Didactic principles and learning strategies play a vital role in medical rehabilitation, whereby the path for knowledge acquisition differs for young and old individuals. These age-specific differences in learning appear to be due to changes in neural systems that assess how much should be learned from changes in the environment [1]. In rehabilitation, the advantages of virtual environments and training programs with a high interactive content can be used for such knowledge acquisition. Positive transfer effects from a virtual space to the real environment are already known. In addition, a virtual training environment can be designed to provide motivational feedback and to directly control the complexity of a therapeutic content or environmental changes according to the patient’s performance. In virtual environments, both lessons and practice sequences can be repeated as often as required, and incorrect actions are reversible and have no consequences. Learning from faults and training at performance limits can be easily controlled. Such learning environments are free of charge and, in principle, have unlimited availability.

Perception and learning under virtual reality (VR) conditions have been studied not only in healthy individuals but also in those with brain injury [2-6]. This indicates that approaches to VR in brain injury rehabilitation are already established in terms of cognitive assessment and cognitive rehabilitation with technically simple systems. However, VR systems have not yet been established in motor rehabilitation. Studies with immersive systems have shown at least preliminary positive effects in upper extremity rehabilitation training [6]. For a general integration into rehabilitation concepts, a comfortable technical applicability and obvious motion detection are central requirements. Therapist-assisted rehabilitation interventions are often superior to purely technical interventions or virtual environments in everyday life. The development of new motion recognition systems for the gaming industry in recent years has made it possible to develop new everyday conditions for the use of virtual environments in motor rehabilitation [7,8]. However, the motivation and acceptance of people confronted with this technology in a therapeutic setting have not been sufficiently investigated. Key questions in this context are as follows:

In complex models describing the probability of user acceptance with an innovation, subjective performance expectancy regarding the benefits of a system is the strongest predictor of behavioral intention to accept an innovation [9-11]. Therefore, in this work, a survey of the subjective performance expectancy of virtual rehabilitation is conducted to provide a basis for the systematic evaluation of the benefits that VR can bring to various areas of medical rehabilitation.

Patients’ demographic data are shown in Table 2. The patients’ age ranged from 32 to 86 (mean 65.3, SD 12.2) years. In total, 62 patients were male and 49 were female. The age distribution in the male and female groups was balanced (mean 65.4 vs 65.2, SD 11.5 y vs 13.1 years). The gender distribution in the age groups “<68 years” and “≥68 years” was similar, with slightly more males than females (male:female 31:26 versus 31:23).

Overall, 56% of respondents were undergoing inpatient medical rehabilitation for the first time. Further, 38% of respondents had been to an inpatient medical rehabilitation facility at least twice, regardless of specialty or diagnosis, and 92% of respondents said they had not heard of virtual rehabilitation and needed an explanation. In these explanations, we followed the definition of VR in the context of neuroplasticity by Weiss et al [14]: “Virtual reality is defined as an approach to a user-computer interface that creates a real-time simulation of an environment, scenario, or activity, allowing the user to perform complex interactions using multiple sensory channels. Virtual rehabilitation training approaches use the latest VR technologies, improved robotic design, the development of haptic interfaces, and modern human-machine interactions for meaningful stimulation of the nervous system, thereby promoting brain plasticity.”

An overview of the patients’ ratings is provided in Figure 1. In general, rehabilitants can imagine the use of VR in rehabilitation. This particularly applies to all items in the categories “activity/movement,” “competence in daily life/communication,” and “education” as well as for the occupational therapy (all these therapeutic measures have median score of 2, which represents the rating “good”), whereas physical therapy and all items in the category “advisory/conversation” exhibited a mean score of 3, which corresponds the rating “adequate.”

The monotonic relationship among the 15 therapeutic fields is displayed in Figure 2. Except for the 2 combinations of therapeutic fields displayed in white, all correlations are significant at a .05 level (2-tailed). A rank correlation with a large effect size can be observed within the categories “activity/movement” and “advisory/conversation” as well within the category “education” but only among the therapeutic fields “health seminars and education,” “nutrition advisory,” and “diabetic training.” The monotonic relationship between the items of the category “competence in daily life/communication” is medium, while there is no significant rank correlation between “relaxation techniques” and “physical therapy.”

Table 3 shows the results of the group comparisons. There was no significant difference in the evaluation of VR between rehabilitants of employable age (aged <68 years) and those aged 68 years or older (Mann-Whitney U test, z=−.137 to −1.802, P=.07 to .90). Regarding the evaluation based on gender, it should be noted that male rehabilitation patients generally report greater subjective expectations for virtual rehabilitation than female patients, but there was only a significant difference with small effect sizes for “sports and exercise therapy,” “psychological individual therapy,” and “psychological group therapy.”

Table 4 shows the distribution of patients’ answers regarding the additional questions. Overall, 78% of the patients believe, that VR can be used to achieve higher motivation and willingness to participate in medical rehabilitation therapy. There is no significant correlation with this answer and the experience with computers or game consoles (P=.08 [Fisher exact chi-square test]; expected cell frequencies were below 5).