This paper presents an in-depth study and analysis of the model of college students’ mental health education using fine-grained parallel computational programming. In the experimental group, the total level of positive thoughts and the level of life satisfaction significantly increased and the level of depression significantly decreased before and after the implementation of the intervention; in the control group, the level of life satisfaction significantly increased before and after the implementation of the intervention, and there was no significant difference in the total level of positive thoughts and the level of depression. Based on the above results, the positive thinking group-assisted training in this study was effective in improving the level of positive thinking and life satisfaction and reducing the level of depression into two categories of high school students: those who were susceptible and those who were symptomatic but satisfied, thus improving their mental health status, and may provide operational references for future intervention studies. At the same time, some studies have pointed out that when college students are faced with stressful situations, they will have higher psychological levels if they take a positive way to deal with them, and when college students are under stress, they will use a positive psychological restraint mechanism to cope. From a macroperspective, the research results can also be used to guide the training system of mental health education teachers, teachers’ professional development, and career development planning, showing certain application value.