Abstract
The core of occupational therapy is to help patients with mental illness recover their social work, give play to their self-worth, obtain financial resources, and improve their self-confidence. Occupational therapy can help patients relieve symptoms and restore social function, reduce disease recurrence, and improve the reemployment rate and the overall health level of patients. In order to deeply excavate the inner connection between the mental health status and physical exercise status of college students, the physical exercise behavior of college students during home isolation is studied. First, the "physical exercise behavior questionnaire" and "symptom self-assessment scale" were used to investigate the physical exercise behavior and mental health status of college students. Second, descriptive statistics, correlation analysis, independent sample t-test, and variance analysis were carried out on the survey results using mathematical statistics methods and big data technology. The survey results show high reliability, and the Cronbach's α coefficients were all greater than 0.9. There was a positive correlation between physical exercise methods and mental health in general, and the difference in the degree of exercise is significantly different from the mental health of students (p < 0.05). With the increase of exercise intensity, the score of "symptom self-assessment scale" first decreased and then increased, and the exercise intensity of medium and high intensity showed the best psychological state. And the correlation dimension of depression was the highest. This indicated that the students who liked family physical exercise were less likely to suffer from depression. In addition, depression was the most relevant dimension with self demand physical exercise, and interpersonal sensitivity was the most relevant dimension with social expansion physical exercise. The conclusion shows that the more active the students participate in family physical exercise, the healthier their mental state is. Occupational therapy has obvious curative effect on depression, which can improve patients' negative symptoms, their living ability, and social function. Meanwhile, analyzing data through big data technology reduces human workload and improves data processing efficiency and accuracy. The scheme proposed here provides some ideas for the application of big data technology in occupational therapy.