202. Positive impacts of cloud computing technology applications on the psychological state of patients with anxiety disorder

Abstract Background Against the backdrop of the rapid development of digital healthcare and smart psychological services, cloud computing technology is gradually being introduced into the field of mental health services, providing new technical support for psychological assessment, intervention management, and continuous follow-up. For patients with anxiety disorders, symptoms fluctuate frequently and they are highly sensitive to external uncertainties. Traditional face-to-face treatment models still have limitations in terms of continuity, accessibility, and self-management support. Existing research shows that structured information support and stable cognitive guidance can help alleviate anxiety experiences and enhance patients’ sense of psychological security. This study aims to explore the role of cloud computing platform-based technology application guidance in anxiety disorder intervention, analyzing its positive impact on patients’ anxiety levels, emotional stability, and subjective psychological state. Methods A controlled intervention design was used, selecting 120 patients diagnosed with anxiety disorder at a mental health institution outpatient clinic and randomly dividing them into an intervention group and a control group, with 60 patients in each group. Both groups received routine psychotherapy and health education. The intervention group, in addition to this, received guidance on the application of cloud computing technology, including cloud-based self-assessment of mental state, visualized feedback on mood changes, and personalized intervention prompts. Anxiety levels were assessed using the Hamilton Anxiety Scale (HAMA), and mental state was measured using the anxiety and depression dimensions of the Symptom Checklist-90 (SCL-90). The intervention lasted for 8 weeks, with assessments conducted before and after the intervention. Statistical analysis used paired t-tests and correlation analysis, controlling for variables such as gender and disease duration. Results After the intervention, the HAMA score in the intervention group decreased from 23.6 ± 5.2 before the intervention to 14.1 ± 4.6, a significantly greater decrease than that in the control group (from 19.8 ± 5.0 to 17.3 ± 4.8), with a statistically significant difference between the groups (t = 4.82, p<.001). The SCL-90 anxiety dimension score decreased from 2.41 ± 0.56 to 1.63 ± 0.48 in the intervention group, while it decreased from 2.28 ± 0.52 to 2.01 ± 0.49 in the control group, with a significant difference between the two groups after the intervention (t = 3.96, p<.001). Correlation analysis showed a significant negative correlation between the frequency of cloud platform use and the degree of improvement in anxiety symptoms (r = -0.41, p<.001). Further analysis indicated that patients in the intervention group significantly outperformed the control group in terms of perceived emotional controllability and treatment adherence. Discussion Cloud computing-based application guidance can significantly improve the mental state of patients with anxiety disorders, playing a positive role in reducing anxiety levels and enhancing emotional stability. Combining information technology with psychotherapy helps compensate for the shortcomings of traditional treatments in terms of continuous support and patient engagement. Future research can further explore the differences in the intervention effects of different cloud platform functional modules on anxiety disorders, and combine long-term follow-up to evaluate its sustained value in relapse prevention and psychological rehabilitation, providing a basis for optimizing digital psychotherapy models.