Full length articleTraining in a comprehensive everyday-like virtual reality environment compared to computerized cognitive training for patients with depression
Introduction
Besides emotional, physical or motivational dysfunctions, neurocognitive impairment is a core feature of depression (Bortolato et al., 2015, Rock et al., 2014). In the DSM-V (American Psychiatric Association, 2013) the impaired capacity to think, to concentrate or to make decisions is one diagnostic criterion for major depressive episode (MDD). Reviews and meta-analysis have underlined neurocognitive impairments in patients suffering from depression, especially in domains of memory, executive functions, attention and psychomotor speed (Beblo et al., 2011, Bora et al., 2013, Lee et al., 2012). In a prospective study, Conradi, Ormel, and De Jonge (2011) found that up to 66% of the patients suffered from neurocognitive impairments during a three year course of major depressive disorder. Moreover, these neurocognitive impairments remained present in up to 44% of the finally remitted patients.
It is well known that cognitive deficits in depressive patients could have important psychosocial as well as clinical implications. For instance, they significantly impair patients' social and occupational life (Evans et al., 2014, McIntyre et al., 2013) and are related to disturbed everyday functioning (Harvey, 2011, Lee et al., 2015). Neurocognitive deficits in depression often attenuate patients adherence (e.g. through memory difficulties) and, therefore compromise effective treatment of the disorder (Papakostas, 2014). In addition, neurocognitive deficits have also found to be associated with increased suicidality (Keilp et al., 2013, Richard-Devantoy et al., 2012).
Given the notable relevance of neurocognitive deficits in persons with depression, effective intervention strategies are needed (cf. Rock et al., 2014). Among non-pharmacological treatment approaches targeting neurocognitive impairments, computerized training programs are often used (see reviews by Coyle et al., 2015, Gates et al., 2011, Leung et al., 2015). In psychiatry, the effectiveness of computer-assisted cognitive trainings have been proven most notably for patients with schizophrenia (Grynszpan et al., 2011, Kurtz et al., 2001, Wykes et al., 2014), but it has also been found to be effective in further diagnoses (Bossert et al., 2014, Choi and Medalia, 2005, Fals-Stewart and Lam, 2010, Lindenmayer et al., 2008, Tchanturia et al., 2008, Vocci, 2008). For example, some initial studies indicate that computerized rehabilitation programs improve the cognitive performance of depressed patients (Bowie et al., 2013, Porter et al., 2013).
As the particular relevance of ecological validity in neuropsychology has been repeatedly emphasized (Chaytor and Schmitter-Edgecombe, 2003, Sbordone, 2008), generalizability and transfer effects were also claimed for computerized cognitive training programs (Jak, Seelye, & Jurick, 2013). Lopresti, Mihailidis, and Kirsch (2004, p. 31) stated: “… the ecological validity of ATC (assistive technology for cognition) interventions will have to be established, since it is unclear whether being able to perform a task in a controlled environment will generalize to performing the identical task in a community environment.“. Similarly, Hampstead, Gillis, and Stringer (2014) describe the ”ultimate goal of any rehabilitation program“ in improving functioning in everyday life. Existing standard cognitive training programs often provide realistic images and scenarios. However, they are presented on a two-dimensional PC screen and, therefore, lack everyday-realism (Bryck & Fisher, 2012). This may be relevant especially in patients with depressive disorders, because they frequently claim pronounced cognitive problems in their daily living (Lahr et al., 2007, Mowla et al., 2007).
One methodology that has been increasingly considered as potential aids in enhancing the ecological validity of cognitive rehabilitation is virtual reality (VR). The various technical opportunities of VR seem to be best suited to both create naturalistic settings as well as to implement standardized procedures in treatment settings (Parsey and Schmitter-Edgecombe, 2013, Rose et al., 2005). By designing virtual environments that not only “look like” the real world, but actually incorporate challenges that require “real-world” functional behaviors, the ecological validity of cognitive rehabilitation is assumed to be enhanced (Rizzo, Schultheis, Kerns, & Mateer, 2004).
The computer-generated simulations of VR-technology engender the impression to the user as if he or she interacts within the real world while concurrently operating with or inside technical appliances (Schultheis, Himelstein, & Rizzo, 2002). Thus VR can be viewed as an advanced form of computer interface that allows the user to “interact” with and become “immersed” in a computer-generated environment (Rizzo, Buckwalter, Neumann, Kesselmann & Thiebaux, 1998). Consequently, a variety of VR approaches are available providing a continuum of experiences of immersion – the level to which the technology itself provides a comprehensible, vivid virtual environment whereby the user feels involved like “being there” (Bohil et al., 2011, Tarr and Warren, 2002). Higher levels of presence (“being there”) will be evoked by sophisticated virtual environments that produce greater senses of immersion compared to less complex VR setups (Cummings and Bailenson, 2015, Witmer and Singer, 1998). For instance, Gorini, Capideville, De Leo, Mantovani, and Riva (2011) found, that students who experienced a virtual environment presented at an external laptop screen (low degree of immersion) stated lower levels of presence compared to those who used a highly immersive Head-Mounted Display (HMD), a display device, worn on the head or as part of a helmet, which fully covers the user's eyes. In this latter highly immersive condition, characters, objects and the environment itself, were perceived as more real, and the experience was judged more interesting and involving than in the low immersive laptop-screen condition. In a study of Juan and Pérez (2009) the use of a HMD-system was compared to the application of an even more immersive system called Cave Automatic Virtual Environment (CAVE), where the user is surrounded by the virtual reality within a large stereoscopic room. The results showed, that this fully-immersive setup induced a higher degree of presence in users. In such highly immersive VR-environments, like CAVE or HMD, “… users are no longer simply external observers of images on a computer screen but are active participants within a computer-generated three-dimensional virtual world” (Riva, Mantovani, & Gaggioli, 2004, p. 2). Examining the aspect of active participation within VR-applications, Freeman, Lessiter, Pugh, and Keogh (2005) gave their participants either the opportunity to autonomously navigate through a virtual environment or told them to passively keep their eyes open while the experimenter navigated the route in accordance to the other group. Subsequently, participants who self-navigated gave significantly higher engagement ratings on a presence questionnaire than persons exposed to the same VR-experience but who did not self-navigate. Diemer, Alpers, Peperkorn, Shiban, and Mühlberger (2015) hypothesized, that the subjective experience of presence in virtual reality is based on the VR-setup's level of immersion as well as the degree of arousal the user feels during his individual VR experience.
Depending on its features and complexity, a VR environment artificially creates sensory experiences and induces multisensory feedback, e.g. auditory, visual and proprioceptive. This could bee viewed as an underlying mechanism of VR in facilitating clinical treatments, because multisensory-training scenarios were attributed to better approximate ecological settings and to be more effective for learning, since it is “likely that the human brain has evolved to develop, learn and operate optimally in multisensory environments” (Shams & Seitz, 2008, p. 1).
Moreover, engaging users in a multisensory VR training environment does not only encourage active participation and involvement, but rather improves neuroplastic changes of the brain (Teo et al., 2016). Precisely, learning and practicing skills in the sense of physical activity or mental stimulation, which are key features of immersive VR applications, have found to be critical for inducing a training-dependent reconfiguration of brain networks (Foster, 2015) and experience-dependent neuroplasticity, respectively (Kleim & Jones, 2008).
Another idea that has been hypothesized as a potential benefit of VR in treatment applications concerns the activation of implicit procedural memory (Rizzo et al., 1998, Rizzo et al., 2004). This idea originally rest upon the observation of persons with neurologically based memory impairment, in which, however, procedural or skill memory capabilities often remain relatively unimpaired. This involves the capacity to learn rule-based or automatic procedures and can be contrasted to declarative memory. Here, interactive and immersive virtual reality applications are thought to provide training environments that encourage cognitive and functional improvement by tying on a person's preserved procedural abilities. Hence, Rizzo et al. (2004) presumed that, “cognitive processes could be restored via procedures practised repetively within a virtual environment that contains functional real-world demands” (p. 218).
Virtual reality has increasingly proven to be an effective tool in neuroscience research as well as treatment settings for neurological and psychiatric patients (see reviews by Bohil et al., 2011, Rose et al., 2005, Parsons, 2015). Regarding neurorehabilitation, there are a lot of studies of the therapeutic use of VR in specific impairments resulting from brain injury, particularly recovery of function after stroke (Laver, George, Thomas, Deutsch, & Crotty, 2015), but also balance disorders, spatial ability impairments, visual neglect or certain cognitive dysfunctions (Rose et al., 2005). Neurorehabilitation using VR interventions offers the opportunity to expose patients to controlled settings under a range of stimulus conditions that are not easily controllable in the real world (Rizzo et al., 2004).
In neuropsychology VR has already been shown to enable an ecologically valid assessment of cognitive functions in neurological as well as psychiatric patients (Parsons, 2011, Rizzo et al., 2004, Rose et al., 2005). Many different virtual environments have yet been created referring to relevant everyday situations, for example supermarkets, grocery store, kitchens, office, apartment, park, library or street crossing; and applications that use driving simulators (Knight and Titov, 2009, Parsons, 2015, Rizzo et al., 2004). However, neuropsychological rehabilitation applications using VR still remain under development, especially in psychiatric settings. Whereas the majority of VR-based interventions in neurorehabilitation were used to train motor deficits or activities of daily living, the application as neuropsychological training scenarios for cognitive and meta-cognitive deficits has also been shown in several studies (Weiss, Kizony, Feintuch, & Katz, 2006). In their recent systematic review on the use of VR for cognitive rehabilitation after brain injury, Shin and Kim (2015) found VR programs to lead to an improvement in cognitive function, especially in the areas of memory and attention but not executive functions.
Regarding psychiatric settings, some few studies showed cognitive rehabilitation programs using VR-based setups to offer the potential for significant improvements in cognitive function compared to control conditions, e.g. in patients with schizophrenia (Marques, Queiros & Rocha, 2008), older adults with chronic schizophrenia (Chan et al., 2010), memory impaired elderly adults (Optale et al., 2010) or children with problems of inattention and impulsiveness (Cho et al., 2004).
To our knowledge, only four studies address the application of VR in patients with depressive disorders. Falconer et al. (2014) used an immersive VR scenario, in which depressed patients practiced delivering and receiving compassion using virtual embodiment. Reductions in depressions severity and self-criticism as well as increased self-compassion were gained after three intervention sessions. Two further studies found depressed patients performed worse than controls on VR navigation measures of visual-spatial memory (Cornwell et al., 2010, Gould et al., 2007), whereas another one revealed no differences in terms of neuropsychological performance during a VR spatial navigation task (Hviid et al., 2010).
Some initial studies showed that computerized rehabilitation approaches can improve cognitive performance of MDD patients (see above). However, the transfer of computerized cognitive training programs to real-world environments in general has been critically discussed (see Bryck and Fisher, 2012, Jak et al., 2013). Thus, we were interested in optimizing the presentation of a computerized training program for MDD patients by the use of VR and its real-world-like features. More precisely, we wanted to investigate, whether MDD patients profit from a comprehensive reality-oriented VR-environment (highly immersive) to a greater extent than from a typical PC desktop VR-application (less immersive). In fact, it has repeatedly been suggested to assess the incremental benefit of VR over already existing methods (Rizzo et al., 2004, Teo et al., 2016). We hypothesize that our highly immersive training setup leads to an improvement of transfer effects of cognitive training on a) everyday-related cognitive and b) functional outcomes (cognitive complaints in everyday-life, real-life performance) as well as on c) neuropsychological measures.
Section snippets
Participants
Patients with depressive disorders were recruited at the Clinic of Psychiatry and Psychotherapy Bethel (Bielefeld, Germany) during their inpatient-treatment. Inclusion criteria for study participation were as follows: diagnosis of MDD according to DSM-IV, age >18 years, at least 14 days of a hospital stay (training duration) and written informed consent prior to participation. Exclusion took place in case of a MDD with psychotic symptoms, neurological disorder with central nervous system
Verbal recall and purchased products
As outlined in Fig. 2, verbal memory and learning performance increased in the course of the training-trials in both groups. Repeated-measures ANOVA of trials 1, 6, 7 and 8 supported the effect of time on the number of verbally recalled products (F(2,43; 84,99) = 161.01, p < 0.001, = 0.821), but showed no group-differences (F(1; 35) = 0.459, p = 0.502, = 0.013) or an interaction-effect (F(2,43; 84,99) = 3.13, p = 0.399, = 0.027). This was also the case for the correctly purchased
Discussion
In this study, we examined the efficacy of a real-life-like VR-environment aiming to improve ecological validity in cognitive rehabilitation for patients with depression in comparison to a desktop-VR application. Since previous computer-based cognitive training approaches had been criticized for insufficient assessments of transfer effects (e.g. Jak et al., 2013), we used a comprehensive examination of self-ratings of everyday-life related cognitive impairment, a real-life task as well as
Acknowledgements
This work was supported by the project CITmed (Cognitive Interaction Technology in Medicine), funded by the EFRE (Europäischer Fonds für Regionale Entwicklung) program of Northrhine Westfalia, and the Cluster of Excellence Cognitive Interaction Technology (EXC 277) at Bielefeld University, funded by the German Research Foundation (DFG).
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