Einsatz von Virtual-Reality und 3D-Modellen zur Patientenschulung vor herzchirurgischen Eingriffen

Hundertmark, Fabian (2026): Einsatz von Virtual-Reality und 3D-Modellen zur Patientenschulung vor herzchirurgischen Eingriffen. Dissertation, LMU München: Faculty of Medicine

Abstract

Background: Cardiac surgery not only poses high physiological stress, but also psychological stress which can contribute to preoperative anxiety. High preoperative anxiety correlates with longer hospital stays, complications, and higher mortality. Limited patient understanding of their condition, surgery, and recovery often reduces compliance, amplifying anxiety and its effects. Modern visualization tools like virtual reality (VR) and 3D-printed anatomical models offer promising potential for improved preoperative patient education. This dissertation aimed to firstly assess the applicability of modern visualization methods in preoperative education, and secondly determine the impact of these methods on patient understanding and preoperative anxiety. Methods: Patient education was provided using one of three methods: standardized paper-based materials (n = 32), 3D-printed models (n = 30), or virtual reality models (n = 31). Procedural understanding and anxiety levels were assessed before and after the education session. To evaluate patient knowledge a self-assessment questionnaire was used. To assess anxiety levels the State-Anxiety Score (SAS) of the State-Trait-Anxiety-Index (STAI) and a Visual Analog Scale for Anxiety (VAS) was used. Education time and overall quality were also evaluated, along with patient characteristics such as age, gender, medical knowledge, history of non-cardiac surgery, Trait-anxiety score (TAS), symptoms of depression using the Beck Depression Inventory (BDI) and prior knowledge of the procedure. The included surgeries were coronary artery bypass grafting, surgical aortic valve replacement, and thoracic aortic aneurysm repair. Analysis of variance was used to determine significant differences between the groups and multiple linear regression analysis was used to identify factors influencing these outcomes. Results: The VR Model Group showed significantly better post-education understanding than the Standard Group (24.7 ± 3.8 vs. 22.7 ± 3.4; p = 0.038). Pre-education understanding was adversely affected by higher BDI scores (p = 0.027) and baseline anxiety levels (VAS1) (p = 0.038), whereas prior knowledge significantly enhanced pre-education understanding (p = 0.002). Education quality was the strongest predictor of post-education understanding (p = 0.03), with the largest improvement seen in patients with higher BDI scores (p = 0.033). Preoperative anxiety (VAS1) was lower in older patients (p = 0.036) and those with better baseline understanding (p = 0.001) but higher in those with elevated trait anxiety (p = 0.01). Anxiety levels between post-education and pre-education decreased significantly in the VR Model Group (5.0 ± 2.7 to 4.32 ± 2.7; p < 0.01). For the other groups no significant difference could be seen. Education quality was rated highest in the VR Model Group compared to the Standard Group (51.25 ± 4.39 vs. 47.43 ± 5.14; p = 0.008). Women had higher post-education anxiety than men (p = 0.05), with prior biomedical knowledge reducing post-education anxiety in the whole cohort (p = 0.03). Conclusion: This study demonstrated that modern visualization methods, such as 3D printing and VR, enhance patient understanding and reduce preoperative anxiety. Furthermore, patient-specific psychological factors, such as trait anxiety and depressive symptoms, play a crucial role in preoperative information processing and anxiety development. Overall, the use of VR and 3D models in preoperative education for cardiac surgery can be considered beneficial. Patients should be evaluated for psychological traits before and after surgery to tailor education and ensure optimal outcomes.

• Item Type: Theses (Dissertation, LMU Munich)
• Subjects: 600 Technology, Medicine; 600 Technology, Medicine > 610 Medical sciences and medicine
• Faculties: Faculty of Medicine
• Language: German
• Date of oral examination: 10. February 2026
• 1. Referee: Hagl, Christian
• Signature of the printed copy: 0700/UMD 22836