NDLI: Food Addiction in Eating Disorders: A Cluster Analysis Approach and Treatment Outcome

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Food Addiction in Eating Disorders: A Cluster Analysis Approach and Treatment Outcome

Content Provider	MDPI
Author	Lucero, Munguía Anah, í Gaspar-Pérez Susana, Jiménez-Murcia Isabel, Sánchez Cristina, Vintró-Alcaraz Carlos, Diéguez Fernando, Fernández-Aranda Granero, Roser Gearhardt, Ashley N.
Copyright Year	2022
Description	Background: A first approach of a phenotypic characterization of food addiction (FA) found three clusters (dysfunctional, moderate and functional). Based on this previous classification, the aim of the present study is to explore treatment responses in the sample diagnosed with Eating Disorder(ED) of different FA profiles. Methods: The sample was composed of 157 ED patients with FA positive, 90 with bulimia nervosa (BN), 36 with binge eating disorder (BED), and 31 with other specified feeding or eating disorders (OSFED). Different clinical variables and outcome indicators were evaluated. Results: The clinical profile of the clusters present similar characteristics with the prior study, having the dysfunctional cluster the highest ED symptom levels, the worse psychopathology global state, and dysfunctional personality traits, while the functional one the lowest ED severity level, best psychological state, and more functional personality traits. The dysfunctional cluster was the one with lowest rates of full remission, the moderate one the higher rates of dropouts, and the functional one the highest of full remission. Conclusions: The results concerning treatment outcome were concordant with the severity of the FA clusters, being that the dysfunctional and moderate ones had worst treatment responses than the functional one.
Starting Page	1084
e-ISSN	20726643
DOI	10.3390/nu14051084
Journal	Nutrients
Issue Number	5
Volume Number	14
Language	English
Publisher	MDPI
Publisher Date	2022-03-04
Access Restriction	Open
Subject Keyword	Nutrients Womens Studies Food Addiction Eating Disorders Treatment Outcome Cluster Analysis Approach
Content Type	Text
Resource Type	Article

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