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Using individual networks to identify treatment targets for eating disorder treatment: a proof-of-concept study and initial data


ABSTRACT:

Background

Eating disorders (EDs) are severe mental illnesses, with high morbidity, mortality, and societal burden. EDs are extremely heterogenous, and only 50% of patients currently respond to first-line treatments. Personalized and effective treatments for EDs are drastically needed.

Methods

The current study (N = 34 participants with an ED diagnosis collected throughout the United States) aimed to investigate best methods informing how to select personalized treatment targets utilizing idiographic network analysis, which could then be used for evidence based personalized treatment development. We present initial data collected via experience sampling (i.e., ecological momentary assessment) over the course of 15 days, 5 times a day (75 total measurement points) that were used to select treatment targets for a personalized treatment for EDs.

Results

Overall, we found that treatment targets were highly variable, with less than 50% of individuals endorsing central symptoms related to weight and shape, consistent with current treatment response rates for treatments designed to target those symptoms. We also found that different aspects of selection methods (e.g., number of items, type of centrality measure) impacted treatment target selection.

Conclusions

We discuss implications of these data, how to use idiographic network analysis to personalize treatment, and identify areas that need future research. Trial registration: Clinicaltrials.gov, NCT04183894. Registered 3 December 2019—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04183894. NCT04183894 (ClinicalTrials.gov identifier).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40337-021-00504-7. Plain English Summary Eating disorders are severe psychiatric illnesses that carry high mortality, morbidity, and societal and personal burden. Treatments for eating disorders only work in 50% of patients, signifying a great need to improve treatments. One reason that treatments may not work, is because eating disorders vary substantially from one individual to the next, which existing treatments do not fully consider. The current study (N = 34 participants with an eating disorder diagnosis) uses a new modeling technique to identify which symptoms should be targeted in treatment in a personalized manner. As expected, we found that, using this modeling technique, symptoms that should be targeted in treatment vary considerably. We discuss how to use this modeling technique to identify individual treatment targets and ways in which the field can use this strategy to improve existing and create new treatments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40337-021-00504-7.

SUBMITTER: Levinson C 

PROVIDER: S-EPMC8567590 | biostudies-literature |

REPOSITORIES: biostudies-literature

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