Personalizing eating disorder treatment using idiographic models: An open series trial.
Аннотация
OBJECTIVE
Treatments for adults with eating disorders (EDs) only work in about 50% of individuals, and for some diagnoses (e.g., anorexia nervosa; atypical anorexia nervosa), there are no existing evidence-based treatments. Part of the reason that treatments may only work in a subset of individuals is because of the high heterogeneity present in the EDs, even within diagnoses. Manualized treatments delivered in a standard format may not always address the most relevant symptoms for a specific individual.
METHOD: The current open series trial recruited participants with transdiagnostic ED diagnoses (N = 79) to investigate the feasibility, acceptability, and initial clinical efficacy of a 10-session network-informed personalized treatment for eating disorders. This treatment uses idiographic (i.e., one-person) network models of ecological momentary assessment symptom data to match participants to evidence-based modules of treatment.
RESULTS
We found that network-informed personalized treatment was highly feasible with low dropout rates, was rated as highly acceptable, and had strong initial clinical efficacy. ED severity decreased from pre- to posttreatment and at 1-year follow-up with a large effect size. ED cognitions, behaviors, clinical impairment, worry, and depression also decreased from pre- to posttreatment.
CONCLUSIONS
These data suggest that network-informed personalized treatment has high acceptability and feasibility and can decrease ED and related pathology, possibly serving as a feasible alternative to existing treatments. Future randomized controlled trials comparing network-informed personalized treatment for ED to existing gold standard treatments are needed. Additionally, more research is needed on this type of personalized treatment both in the EDs, as well as in additional forms of psychopathology, such as depression. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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