Anxiety and depression are common psychological disorders among adolescents, mainly caused by internal factors such as individual personality and physical and mental health, as well as external influences from family, school, and society. The manifestations on students are firstly pressure such as academic discomfort and confusion about future employment; and secondly anxiety and fear towards interpersonal relationships and interactions with people surroundings. The study uses psychological intervention to treat students with psychological anxiety in order to alleviate their symptoms and maintain a sound mental health.

60 students aged 10-14 from a certain school were chosen and divided into a male group of 30 and a female group of 30. Before and after treatment, the Simplified Mental State Score (MMSE) and Pittsburgh Sleep Quality Index (PSQI) scores of adolescents were performed, and the effects of single drug treatment and combination treatment were compared. Finally, SPSS 23.0 was used for data analysis, and the measurement data were expressed in the form of mean ± standard deviation and t-test was used.

The MMSE scores of single drug therapy and combination therapy before treatment were analyzed as t=0.01 and P>0.05, while the PSQI scores were analyzed as t=0.02 and P>0.05; The data analysis of MMSE scores for single drug therapy and combination therapy after treatment was t=4.39, P<0.05, and the data analysis of PSQI scores was t=6.02, P<0.05. The best effect of combination therapy was summarized.

Psychological anxiety problems among students often affect their cognition, memory, and life skills. Medication and psychological intervention can alleviate students’ anxiety and improve their quality of life.

Central Party School, research on digital agriculture in the context of rural revitalization (No. 2023DXXTZDDYKT126); Party School of Liaoning Provincial Committee, strengthen the strategic research of agricultural strong province supported by digital technology (No.ZKLM23002); Research on the key technology of traffic big data fusion mining under the background of epidemic prevention and control normalization (No. L22AGL002).