Online Test of Risk Self-Detection of Eating Disorders

Abstract

This study’s central aim was to examine the effectiveness of an online test of the Risk Self-Detection of Eating Disorders through the evaluation of (1) its psychometric properties, the significant probability of predicting risk eating behavior and the correct classification of membership to the risk or non-risk group and (2) the ability to measure users’ risk self-awareness through a group of statements and explore the expected responses through frequency analysis of the content provided by the users. The non-probability sample was comprised of n = 541 women aged 15 to 25 (M = 18.3; SD = 2.4). The instrument showed good psychometric properties, a structure of three predictive risk factors, and proper effect sizes (R2 = 0.67–0.69). Among the most critical findings were high percentages of correct classification (94–97%) and expected responses (61%). The logistic regression analysis showed that the risk of presenting eating disorders was higher if the participants smoked, consumed alcohol, had sexual experiences before the age of 15, and if those sexual experiences were non-consensual. Evidence is presented about the promising results of the online data collection method and its potential benefits.