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Updated: Sep 19, 2025

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
Published on: May 10, 2022
Beyond the Diagnostic Checklist: A Large-Scale Analysis of Under-Recognized Weight Loss Behaviors in Individuals With
Saakshi Kakar1,2, Una Foye1,3, Helena L Davies1,2,4,5
1Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Objective:
This study aimed to explore the diverse range of weight loss behaviors that extend beyond traditional diagnostic criteria, highlighting the variability in symptom presentation.
Method:
We text mined free-text responses from 1675 participants with anorexia nervosa, bulimia nervosa, or binge-eating disorder in the Genetic Links to Anxiety and Depression (GLAD) Study and the Eating Disorders Genetics Initiative UK (EDGI UK). In secondary analyses, we investigated differences by eating disorder and gender.
Results:
Frequently endorsed behaviors included structured diets (619 endorsements) and calorie counting (422 endorsements), but also less commonly considered behaviors like compression garments (147 endorsements) and self-harm (88 endorsements). We identified four overarching themes: restriction-based approaches, medical intervention, body manipulation, and food avoidance. The most frequently reported weight loss behaviors and resultant themes did not differ among eating disorders or genders, closely resembling those in the broader sample. Notably, 81 participants with binge-eating disorder, which typically lacks the endorsement of recurrent compensatory behaviors, reported weight loss and compensatory behaviors.
Discussion:
Our findings identify a crucial gap in current diagnostic assessments, which may hamper recognition and lead to underdiagnosis of eating disorders. By incorporating our insights into an inclusive assessment process that expects and accommodates novel behaviors, clinicians could capture a broader spectrum of behaviors, thus improving diagnostic accuracy. However, our sample homogeneity implies the need for more diverse samples. Our study contributes essential insights for enhancing diagnostic criteria.
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