Video Game-Based Exercises for Older People With Chronic Low Back Pain: A Randomized
Controlled Trial (GAMEBACK)
RUNNING HEAD: GAMEBACK
ARTICLE TYPE: Original Research
SECTION/TOC CATEGORY: Musculoskeletal
AUTHOR BYLINE: Joshua R. Zadro, Debra Shirley, Milena Simic, Seyed J. Mousavi, Dragana
Ceprnja, Katherine Maka, Jennie Sung, Paulo Ferreira
AUTHOR INFORMATION:
J.R. Zadro, PhD, Department of Physiotherapy, Faculty of Health Sciences, The University of
Sydney, 75 East St, Lidcombe, NSW 2141, Australia. Address all correspondence to Mr Zadro
at: [email protected].
D. Shirley, PhD, Department of Physiotherapy, Faculty of Health Sciences, The University of
Sydney.
M. Simic, PhD, Department of Physiotherapy, Faculty of Health Sciences, The University of
Sydney.
S. J. Mousavi, PhD, Department of Orthopaedic Surgery, Harvard Medical School, Boston,
Massachusetts; and Center for Advanced Orthopaedic Studies, Beth Israel Deaconess Medical
Center, Boston, Massachusetts.
D. Ceprnja, BPhty (Hons), Department of Physiotherapy, Westmead Public Hospital, Western
Sydney Local Health District, Westmead, NSW Australia.
K. Maka, BAppSc (Phty), Department of Physiotherapy Department, Westmead Public Hospital,
Western Sydney Local Health District.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
J. Sung, BAppSc (Phty) (Hons), Department of Physiotherapy, Westmead Public Hospital,
Western Sydney Local Health District.
P. Ferreira, PhD, Department of Physiotherapy, Faculty of Health Sciences, The University of
Sydney.
ACCEPTED: July 16, 2018
SUBMITTED: October 19, 2017
Abstract
Background. Video game technology increases adherence to home exercise and could support
self-management for older people with chronic low back pain (LBP).
Objectives. The objective was to investigate the effects of home-based video game exercises on
pain self-efficacy and care seeking in older people with chronic LBP.
Design. The study was a randomized controlled trial.
Setting. The setting was a community and waiting list.
Patients. Sixty participants, aged 55 years or older, with chronic LBP were randomized (1:1) to
Wii Fit U exercises or to continue their usual activities for 8 weeks.
Intervention. Home-based Wii Fit U flexibility, strengthening, and aerobic exercises, for 60
minutes, 3 times per week, with fortnightly calls from a physical therapist was prescribed.
Measurements. Measurements included pain self-efficacy and care seeking (primary outcomes),
and physical activity, pain, function, disability, fear of movement/re-injury, falls-efficacy,
recruitment and response rates, adherence, experience with the intervention, and adverse events
(secondary outcomes).
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Results. The mean age of participants was 67.8 (SD = 6.0) years. Adherence to the total
recommended exercise time was 70.8%, and no adverse events were reported. Participants
completing Wii Fit U exercises had significantly higher pain self-efficacy at 6 months, but not
immediately post-intervention or at 3 months; there were no between-group differences in care-
seeking. Compared with the control group, participants completing Wii Fit U exercises
demonstrated significantly greater improvements in pain and function at 8 weeks and were more
likely to engage in flexibility exercises at 6 months. There were no significant between-group
differences for the remaining outcomes.
Limitations. Participants and therapists were not blinded.
Conclusion. Wii Fit U exercises improved pain self-efficacy at 6 months and pain and function
immediately post-intervention in older people with chronic LBP, but the clinical importance of
these changes are questionable. Wii Fit U exercises had no effect on care-seeking, physical
activity, disability, fear of movement/re-injury, or falls-efficacy.
KEYWORDS
Home Exercise, Low Back Pain, Video-Game, Nintendo Wii, Older People
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Low back pain (LBP) is the most disabling and costly musculoskeletal condition worldwide,
1-3
with the majority of this burden accounted for by older people who develop chronic symptoms.
4
Chronic LBP becomes more severe
5
and disabling with age,
6
and can have a significant impact
on physical functioning.
7
Despite this, older people with chronic LBP are commonly excluded
from randomized controlled trials (RCT) evaluating treatment options
8
; and given the global
population of people over 60 years old expected to triple by 2050,
9
more research on this
population should be a priority.
Structured exercise programs are recommended for the management of chronic LBP,
10
however,
adherence to unsupervised home-exercise is poor.
10-13
Nevertheless, older people with poor
physical functioning prefer home-based exercises as travelling to treatment facilities can be
difficult and supervised exercise can be costly.
14
Poor adherence to home-exercise is likely
explained by a lack of motivation to perform exercises without supervision, but could also be the
result of poor pain self-efficacy.
15
Pain self-efficacy is the ability to continue daily activities
despite pain
16
and has been shown to significantly influence treatment outcomes in people with
chronic pain.
13
Pain self-efficacy is also a mediator explaining how pain leads to disability.
17
Therefore, given that disability is associated with greater care-seeking,
18
improving pain self-
efficacy should be a priority if older people with chronic LBP are to effectively self-manage their
condition and reduce their health-care utilization.
19
Video-game exercise programs are being increasingly used for musculoskeletal rehabilitation,
20
and can improve balance
21
and falls-efficacy
22
in older people with poor physical function.
Video-game exercises can also improve pain, disability, fear avoidance, and quality of life in
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
adults with chronic LBP,
23,24
but have not been investigated as a self-management strategy for
older people with chronic LBP. Video-game exercises are interactive and may increase patients‟
adherence to home-exercise,
25,26
mostly because of video and audio instructions, and feedback on
performance.
27,28
With this in mind, video-game exercises could be a unique solution to increase
older people‟s motivation to self-manage their chronic LBP through home-exercise and improve
their pain self-efficacy. Using video-game exercises as a self-management strategy could also
reduce care-seeking, and has important implications for reducing health-care costs for chronic
LBP in the long-term.
The primary aim of this RCT is to investigate the effects of an unsupervised home-based video-
game exercise program for improving pain self-efficacy and care-seeking at 3 and 6 months in
older people with chronic LBP. The secondary aim is to investigate whether the intervention
improves physical activity, pain, function, disability, fear of movement/re-injury, and falls-
efficacy more than a control group, and to evaluate the recruitment and response rates,
adherence, experience with the intervention, and the incidence of adverse events.
Methods
Design
We conducted a single-blinded RCT in people 55 years or older with chronic LBP and compared
an unsupervised home-based video-game exercise program to a control group instructed to
maintain their usual activities (including care-seeking behaviours). This trial is reported in
accordance with the CONsolidated Standards OF Reporting Trials (CONSORT) statement
29
and
the intervention has been documented according to the Template for Intervention Description
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
and Replication (TIDieR) checklist.
30
The study protocol was registered prospectively with the
Australian New Zealand Clinical Trials Registry (ACTRN12615000703505) and has been
published.
31
All recruitment and data collection procedures were approved by the Human
Research Ethics Committee from the Western Sydney Local Health District [Local HREC
reference: (4266) AU RED HREC/15/WMEAD/143] and participants gave informed written
consent.
Participants
Sixty participants over 55 years with chronic LBP were randomly allocated to a video-game
exercise (n = 30) or control group (n = 30). The inclusion/exclusion criteria we specified in our
protocol are found in Table 1. However, to increase the recruitment rate we did not exclude
participants who received physical therapy for their LBP in the past 6 months.
Sample Size Estimation
Sample size estimation was performed using GPower (Version 3.1). We require 30 participants
per group to detect a 10.9 point difference between groups on the 60-point pain self-efficacy
questionnaire (PSEQ). This value is based on the smallest detectable change in the PSEQ
following an exercise therapy intervention in people with chronic LBP.
32
Our calculations were
based on a post-intervention standard deviation of 15,
32
using a two group, one-tailed t-test (P =
.05) with 80% power. These calculations assumed a worst-case loss to follow-up of 20%.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Recruitment method and screening procedures
Participants were recruited from: i) the local community via advertisements in an online seniors‟
newsletter; and ii) the waiting list of the Outpatient Physiotherapy Department at Westmead
Hospital, Sydney, Australia. People over 55 years on the waiting list with a referral for chronic
LBP treatment were contacted via mail or presented with information about the study during
routine telephone communication from their physical therapist. Those interested in the trial
contacted a research investigator who clarified the inclusion/exclusion criteria over the phone,
sent them detailed information about the trial, and screened consenting and potentially eligible
participants. Eligible participants were guided through the baseline assessment by a qualified
physical therapist who remained blind to group allocation. From November 2015 to August 2016
only four participants from the waiting list were interested and eligible for the trial, so we
modified our recruitment strategy to include participants from the general community to increase
the recruitment rate.
Randomization
Following the baseline assessment, the assessing physical therapist contacted a blinded “off-site”
investigator who used a computer-generated number system to determine group allocation.
Participants were randomized (1:1) to either the video-game exercise or control group, with
randomization performed in ten blocks of six to ensure balance in sample size across groups over
time.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Intervention
Participants in the video-game exercise group engaged in an unsupervised home-based exercise
program for 8 weeks using a Nintendo Wii U console with Wii Fit U software. All video-game
equipment used in this trial was owned by The University of Sydney and was loaned to
participants for the trial period. Participants in the intervention group were visited at home by a
physical therapist with three years clinical experience who set up the video-game equipment and
guided them through their first session. This session took 1-2 hours depending on the participants
understanding and confidence to use the program once left unsupervised. The Wii Fit U
exercises are commercially available and it was not possible to alter which exercises were
displayed to participants. Therefore, participants were given a booklet which outlined a range of
flexibility, body weight resistance, and aerobic exercises pre-selected by the research team to
standardize the intervention. Prior to instructing the participant how to perform Wii Fit U
exercises, the physical therapist assessed their ability to perform several movements included in
the program. If the participant appeared unsafe while performing any of these movements or
reported at least a 2/10 increase in their pain that failed to subside when the movement stopped,
Wii Fit U exercises that involved these movements were removed from the exercise list. Further
details regarding the included Wii Fit U exercises and the movements assessed during the initial
visit can be found elsewhere.
31
Wii Fit U exercises included video and audio instructions, gave
participants feedback on their performance during and after exercises, and scored their
performance. For example, a pressure meter encouraged participants to perform „lunges‟ with
more hip and knee flexion (and subsequently more pressure on the balance board). Once the
participant felt confident performing Wii Fit U exercises independently the physical therapist
outlined the exercise protocol they were to follow over the next 8 weeks.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Participants were asked to perform Wii Fit U exercises for 60 minutes, 3 times per week.
31
They
were instructed to have at least one day of rest between exercise sessions and to use their
symptoms in the 24 hours post-exercise to guide whether they should increase or decrease the
duration and intensity of subsequent sessions. A physical therapist contacted participants
fortnightly via telephone to encourage them to progress their exercises if appropriate, while also
monitoring for any adverse events or equipment issues. Exercise progression was centered on
increasing the repetitions of an exercise or selecting more challenging exercises to maintain a
perceived exertion of 13 on the Borg rating scale. On the other hand, participants were
encouraged to modify exercises they found too difficult by reducing the repetitions, range of
movement, balance requirements, or the duration of the exercise sessions to maintain a similar
perceived exertion.
Outcomes
All baseline data was collected in-person at The University of Sydney (participants from the
community) or at the Outpatient Physiotherapy Department of Westmead Hospital (participants
on the waiting list). All remaining follow-up surveys (8 weeks, 3 and 6 months) were either sent
to participants‟ email address via Research Electronic Data Capture (REDCap) or posted to their
residential address. Participants who did not adhere to the intervention were encouraged to
complete all follow-up assessments. All study data were collected and managed using REDCap
electronic data capture tools hosted at The University of Sydney.
33
Our primary outcomes were pain self-efficacy and care-seeking at 3 and 6 months from baseline.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Pain self-efficacy was assessed using the 10-item Pain Self-Efficacy Questionnaire (PSEQ), a
valid and reliable tool for detecting changes in people with chronic pain over time.
16
PSEQ
scores range from 0-60, with higher scores indicating higher pain self-efficacy. Care-seeking was
assessed using a 3-item questionnaire developed for this trial which asked participants to indicate
whether they were: i) currently receiving treatment (e.g. GP visits, private physical therapy, etc.);
ii) planning to start treatment in the coming months; or iii) currently taking medication for their
LBP. Engagement in physical activity was assessed by the RAPA questionnaire, a valid tool for
discriminating between active and inactive older adults.
34
Participants selected the time and
intensity of physical activity that bests described how much aerobic physical activity they
usually do over the course of a week (e.g. “I do 30 minutes or more per day of moderate physical
activities 5 or more days per week”). Participants also indicated whether they performed any
„strength‟ or „flexibility‟ exercises at least once per week. The American College of Sports
Medicine (ACSM) recommends that all adults perform a weekly minimum of 150 minutes
moderate-intensity or 60 minutes vigorous-intensity physical activity.
35
In light of these
recommendations, we formed three categories of physical activity engagement that has also been
used in a previous study
36
: i) sedentary or only light physical activity (items 1-3); ii) moderate or
vigorous-intensity physical activity less than recommended by the ACSM (items 4-5); and iii)
physical activity that met the ACSM recommendations (items 6-7). Data on pain self-efficacy,
care-seeking, and engagement in physical activity levels were collected at baseline, 8 weeks, 3
months, and 6 months.
The remaining outcomes were only collected at baseline and 8 weeks.
31
Usual pain intensity over
the last week was assessed using the 11-point NRS.
37
Function was assessed using the Patient
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Specific Functional Scale (PSFS), a valid, reliable, and responsive tool for detecting changes in
function over time in people with LBP.
38
Disability was measured using the 24-item Roland
Morris Disability Questionnaire (RMDQ) which has demonstrated good validity, reliability and
sensitivity for detecting changes in disability over time in people with LBP.
39
Fear of
movement/re-injury was assessed using the 17-item Tampa Scale of Kinesiophobia (TSK) which
has demonstrated good validity, reliability and responsiveness for evaluating changes in pain-
related fear in people suffering chronic LBP.
40
Falls-efficacy was measured using the 16-item
Falls-Efficacy Scale-International (FES-I) questionnaire which assesses participants‟ concerns
about the possibility of falling during a number of daily activities (e.g. walking upstairs).
41
We
assessed a large number of secondary outcomes to identify important variables to assess in
follow-up studies in this area, particularly since this is the first trial to investigate an
unsupervised home-based video-game exercise program for older people with chronic LBP.
Feasibility outcomes
Adherence. Participants tracked the duration and frequency of their exercise sessions in a paper
exercise diary. Despite reporting issues associated with paper exercise diaries
42
it is simple and
likely appropriate for an older population.
43
Adherence was based on the extent the participants
exercise behaviours corresponded to our recommendations
15
: i) total minutes, expressed as a
percentage of the total recommended exercise time (60 minutes x 3 x 8 weeks = 1,440 minutes);
ii) number of weeks adherent to the protocol (≥180 minutes/week), expressed as a percentage of
8 weeks; iii) total number of sessions ≥60 minutes; and iv) total number of sessions, irrespective
of duration. Both iii) and iv) were expressed as a percentage of the total number of recommended
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
sessions (n = 24).
Following trial registration, we also decided to collect data on the recruitment and response rates,
experience with the intervention, and the incidence of adverse events. Further details about these
outcomes can be found in our protocol.
31
Experience with the intervention. Participants in the video-game exercise group completed a 12-
item questionnaire that allowed them to rate the following aspects of the intervention: i)
usability; ii) exercise variation; iii) ease of exercise progression; iv) the extent symptoms
interfered with the program; and v) overall experience (eAppendix A).
Data Analysis
We reported data on feasibility outcomes using descriptive statistics [means, standard deviations
(SD), %]. We performed linear regression analyses for continuous outcome variables and logistic
regression analyses for dichotomous outcome variables. Estimates were adjusted for baseline
covariates and any variable that was significantly different between groups at baseline. STATA
statistical software (version 13.1) was used to conduct all analyses (StataCorp LP. 2013, College
Station, TX, USA). Coefficients (β) and 95% confidence intervals (CI) were calculated from
regression models, with significance level set at 0.05. We attempted to follow up all participants
regardless of whether they withdrew from their allocation. All analyses were performed as per
intention-to-treat.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Results
One hundred and seventeen individuals with chronic LBP interested in participating in this trial
were screened for eligibility between November 2015 and February 2017 (Figure). Sixty people
(51%) were eligible to participate and were randomized to the video-game exercise (n=30) or
control group (n=30), with 56 participants (93.3%) recruited from the community and four
participants (6.7%) from the waiting list. The recruitment rates for the total sample, participants
on the waiting list, and participants from the community were 4.3, 0.4 and 11.2 participants per
month, respectively. The mean age (SD) of participants was 67.8 (6.0) years old, and there were
31 females (51.7%). At baseline, participants allocated to receive Wii Fit U exercises had higher
levels of function (PSFS) [5.3 (1.4) vs. 4.3 (2.1), P = .04]. There were no significant between-
group differences for the remaining baseline characteristics (Tab. 2).
Of the 30 participants allocated to receive Wii Fit U exercises, four participants were not able to
start the program due to personal commitments. The remaining participants commenced the
program (n = 26). All participants in the intervention group and 28 participants in the control
group (93.3%) completed the post-intervention follow-up questionnaire. Follow-up data was
available from 56 (93.3%) and 57 (95.0%) participants at 3 and 6 months respectively (Figure),
as one participant responded to the questionnaire at 6 months, but not at 3 months. During the
fortnightly calls, it was relatively common for participants to report some temporary soreness
during or after performing Wii Fit U exercises. However, no participant reported any soreness
that limited their participation in the program or any other adverse events related to Wii Fit U
exercises (e.g. fall, injury, etc.).
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
There were no between-group differences in PSEQ scores immediately post-intervention
(β=1.20, 95%CI: -3.23-5.64, P = .59) or at 3 months (β=4.33, 95%CI: -0.24-8.80, P=.06).
However, participants completing Wii Fit U exercises had significantly higher PSEQ scores at 6
months compared to the control group (β=5.17, 95%CI: 0.52-9.82, P=.03) (Tab. 3). Participants
completing Wii Fit U exercises also demonstrated significantly greater improvements in pain
(β=-1.07, 95%CI: -2.11-(-)0.03, P=.04) and function (β=1.21, 95%CI: 0.10-2.33, P=.03)
immediately post-intervention compared to the control group. There were no significant
between-group differences in disability (β=-0.85, 95%CI: -2.58-0.89, P=.33), fear of
movement/re-injury (β=-2.97, 95%CI: -6.14-0.21, P=.07), and falls-efficacy (β=-1.08, 95%CI: -
3.08-0.92, P=.28) immediately post-intervention, or in any care-seeking or physical activity
behaviours at 8 weeks and 3 months (Tab. 4). However, participants completing Wii Fit U
exercises were significantly more likely to engage in flexibility exercises at least once per week
at 6 months (OR=4.36, 95%CI: 1.06-17.93, P=.04) (Tab. 4).
Adherence
Data on total exercise time and the number of sessions irrespective of duration was normally
distributed (Shapiro-Wilk test p-value: 0.788 and 0.590, respectively). Data on the number of
sessions ≥60 minutes and weeks adherent to the protocol were not normally distributed (p=0.026
and p=0.038, respectively). The mean (SD) total exercise time (minutes) and number of sessions
irrespective of duration was 1019.1 (489.5) (70.8% of recommendation) and 20.4 (9.3) (85.1% of
recommendation), respectively. However, the median (interquartile range, IQR) number of
sessions ≥60 minutes was only 8 (15) (33.3% of recommendation). The median (IQR) number of
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
weeks participants were adherent to the protocol was 2 (3) (25% of recommendation), and
adherence to Wii Fit U exercises tended to decrease throughout the trial period (Tab. 5).
Experience with the intervention
Overall, participants reported high usability (average scores ranged from 7.9-8.7/10), sufficient
exercise variety (8.2/10) and challenge (7.4/10), and a positive overall experience using the
program (7.3/10). Participants felt confident to progress their exercises throughout the program
with (7.6/10) or without (6.8/10) the physical therapist‟s guidance, rarely had symptoms that
stopped them from using the program (3.3/10), but occasionally experienced symptoms
following an exercise session (5.7/10). On average, participants indicated that a 50.8%
improvement in their LBP would make participating in the 8 week program worthwhile
(eAppendix B).
Discussion
Participants completing Wii Fit U exercises reported significantly higher pain self-efficacy at 6
months compared to a control group (but not immediately post-intervention or at 3 months), and
there was no between-group difference in care-seeking at any time-points. Participants
completing Wii Fit U exercises demonstrated significantly greater improvements in pain and
function immediately post-intervention compared to the control group, and were more likely to
be engaged in flexibility exercises (only at 6 months). However, these effects were small and
didn‟t reach the minimal clinically important difference (MCID). The adjusted between-group
difference in pain self-efficacy scores at 6 months was 5.2 (MCID: 11),
32
while the adjusted
between-group difference in pain and function immediately post-intervention were 1.1 (MCID:
2) and 1.2 (MCID: 2),
32,44
respectively. Despite these small improvements, Wii Fit U exercises
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
are an active approach to the treatment of chronic LBP and can be performed at home without
therapist supervision. Future studies investigating different doses of exercise, forms of
progression, and potentially combining home-based video-game exercises with other therapies
could increase the effect sizes found in our study. This would support widespread
implementation of this novel approach to self-management in older people with chronic LBP.
Our study showed that adherence to Wii Fit U exercises in older people with chronic LBP (based
on total time and total number of sessions performed) is high, particularly when compared to
studies where people with chronic LBP were instructed to exercise without supervision.
11,12,15,45-
47
For example, adherence to an unsupervised exercise program at local health clubs in people
with chronic LBP was only 33% (based on the proportion of recommended sessions
completed).
47
This figure is similar across other studies
12,45,46
and is considerably less than the
corresponding value found in our study (85%). In contrast, Hurley and colleagues (2015)
48
reported 80% adherence to an individualized walking intervention for people with chronic LBP.
However, weekly contact with a therapist, combined with the convenience and simplicity of a
walking intervention might explain the high adherence. High adherence to Wii Fit U exercises in
our study – based on total time and total number of sessions performed – could be due to a
number of factors. Adherence was likely facilitated during the fortnightly follow-up calls where
participants were encouraged to progress their exercises. Further, Wii Fit U exercises provide
video and audio instructions, and feedback on performance; factors that promote adherence to
home exercise in people with chronic LBP.
27,28
Video-game technology also increases
motivation to perform home exercises,
25
and there is preliminary evidence supporting the use of
supervised Wii Fit U exercises for adults with chronic LBP.
23,24
However, since this is the first
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
study to investigate unsupervised Wii Fit U exercises for older people with chronic LBP,
additional studies are needed to explore how Wii Fit U exercises influence adherence to home-
exercise in this population.
Although adherence based on the total time and total number of sessions was high, we need to
acknowledge that adherence based on the number of sessions ≥60 minutes or a weekly total ≥180
minutes was low; with the median number of adherent weeks being two and adherence gradually
decreasing throughout the trial. This was despite fortnightly calls to participants and suggests our
recommendation of three 60 minutes sessions per week needs to be revised for future trials in
this population. However, with the total time engaged in Wii Fit U exercises and total number of
sessions close to our recommendations (85% and 71%, respectively), it appears older people
with chronic LBP prefer more frequent sessions of shorter duration.
Despite high adherence to Wii Fit U exercises in our trial, there were no between-group
differences in physical activity behaviours at any time-point (excluding flexibility exercises at 6
months). This suggests Wii Fit U exercises had no influence on self-reported physical activity
levels and we hypothesise a number of reasons for this. At baseline, most participants performed
either moderate or vigorous-intensity physical activities each week (n = 46, 76.7%), with 25
reporting that they met the ACSM physical activity guidelines (41.7%). This suggests the
majority of participants were reasonably active before entering the trial, and it is possible that
Wii Fit U exercises failed to give those who were inactive enough additional physical activity to
increase their classification. Further, the measure of physical activity used in this study might not
have been sensitive enough to capture changes in physical activity following the intervention.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
More sensitive physical activity assessment tools, including objective measures (e.g.
accelerometers) should be used in future trials. Finally, it is possible that motivation to continue
being physically active decreased after the video-game equipment was collected at 8 weeks.
Exercise self-efficacy is an important predictor of ongoing physical activity engagement in older
people engaged in a structured exercise program
49
and should be assessed in future studies to
better understand between-group differences in physical activity engagement. Further, given that
adherence gradually decreased throughout the trial, strategies to maintain adherence and support
physical activity engagement should be considered in future trials.
Our study showed a high recruitment rate in community-dwelling older people (11.2
participants/month), but a very low recruitment rate from the waiting list (0.4
participants/month). This is despite reassuring people they would not lose their position on the
waiting list, which suggests recruiting older people with chronic LBP from an outpatient waiting
list wasn‟t feasible. Nevertheless, the possibility that this approach might be feasible for multi-
site trials or trials with a larger budget to dedicate towards recruitment cannot be excluded. We
hypothesise recruitment rate differences between patients on the waiting list and people in the
community are due to the sample‟s desire to self-manage their condition through home-exercise,
which is likely a reflection of their pain self-efficacy and disability. Participants in our trial had
high pain self-efficacy and low disability at baseline, with 56 participants recruited from the
community and four from the waiting list. With this in mind, high pain-self efficacy and low
disability might be a trait of participants willing to engage in home-based Wii Fit U exercises
and might not be common in patients on a waiting list for treatment. In addition, older people
could be more willing to engage in Wii Fit U exercises if they are already managing their pain in
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
the community, rather than being on a waiting list. High baseline pain self-efficacy might also
explain why there was a significant between-group difference at 6 months, but not immediately
post-intervention. However, the between-group difference at 6 months was primarily due to a
decline in pain self-efficacy in the control group. Previous studies have demonstrated post-
intervention improvements in pain self-efficacy for people with chronic LBP when the sample
had low baseline pain self-efficacy,
50-55
since high baseline pain self-efficacy likely reduces the
scope for improvement (ceiling effect). Therefore, a home-based video-game exercise program
may be even more beneficial for older people with chronic LBP and lower levels of pain self-
efficacy, and strategies to recruit these individuals should be considered in future trials.
Alternatively, if it isn‟t feasible to recruit individuals with low pain self-efficacy, it might be
more appropriate to change the primary outcome measure to either pain or function.
Given the enormous global cost of chronic LBP,
3,56
increasing an individual‟s capacity to self-
manage their pain, while reducing the need for therapist supervision, should be a priority.
Numerous studies have investigated self-management approaches involving pain education and
exercise,
57
showing moderate effect sizes for pain and disability.
57
However, most of these
interventions involve extensive interactions with a therapist.
57,58
Despite this, the few studies that
investigated self-management strategies for chronic LBP with minimal supervision show
promising results.
59-61
For example, a moderated email discussion group, combined with pain
education and exercise advice was more beneficial than usual care for reducing pain and
disability.
60
On the other hand, there has only been one study investigating a self-management
approach for older people with chronic LBP, and this involved extensive therapist supervision.
This study compared six weekly education seminars on the benefits of exercise, relaxation, and
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
goal setting, to a waiting list control group, but found no between-group differences in pain and
self-management attitudes.
62
A possible explanation for these findings could be poor adherence
to the seminars, with only 16% of participants attending every session. However, the possibility
that promoting self-management in older people with chronic LBP is more complex, cannot be
ruled out. This is highlighted by the findings of our trial, where pain and function significantly
improved following Wii Fit U exercises, but improvements in pain self-efficacy were only
greater than the control group at 6 months. Furthermore, there were no between-group
differences in the remaining physical activity and care-seeking variables, nor disability, fear of
movement/re-injury and falls efficacy at any time point. Despite high adherence, improvements
in these outcomes may be more dependent on therapist supervision and may not be adequately
addressed during an unsupervised exercise program. In addition, the lack of research on web-
based or video-game self-management strategies in older people with chronic LBP may reflect
concerns with the familiarity and access to modern technology, but should nonetheless be a
consideration for future research.
Strengths and limitation
This study has numerous strengths. First, we ensured transparency by registering and publishing
our study protocol.
31
Second, Wii Fit U exercises are commercially available and of relative low
cost, making it suitable for use at home and direct implementation to the community if shown to
be effective in a large trial. In contrast, video-game interventions developed specifically for
research are rarely manufactured on a large scale, resulting in issues related to cost and
accessibility.
63-66
Third, consistency of the intervention was enhanced by only one physical
therapist setting up the exercise program. Finally, we had a high response rate to the
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
questionnaires posted to participants at 3-months (93.3%) and 6-months (95.0%), which was
likely due to participants in the control group being offered Wii Fit U exercises following the
completion of the trial.
This study has limitations. First, participants completing Wii Fit U exercises received fortnightly
follow-up calls during the first 8 weeks, and had contact with the therapist when the video-game
equipment was set-up and collected. Participants in the control group were not contacted during
this time. Therefore, the possibility that differences in participant-therapist interaction could
explain the between-group differences in clinical outcomes cannot be ruled out. Future trials
should consider matching therapist contact between the groups to reduce confounding and more
accurately determine the effect size of Wii Fit U exercises. Second, we were unable to blind the
participants and physical therapist administering the intervention. However, since Wii Fit U
exercises were performed without supervision this is unlikely to have a large impact on internal
validity. Third, participants used a paper exercise diary to track adherence, which may result in a
degree of inaccuracy.
42
However, unlike other studies in the field, we expressed adherence in
numerous ways to get an overall picture of how compliant the participants were to our
recommendations.
43
We also decided not to use exercise adherence data from the Wii Fit U
software as it only records exercise time when the participant registers a score. This becomes
problematic when a participant fails to complete an exercise using the technique specified by the
software. For example, participants performing a squat on the balance board might not register a
score if they don‟t move their centre of mass far enough posteriorly. In addition, the Wii Fit U
software only records exercise time when the participant is engaged in a selected exercise, and
not when the participant is learning an exercise during a demonstration, or when transitioning
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
between exercises (i.e. rest time). Finally, it was not possible to extract exercise selection data
from the software so there was no way to ensure participants stuck to our recommendations,
despite being reminded during fortnightly follow-up calls. In addition, we did not ask
participants to write down which exercises they performed each session as this could have
decreased motivation to use the program. However, since no single type of exercise is superior
for people with chronic LBP,
67-69
this information is unlikely to influence the design of future
trials.
Conclusion
Wii Fit U exercises can improve pain self-efficacy (at 6 months), and pain and function
(immediately post-intervention) in older people with chronic LBP, but the clinical importance of
these changes are questionable. Wii Fit U exercises were not effective for improving care-
seeking, physical activity, disability, fear of movement/re-injury, or falls-efficacy. Future trials
investigating home-exercise programs for older people with chronic LBP must consider ways to
target improvements in these outcomes.
Author Contributions and Acknowledgments
Concept/idea/research design: J.R. Zadro, D. Shirley, M. Simic, S.J. Mousavi, D. Ceprnja, K.
Maka, J. Sung, P. Ferreira
Writing: J.R. Zadro, D. Shirley, M. Simic, S.J. Mousavi
Data collection: J.R. Zadro, D. Shirley, K. Maka, J. Sung
Data analysis: J.R. Zadro, D. Shirley, S.J. Mousavi
Project management: J.R. Zadro, D. Ceprnja, K. Maka, P. Ferreira
Fund procurement: P. Ferreira
Providing participants: K. Maka, J. Sung
Providing facilities/equipment: D. Ceprnja, K. Maka, J. Sung
Providing institutional liaisons: D. Shirley, D. Ceprnja, P. Ferreira
Consultation (including review of manuscript before submitting): J.R. Zadro, D. Shirley, M.
Simic, D. Ceprnja, K. Maka, J. Sung, P. Ferreira
The authors would like to acknowledge the contribution of 12 Nintendo Wii U consoles from
S.J. Mousavi, using funds from his International Postdoctoral Research Fellowship – The
University of Sydney. The authors would also like to acknowledge the in-kind contribution of
three Nintendo Wii U consoles from Nintendo, and the enormous contribution from numerous
physical therapy and administrative Staff at Westmead Hospital, Sydney, Australia.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Ethics Approval
All recruitment and data collection procedures were approved by the Human Research Ethics
Committee from the Western Sydney Local Health District [Local HREC reference: (4266) AU
RED HREC/15/WMEAD/143], and participants gave informed written consent.
Funding
None received.
Disclosures and Presentations
The authors completed the ICJME Form for Disclosure of Potential Conflicts of Interest. They
reported no conflicts of interest.
Zadro JR, Shirley D, Simic M, Mousavi SJ, Cerpjna D, Maka K, Ferreira PH. Video-game based
exercises for older people with chronic low back pain: A protocol for a pilot randomized
controlled trial (the GAMEBACK Trial). XIV International Back and Neck Pain Forum 2016;
Buxton, Derbyshire, UK. Presented as a poster presentation by Zadro JR.
Zadro JR, Shirley D, Simic M, Mousavi SJ, Cerpjna D, Maka K, Ferreira PH. Video-game based
exercises for older people with chronic low back pain: A protocol for a pilot randomized
controlled trial (the GAMEBACK Trial). Allied Health Research Symposium. Westmead
Hospital. August 2016. Presented as an oral presentation by Zadro JR.
Zadro JR, Shirley D, Simic M, Mousavi SJ, Cerpjna D, Maka K, Ferreira PH. Video-game based
exercises for older people with chronic low back pain: A pilot randomized controlled trial (the
GAMEBACK Trial). XV International Back and Neck Pain Forum 2017; Oslo, Norway.
Presented as an oral presentation by Zadro JR.
No further presentations are planned.
References
1. Vos T, Barber RM, Bell B, et al. Global, regional, and national incidence, prevalence,
and years lived with disability for 301 acute and chronic diseases and injuries in 188
countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.
Lancet. 2015;386:743-800.
2. Walker BF, Muller R, Grant WD. Low Back Pain in Australian Adults: The Economic
Burden. Asia Pac J Public Health. 2003;15:79-87.
3. Wenig CM, Schmidt CO, Kohlmann T, Schweikert B. Costs of back pain in Germany.
Eur J Pain. 2009;13:280-286.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
4. Frymoyer JW, Cats-Baril WL. An overview of the incidences and costs of low back pain.
Orthop Clin North Am. 1991;22:263-271.
5. Dionne CE, Dunn KM, Croft PR. Does back pain prevalence really decrease with
increasing age? A systematic review. Age Ageing. 2006;35:229-234.
6. Buchbinder R, Blyth FM, March LM, Brooks P, Woolf AD, Hoy DG. Placing the global
burden of low back pain in context. Best Pract Res Clin Rheumatol. 2013;27:575-589.
7. Pereira LS, Sherrington C, Ferreira ML, et al. Self-reported chronic pain is associated
with physical performance in older people leaving aged care rehabilitation. Clin Interv
Aging. 2014;9:259-265.
8. Paeck T, Ferreira ML, Sun C, Lin CW, Tiedemann A, Maher CG. Are older adults
missing from low back pain clinical trials? A systematic review and meta-analysis.
Arthritis Care Res (Hoboken). 2014;66:1220-1226.
9. Department of Economic and Social Affairs Population Division. World population
ageing 2009. New York: United Nations Publication; 2010.
10. van Middelkoop M, Rubinstein SM, Verhagen AP, Ostelo RW, Koes BW, van Tulder
MW. Exercise therapy for chronic nonspecific low-back pain. Best Pract Res Clin
Rheumatol. 2010;24:193-204.
11. Basler HD, Bertalanffy H, Quint S, Wilke A, Wolf U. TTM-based counselling in
physiotherapy does not contribute to an increase of adherence to activity
recommendations in older adults with chronic low back pain--a randomised controlled
trial. Eur J Pain. 2007;11:31-37.
12. Friedrich M, Gittler G, Halberstadt Y, Cermak T, Heiller I. Combined exercise and
motivation program: effect on the compliance and level of disability of patients with
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
chronic low back pain: a randomized controlled trial. Arch Phys Med Rehabil.
1998;79:475-487.
13. Asghari A, Nicholas MK. Pain self-efficacy beliefs and pain behaviour. A prospective
study. Pain. 2001;94:85-100.
14. Franco MR, Howard K, Sherrington C, et al. Eliciting older people's preferences for
exercise programs: a best-worst scaling choice experiment. J Physiother. 2015;61:34-41.
15. Beinart NA, Goodchild CE, Weinman JA, Ayis S, Godfrey EL. Individual and
intervention-related factors associated with adherence to home exercise in chronic low
back pain: a systematic review. Spine J. 2013;13:1940-1950.
16. Nicholas MK. The pain self-efficacy questionnaire: Taking pain into account. Eur J Pain.
2007;11:153-163.
17. Lee H, Hubscher M, Moseley GL, et al. How does pain lead to disability? A systematic
review and meta-analysis of mediation studies in people with back and neck pain. Pain.
2015;156:988-997.
18. Ferreira ML, Machado G, Latimer J, Maher C, Ferreira PH, Smeets RJ. Factors defining
care-seeking in low back pain--a meta-analysis of population based surveys. Eur J Pain.
2010;14:747.e1-7.
19. Lazkani A, Delespierre T, Bauduceau B, et al. Healthcare costs associated with elderly
chronic pain patients in primary care. Eur J Clin Pharmacol. 2015;71:939-947.
20. Ravenek KE, Wolfe DL, Hitzig SL. A scoping review of video gaming in rehabilitation.
Disabil Rehabil Assist Technol. 2016;11:445-453.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
21. Szturm T, Betker AL, Moussavi Z, Desai A, Goodman V. Effects of an interactive
computer game exercise regimen on balance impairment in frail community-dwelling
older adults: a randomized controlled trial. Phys Ther. 2011;91:1449-1462.
22. Jorgensen MG, Laessoe U, Hendriksen C, Nielsen OB, Aagaard P. Efficacy of Nintendo
Wii training on mechanical leg muscle function and postural balance in community-
dwelling older adults: a randomized controlled trial. J Gerontol A Biol Sci Med Sci.
2013;68:845-852.
23. Kim SS, Min WK, Kim JH, Lee BH. The Effects of VR-based Wii Fit Yoga on Physical
Function in Middle-aged Female LBP Patients. J Phys Ther Sci. 2014;26:549-552.
24. Park JH, Lee SH, Ko DS. The Effects of the Nintendo Wii Exercise Program on Chronic
Work-related Low Back Pain in Industrial Workers. J Phys Ther Sci. 2013;25:985-988.
25. Miller KJ, Adair BS, Pearce AJ, Said CM, Ozanne E, Morris MM. Effectiveness and
feasibility of virtual reality and gaming system use at home by older adults for enabling
physical activity to improve health-related domains: a systematic review. Age Ageing.
2014;43:188-195.
26. Warburton DE, Bredin SS, Horita LT, et al. The health benefits of interactive video game
exercise. Appl Physiol Nutr Metab. 2007;32:655-663.
27. Jordan JL, Holden MA, Mason EE, Foster NE. Interventions to improve adherence to
exercise for chronic musculoskeletal pain in adults. Cochrane Database Syst Rev.
2010:Cd005956.
28. Escolar-Reina P, Medina-Mirapeix F, Gascon-Canovas JJ, et al. How do care-provider
and home exercise program characteristics affect patient adherence in chronic neck and
back pain: a qualitative study. BMC Health Serv Res. 2010;10:60.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
29. Schulz KF, Altman DG, Moher D. CONSORT 2010 statement: Updated guidelines for
reporting parallel group randomised trials. J Pharmacol Pharmacother. 2010;1:100-107.
30. Hoffmann TC, Glasziou PP, Boutron I, et al. Better reporting of interventions: template
for intervention description and replication (TIDieR) checklist and guide. BMJ.
2014;348:g1687.
31. Zadro JR, Shirley D, Simic M, et al. Video-game based exercises for older people with
chronic low back pain: a protocol for a feasibility randomised controlled trial (the
GAMEBACK trial). Physiotherapy. 2017;103:146-153.
32. Maughan E, Lewis J. Outcome measures in chronic low back pain. Eur Spine J.
2010;19:1484-1494.
33. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic
data capture (REDCap) - A metadata-driven methodology and workflow process for
providing translational research informatics support. J Biomed Inform. 2009;42:377-381.
34. Topolski TD, LoGerfo J, Patrick DL, Williams B, Walwick J, Patrick MB. The Rapid
Assessment of Physical Activity (RAPA) among older adults. Prev Chronic Dis.
2006;3:A118.
35. Garber CE, Blissmer B, Deschenes MR, et al. American College of Sports Medicine
position stand. Quantity and quality of exercise for developing and maintaining
cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults:
guidance for prescribing exercise. Med Sci Sports Exerc. 2011;43:1334-1359.
36. Adams SA, Wirth MD, Khan S, et al. The association of C-reactive protein and physical
activity among a church-based population of African Americans. Prev Med.
2015;77:137-140.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
37. Von Korff M, Jensen MP, Karoly P. Assessing global pain severity by self-report in
clinical and health services research. Spine. 2000;25:3140-3151.
38. Stratford P, Gill C, Westaway M, Binkley J. Assessing disability and change on
individual patients: a report of a patient specific measure. Physiother Can. 1995;47:258-
263.
39. Roland M, Morris R. A study of the natural history of back pain. Part I: development of a
reliable and sensitive measure of disability in low-back pain. Spine. 1983;8:141-144.
40. Woby SR, Roach NK, Urmston M, Watson PJ. Psychometric properties of the TSK-11:
A shortened version of the Tampa Scale for Kinesiophobia. Pain. 2005;117:137-144.
41. Hauer K, Yardley L, Beyer N, et al. Validation of the Falls Efficacy Scale and Falls
Efficacy Scale International in geriatric patients with and without cognitive impairment:
results of self-report and interview-based questionnaires. Gerontol. 2010;56:190-199.
42. Stone AA, Shiffman S, Schwartz JE, Broderick JE, Hufford MR. Patient compliance with
paper and electronic diaries. Control Clin Trials. 2003;24:182-199.
43. Nicolson PJ, Bennell KL, Dobson FL, Van Ginckel A, Holden MA, Hinman RS.
Interventions to increase adherence to therapeutic exercise in older adults with low back
pain and/or hip/knee osteoarthritis: a systematic review and meta-analysis. Br J Sports
Med. 2017;51:791-799.
44. Salaffi F, Stancati A, Silvestri CA, Ciapetti A, Grassi W. Minimal clinically important
changes in chronic musculoskeletal pain intensity measured on a numerical rating scale.
Eur J Pain. 2004;8:283-291.
45. Harkapaa K, Jarvikoski A, Mellin G, Hurri H. A controlled study on the outcome of
inpatient and outpatient treatment of low back pain. Part I. Pain, disability, compliance,
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
and reported treatment benefits three months after treatment. Scand J Rehabil Med.
1989;21:81-89.
46. Sluijs EM, Kok GJ, van der Zee J. Correlates of exercise compliance in physical therapy.
Phys Ther. 1993;73:771-782.
47. Reilly K, Lovejoy B, Williams R, Roth H. Differences between a supervised and
independent strength and conditioning program with chronic low back syndromes. J
Occup Med. 1989;31:547-550.
48. Hurley DA, Tully MA, Lonsdale C, et al. Supervised walking in comparison with fitness
training for chronic back pain in physiotherapy: results of the SWIFT single-blinded
randomized controlled trial (ISRCTN17592092). Pain. 2015;156:131-147.
49. Neupert SD, Lachman ME, Whitbourne SB. Exercise Self-Efficacy and Control Beliefs
Predict Exercise Behavior After an Exercise Intervention for Older Adults. J Aging Phys
Act. 2009;17:1-16.
50. Vong SK, Cheing GL, Chan F, So EM, Chan CC. Motivational enhancement therapy in
addition to physical therapy improves motivational factors and treatment outcomes in
people with low back pain: a randomized controlled trial. Arch Phys Med Rehabil.
2011;92:176-183.
51. Wajswelner H, Metcalf B, Bennell K. Clinical pilates versus general exercise for chronic
low back pain: randomized trial. Med Sci Sports Exerc. 2012;44:1197-1205.
52. Tilbrook HE, Cox H, Hewitt CE, et al. Yoga for chronic low back pain: a randomized
trial. Ann Intern Med. 2011;155:569-578.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
53. Lamb SE, Lall R, Hansen Z, et al. A multicentred randomised controlled trial of a
primary care-based cognitive behavioural programme for low back pain. The Back Skills
Training (BeST) trial. Health Technol Assess. 2010;14:1-253, iii-iv.
54. Woods MP, Asmundson GJ. Evaluating the efficacy of graded in vivo exposure for the
treatment of fear in patients with chronic back pain: a randomized controlled clinical trial.
Pain. 2008;136:271-280.
55. van Hooff ML, van der Merwe JD, O'Dowd J, et al. Daily functioning and self-
management in patients with chronic low back pain after an intensive cognitive
behavioral programme for pain management. Eur Spine J. 2010;19:1517-1526.
56. Gore M, Sadosky A, Stacey BR, Tai KS, Leslie D. The burden of chronic low back pain:
clinical comorbidities, treatment patterns, and health care costs in usual care settings.
Spine. 2012;37:E668-E677.
57. Du S, Hu L, Dong J, et al. Self-management program for chronic low back pain: A
systematic review and meta-analysis. Patient Educ Couns. 2017;100:37-49.
58. Moessner M, Schiltenwolf M, Neubauer E. Internet-based aftercare for patients with back
pain-a pilot study. Telemed J E Health. 2012;18:413-419.
59. Carpenter KM, Stoner SA, Mundt JM, Stoelb B. An online self-help CBT intervention
for chronic lower back pain. Clin J Pain. 2012;28:14-22.
60. Lorig KR, Laurent DD, Deyo RA, Marnell ME, Minor MA, Ritter PL. Can a Back Pain
E-mail Discussion Group improve health status and lower health care costs?: A
randomized study. Arch Intern Med. 2002;162:792-796.
61. Irvine AB, Russell H, Manocchia M, et al. Mobile-Web app to self-manage low back
pain: randomized controlled trial. J Med Internet Res. 2015;17:e1.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
62. Haas M, Groupp E, Muench J, et al. Chronic disease self-management program for low
back pain in the elderly. J Manipulative Physiol Ther. 2005;28:228-237.
63. Thomas JS, France CR, Applegate ME, Leitkam ST, Walkowski S. Feasibility and Safety
of a Virtual Reality Dodgeball Intervention for Chronic Low Back Pain: A Randomized
Clinical Trial. J Pain. 2016;17:1302-1317.
64. Chan EA, Chung JW, Wong TK, Lien AS, Yang JY. Application of a virtual reality
prototype for pain relief of pediatric burn in Taiwan. J Clin Nurs. 2007;16:786-793.
65. Sato K, Fukumori S, Matsusaki T, et al. Nonimmersive virtual reality mirror visual
feedback therapy and its application for the treatment of complex regional pain
syndrome: an open-label pilot study. Pain Med. 2010;11:622-629.
66. Botella C, Garcia-Palacios A, Vizcaino Y, Herrero R, Banos RM, Belmonte MA. Virtual
reality in the treatment of fibromyalgia: a pilot study. Cyberpsychol Behav Soc Netw.
2013;16:215-223.
67. Bystrom MG, Rasmussen-Barr E, Grooten WJ. Motor control exercises reduces pain and
disability in chronic and recurrent low back pain: a meta-analysis. Spine. 2013;38:E350-
E358.
68. Ferreira ML, Ferreira PH, Latimer J, et al. Comparison of general exercise, motor control
exercise and spinal manipulative therapy for chronic low back pain: A randomized trial.
Pain. 2007;131:31-37.
69. Wells C, Kolt GS, Marshall P, Hill B, Bialocerkowski A. Effectiveness of Pilates
exercise in treating people with chronic low back pain: a systematic review of systematic
reviews. BMC Med Res Methodol. 2013;13:7.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Figure. CONSORT flowchart.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Table 1. Inclusion and Exclusion Criteria
a
Type of Criterion
Description
Inclusion
>55 y old
Nonspecific mechanical LBP for at least 3 mo
Usual pain intensity of 3/10 or greater on the
numeric rating scale
Sufficient English ability to understand
exercise instructions
Ability to mobilize independently without the
use of walking aids
Access to a high-definition multimedia
interface–compatible television at home
Exclusion
Diagnosis of serious pathology in the spine
(such as fracture, metastatic disease, spinal
stenosis, or cauda equina syndrome)
Evidence of nerve root compromise
Any medical condition or disability that will
prevent participation in the exercise program,
including:
Cardiovascular risk factors assessed with
the PAR-Q, a screening tool recommended
for all adults willing to initiate an exercise
program
70
Cognitive limitations, as indicated by a
score of <25/30 on the Mini-Mental State
Examination, a reliable and valid test of
cognitive function
71
High risk of falls, as indicated by a score
of >15 on the Falls Risk Assessment Tool,
a reliable measure of the risk of falls in
older adults
72
Physical therapist treatment for LBP in the
preceding 6 mo
a
For potential participants who experienced dizziness or altered consciousness, used prescribed
medications, or had uncontrolled diabetes, clearance from their general practitioners was needed
before they could join the trial. LBP = low back pain; PAR-Q = Physical Activity Readiness
Questionnaire.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Table 2. Baseline Demographic and Outcome Characteristics of Included Participants
a
Variables
Total
Sample (n =
60)
b
Video Game
Exercise
Group (n =
30)
b
Between-
Group
Difference (P)
Demographic
Men
29 (48.3)
12 (20)
.20
Women
31 (51.7)
18 (30)
.20
Age, y
c
68.3 (5.7)
68.8 (5.5)
.47
Body mass index
c
27.2 (3.9)
26.9 (4.1)
.56
Married
48 (80.0)
26 (43.3)
.40
Alcohol consumption
d
29 (48.3)
14 (23.3)
.64
Currently smoking
2 (3.3)
1 (1.7)
1.00
Completed at least high
school
53 (88.3)
26 (43.3)
.26
Employed
13 (21.7)
6 (10.0)
.35
No. of comorbidities
c
1.2 (1.4)
1.1 (1.3)
.64
Outcome
PSEQ score
c
49.5 (8.3)
50.7 (8.2)
.23
Care seeking
Current
e
27 (45.0)
16 (26.7)
.19
Future
f
12 (20.0)
6 (10.0)
1.00
Medication
g
27 (45.0)
16 (26.7)
.19
PA
Strength exercises
h
24 (40.0)
12 (20.0)
1.00
Flexibility exercises
i
44 (73.3)
24 (40.0)
.24
Sedentary or light
PA
j
14 (23.3)
8 (13.3)
.54
PA less than
recommended
k
21 (35.0)
10 (16.7)
.79
PA more than
recommended
l
25 (41.7)
12 (20)
.79
NRS score (0–10)
c
5.0 (1.7)
5.2 (1.6)
.42
PSFS score (0–10)
c
4.8 (1.8)
5.3 (1.4)
.04
m
RMDQ score (0–24)
c
6.8 (5.0)
6.3 (4.8)
.39
TSK score (17–68)
c
34.2 (5.9)
33.6 (6.1)
.48
FEQ-I score (16–64)
c
22.2 (6.2)
21.5 (6.1)
.37
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
a
FEQ-I = Falls Efficacy Questionnaire–International; NRS = numeric rating scale; PA = physical
activity; PSEQ = Pain Self-Efficacy Questionnaire; PSFS = Patient-Specific Functional Scale;
RMDQ = Roland-Morris Disability Questionnaire; TSK = Tampa Scale of Kinesiophobia.
b
Data are reported as number (percentage) of participants unless otherwise indicated.
c
Data are reported as mean (SD).
d
A few times per week or more.
e
Currently receiving treatment for low back pain.
f
Planning to start treatment for low back pain in the coming months.
g
Currently taking medication for low back pain.
h
Engagement in exercises to increase strength at least once per week.
i
Engagement in exercises to improve flexibility at least once per week.
j
Engagement in no PA or only light PA each week.
k
Engagement in levels of moderate- or vigorous-intensity PA each week that were lower than
those recommended by the American College of Sports Medicine (ACSM).
l
Engagement in PA levels that met ACSM recommendations.
m
Significant value.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Table 3. Effect of a Video Game Exercise Program on Pain Self-Efficacy, Pain, Function,
Disability, Fear of Movement/Reinjury, and Falls Efficacy
a
Outcomes
Mean (SD) for:
Unadjusted Between-
Group Difference
Adjusted Between-
Group Difference
Video
Game
Exercise
Group
b
Control
Group
c
β
95% CI
P
β
d
95%
CI
P
Primary
PSEQ score
Baseline
50.7 (8.2)
48.2 (8.3)
8 wk
47.8 (10.3)
44.6 (9.6)
3.20
−2.04 to
8.43
.23
1.20
−3.23
to 5.64
.59
3 mo
49.2 (8.8)
43.1 (12.1)
6.06
0.43 to
11.69
.04
4.33
−0.24
to 8.80
.06
6 mo
48.8 (10.5)
41.7 (11.2)
7.11
1.34 to
12.89
.02
5.17
0.52 to
9.82
.03
Secondary
NRS score
Baseline
5.2 (1.6)
4.8 (1.7)
8 wk
3.8 (2.4)
4.4 (2.3)
−0.66
−1.90 to
0.58
.29
−1.07
−2.11
to
−0.03
.04
PSFS score
Baseline
5.3 (1.4)
4.3 (2.1)
8 wk
6.5 (2.1)
4.8 (2.5)
1.69
0.50 to
2.88
.01
1.21
0.10 to
2.33
.03
RMDQ score
Baseline
6.3 (4.8)
7.4 (5.2)
8 wk
4.9 (4.5)
6.4 (4.4)
−1.49
−3.85 to
0.86
.21
−0.85
−2.58
to 0.89
.33
TSK score
Baseline
33.6 (6.1)
34.7 (5.8)
8 wk
32.3 (7.1)
35.9 (5.8)
−3.52
−6.97 to
−0.08
.05
−2.97
−6.14
to 0.21
.07
FEQ-I score
Baseline
21.5 (6.1)
22.9 (6.2)
8 wk
21.1 (5.8)
23.4 (7.0)
−2.30
−5.65 to
.18
−1.08
−3.08
.28
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
1.06
to 0.92
a
Bold type indicates significant values. FEQ-I = Falls Efficacy Questionnaire–International; NRS
= numeric rating scale; PSEQ = Pain Self-Efficacy Questionnaire; PSFS = Patient-Specific
Functional Scale; RMDQ = Roland-Morris Disability Questionnaire; TSK = Tampa Scale of
Kinesiophobia.
b
There were 30, 30, 29, and 29 participants with follow-up data at baseline, 8 wk, 3 mo, and 6
mo, respectively.
c
There were 30, 28, 27, and 28 participants with follow-up data at baseline, 8 wk, 3 mo, and 6
mo, respectively.
d
Adjusted for baseline values and function (baseline PSFS).
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Table 4. Effect of a Video Game Exercise Program on Care-Seeking and Physical Activity
Behaviors
a
Outcomes
No. (%) of
Participants in:
Unadjusted Between-
Group Difference
Adjusted Between-
Group Difference
b
Video
Game
Exercise
Group
c
Control
Group
d
OR
95% CI
P
OR
95% CI
P
Care seeking
(primary)
Current
treatment
Baseline
16 (53.3)
11 (36.7)
8 wk
13 (43.3)
15 (53.6)
0.66
0.24–
1.87
.44
0.50
0.14–1.75
.28
3 mo
9 (31.0)
8 (29.6)
1.07
0.34–
3.34
.91
1.40
0.38–5.13
.61
6 mo
7 (24.1)
9 (32.1)
0.67
0.21–
2.15
.50
0.50
0.13–1.91
.31
Planning to
start treatment
in coming
months
Baseline
6 (20.0)
6 (20.0)
8 wk
8 (26.7)
7 (25.0)
1.09
0.34–
3.54
.89
1.16
0.33–4.13
.82
3 mo
5 (17.2)
7 (25.9)
0.60
0.16–
2.17
.43
0.65
0.16–2.58
.54
6 mo
3 (10.3)
4 (14.3)
0.69
0.14–
3.42
.65
1.06
0.17–6.48
.95
Currently
taking
medication
Baseline
16 (53.3)
11 (36.7)
8 wk
16 (53.3)
13 (45.4)
1.32
0.47–
3.70
.60
1.28
0.34–4.78
.71
3 mo
11 (37.9)
9 (33.3)
1.22
0.41–
3.66
.72
0.76
0.18–3.20
.71
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
6 mo
10 (34.5)
14 (50.0)
0.53
0.18–
1.53
.24
0.24
0.06–1.04
.06
Physical activity
(secondary)
Strength
exercises at
least once/wk
Baseline
12 (40.0)
12 (40.0)
8 wk
15 (50.0)
12 (42.9)
1.33
0.47–
3.76
.59
1.58
0.45–5.55
.48
3 mo
14 (48.3)
10 (37.0)
1.59
0.55–
4.62
.40
2.33
0.51–
10.53
.27
6 mo
10 (34.5)
12 (42.9)
0.70
0.24–
2.05
.52
0.68
0.18–2.53
.57
Flexibility
exercises at
least once/wk
Baseline
24 (80.0)
20 (66.7)
8 wk
24 (80.0)
18 (64.3)
2.22
0.68–
7.25
.19
1.97
0.41–9.58
.40
3 mo
24 (82.8)
20 (74.1)
1.68
0.46–
6.12
.43
1.45
0.33–6.43
.62
6 mo
25 (86.2)
16 (57.1)
4.69
1.29–
17.10
.02
4.36
1.06–
17.93
.04
Sedentary or
only light
physical
activity each
week
Baseline
8 (26.7)
6 (20.0)
8 wk
5 (16.7)
4 (14.3)
1.20
0.29–
5.01
.80
1.24
0.22–7.04
.81
3 mo
4 (13.8)
5 (18.5)
0.70
0.17–
2.96
.63
0.67
0.12–3.60
.64
6 mo
4 (13.8)
4 (14.3)
0.96
0.22–
4.28
.96
1.07
0.17–6.63
.95
Moderate- or
vigorous-
intensity
physical
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
activity at
levels lower
than ACSM
recommendatio
ns
Baseline
10 (33.3)
11 (36.7)
8 wk
9 (30.0)
10 (35.7)
0.77
0.26–
2.31
.64
1.00
0.27–3.63
1.00
3 mo
8 (27.6)
5 (18.5)
1.68
0.47–
5.95
.42
1.58
0.42–5.86
.50
6 mo
6 (20.7)
9 (32.1)
0.55
0.17–
1.83
.33
0.85
0.22–3.32
.81
Physical
activity that
met ACSM
recommendatio
ns
Baseline
12 (40.0)
13 (43.3)
8 wk
16 (53.3)
14 (50.0)
1.14
0.41–
3.20
.80
1.02
0.28–3.72
.98
3 mo
17 (58.6)
17 (63.0)
0.83
0.28–
2.44
.74
1.04
0.28–3.83
.95
6 mo
19 (65.5)
15 (53.6)
1.65
0.57–
4.79
.36
1.33
0.36–4.89
.67
a
Bold type indicates significant values. ACSM = American College of Sports Medicine; OR =
odds ratio.
b
Adjusted for baseline values and function (baseline Patient-Specific Functional Scale).
c
There were 30, 30, 29, and 29 participants with follow-up data at baseline, 8 wk, 3 mo, and 6
mo, respectively.
d
There were 30, 28, 27, and 28 participants with follow-up data at baseline, 8 wk, 3 mo, and 6
mo, respectively.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018
Table 5. Adherence to Wii Fit U
a
Exercises
b
Week
Minutes of Exercise Time
No. of Sessions ≥ 60
Minutes (as
recommended by
protocol)
No. of Any Sessions
Mean (SD)
Median
(IQR)
Mean (SD)
Median
(IQR)
Mean (SD)
Median
(IQR)
1
169.3 (86.3)
150 (63)
1.4 (1.1)
1 (1)
3.5 (1.0)
3 (1)
2
146.4 (88.1)
150 (80)
1.5 (1.4)
2 (2)
2.9 (1.4)
3 (2)
3
131.7 (76.6)
126 (108)
1.3 (1.2)
1 (2)
2.8 (1.7)
3 (1)
4
126.8 (72.3)
138 (120)
1.3 (1.3)
1 (2)
2.5 (1.3)
3 (2)
5
126.7 (105.1)
120 (130)
1.3 (1.6)
1 (2)
2.4 (1.9)
2 (3)
6
124.2 (88.2)
133 (140)
1.2 (1.5)
0 (3)
2.4 (1.7)
3 (3)
7
107.3 (85.3)
96 (140)
1.2 (1.3)
1 (2)
2.1 (1.7)
2 (2)
8
93.7 (90.9)
80 (180)
0.8 (1.3)
0 (1)
1.9 (2.0)
2 (3)
Total
1019.1 (489.5)
1126 (589)
10.1 (8.3)
8 (15)
20.4 (9.3)
21 (15)
a
Nintendo, Kyoto, Japan.
b
IQR = interquartile range.
Downloaded from https://academic.oup.com/ptj/advance-article-abstract/doi/10.1093/ptj/pzy112/5104462 by Sydney College of Arts user on 20 September 2018