With the vigorous development of big data technology, exploring its potential in sports behavior analysis and mental health intervention has emerged as a crucial research direction. This experiment enrolled 62 participants aged 18-60 years who were randomly assigned to an observation group and a control group based on a pre-/post-experimental control group design. Exercise intensity, frequency, and duration were monitored via wearable devices, and mental health status was evaluated using eight indicators, including the Self-Rating Depression Scale and the Self-Rating Anxiety Scale. The participants in the observation group received personalized mental health interventions based on big data analysis, whereas those in the control group maintained their usual lifestyle. Data were analyzed using SPSS, independent samples t-tests, and paired samples t-tests. Results indicate that after the intervention, the observation group exhibited significant improvements in exercise metrics along with reduced scores for depression, anxiety, and sleep quality and increased scores for life satisfaction and psychological resilience. Statistically significant differences were observed between the scores of the two groups, thus confirming the effectiveness of the intervention program.

big data, physical activity behavior, mental health, intervention