Screening for eating disorders in adolescents with chronic pain: the Eating Attitudes Test-16-Chronic Pain

Leslie Sim; Amy Fahrenkamp; Jennifer R Geske; Jocelyn Lebow; Hope Thilges; Carol B Peterson; Abigail Matthews; Cynthia Harbeck-Weber

doi:10.1186/s40337-024-01014-y

Screening for eating disorders in adolescents with chronic pain: the Eating Attitudes Test-16-Chronic Pain

J Eat Disord. 2024 May 10;12(1):56. doi: 10.1186/s40337-024-01014-y.

Authors

Leslie Sim¹, Amy Fahrenkamp², Jennifer R Geske³, Jocelyn Lebow^{4

5}, Hope Thilges⁶, Carol B Peterson⁷, Abigail Matthews⁴, Cynthia Harbeck-Weber⁴

Affiliations

¹ Department of Psychiatry and Psychology, Mayo Clinic College of Medicine and Science, 200 First Street SW, Rochester, MN, 55905, USA. sim.leslie@mayo.edu.
² Pain, Palliative Care, and Integrative Medicine Department, Children's Hospitals and Clinics of Minnesota, Minneapolis, MN, USA.
³ Department of Quantitative Health Sciences, Mayo Clinic College of Medicine and Science, Rochester, MN, USA.
⁴ Department of Psychiatry and Psychology, Mayo Clinic College of Medicine and Science, 200 First Street SW, Rochester, MN, 55905, USA.
⁵ Department of Pediatric and Adolescent Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA.
⁶ Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA.
⁷ Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA.

Abstract

Background: Few measures have been validated to screen for eating disorders (ED) in youth with chronic pain. We conducted confirmatory (CFA) of two established factor structures of the Eating Attitudes Test-26 (EAT-26) in a sample of youth with chronic pain attending an intensive interdisciplinary pain treatment (IIPT) program and examined the validity of the best-fitting model in predicting ED diagnoses in this sample.

Methods: Participants were 880 adolescents (M age = 16.1, SD = 2.1) consecutively admitted into an IIPT program who completed the EAT-26 upon admission. CFA was conducted and in the case of inadequate fit, EFA was planned to identify alternative models. Factors of the best-fitting model were included in a logistic regression analysis to predict ED diagnoses.

Results: The TLIs (0.70; 0.90), RMSEAs (0.09; 0.07) and CFIs (0.73; 0.92) suggested poor fit of one model and adequate of the second model. Goodness of fit indices from EFA (TLI:0.85, RMSEA:0.06) did not outperform the fit of the second CFA. As such, the second model was retained with the exception of one factor. The items loaded onto a 16-item, five factor model: Fear of Getting Fat, Social Pressure to Gain Weight, Eating-Related Control, Eating-Related Guilt and Food Preoccupation. Based on chart review, 19.1% of the participants were diagnosed with an eating disorder. Logistic regression analyses indicated the new 16-item measure and Fear of Getting Fat, significantly predicted an ED diagnosis that did not include avoidant restrictive food intake disorder (ARFID) and Social Pressure to Gain Weight significantly predicted a diagnosis of ARFID.

Conclusions: An alternative 16-item, 5-factor structure of the EAT-26 should be considered in screening for EDs with youth with chronic pain.

Keywords: Adolescents; Chronic pain; Eating disorders; Factor analysis.