LAUSR

Objective: Although 2 screening tests exist for having a high risk of muscle dysmorphia (MD) symptoms, they both require a long time to apply. Accordingly, we proposed the construction, validation, and implementation of such a test in a mobile application using easy-to-measure factors associated with MD. Design: Cross-sectional observational study. Setting: Gyms in Alicante (Spain) during 2013 to 2014. Participants: One hundred forty-one men who engaged in weight training. Assessment of Risk Factors: The variables are as follows: age, educational level, income, buys own food, physical activity per week, daily meals, importance of nutrition, special nutrition, guilt about dietary nonadherence, supplements, and body mass index (BMI). A points system was constructed through a binary logistic regression model to predict a high risk of MD symptoms by testing all possible combinations of secondary variables (5035). The system was validated using bootstrapping and implemented in a mobile application. Main Outcome Measures: High risk of having MD symptoms (Muscle Appearance Satisfaction Scale). Results: Of the 141 participants, 45 had a high risk of MD symptoms [31.9%, 95% confidence interval (CI), 24.2%-39.6%]. The logistic regression model combination providing the largest area under the receiver operating characteristic curve (0.76) included the following: age [odds ratio (OR) = 0.90; 95% CI, 0.84-0.97, P = 0.007], guilt about dietary nonadherence (OR = 2.46; 95% CI, 1.06-5.73, P = 0.037), energy supplements (OR = 3.60; 95% CI, 1.54-8.44, P = 0.003), and BMI (OR = 1.33, 95% CI, 1.12-1.57, P < 0.001). The points system was validated through 1000 bootstrap samples. Conclusions: A quick, easy-to-use, 4-factor test that could serve as a screening tool for a high risk of MD symptoms has been constructed, validated, and implemented in a mobile application.