration into clinical practice. We review potential advantages and limitations for clinical utility, including case conceptualization and treatment planning. We illustrate what a HiTOP approach might look like in practice relative to traditional nosology. Finally, we discuss common barriers to using HiTOP in real-world healthcare settings and how they can be addressed.

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A new approach to eating‐disorder classification: Using empirical methods to delineate diagnostic dimensions and inform care

Cited by 51 publications

References 67 publications

Using network analysis to identify central eating disorder symptoms among men

Using network analysis to identify central eating disorder symptoms among men

Testing structural models of psychopathology at the genomic level

Integrating a Dimensional, Hierarchical Taxonomy of Psychopathology into Clinical Practice_

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