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230 – Innovative STEAMS Methodology Over STEM

STEAMS Application on Chronic Low Back Pain and Exercise Intervention

at Taipei First Girls' High School

This paper adopts STEAMS (Science, Technology, Engineering, Artificial Intelligence, Math, Statistics) methodology to investigate practical facts about exercise intervention on chronic low back pain population. In the modern Big Data era, the application of Artificial Intelligence (AI), data analysis and statistics are becoming more and more important. Therefore, integrating AI and Statistics with STEM (Science, Technology, Engineering, Math) to become STEAMS, will be a very powerful methodology to investigate scientific issues and solve problems. The science research revealed chronic low back pain (CLBP) is a common, long-lasting, and disabling condition with high costs for society and patients. Impairment of lumbopelvic stability is considered as a significant factor in patients with CLBP, and lumbopelvic stabilization exercise has been established as a treatment of chronic low back pain. Pilates is a recognized fitness program that follows core strengthening and also trains lumbopelvic stability. 45 CLBP participants undertook a 6-week Specific Pilates Exercise Program emphasizing on lumbopelvic stabilization, posture training and body awareness. We used visual analogue scale(VAS), Oswestry Low Back Disability Questionnaire, and pressure biofeedback unit to assess pain intensity, functional limitation and lumbopelvic stability before and after the exercise program. There were many previous researches investigating the effectiveness of Pilates exercise on improving CLBP patients, and the results among different researches are arguable. We believe the difference in the subjects‘ characteristics may be one of the reason that causes different results among those researches. In our paper, first, we used paired t test to determine if the 6-week Specific Pilates Exercise Program will improve pain intensity and the results showed improvement with statistics significance. Second, logistic regression and profiler and sensitivity analysis were used to investigate a predictive model of pain improvement. Occupation and age*occupation interaction were determined as the top two ranked variables related to improving pain condition after the program. This research also successfully demonstrated that “STEAMS” approach is very useful for conducting health science research.