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Predicting and comparing the long-term impact of lifestyle interventions on individuals with eating disorders in active population: A machine learning evaluation
The purpose of this project by Irandoust et al. (2024) is to use machine learning techniques to assess and forecast the long-term efficacy of five lifestyle treatments for people with eating disorders. The study evaluated the impact of five lifestyle treatments on people with eating disorders, as determined by The Eating Disorder Diagnostic Scale (EDDS) and was carried out between August 2021 and August 2023. The following were the interventions: (1) counseling, exercise, and diet; (2) aerobic exercise and diet; (3) walking and diet; (4) exercise and flexible diet; and (5) exercise using apps and online programs. The following measurements were taken at the start, middle, and conclusion of the intervention: weight, body fat percentage (BFP), fasting blood sugar (FBS), waist-hip ratio (WHR), low-density lipoprotein (LDL) cholesterol, total cholesterol (CHO), and triglycerides (TG). Of the 955 participants who enrolled, 706 finished the study. Analysis of the results revealed a ranking of the intervention methods according to their efficacy, as follows: counseling with a diet and exercise, cardio exercises with a diet, walking with a diet, exercise with a flexible diet, and workouts through online platforms. The study’s results indicate that machine learning models can effectively predict the long-term effectiveness of lifestyle interventions. These results highlight the possibility of creating individualized health plans and figuring out the best treatments for those who suffer from eating problems. The study also recommends expanding the participant demographics and study locations, extending the study duration, using more advanced machine learning techniques, and including psychological and social factors related to adherence. In the end, these results can help legislators and healthcare professionals develop tailored, focused lifestyle programs and apply machine learning to predictive healthcare solutions. [NPID: lifestyle interventions, long-term health outcomes, machine learning, prediction, eating disorders]
Year: 2024
