Published online Jul 19, 2021. doi: 10.5498/wjp.v11.i7.375
Peer-review started: February 8, 2021
First decision: March 30, 2021
Revised: April 9, 2021
Accepted: June 16, 2021
Article in press: June 16, 2021
Published online: July 19, 2021
Grouping eating disorders (ED) patients into subtypes could help improve the establishment of more effective diagnostic and treatment strategies.
To identify clinically meaningful subgroups among subjects with ED using multiple correspondence analysis (MCA).
A prospective cohort study was conducted of all outpatients diagnosed for an ED at an Eating Disorders Outpatient Clinic to characterize groups of patients with ED into subtypes according to sociodemographic and psychosocial impairment data, and to validate the results using several illustrative variables. In all, 176 (72.13%) patients completed five questionnaires (clinical impairment assessment, eating attitudes test-12, ED-short form health-related quality of life, metacognitions questionnaire, Penn State Worry Questionnaire) and sociodemographic data. ED patient groups were defined using MCA and cluster analysis. Results were validated using key outcomes of subtypes of ED.
Four ED subgroups were identified based on the sociodemographic and psychosocial impairment data.
ED patients were differentiated into well-defined outcome groups according to specific clusters of compensating behaviours.
Core Tip: This is the first study to apply multiple correspondence analysis to eating disorders (ED) diagnostic data and to use cluster analysis (CA) in such detail to search for ED patient groups in this area. Multiple correspondence analysis and CA made it possible to identify different typologies of patients with specific features. Grouping ED patients into subtypes could help improve the establishment of more effective strategies of diagnosis and treatment, and improve patient care and prognosis in clinical practice.