IntroductionSince COVID-19, medical resources have been tight, making it inconvenient to go offline for the sequelae of diseases such as post-stroke depression (PSD) that require long-term follow-up. As a new digital therapy, VRTL began to gain popularity.MethodThe research is divided into two parts: pre-test and post-test. In the pre-test, an evaluation method integrating reality-based interaction (RBI), structural equation model (SEM), analytic hierarchy process (AHP), and entropy weight method is proposed. In the post-test the patients’ physiological indicators (Diastolic blood pressure, systolic blood pressure and heart rate) are measured to verify the effectiveness of RBI-SEM model using T-test method.ResultsIn the pre-test, using SEM, it was confirmed that Pi physical awareness, Bi body awareness, Ei environmental awareness, and Si social awareness were significantly correlated and positively affected VRTL satisfaction (p >> F 0.217; B >> F 0.130; E >> F 0.243; S >> F 0.122). The comprehensive weight ranking based on RBI-SEM considered light environment (0.665), vegetation diversity (0.667), accessible roaming space (0.550) et al. relatively of importance. And T-tset in the post-test experiment considered that the data of the two measurements before and after the VRTL experience, systolic blood pressure (p < 0.01), diastolic blood pressure (p < 0.01), and blood pressure (p < 0.01) were significantly decreased; one-way ANOVA concluded that there was no significant difference in the changes of blood pressure and heart rate among participants of different ages and genders (p > 0.01).ConclusionThis research validated the effectiveness of RBI theory for VRTL design guidelines, established an RBI-SEM based VRTL evaluation model, and the output VRTL for PSD in the older adults was confirmed to have significant therapeutic benefits. This lays the foundation for designers to decompose design tasks and integrate VRTL into traditional clinical treatment systems.Contribution from the public or patientsFour public health department employees helped to improve the research’s content.

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