Discussion
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This study provided evidence of the short-term effectiveness of a psychoeducational e-Health intervention for reducing ED risk. Compared to a wait-list condition, the e-Health prevention program led to a statistically significant reduction in oral control subscale behaviors post-intervention. There were no significant sex differences. Notably, we did not find evidence for most of the EAT-26 subscales, suggesting that the reduction in ED risk may be primarily attributable to the impact of the program on self-control of eating (e.g., eating restricted behaviors).In this study, correlational analyses showed a relationship between baseline BMI, weight (in the total sample and by sex), self-esteem (in the total sample, but not by sex) and the EAT-26 dieting subscale. Based on these results and prior research, it may be that individuals with higher BMIs, greater weight, and low self-esteem have more concerns about shape and weight and could be more likely to be at risk of developing EDs (Puhl & Lessard, Prior studies have shown that selective prevention e-Health interventions are associated with significant decreases in body and weight concerns, dietary restriction, drive for thinness, internalization of the thin ideal and symptoms of EDs at post-intervention (Harrer et al., In addition, the program aimed to educate participants specifically about binge eating, its causes and consequences, and how to prevent it (e.g., eating 5 meals a day). There is also a link between attitude and behavior (Ajzen, On a related note, the program was online and so participants would be expected to have had effective exposure to the program. The content was accessible 24/7 and given that a digital device was required to access the program, most families were expected to be involved. Although it was not evaluated, it is arguable that families helped the young people to interpret messages and exercises and that may have fostered critical thinking in families as well. The literature has previously reported that interventions involving parents can boost the effectiveness of school-based prevention programs (Cuijpers, Another likely explanation of the current findings is related to the inclusion of behavioral activation, which has been shown to be successful in improving diet quality in adults (Paans et al., The study is not without limitations. Firstly, the results may be biased because of the relatively small sample size. Secondly, because of the pandemic, face-to-face follow-up assessments were not feasible as planned and long-term effects of the e-Health intervention cannot be concluded. On a related note, the COVID-19 pandemic may have influenced family function and self-esteem, and may have biased the results. Furthermore, in part due to time constraints during teaching hours, other potentially relevant outcome variables were not explored. Similarly, it was not possible to perform a process evaluation (e.g., adherence of the teachers to the program curriculum). On another note, feasibility and accessibility are two variables that should be considered as well, particularly to gather information on teachers’ and families’ acceptance levels and barriers towards accessing and adhering to the content. Future studies should gather data on these aspects as well as on potential moderators and mediators framed by TPB. The RE-AIM evaluation framework is a suitable and widely accepted approach for this endeavor that suggests using a 6 month-2 + year assessment time frame (Glasgow et al., 