98. The intervention effect of computer network environment on the emotions and behaviors of patients with schizophrenia

Abstract Background In the treatment of schizophrenia, traditional drug therapy has a bottleneck in improving patients’ emotional apathy, depression, and social withdrawal behavior. Physical rehabilitation resources are limited by space and manpower allocation, making it difficult to achieve high-frequency personalized training. Currently, computer network technology provides a controllable virtual interactive medium for mental rehabilitation, and by building a low social pressure digital environment, it is expected to become a new way to regulate patients’ psychological functions. Therefore, the study investigated the intervention efficacy of structured computer network environment on negative emotions and adaptive behaviors in patients with schizophrenia, in order to demonstrate the clinical value of digital methods in psychiatric adjuvant therapy. Methods 160 patients with chronic schizophrenia in a closed ward of a mental health center were selected as experimental subjects and divided into a network intervention group and a conventional control group, with 80 patients in each group. The control group maintained the original atypical antipsychotic drug treatment and routine nursing care. On this basis, the network intervention group entered a specially designed LAN virtual community rehabilitation system for training, including emotion recognition interactive games, network social scenario simulation, and cognitive task collaboration. The frequency was 5 times a week, each session lasting 60 minutes, with a continuous intervention period of 24 weeks. The study used the Positive and Negative Syndrome Scale (PANSS) to assess the severity of psychiatric symptoms, and introduced the Nurses’ Observation Scale for Inpatient Evaluation (NOSIE) and Self Rating Depression Scale (SDS) to evaluate patients’ hospitalization behavior and depressive mood, respectively. Results After 24 weeks of systematic intervention, experimental data showed that the online intervention group was significantly better than the conventional control group in improving emotional delay and enhancing positive social behavior. There was no statistically significant difference in baseline indicators between the two groups at the time of enrollment, but there were significant statistical differences in various indicators after intervention. Among them, the SDS depression index of the online intervention group decreased to 41.23 points, significantly lower than the control group’s 52.45 points, and the difference was statistically significant (p<.05). The instant feedback and achievement reward mechanism in the online environment effectively alleviate patients’ low mood. At the same time, the total score of NOSIE reflecting behavioral function reached 168.34 in the online intervention group, and the social interest factor score improved significantly, indicating that online virtual social training can gradually be transferred to the real environment, promoting the benign reshaping of patients’ interpersonal communication initiative and social adaptation behavior. Discussion Structured interventions in computer network environments can effectively compensate for the shortcomings of simple drug therapy in improving negative symptoms and emotional disorders, and reduce patients’ social anxiety by simulating safe social situations. Future research directions should focus on developing immersive rehabilitation systems that combine virtual reality technology with wearable biofeedback devices, in order to further explore personalized mental rehabilitation pathways based on artificial intelligence algorithms.