A comparative network analysis of eating disorder psychopathology and co-occurring depression and anxiety symptoms before and after treatment.
Anxiety
classification
depression
eating disorders
network analysis
treatment
Journal
Psychological medicine
ISSN: 1469-8978
Titre abrégé: Psychol Med
Pays: England
ID NLM: 1254142
Informations de publication
Date de publication:
01 2019
01 2019
Historique:
pubmed:
16
4
2018
medline:
14
3
2020
entrez:
16
4
2018
Statut:
ppublish
Résumé
Network analysis is an emerging approach in the study of psychopathology, yet few applications have been seen in eating disorders (EDs). Furthermore, little research exists regarding changes in network strength after interventions. Therefore the present study examined the network structures of ED and co-occurring depression and anxiety symptoms before and after treatment for EDs. Participants from residential or partial hospital ED treatment programs (N = 446) completed assessments upon admission and discharge. Networks were estimated using regularized Graphical Gaussian Models using 38 items from the Eating Disorders Examination-Questionnaire, Quick Inventory of Depressive Symptomatology, and State-Trait Anxiety Inventory. ED symptoms with high centrality indices included a desire to lose weight, guilt about eating, shape overvaluation, and wanting an empty stomach, while restlessness, self-esteem, lack of energy, and feeling overwhelmed bridged ED to depression and anxiety symptoms. Comparisons between admission and discharge networks indicated the global network strength did not change significantly, though symptom severity decreased. Participants with denser networks at admission evidenced less change in ED symptomatology during treatment. Findings suggest that symptoms related to shape and weight concerns and guilt are central ED symptoms, while physical symptoms, self-esteem, and feeling overwhelmed are links that may underlie comorbidities in EDs. Results provided some support for the validity of network approaches, in that admission networks conveyed prognostic information. However, the lack of correspondence between symptom reduction and change in network strength indicates that future research is needed to examine network dynamics in the context of intervention and relapse prevention.
Sections du résumé
BACKGROUND
Network analysis is an emerging approach in the study of psychopathology, yet few applications have been seen in eating disorders (EDs). Furthermore, little research exists regarding changes in network strength after interventions. Therefore the present study examined the network structures of ED and co-occurring depression and anxiety symptoms before and after treatment for EDs.
METHOD
Participants from residential or partial hospital ED treatment programs (N = 446) completed assessments upon admission and discharge. Networks were estimated using regularized Graphical Gaussian Models using 38 items from the Eating Disorders Examination-Questionnaire, Quick Inventory of Depressive Symptomatology, and State-Trait Anxiety Inventory.
RESULTS
ED symptoms with high centrality indices included a desire to lose weight, guilt about eating, shape overvaluation, and wanting an empty stomach, while restlessness, self-esteem, lack of energy, and feeling overwhelmed bridged ED to depression and anxiety symptoms. Comparisons between admission and discharge networks indicated the global network strength did not change significantly, though symptom severity decreased. Participants with denser networks at admission evidenced less change in ED symptomatology during treatment.
CONCLUSIONS
Findings suggest that symptoms related to shape and weight concerns and guilt are central ED symptoms, while physical symptoms, self-esteem, and feeling overwhelmed are links that may underlie comorbidities in EDs. Results provided some support for the validity of network approaches, in that admission networks conveyed prognostic information. However, the lack of correspondence between symptom reduction and change in network strength indicates that future research is needed to examine network dynamics in the context of intervention and relapse prevention.
Identifiants
pubmed: 29655386
pii: S0033291718000867
doi: 10.1017/S0033291718000867
pmc: PMC6310232
mid: NIHMS975755
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
314-324Subventions
Organisme : NIMH NIH HHS
ID : T32 MH082761
Pays : United States
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