Digital nature: Unveiling the impact and safety of FlowVR group intervention for depression in a feasibility trial.

Abstract

This study addresses the limitations of existing interventions for depression, such as a deficit-oriented focus, overlooking the utilization of positive elements such as nature, and neglecting the incorporation of group effects. The present feasibility study examines FlowVR, a resource-oriented, nature-inspired virtual reality (VR)-based group therapy. Previously tested individually in a pilot study for non-clinical participants, FlowVR has demonstrated positive effects on depressive symptoms. This study assesses the impact and safety of FlowVR in a group setting within a clinical sample using a one-armed study design. Forty-two inpatients and day patients with depression were recruited. Before and after the FlowVR intervention period of 4 weeks (two sessions per week), depressive symptoms were assessed (Beck Depression Inventory-II; BDI). Symptomatology (i.e., depressive symptoms), depression-associated variables (i.e., self-efficacy), intervention-specific variables (feeling of flow), and VR-specific variables (simulator sickness) were assessed before and after each session. Linear mixed effect models showed that symptomatology (depression, negative affect, current anxiety), depression-associated constructs (self-efficacy, motivation), and intervention-specific variables (flow) improved over the course of the sessions. No variable deteriorated more in one session compared to any other session. The lasso regression identified five potential predictors for the change in depression (BDI-II), yet these could not be validated in a subsequent linear regression analysis. To conclude, FlowVR had the hypothesized positive impact over the course of the sessions, showing, for example, improvements in symptomatology. The sessions have demonstrated safety with no notable deteriorations. Therefore, FlowVR is deemed safe for clinical patients and group settings. However, further research is needed to explore predictors for the change in depression.