Evidence map›Paper›PMID 33179347›Full record

ArticleThe International journal of eating disorders2020

Personalized networks of eating disorder symptoms predicting eating disorder outcomes and remission.

Cheri A Levinson, Elizabeth Cash, Karla Welch, Sacha Epskamp, Rowan A Hunt, Brenna M Williams, Ani C Keshishian, Samantha P Spoor

Abstract read
In one paragraph

Article in The International journal of eating disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Cheri A LevinsonDepartment of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky, USA.ORCID 0000-0002-8098-6943
Elizabeth CashSchool of Medicine, University of Louisville, Louisville, Kentucky, USA.
Karla WelchDepartment of Engineering, University of Louisville, Louisville, Kentucky, USA.
Sacha EpskampDepartment of Psychological Methods and Psychometrics, University of Amsterdam, Amsterdam, The Netherlands.
Rowan A HuntDepartment of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky, USA.ORCID 0000-0002-7626-7049
Brenna M WilliamsDepartment of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky, USA.ORCID 0000-0002-3938-9610
Ani C KeshishianDepartment of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky, USA.
Samantha P SpoorDepartment of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky, USA.

Funding

WKU Lead Faculty AwardP20GM103436 · NIGMS · UNIVERSITY OF LOUISVILLE · PI Bruce A Mattingly · 2012 to 2026
$60.1M
Innovations in Personalizing Treatment for Eating Disorders Using Idiographic Methods and the Impact of Personalization on Psychological, Physical, and Sociodemographic OutcomesDP2MH136495 · NIMH · UNIVERSITY OF LOUISVILLE · PI Cheri Alicia Levinson · 2023 to 2026
$2.6M
Personalized Networks and Sensor Technology Algorithms of Eating Disorder Symptoms Predicting Eating Disorder OutcomesR15MH121445 · NIMH · UNIVERSITY OF LOUISVILLE · PI LEVINSON, CHERI ALICIA · 2020 to 2023
$1.1M
NIGMS NIH HHS P20 GM103436NIMH NIH HHS DP2 MH136495NIMH NIH HHS R15 MH121445
6 · The paper itself

Abstract

Enhanced cognitive-behavioral therapy (CBT-E) is one of the primary evidence-based treatments for adults with eating disorders (EDs). However, up to 50% of individuals do not respond to CBT-E, likely because of the high heterogeneity present even within similar diagnoses. This high heterogeneity, especially in regard to presenting pathology, makes it difficult to develop a treatment based "on averages" and for clinicians to accurately pinpoint which symptoms should be targeted in treatment. As such, new models based at both the group, and individual level, are needed to more accurately refine targets for personalized evidence-based treatments that can lead to full remission. The current study (Expected N = 120 anorexia nervosa, atypical anorexia nervosa, and bulimia nervosa) will build both group and individual longitudinal models of ED behaviors, cognitions, affect, and physiology. We will collect data for 30 days utilizing a mobile application to assess behaviors, cognition, and affect and a sensor wristband that assesses physiology (heart rate, acceleration). We will also collect outcome data at 1- and 6-month follow-ups to assess ED outcomes and remission status. These data will allow for identification of "on average" and "individual" targets that maintain ED pathology and test if these targets predict outcomes, including ED remission.

Indexed as

AdolescentAdultAgedCognitive Behavioral TherapyFeeding and Eating DisordersFemaleHumansLongitudinal StudiesMaleMiddle AgedPrecision MedicineTreatment OutcomeYoung Adulteating disorderslongitudinal modelingnetwork analysisphysiologyremission

Identifiers

PMID33179347
PMCPMC7864225

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.