Abstract
Background Virtual reality (VR)–based rehabilitation is gaining attention as a way to promote early mobilization in patients with acute stroke. However, given the motor weakness and cognitive impairment associated with acute stroke, implementation strategies for overcoming patient-perceived difficulty need to be developed to enhance their motivation for training.
Objective The purpose of this study was to explore patient-perceived difficulty and enjoyment during VR-based rehabilitation and the factors affecting those experiences.
Design An exploratory mixed-method design was used in this study.
Methods Eight individuals with acute stroke participated in 2 training modes of VR-based rehabilitation (ie, workout and game modes) 20 to 30 minutes per day for 5 to 8 sessions. A visual analog scale was used to assess patient-perceived difficulty and enjoyment at every session. Then semistructured interviews were conducted to explore the factors affecting those experiences.
Results Levels of difficulty and enjoyment varied depending on the training mode and participants' phases of recovery. Five major factors were identified as affecting those varied experiences: (1) ease of following the directions, (2) experience of pain, (3) scores achieved, (4) novelty and immediate feedback, and (5) self-perceived effectiveness.
Conclusions Levels of difficulty and enjoyment during VR-based rehabilitation differed depending on the phases of recovery and training mode. Therefore, graded implementation strategies for VR-based rehabilitation are necessary for overcoming patient-perceived difficulty and enhancing enjoyment. Ease of following the directions might be best considered in the very early stage, whereas multisensory feedback may be more necessary in the later stage. Health professionals also should find a way for patients to avoid pain during training. Feedback, such as knowledge of results and performance, should be used appropriately.
Benefits of early mobilization after stroke have been emphasized in previous studies. For example, a minimum of 16 hours of exercise therapy in the early stage has been reported to induce a 5% increase in activities of daily living (ADL) performance and to improve long-term physical outcomes.1–3 Nevertheless, the actual time that patients spend on exercise is rather low4 due to practical limitations, such as the time-consuming and labor-intensive nature of conventional therapy and difficulty traveling to special facilities.5,6
Virtual reality (VR)–based rehabilitation in the early stage of recovery has received attention as a way of filling this gap between reality and ideals, owing to its capacity to provide high-intensity, repetitive, and task-oriented training.7,8 Furthermore, the outstanding characteristic of VR training—multisensory feedback9,10—allows patients to recognize their own level of performance and to adjust their posture, which increases its utility as a self-rehabilitation tool after hospital discharge.
The effects of VR-based rehabilitation in patients with acute stroke have been verified in several previous studies. Some randomized controlled trials11–14 examined the effects of VR-based rehabilitation on upper extremity (UE) function using self-developed11 or commercially available12–14 devices. Virtual reality–based rehabilitation showed improvements similar to those of conventional physical therapy and occupational therapy,11,12,14 but greater than with recreational therapy, such as playing cards.13
Even with these positive effects, caution should be taken when applying VR-based rehabilitation in patients in the early stage of recovery. Most patients in this period have some extent of motor weakness and cognitive impairment and, therefore, are prone to experience physical and cognitive challenges during VR-based rehabilitation, which could result in depression or abandonment of training.15 Thus, to facilitate continuous participation in VR-based rehabilitation, patient-perceived difficulty during training needs to be explored, and strategies to overcome such challenges need to be developed.
Meanwhile, flow experience has recently emerged as a primary factor affecting patient adherence to VR-based rehabilitation.15,16 One qualitative study reported that patients with acute stroke experienced positive feelings, such as “enjoyment” and “engagement,” while conducting VR-based rehabilitation, causing them to think of rehabilitation as a meaningful occupation.15 Another study indicated that patients frequently reported that they were so engaged in the VR-based rehabilitation that they lost track of time while watching real-time feedback and perceived that “a good intervention” would help them persevere with rehabilitation for long periods by providing a flow experience.16 From these studies, we can assume that maintaining a state of flow may be important in inducing patients adherence to VR-based rehabilitation.
The means of maintaining a flow state is suggested by Flow Theory.17 Flow Theory defines flow as the feeling of complete and energized engagement in an activity, with a high level of enjoyment and fulfillment. The theory hypothesizes a Flow Zone, meaning that a person would be at a high level of enjoyment when the level of difficulty of a task is appropriate, with a balance between the difficulties of the task and the abilities of the person. Hence, according to Flow Theory, the level of enjoyment could be an indicator of whether the level of difficulty is appropriate.
This theoretical framework was applied in a study that examined the levels of difficulty and enjoyment for 6 kinds of VR-based exercises in healthy young adults.18 In this previous study, participants rated the level of enjoyment high when they perceived the difficulty to be in the lower middle level, indicating that the content had appropriate difficulties, balanced between the difficulties of the task and the abilities of the person.18 In patients with acute stroke, recent studies qualitatively explored patient experiences during VR-based rehabilitation.15,16 However, little is known about the level of difficulty and enjoyment during VR-based rehabilitation based on this theoretical framework and the factors that may affect these experiences.
Therefore, in this study, we explored the levels of difficulty and enjoyment that patients experienced during VR-based rehabilitation to verify whether the enjoyment level could be an indicator of the appropriateness of the level of difficulty for patients with acute stroke who had differing physical and cognitive status, as Flow Theory hypothesizes. We also explored the possible factors affecting such difficulty and enjoyment in order to identify a means of overcoming such difficulty and enhancing enjoyment during VR-based rehabilitation. Finally, we examined the effects of VR-based rehabilitation on UE function and ADL performance in order to identify physical benefits. The results of this study provide information on implementation strategies necessary to set an appropriate level of difficulty, which enables patients with acute stroke to achieve a high level of enjoyment during VR-based rehabilitation.
Method
Participants
A total of 11 inpatients with stroke were recruited from a rehabilitation center at Korea University Anam Hospital in Seoul, South Korea, and assessed for their eligibility. Three participants were excluded, resulting in 8 enrolled participants. Participants were chosen to reflect diversity in age, sex, and physical and cognitive impairments. In particular, because we intended to achieve a broad representation of physical and cognitive impairments, we did not put a specific limit on physical or cognitive function when recruiting participants. Potential participants were first screened by a physiatrist for the following inclusion criteria: (1) age ≥18 years, (2) onset of unilateral stroke within the past 2 months, and (3) manual muscle test score of the affected shoulder joint >1 (trace). Patients were excluded if they had the following: (1) severe listening or visual impairment, (2) transient ischemic attack, (3) epilepsy, (4) headaches, or (5) dizziness. Written informed consent was obtained from all participants.
Study Design
An exploratory mixed-method design using quantitative and qualitative analyses was adopted in this study.19,20 The mixed-method design enabled collection of information on participants' experiences during VR-based rehabilitation and the factors affecting those experiences from various perspectives.
VR-Based Rehabilitation System
Hardware.
The VR system used in this study utilized a motion capture sensor (Kinect, Microsoft Inc, Redmond, Washington), portable notebook computer, and 127-cm (50-in) display monitor. The motion capture sensor, which was placed on top of the display monitor, tracked and captured 20 body segments of the participants and translated the collected data into on-screen action. Thereby, participants were able to identify their own 3-dimensional avatar reflected in a virtual environment on the 2-dimensional monitor screen without any haptic devices or controllers.
Software.
We designed a software program tailored to patients with hemiplegic stroke in the Applied Neuro-Dynamic Laboratory of Korea University through consultation with physical therapists who routinely worked with this population at the hospital, and the animations were created by a specialized company (Unimation Korea Inc, Seoul, South Korea). The therapeutic method embedded in the software was based on a proprioceptive neuromuscular facilitation stretching technique comprising diagonal and spiral patterns of movement using multiple joints. This technique is widely used clinically to increase range of motion and relax the muscles,21 and its effects on improving UE function in patients with stroke have been verified.22,23 We designed 2 different training modes to compare participants' preferences and experiences: (1) a workout mode and (2) a game mode. Figure 1 shows participants conducting each mode of training.
Virtual reality (VR)–based rehabilitation software tailored to patients with hemiplegic stroke. (A) and (B) show a participant performing the workout mode of training and the VR content reflected back to the participant. (C) and (D) show a participant performing the game mode of training and the VR content including a hammer (participant's hand movement) and a mole (target). The software was developed based on a proprioceptive neuromuscular facilitation stretching technique.
In the workout mode of training, participants could identify their own 3-dimensional avatar on the right side of the screen, while simultaneously seeing a virtual instructor, who appeared as a human-like figure on the left side of the screen; this way, participants could imitate the movements of the virtual instructor. The following 4 patterns of UE movement were guided by the virtual instructor: (1) diagonal 1 flexion, (2) diagonal 1 extension, (3) diagonal 2 flexion, and (4) diagonal 2 extension. Diagonal 1 flexion and extension patterns were combined in one session, as the diagonal 1 extension pattern is the reverse of the diagonal 1 flexion pattern. Diagonal 2 flexion and extension patterns also were combined for the same reason. Two combined movement patterns were designed to be repeated 8 times in sequence as a blocked practice for a total of 5 minutes (Fig. 1A and B).
During the workout mode of training, the software provided visual and auditory feedback for the participants, including knowledge of results (KR) and knowledge of performance (KP). For example, if the participant's movement was correct, the software provided verbal praise, such as “excellent” or “good job,” with light flashing around the participant's avatar (KR). However, if the movement was not correct, the software encouraged the participant with a comment, such as “raise your arm more” or “try harder” (KP).
In the game mode of training, a mole appeared in a cave as a target, while a hammer reflected the participant's hand movement. The moles were designed to appear one at a time in the following patterns in random order: (1) right up and then left down, (2) right down and then left up, (3) left up and then right down, and (4) left down and then right up. In the process of hitting the moles with the hammer, participants performed diagonal 1 and 2 flexion and extension patterns of movement. The game took 5 minutes to complete (Fig. 1C and D).
During the game mode of training, if the hammer hit the mole with the correct angle and velocity, the mole disappeared, grimacing and saying “Ouch!” (KR). If the hammer did not hit the mole, it just disappeared from the cave within 5 seconds. The software guided the direction from where the mole would appear with an arrow so that participants could easily perform diagonal 1 and 2 flexion and extension patterns of movement (KP). Number of points accumulated by successfully hitting the mole was presented as scores in real time on the screen (KR). The software provided participants' total scores on the screen after completion of both workout and game modes of training (KR).
Training Protocol
The training protocol consisted of workout and game modes of training, each of which was conducted twice consecutively, resulting in 4 sections for about 20 minutes. However, participants were allowed to conduct each mode of training just once depending on their condition by judgment of the supervising researcher. The order of the training modes was planned using an online random number generator (http://www.random.org) at every session to avoid order bias. After finishing one mode of training, participants were given an approximately 5-minute break. Participants were asked to conduct the training in the sitting position.
The first day of training served as a “familiarization phase,” during which participants were provided a guide to practice the 2 different training modes using the unaffected UE; the familiarization phase could be prolonged based on a participant's demands. After that, the “treatment phase” began, during which participants were asked to conduct the training using the affected UE or bilateral UEs depending on the judgment of the physiatrist at the rehabilitation center. However, even if the physiatrist recommended use of the affected UE, the participants were allowed to use bilateral UEs if they asked to do so. Use of bilateral UEs was permitted for participants to avoid pain and due to the verified effects of bilateral arm training on improving UE function after stroke.24,25
Procedure
Each participant attended 5 to 8 sessions of the VR-based training program, which were held 3 days per week for approximately 20 to 30 minutes per day at the rehabilitation center of the hospital. Other routine treatments, such as conventional physical therapy or occupational therapy, were continued as usual during the intervention period.
One researcher (J.K.), a certified physical therapist, supervised the participants throughout the intervention period and recorded the following data at every session: (1) side of UE used for training (unaffected, affected, or bilateral), (2) level of assistance required for training (none, minimal, or maximal), and (3) experience of pain. In particular, we defined the level of assistance required for training as follows: none (the patient did not require any verbal or physical assistance), minimal (the patient required verbal cues or hand commands without physical assistance), or maximal (the patient required physical assistance).
To explore participants' experiences during VR-based rehabilitation, levels of difficulty, enjoyment, and training intensity were assessed quantitatively at every session. To further explore participants' experiences and the factors affecting those experiences, the first author (M.L.) conducted a single semistructured interview immediately after completion of the entire intervention. Physical outcomes were assessed at baseline and after completion of the entire intervention by 2 intervention-blinded physical therapists with more than 3 years of clinical experience.
Data Collection
At baseline, demographic (age and sex) and clinical (stroke etiology, site of stroke, stroke onset, and severity of physical and cognitive impairments) data were obtained. Severity of stroke was based on the National Institutes of Health Stroke Scale (NIHSS) score (0=normal, 1–4=minor, 5–15=moderate, 16–20=moderately severe, and >20=severe).26 Severity of cognitive impairment was based on the Mini-Mental State Examination (MMSE) score (24–30=normal, 18–23=mild, and 0–17=severe).27
A visual analog scale (VAS)—a 10-cm horizontal line with anchor words placed at both ends—was used to assess the levels of difficulty (very easy–very challenging) and enjoyment (very boring–very enjoyable) of the participants after completion of each training mode at every session.28 Self-rated mood status assessment using a VAS has been shown to have high reliability and validity in the health and clinical domains.28
Semistructured interviews were used to further explore participants' experiences and the factors affecting patient-perceived difficulty and enjoyment after completion of the entire intervention period. Interviews were semistructured to help participants answer the questions easily and to facilitate participant storytelling with open-ended questions around topics, including: (1) Which training mode, if any, was more challenging or enjoyable? and (2) What aspects of the training mode made you feel challenged or enjoyment? Verbal and physical reactions during the interviews also were recorded by the researcher (J.K.) in the field notes,29 under the guidance of the first author. Some caregivers were asked to accompany participants during the interviews to provide clarification and background about participant comments. Each interview took approximately 30 minutes to complete. All interviews were audio-recorded with consent of the participants and caregivers.
For training intensity, ratings of perceived exertion (RPEs) were used to measure patient-perceived training intensity after completion of training at every session using the following ratings: 0 (no exertion at all), 1 (very light), 2 (light), 3 (moderate), 4 (somewhat hard), 5 (hard), 6–7 (very hard), and 8–10 (very, very hard).30 A portable heart rate monitor (RS800CX, Polar Electro Inc, Lake Success, New York) and heart rate sensor (H2, Polar Electro Inc) were used to measure training intensity objectively in both modes of training at every session. Before starting each mode of training, each participant's resting heart rate (RHR) was measured for 5 minutes in a sitting position.
For physical outcome, the UE portion of the Fugl-Meyer Assessment (UE-FMA)31 was used to evaluate motor recovery in reflexes, range of motion, synergy, sensation, and hand movement. The UE-FMA uses a scale of 0 to 66, and the score can be divided into the following 4 parts: (1) shoulder, elbow, and forearm (36 points); (2) wrist (10 points); (3) hand (14 points); and (4) coordination (6 points). The Manual Function Test (MFT)32 was used to evaluate UE motor dexterity. The MFT uses a scale of 0 to 32, and the score can be divided into the following 2 parts: (1) shoulder, elbow, and forearm (16 points) and (2) hand (16 points). The Box and Block Test (BBT)33 was used to evaluate gross manual dexterity. The Modified Barthel Index (MBI)34 was used to measure basic ADL performance as follows: 0–24 (totally dependent), 25–49 (severely dependent), 50–74 (moderately dependent), 75–90 (mildly dependent), 91–99 (minimally dependent), and 100 (totally independent).
Data Analysis
The levels of difficulty and enjoyment, which were measured using the VAS at each session, are presented for each mode of training in Figure 2. For qualitative analysis, all audio-recorded interviews and verbal and physical reactions recorded in the field notes were transcribed verbatim into text by 2 intervention-blinded researchers to avoid selective coding of information.35 A summative content analysis was used to evaluate the transcribed interviews and verbal and physical reactions, which involved counting and comparing key words in the text with the object of understanding the contextual meaning of the words.36 Each of the researchers independently coded the transcribed interviews by sentence and determined the main factors affecting patient-perceived difficulty and enjoyment based on key words that were mentioned in the codes. Finally, emerged factors and sorted codes were assessed for their credibility through discussion with all research members and 2 specialists (a professor of the physical therapy department with more than 10 years of clinical experience and a sociologist with more than 20 years of qualitative research experience) to verify whether participants' experiences and factors affecting those experiences were accurately and fully represented.
Patient-perceived levels of difficulty and enjoyment in each mode of training. “u” on the x-axis indicates the unaffected upper extremity was used; “b” indicates bilateral upper extremities were used. Otherwise, the affected upper extremity was used. P=participant.
For training intensity, the median RPE for each participant was obtained by arranging the values from all sessions from lowest to highest and choosing the middle value. The mean heart rate (MHR) of each participant was obtained by averaging all values. For physical outcome measures (ie, UE-FMA, MFT, BBT, and MBI), within-group changes from baseline to follow-up were analyzed using the Wilcoxon signed rank test because of the small sample size (N=8). Significance levels were set at P<.05 for all analyses. Effect size (ie, Cohen d)37 was calculated by dividing the mean change scores by the standard deviation of the baseline scores. Effect size values above 0.80 were regarded as large, values of 0.50 to 0.80 were regarded as moderate, and values of 0.20 to 0.50 were regarded as small. Quantitative measurements were analyzed using IBM SPSS version 21.0 (IBM Corp, Armonk, New York).
Role of the Funding Source
This research was supported by R&D grant (No. 2013006) on rehabilitation by Korea National Rehabilitation Center Research Institute, Ministry of Health & Welfare.
Results
Eleven inpatients were recruited, but 3 were excluded for the following reasons: unwillingness to participate (n=1) and ineligibility according to the inclusion criteria (n=2). Thus, data analyses were based on 8 participants who attended 5 to 8 sessions of the VR-based training program before being discharged from the hospital. However, in the course of the intervention period, we excluded 4 participants from VAS and RPE assessment because we judged that they could not reasonably determine the level of difficulty, enjoyment, and training intensity by indicating a level on the horizontal line of the VAS. However, they had no significant difficulty performing the training and expressing their difficulty and enjoyment using verbal or physical reactions, so we allowed them to continue the training. Participants' age (32–84 years), sex (male, n=4; female, n=4), and severity of stroke (NIHSS score=3–13) and cognitive impairment (MMSE score=10–29) varied. Participants' characteristics are shown in Table 1.
Participants' Demographic and Clinical Characteristicsa
Participants' Experiences
Figure 2 shows the experiences of 4 participants during both modes of VR-based rehabilitation and indicates the side of UE used for training. The experiences of the other 4 participants, who had a difficulty in measuring the levels of difficulty and enjoyment, were explored through semistructured interviews, including their physical and verbal reactions. As training changed from the familiarization phase to the treatment phase, the level of difficulty of some participants (n=3) tended to increase, whereas that of enjoyment decreased at the same time.
In the treatment phase, participant 1 performed training using bilateral UEs due to motor weakness, without any assistance. In the workout mode of training, the level of enjoyment was consistently high, whereas that of difficulty was consistently low. In comparison, in the game mode of training, the level of difficulty was slightly increased until the third session and then decreased.
Participant 2 used the affected UE until the fourth session, following the physiatrist's recommendation, but changed to bilateral UEs due to pain. She could conduct the workout mode of training without any assistance, whereas she needed minimal assistance in the game mode of training because she confused the direction in which the hammer and moles were located without verbal cues. In the workout mode of training, the level of enjoyment was consistently high following the third session, whereas that of difficulty gradually decreased. On the contrary, in the game mode of training, the level of enjoyment gradually decreased, but that of difficulty tended to increase.
Participant 3 performed training using bilateral UEs throughout the treatment phase due to motor weakness and compensational movements and performed both modes of training without any assistance. In both modes of training, the level of difficulty was consistently moderate throughout the intervention period, whereas that of enjoyment increased at the second session, slightly dropped, and then was consistently moderate.
Participant 4 used bilateral UEs until the fourth session on his demand, although the physiatrist recommended use of the affected UE, and then changed to the affected UE from the fifth session. He performed both modes of training without any assistance by the time of the final session, but in earlier sessions, he showed a poor sense of velocity during the game mode of training and required minimal assistance. In the workout mode of training, the level of enjoyment gradually increased, whereas that of difficulty abruptly increased in the middle of the sessions when the training side changed from bilateral UEs to the affected UE and then decreased again. In the game mode of training, the level of enjoyment was rather low until the sixth session and then sharply increased in the latter sessions, whereas that of difficulty was rather high until the middle of the sessions and then slightly decreased in the latter sessions.
Participant 5 performed training using the affected UE without any assistance in the workout mode of training, but she could not catch the moles without minimal assistance in the game mode of training. She was always ready to perform the training before the software began, taking the training pose for herself. Her caregiver commented that she did not like to go to other therapies, such as using the cycle ergometer, and did not cooperate with the therapists during such training, as she did during VR-based training.
Participants 6 through 8 performed training using bilateral UEs. Participant 6 performed the workout mode of training without assistance, showing a positive attitude, including counting for himself during training, whereas he required minimal assistance during the game mode of training. Participant 7 required minimal assistance to keep participating in the workout mode of training, whereas he could not continue the game mode of training without a physical therapist's active physical assistance until the final session. Participant 8 initially could not understand the rules of either modes of training and did not actively cooperate with the physical therapist's assistance. However, from the third session, she became to perform the workout mode of training with minimal assistance.
In summary, the majority of participants (n=6) could perform the workout mode of training independently but required minimal (n=3) to maximal (n=3) assistance in the game mode of training. Two participants (participants 1 and 3) showed a relatively similar pattern of changes in patient-perceived difficulty and enjoyment during both modes of training, whereas 2 other participants (participants 2 and 4) showed different patterns of changes during each mode of training.
Factors Affecting Participants' Experiences
Five factors were identified as affecting patient-perceived difficulty and enjoyment: (1) ease of following the directions, (2) experience of pain, (3) scores achieved, (4) novelty and immediate feedback, and (5) self-perceived effectiveness.
Ease of Following the Directions
Four participants suggested that ease of imitating or following the training affected their enjoyment and difficulty. Participants 2 and 4 said that the workout training mode was more interesting because it enabled them to “imitate the movements of the virtual trainer.” In particular, participant 2 implied the necessity of the virtual trainer by saying, “Where is my trainer (whose movements I should follow)?” at every session, even while conducting the game mode of training. Participant 5 also consistently mentioned, “The workout mode of training is more enjoyable, and the game mode is too difficult for me.” Participant 7 stated that he preferred the workout mode of training because it is easy to conduct.
Experience of Pain
Experience of pain during training was found to be a major factor affecting patient-perceived difficulty and enjoyment. For example, participant 2 said that she became reluctant to do the training due to pain in the back of her neck and flank while performing the training using her affected UE at the second through fourth sessions; she was absent from the training at the fifth session. Participant 4 said, “I was afraid of coming to conduct the training until the third session because it made me feel pain in my flank during the weekend.” Participant 8 said, “I initially felt enjoyment for the novelty of the training applying the VR system; however, I could not feel enjoyment anymore since the middle of the intervention period since I felt pain whenever I raised the UE like this (above 90° of the affected side of shoulder).”
Scores Achieved
Some participants (n=3) were very sensitive about the scores achieved and became depressed and marked a low level of enjoyment when they got disappointing scores. Participant 4 mentioned, “When I first saw the game, it did not seem very difficult to me, but when I actually tried it, the scores were disappointing. This made me depressed, and I came to prefer the workout mode. In the later sessions, as the range of motion of my shoulder increased, the scores also increased, so I again enjoyed the game.”
Novelty and Immediate Feedback
Immediate feedback in the process of training also emerged as a factor related to enjoyment. For example, participant 1 preferred the game mode to the workout mode, as well as conventional therapy, because the game mode of training felt like just play for her. She stated, “Actually, the game was more difficult (than the workout mode) because I could not predict where the moles would appear. Nevertheless, I felt that the game was more enjoyable because if I caught the moles, they disappeared with a sound such as ‘Ouch!’ and it made me feel like being a child again.” She also said, “This training (game mode) felt like just play for me, so it is more fun than the cycle ergometer…. It (cycle ergometer) is so boring and hard for me.” Participant 3 gave the researcher a “thumbs-up,” saying, “I have never encountered these interesting games before; actually, I have never played games before.”
Self-perceived Effectiveness
Two participants said that the workout mode of training seemed to be more effective, so they preferred it, although the game mode was “not bad.” Participant 6 said, “I could not extend my elbow at all when I first started the (workout mode of) training; however, yesterday, I found that my elbow fully extended when I did that movement lying down on the bed.”
Training Intensity
The median RPE (interquartile range) of each participant was as follows: participant 1, 3.00 (2.00–3.00); participant 2, 3.00 (2.00–4.00); participant 3, 1.50 (1.00–2.25); and participant 4, 3.00 (1.25–3.00). The MHR of each participant varied from 81 to 104 bpm in the workout mode of training and from 86 to 106 bpm in the game mode of training, although we could not take the MHR of participant 8 in the game mode of training due to her complaint of fatigue. These values were approximately 10% of the heart rate reserve from the RHR of each participant, according to the Karvonen formula,38 indicating that the VR-based rehabilitation had a very low intensity. Table 2 shows the RHR, MHR, and 10% of the heart rate reserve of each participant.
Mean Heart Rates Depending on the Mode of Traininga
Physical Outcomes
Participants showed increases in UE function and ADL performance (Tab. 3). According to the UE-FMA, there were significant increases in total score (P=.018, d=.50) and shoulder, arm, and elbow score (P=.018, d=.57), but not in wrist score (P=.109, d=.24), hand score (P=.102, d=.54), or coordination score (P=.180, d=.31). According to the MFT, there were significant increases in all UE parts, including total score (P=.018, d=.69), shoulder, elbow, and forearm score (P=.017, d=.59), and hand score (P=.026, d=.68). Participants also demonstrated significant increases in BBT score (P=.043, d=.52) and MBI score (P=.012, d=.96).
Upper Extremity Function and Activities of Daily Living Performance Before and After the Interventiona
Discussion
In this study, we explored patient-perceived difficulty and enjoyment during VR-based rehabilitation in the theoretical framework based on Flow Theory and the factors affecting those experiences. As a result, we found that the level of enjoyment could be an indicator of the appropriateness of the level of difficulty for participants with acute stroke, as Flow Theory hypothesizes, because there was a reciprocal relationship between levels of difficulty and enjoyment, meaning that enjoyment occurred when the difficulties of the task and the abilities of the participant were balanced.
Participants showed very different levels of difficulty and enjoyment during VR-based rehabilitation. That is, we found that some participants seemed to easily adjust to VR-based rehabilitation, showing steady high or middle levels of enjoyment; some participants showed many changes as time went on; and other participants could not understand the rules of the training until completion of the intervention period. According to Flow Theory, this finding can be interpreted to mean that enjoyment occurred when the difficulties of the task and the abilities of the participant were balanced, and for some participants, depending on their phase of recovery and other conditions, this balance was not achieved in a certain part of or to the end of the intervention period.17 Therefore, it might be necessary to use VR content with varied levels of difficulty to accommodate a wide range of patients with various levels of stroke severity and in different phases of recovery.
There were complex determinant factors for such different levels of difficulty and enjoyment, including differences in physical, cognitive, and proprioceptive abilities of the participants and their individual experiences. Cognitive ability alone did not appear to be the determining factor for such differences. For example, some participants with normal cognitive ability could not understand the rules of the game mode of training until completion of the intervention period, whereas other participants with mild cognitive impairment could enjoy the game with only minimal assistance. Therefore, it would not be appropriate for health professionals or researchers to assume the inapplicability of VR-based rehabilitation beforehand only due to the low cognitive ability.
We also found that there tended to be a reciprocal relationship between levels of difficulty and enjoyment. That is, when participants perceived a high level of difficulty, they tended to perceive a low level of enjoyment at the same time, and vice versa, indicating that the level of enjoyment could be indicator of appropriateness of the level of difficulty, as Flow Theory hypothesizes. A similar trend also was identified by a previous study of VR-based exercise in healthy young adults, suggesting that participants rated the level of enjoyment high when they perceived the difficulty to be in the lower middle level.18 This result implies that the participants tended to experience a high level of enjoyment when they perceived that the task was sufficiently easy to perform. For example, for participant 4, the level of enjoyment sharply dropped immediately after he changed the training side from the unaffected UE to the bilateral UEs in the game mode of training; however, this recovered again to the initial level following the sixth session. This very fluid situation might be due to the young age of the participant (32 years) and can be explained by his comments in the semistructured interview: “When I first saw the game, it did not seem very difficult to me, but when I actually tried it, the scores were disappointing. This made me depressed, and I came to prefer the workout mode. In the later sessions, as the range of motion of my shoulder increased, the scores also increased, so I again enjoyed the game.” This finding might verify the hypothesis of the Flow Zone and might be a step forward from previous studies15,16 that qualitatively explored patient experiences. In other words, we identified a reciprocal relationship between levels of difficulty and enjoyment in the patients with stroke while they performed VR-based rehabilitation, as it was assumed by Flow Zone, and this finding might provide health professionals with clinically useful information in determining the appropriate level of difficulty of VR-based rehabilitation, by reference to the level of enjoyment.
Five main factors were identified as affecting patient-perceived difficulty and enjoyment: ease of following the directions, experience of pain, scores achieved, novelty and immediate feedback, and self-perceived effectiveness. First, for those participants who emphasized ease of following the directions, some participants mentioned that the workout mode was easier than the game mode because they could “imitate the movements of the virtual trainer” rather than judging the situation for themselves, even though the training intensity was similar between the 2 modes, requiring only approximately 10% of the heart rate reserve. This situation occurred not only in participants with severe cognitive impairment, but also in those with mild-to-moderate impairment. This result implies that the range of patients who are able to participate in VR-based rehabilitation in the early stage would differ depending on the training mode and the method for implementing it. However, most previous studies about VR-based rehabilitation in patients with acute stroke have adopted the game mode of training.11–14 Applying the workout mode of training in the very early stage would be better to accommodate a wide range of patients with various levels of stroke severity because the human-like virtual trainer is easy to follow.
Second, experience of pain directly affected participants' difficulty and enjoyment. That is, experiences of pain made some participants view the VR-based rehabilitation as something to avoid or fear. One participant was even absent from training due to her pain experience. Muscle soreness during VR-based rehabilitation also emerged as a main theme related to the feasibility of training in patients with chronic stroke in a previous study.39 Patients with acute stroke more commonly have motor weakness compared with patients with chronic stroke due to their drastically decreased activity since the recent onset of stroke. Therefore, it is certainly necessary to find a way for patients to avoid pain so they do not lose interest in the VR-based rehabilitation.
Third, feedback during training, including both KR and KP, affected patient-perceived difficulty and enjoyment, but in opposite ways. That is, scores achieved (KR) made some participants mark a low level of enjoyment, whereas novelty and multisensory feedback in the process of training (KP) had a positive effect on participants' enjoyment. With regard to the effect of KR, we can assume that participants tended to have a lack of confidence due to their impairments, which might make them sensitive to their scores. Thus, it would be better not to discourage patients by showing or providing low scores. Not presenting the numerical scores to the patient would be one alternative. However, more fundamentally, it would be better to progress the level of difficulty of the training considering the process of the patient's recovery in order to balance the difficulty of the task and the individual's capability level,17 meaning that software should be developed to support the patient being in the Flow Zone during VR-based rehabilitation. Meanwhile, participants who understood the rules of the game mode of training commonly reported immediate feedback in the process of training as a main factor affecting their enjoyment. Therefore, we suggest applying the game mode of training with multisensory feedback only in patients who understand the rules of the game in order to maintain their enjoyment.
Fourth, participants' self-perceived effectiveness affected their positive attitude toward training. The effect of the software program applied in the current study on physical outcomes might be verified indirectly by comparison with the results of previous studies. For example, the increase of UE function measured by UE-FMA in the current study (169%) was higher than that of previous studies (64%–70%)11,12 that applied VR-based rehabilitation in addition to conventional therapy; however, the baseline UE function in the current study was significantly lower than in the previous studies. Furthermore, the improvement was great enough so that participants could perceive it themselves, resulting in a positive attitude toward training. Therefore, it would be necessary to apply VR content to a training program adequately effective at improving physical outcomes in order to induce patients to continue training with a positive attitude.
Limitations, Strengths, and Future Directions
This study explored the experiences of a small sample of participants with varied age and severity of stroke; therefore, the results cannot be generalized. Another limitation is that the physical improvements could have been due to spontaneous recovery because participants were within 2 months poststroke and conventional therapy was continued as usual during the intervention period. Thus, further study using a control group is needed to establish the causal effect of VR on improved performance. Despite these limitations, to our knowledge, this is one of the first studies analyzing the difficulties and enjoyments of patients with acute stroke in the theoretical framework based on Flow Theory while they participated in VR-based rehabilitation. Through this study, we suggested implementation strategies, which should be applied to VR-based rehabilitation for patients with acute stroke, including those with severe physical and cognitive impairments.
In conclusion, the level of enjoyment could be an indicator of the appropriateness of the level of difficulty because enjoyment occurred when the difficulties of the task and the abilities of the participant were balanced. Therefore, we suggest an implementation strategy for VR-based rehabilitation that supports the patient by achieving balance between the difficulties of the task and the abilities of the patient, by reference to the level of enjoyment. For overcoming patient-perceived difficulty and enhancing enjoyment, ease of following the directions would be best considered in the very early stage, whereas multisensory feedback is more necessary in the later phase for those patients who understand the rules of the game. Health professionals should find a way for patients to avoid pain during training. Knowledge of results should be presented to patients in a positive manner. A training program sufficiently effective in improving physical outcomes needs to be embedded in the VR contents in order to induce patients to continue training with a positive attitude.
Footnotes
Ms Lee, Dr Chung, and Mr Kim provided concept/idea/research design. Mr Lee provided writing. Professor Pyun and Mr Kim provided data collection. Ms Lee, Dr Eun, and Professor Yoon provided data analysis. Professor Yoon provided project management. Dr Eun provided fund procurement. Professor Pyun provided participants, facilities/equipment, and institutional liaisons. Dr Chung provided consultation (including review of manuscript before submission). The authors thank the physical therapists of Korea University Anam Hospital for their contribution to the design of software for this study. They also thank all participants of this study.
Approval for this study was obtained from the Institutional Review Board of Korea University Anam Hospital (ED13049).
This research was supported by R&D grant (No. 2013006) on rehabilitation by Korea National Rehabilitation Center Research Institute, Ministry of Health & Welfare.
Clinical trial registration: ISRCTN04144761
- Received May 10, 2015.
- Accepted April 28, 2016.
- © 2016 American Physical Therapy Association
References
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