everyBody–Tailored online health promotion and eating disorder prevention for women: Study protocol of a dissemination trial

2019
Abstract Background Although there is extensive evidence for the efficacy of online eating disorder(ED) prevention programs in clinical trials, these programs have rarely been adopted beyond the trial phase and offered to a wider audience. As risk factors for eating disordersare partly associated with overweight and overweight in turn is correlated to disordered eating, this study will offer a combined eating disorderprevention program which also promotes a balanced lifestyle to normal weight and overweight individuals alike. The efficacy of the program has been proven in previous trials. The study aims to evaluate the disseminationof a combined eating disorderprevention and health promotion program (everyBody) to women of all age groups and varying levels of ED risk status in the general population. Methods A disseminationtrial will be conducted in German-speaking countries, including 4160 women from the general population. Participants will be screened to exclude participants who are likely to have an ED. Eligible participants will be allocated to one of five program arms based on their BMI and respective ED symptoms. The guided program consists of 4 to 12 weeks of weekly sessions offering CBT-based exercises, psychoeducationalmaterial, self-monitoring, and group discussions. Outcomes will be assessed according to the RE-AIM model, including measures of effectiveness, reach, adoption, implementation, and maintenance of the program. Discussion/conclusions This trial aims to disseminatea combined ED prevention and health promotion program in the general population, offering universal, selective and indicated prevention in one program. To our knowledge, it is the first trial to systematically evaluate disseminationefforts based on the RE-AIM model. This trial will be conducted as part of the EU-funded ICare (Integrating Technology into Mental Health Care Delivery in Europe) project.
    • Correction
    • Source
    • Cite
    • Save
    54
    References
    13
    Citations
    NaN
    KQI
    []
    Baidu
    map