Accepted Manuscript The Effectiveness of Exergaming Training for Reducing Fall Risk and Incidence among the Frail Older Adults with a History of Falls Amy S.N. Fu, PhD, Kelly L. Gao, MPT, K.K. Tung, DHS, William W.N. Tsang, PhD, Marcella M.S. Kwan, PhD PII:
S0003-9993(15)01155-7
DOI:
10.1016/j.apmr.2015.08.427
Reference:
YAPMR 56304
To appear in:
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
Received Date: 14 January 2015 Revised Date:
30 July 2015
Accepted Date: 13 August 2015
Please cite this article as: Fu ASN, Gao KL, Tung KK, Tsang WWN, Kwan MMS, The Effectiveness of Exergaming Training for Reducing Fall Risk and Incidence among the Frail Older Adults with a History of Falls, ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION (2015), doi: 10.1016/ j.apmr.2015.08.427. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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The Effectiveness of Exergaming Training for Reducing Fall Risk and Incidence among the Frail Older Adults with a History of Falls Amy S.N. Fu1, PhD, Kelly L. Gao1, MPT, K.K. Tung1, DHS, William W.N. Tsang1, PhD ( Marcella M.S. Kwan2, PhD 1
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Running title: exergaming training prevents falls
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Submitted to Archives of Physical Medicine and Rehabilitation
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Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China 2 Rural Clinical School, School of Medicine, The University of Queensland
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( ) Correspondence addresses: William W.N. Tsang, PT, PhD Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Phone: (852) 2766 6717 Fax: (852) 2330 8656 Email:
[email protected]
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ACKNOWLEDGMENTS The authors thank all subjects who participated in this study and Mr. Bill Purves for his English
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editorial advice.
Conflict of Interest: The authors declare that they have no conflicts of interest with respect to
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the authorship or publication of this report. No funding was provided for its preparation.
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Author Contributions: The authors have worked as a team on all aspects of this research from
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design of the study through the implementation, analysis, and development of the manuscript.
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The Effectiveness of Exergaming Training for Reducing Fall Risk and Incidence among
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the Frail Older Adults with a History of Falls
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5 6 7 ABSTRACT
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Objective: To use Nintendo’s Wii Fit® balance board to determine the effectiveness of
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exergaming training in reducing risk and incidence of falls among the older adults with a
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history of falls.
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Design: Randomized controlled clinical trial.
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Setting: A nursing home for older adults.
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Participants: Sixty older adults aged 65 or above.
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Intervention: Participants who lived in a nursing home had six weeks of balance training
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with either Wii Fit equipment or conventional exercise.
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Main Outcome Measures: Physiological Profile Assessment (PPA) scores and incidence of
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falls were observed with subsequent intention-to-treat statistical analyses.
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Results: PPA scores and fall incidence improved significantly in both groups after the
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intervention, but the subjects in the Wii Fit training group showed significantly greater
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improvement in both outcome measures.
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Conclusions: In institutionalized older adults with a history of falls, Wii Fit balance training
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was more effective than conventional balance training in reducing the risk and incidence of
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falls.
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Key words: virtual reality; exergame; older adults; falls; balance exercise
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COP – Center of Pressure
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FAC – Functional Ambulatory Category
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PPA – Physical Profile Assessment
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SPSS – Statistical Package for the Social Sciences
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VR – Virtual Reality
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RCT – Randomized controlled clinical trial
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List of Abbreviations
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ACCEPTED MANUSCRIPT Falls are the second leading cause of accidental deaths worldwide,1,2 and adults older
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than 65 suffer the greatest number of fatal falls. Even non-fatal falls can impact on one’s
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quality of life as a result of severe fall-related injuries and fractures. Moreover, older people
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who report a fall in the past year are likely to fall again.3 Falls can lead to fear of falling,4
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which may lead to a debilitating spiral marked by loss of confidence and restriction of
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activity, resulting ultimately in a loss of independence.5 Falls have also shown to be a strong
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predictor of nursing home admission.6 Research showed that fall incidence in
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institutionalized older people are about three times more than those living in the community.7-
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falls.9 A fall prevention program aimed at this frail elderly population is therefore important.
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Exercise have been shown to be effective in reducing falls in the community,10 however it has
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failed to reduce the rate of falls or risk of falling as a single intervention in nursing care
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facilities.11
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A recent study found that 89% of preventable deaths of nursing home residents were due to
Virtual reality (VR) and exergaming technologies have been used as an assessment and
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treatment tool in rehabilitation.12,13 Some VR training environments have been enhanced by
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the addition of video games, increasing participants’ motivation and enjoyment.14-16 Nintendo
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released the Wii Fit® platform that includes a built-in center of pressure (COP) sensor which
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can enhance yoga, strength training, aerobics, and balance games. The system offers feedback
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to the participants, enabling them to identify improved balance capabilities.
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Although there is some evidence of the effectiveness of virtual reality and the use of
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video games in enhancing balance control,17 empirical evidence in falls prevention
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particularly with a randomized controlled clinical trial (RCT) design is still lacking.18 While
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there is research on exergaming in patients with chronic stroke19 and multiple sclerosis20, but
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still little research on the effectiveness of the Wii Fit apparatus in the treatment of balance
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dysfunction among the frail elderly who are at risk of falls. This study was therefore designed
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to investigate the effect of interactive exergaming training exercise on balance control, fall
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risk factors and the incidence of falls among frail elderly persons living in a nursing home.
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METHODS
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Study Design
This was a single-blinded, RCT with a control group (a conventional balance training group) and an intervention group (the Wii Fit balance training group).
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68 Participants
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Sixty participants aged 65 or over living in a nursing home were recruited. Each was
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assessed with a Functional Ambulatory category (FAC) of grade 2 or 3. The FAC grade 2
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subjects required manual contact with one person during ambulation on a level surface to
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prevent falling. The manual contact usually consisted of continuous or intermittent light
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touches to assist balance or coordination. The FAC grade 3 subjects could walk on a level
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surface without such contact, but for safety’s sake they required a guard standing by because
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of either poor judgment, questionable cardiac status, or a need for verbal cueing. All of the
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participants were alert and medically stable and able to follow instructions. Each had history
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of falls in the previous year. A fall was defined as “inadvertently coming to rest on the ground
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or other lower level with or without loss of consciousness, and other than as a consequence of
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sudden onset of paralysis, epileptic seizure, excess alcohol intake or overwhelming external
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force”.21 Residents who had visual problems which might affect their training, who were
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unable to follow instructions or who had any history of seizure, stroke, Parkinsonism or
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uncontrolled cardiovascular disease were excluded.
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Approval from the nursing home was obtained prior to conducting the study, and ethical
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clearance was obtained before the study began from the ethics committees of both the nursing
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home and The Hong Kong Polytechnic University. Informed voluntary consent was obtained
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from each participant after thorough explanation.
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89 Procedures
Subjects were randomly assigned to the conventional or Wii Fit balance training group by using a random number produced by the computerized method of minimization (Figure 1).
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The conventional balance exercise regime used was that developed by Campbell and
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colleagues specifically for fall prevention among elderly women.22 It has been shown to be
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effective in reducing falls incidence in an elderly population. The exercise regime included
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lower limb muscles strengthening exercises, tandem standing exercises in parallel bars,
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tandem walking exercises in parallel bars, sideways and turn round walking exercise in
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parallel bars, stepping exercise, sitting to standing exercise, and half-squats. Subjects were
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rested for one to two minute between sets. The exercise was organized in one-hour sessions,
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which were held on three days a week for six weeks. A physiotherapist conducted the whole
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training regime for all conventional and Wii Fit subjects during this six-week period.
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Subjects who were randomized to the Wii Fit balance training group received balance training using a Nintendo’s Wii Fit® balance board.a Three balance training games—namely
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Soccer Heading, Table Tilt and Balance Bubble—were selected. In Soccer Heading, the
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subjects mimicked soccer players and took turns kicking soccer balls, cleats, or panda heads
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at each other. Subjects scored a point if their head butted a soccer ball, but lost a point if a
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cleat hit them and three points if they were nailed by a panda head. To perform these
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maneuvers the subjects had to shift their body weight left or right while standing on the
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platform. In the Table Tilt game the subjects tilted a board to roll marbles into holes by
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ACCEPTED MANUSCRIPT shifting their body weight. They had to carefully manipulate the board to roll the balls into
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the holes without dropping a ball off the table. In Balance Bubble the players were required to
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steer the bubble through a hazard-filled course, again by shifting their body weight while
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standing on the balance board. The farther the subjects leaned, the faster the bubble traveled
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in that direction. Subjects progress to the harder mode of the game at their own pace. This
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pace was determined through the game’s “star system” that rates the player’s performance on
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each individual game. Subjects were rested while each game was being restarted.
These activities exercised various components of the balance control system including
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the musculoskeletal components, the sensory system, neuromuscular strategies and
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anticipatory control. The Wii Fit training was also for one hour per session, three sessions a
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week for six weeks. Since all the participants had history of falls, they were accompanied by
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a rehabilitation assistant who provided immediate manual support when necessary during
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both the Wii Fit and the conventional balance exercises.
After the six-week intervention period, both groups resumed the routine mobilizing and
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strengthening exercises without receiving either the Wii Fit or the conventional balance
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training.
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Outcome measures
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Falls incidence was recorded by the nursing staff according to the aforementioned
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definition and reported to the investigator for each subject monthly over the 12-month period
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after randomization. Nurses at the nursing home who documented falls were unaware of
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subjects’ group allocation.
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Fall risk was determined using the short-form physiological profile assessment (PPA)
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composed of five validated measures of physiological function.23 Weighted combinations of
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these measures can provide a falls risk score that can predict people at risk of multiple falling
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quadriceps strength, simple reaction time and postural sway. Visual contrast sensitivity was
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assessed using the Melbourne Edge Test.24 Proprioception was measured using a lower limb-
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matching task. Errors in degrees were recorded using a protractor inscribed on a vertical clear
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acrylic sheet (60cm x 60cm x 1cm) placed between the legs. Quadriceps strength in both legs
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was measured isometrically in kilograms while the participants were seated with the hip and
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knee flexed at 90 degrees. Simple reaction time in milliseconds was measured using a light as
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the stimulus and a finger-press as the response. Postural sway while subjects stood on foam
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with double legs and eyes open was measured using a sway meter recording displacements of
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the body at the level of the pelvis. A research assistant blinded to the subjects’ allocation was
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responsible for the PPA assessment. Fall risk was assessed before and after the six-week
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training program.
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Statistical Analysis
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The data were analysed using version 19 of the Statistical Package for the Social Sciences (SPSS) software package (IBM Corp. 2010) and Stata v12 (StataCorp. 2011).
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Independent t-tests and chi-square tests were conducted to compare the two groups in terms
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of age, height, weight, BMI, as well as the distribution of genders and functional ambulation
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categories. For the PPA z-scores, independent t-tests were used to compare the between-
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group difference, while paired t-tests were performed to compare the within group
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measurements. For the numbers of falls, negative binomial regression models were employed
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to estimate the difference in rates of falls between the two groups. Additional models adjusted
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for sex, age and number of falls in previous year before the intervention were used. The
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intention-to-treat was employed in the statistical analyses and the alpha level was set at 0.05.
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RESULTS All 60 subjects completed the six-week training and the post-intervention assessment (Figure 1). Two subjects from the Wii Fit balance training group and three from the
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conventional training group could not complete the full year of surveillance due to illness or
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death, so the completion rates were 93.3% for the Wii Fit group and 90% for the conventional
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balance training group.
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The demographic data are shown in Table 1. There was no statistically significant
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difference in average age, gender, height, weight, BMI, FAC distribution or number of falls
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over the previous year between the two groups.
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Fall risk
Table 2 presents the means and standard deviations of the five items of the PPA short
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form and PPA z-scores before and after intervention. Independent t-tests showed that there
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was no statistically significant difference in the average pre-test PPA values of the two
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groups. Within both the Wii Fit and conventional balance training groups, paired t-tests
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showed that there were significant differences in their PPA z-scores before and after the
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respective interventions. However, independent t-test showed that there was statistically
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significant difference in the post-test PPA z-scores between the two groups. Subjects who had
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received the Wii Fit balance training achieved significantly greater muscle strength (p <
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0.001), faster reaction times (p <0.001), and less body sway (p = 0.013) when compared with
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those who had received conventional balance training (Table 2).
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Figure 2 shows the fall risks of the participants between the Wii Fit balance and
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conventional balance training groups, with the higher the z-score, the greater a person’s fall
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risk. It also shows the fall risk scores before and after the intervention. Prior to intervention,
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the mean z-score for both groups was 3.7, in the marked risk category. After training, the
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mean z-score of the conventional training group was 3.3 while it was 2.4 for the Wii Fit
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training group. The decrease in fall risk was more marked in the Wii Fit training group than
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the conventional exercise group (p = 0.004).
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The overall incidence of falls in the intervention group was 0.54 per person years (range 0-1)
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compared with 1.52 per person years in the control group (range 0-3) (Table 2). The
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incidence rate ratio (IRR) adjusted for age and sex (common confounders though not
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significant in univariate analysis) was 0.35 (95% confidence interval (CI) 0.20 to 064, p =
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0.001). Inclusion of previous falls in the model resulted in an improved IRR of 0.31 (95% CI
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0.17 to 0.57, p<0.001).
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Wii Fit games in reducing falls & fall risk
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This study is the first RCT utilizing Wii Fit balance games or exergame as a training technique for fall prevention in older adults. The Wii Fit balance training has shown to reduce
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falls by 69% compared to the conventional exercise. In terms of fall risk, the Wii Fit balance
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training has a 35% improvement in the fall risk z-score, significantly higher than 11% in the
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conventional exercise group. The findings echo the results of Campbell and colleagues22
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whose exercise regime was adopted for the control group of this study.
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Wii Fit games as balance training Wii Fit games have been shown to improve balance in patient groups such as those who
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suffered chronic stroke and multiple sclerosis,19,20 but no RCT has been conducted in the
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context of fall prevention. Clark and Kraemer25 reported a case study investigating the
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falling. They report that clinical outcomes such as Berg Balance Scale scores, timed up and
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go test times and dynamic gait index ratings were improved. Another case study was
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conducted by Hakin and colleagues26 in a community-dwelling older adults suffering from
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bilateral peripheral neuropathy. There were improvements found in tests conducted by the
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computerized dynamic posturography as well as clinical tests.
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Rendon and colleagues27 adopted a RCT design for a total of 40 community-dwelling older adults. The Wii Fit balance group received an intensity of intervention of 3x/week for 6
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weeks while the control group received no intervention. The clinical tests using 8-foot Up &
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Go test and Activities-specific Balance Confidence showed significant improvement in the
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Wii Fit group. Another RCT was conducted by Jorgensen and colleagues28 investigating the
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Wii Fit training on muscle strength and postural control in community-dwelling older adults.
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The investigators found an 18% increase in maximum muscle strength after the intervention
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in comparison to the control group who wore shoe insoles. This increase was comparatively
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higher than ours (14%) possibly due to the younger mean age of their group 75 years and a
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passive intervention mode in the control group. However, there was no difference in the
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bilateral static stance in term of COP velocity moment whereas we found a lower body sway
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area (21.7%) in the Wii Fit group when subjects were standing on a foam with eyes open.
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A recent RCT conducted by Cone and colleagues29 on young healthy adults (18-35
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years) using the dosage of six weeks (2-4 x/week, 30-45 min/day). They found that the Wii
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Fit group achieved better in condition 5 of the sensory organization test (condition where the
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visual input is occluded with inaccurate somatosensory input) and better spatial and temporal
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domains in the limits of stability test. The investigators suggested that improved postural
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control when subjects relied on vestibular input to maintain postural control might be due to
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the frequent movement of head during the game play. The game also challenged the players
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in their reaction time and stability limit and these improvements were being reflected in the
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limits of stability test.
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All of these studies were either single subject case reports or studies recruiting healthy elderly persons.17 There has been no RCT performed with an elderly population at risk of
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falls, especially frail elderly persons with functional disability (FAC grade 2 or 3).
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Is Wii Fit balance training better than conventional balance training?
The five test items of the PPA short form are i) contrast sensitivity, ii) proprioception, iii)
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quadriceps strength, iv) reaction time, and v) body sway. In Wii Fit groups, significant
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improvements after training were observed in reaction time; quadriceps strength and body
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sway while improvements in reaction time and quadriceps were only found in the control
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subjects. Any changes in proprioception and contrast sensitivity were not significant. The
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significantly better performance in these test items observed in Wii Fit group over the
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conventional exercise group may be explained by the different training modes and
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environments of the two protocols.
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During the Wii Fit training, the trainees had to shift their body quickly in different directions with appropriate timing in order to gain points and not lose in the games. Such
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training would be expected to strengthen the legs, improve the reaction time in response to
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external cues, and improve control of body sway. Moreover, exergaming provides real-time
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performance feedback, cuing stimuli to support error-free learning. Performance feedback as
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to the status and outcome of a response is generally accepted to be necessary for most forms
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of learning or skill acquisition, including the learning process that underlies rehabilitation.30
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So the real time visual feedback to the subjects would be expected to enhance the training
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process compared with conventional training. Moreover, the exergaming environment allows
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dynamic stimulus delivery and control. This also allows for the presentation of cuing stimuli
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the participants in Wii Fit group, control subjects only improved in reaction time and
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quadriceps strength, but not in the postural sway. In the PPA, it assesses the body sway during
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standing on foam with eyes open. However, the exercise regime designed by Campbell and
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colleagues22 consists of more dynamic balance training, such as tandem walking, sideways
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and turn around exercises. Due to training specificity, the effect of a more dynamic balance
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could not be reflected on a static standing assessment.
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Study Limitations
We acknowledge the study has certain limitations. Firstly, the difficulty level of the
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games might be too hard for frailer adults, as they were originally designed for people of
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relatively younger age. Subsequently, each game lasts only few minutes, so they had to be re-
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started regularly, which could potentially decrease the efficiency of the training. Although
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Wii Fit games have been used and accepted by other high fall risk population such as
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multiple sclerosis, studies often recruited younger age group as in Kramer and colleagues’
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study with mean age of 47.20 These limitations arose due to the commercial nature of the
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games, therefore, balance training games targeting the older adults need to be designed
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specifically for clinical application. Secondly, the amount of rest time in each subject was not
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recorded. This might result in inconsistency between the two groups in training duration.
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Thirdly, the physiological outcome measures were only re-assessed post intervention, how
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much training effect is maintained throughout the follow-up period is not known. However,
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any deficits in the physiological function would be reflected by number of falls occurred.3,23
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Finally, as the trial was undertaken in a nursing home setting, we acknowledge our findings
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may not be generalizable to older people living in the community.
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CONCLUSIONS Wii Fit balance training was demonstrated to be significantly more effective than
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conventional balance training for reducing falls among the institutionalized, frail, elderly
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people most at high risk of recurrent falls.
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23. Lord SR, Menz HB, Tiedemann A. A physiological profile approach to fall risk assessment and prevention. Phys Ther 2003; 83: 237–252. 24. Verbaken J. Population norms for edge contrast sensitivity. Am J Optom Phys Optom 1986;63:724–32.
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25. Clark R and Kraemer T. Clinical use of Nintendo Wii™ bowling simulation to decrease
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fall risk in an elderly resident of a nursing home: A case report. J Geriatr Phys Ther
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2009: 32(4): 174–180.
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26. Hakim RM, Salvo CJ, Balent A, Keyasko M, McGlynn D. Case report: a balance
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training program using the Nintendo Wii Fit to reduce fall risk in an older adult with
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bilateral peripheral neuropathy. Physiother Theory Pract 2015;31(2):130-9. 27. Rendon AA, Lohman EB, Thorpe D, Johnson EG, Medina E, Bradley B. The effect of
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virtual reality gaming on dynamic balance in older adults. Age Ageing 2012;4(14)549-
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52.
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28. Jorgensen MG, Laessoe U, Hendriksen C, Nielsen OB, Aagaard P. Efficacy of Nintendo
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Wii training on mechanical leg muscle function and postural balance in community-
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dwelling older adults: a randomized controlled trial. J Gerontol A Biol Sci Med Sci
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2013;68(7):845-52.
372 373
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29. Cone BL, Levy SS, Goble DJ. Wii Fit exer-game training improves sensory weighting and dynamic balance in healthy young adults. Gait & posture 2015;41(2):711-5. 30. Sohlberg
MM,
and
Mateer
CA.
Cognitive
rehabilitation:
An
integrative
neuropsychological approach. New York: Guilford, 2001
TE D
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SC
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31. Rizzo AA, Bowerly T, Buckwalter JG, Schltheis M, Matheis R, Shahabi C, Neumann U,
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Kim L, Sharifzadeh M. Virtual environments for the assessment of attention and
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memory processes: the virtual classroom and office. In Proceedings of the 4th
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International Conference on Disability, Virtual Reality and Associated Technology,
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2002, Vresprem, Hungary, page 3–11.
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AC C
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Figure Legends:
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Figure 1. Study Flowchart
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Figure 2. A scatter plot showing the PPA z-scores pre and post-intervention between the Wii
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Fit balance and conventional balance training groups
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Supplier’s List:
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a
AC C
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Nintendo, Redmond, Washington, US
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Conventional balance training group
Wii Fit balance training group (N=30)
82.3 ± 4.3
82.4 ± 3.8
0.975
10 / 20
11 / 19
Height (m)
1.58 ± 0.5
1.55 ± 0.3
Weight (kg)
59.7 ± 0.5
BMI (kg/m2)
23.9 ± 0.5
Gender (Male/Female)
Functional Ambulatory Category (grade 2 / 3)
(1 - 4)
AC C
0.657
59.4 ± 0.6
0.542
24.7 ± 0.4
0.481
14 / 16
0.797
TE D
2.2 ± 0.9
EP
No. of falls over previous one year (range)
16 / 14
0.995
M AN U
Age (Years)
p
SC
(N=30)
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Table 1. Baseline characteristics of subjects in both groups. Values are mean ± SD unless otherwise stated.
2.5 ± 1.1
0.307 (1 - 5)
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Table 2. Comparison of outcome measurements between the conventional balance training group and Wii Fit balance training group
17.3±1.5
17.3±1.5
Proprioception (degree)
2.6±1.0
2.6±1.0
Quadriceps strength (kg)
4.1±0.4
5.1±0.6 a
338.9±87.6 a
EP
Reaction time 346.6±89.0 (ms)
AC C
Postural sway 1213.5±390.7 1330.8±510.4 (mm2)
PPA z-scores
3.7 ± 1.2
17.4±1.6
3.3 ± 1.2 a
Post-test
p Value
Pre-test
Post-test
(between groups)
(between groups)
17.4±1.6
0.986
0.986
2.3±1.2
2.2±1.0
0.894
0.809
4.3±0.5
5.8±0.8 a
0.637
<0.001 b
315.5±74.2 a
0.785
<0.001 b
0.146
0.013 c
0.896
0.004 b
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Contrast sensitivity (db)
Pre-test
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Post-test
SC
Pre-test
Wii Fit balance training group (N=30)
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Conventional balance training group (N=30)
344.3±77.3
1364.0±372.5 1042.0±317.2 a
3.7 ± 1.0
2.4 ± 1.0 a
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2.2 ± 0.9
1.5 ± 0.6 a
2.5 ± 1.1
Note. Values are mean ± SD or p values. Within group:
0.330
<0.001 b
Denotes a difference at the alpha = 0.01 significance level when compared with the pre-test values.
SC
a
0.5 ± 0.5 a
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No. of falls
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Between the two groups: Denotes a difference at the alpha = 0.01 significance level.
c
Denotes a difference at the alpha = 0.05 significance level.
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b
ACCEPTED MANUSCRIPT Assessed for eligibility (n=82)
Randomised (n=60)
Conventional Exercise Group (n=30)
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Wii Exercise Group (n=30)
Conventional exercise X6 weeks, 3x/ week, 1h/ session Received allocated intervention (n=30)
Post-intervention assessment on PPA (n=30)
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Post-intervention assessment on PPA (n=30)
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Pre-intervention assessment on PPA
Wii balance exercise X6 weeks, 3x/ week, 1h/ session Received allocated intervention (n=30)
AC C
EP
Completed 12 month follow-up on falls surveillance (n=28) Did not complete (n=2): Illness (n=2) Death (n=0)
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Excluded (n=22): No fall in previous year (n=5) Unable to follow instruction (n=4) Visual problem (n=3) FAC grade<2 (n=4) Declined (n=6)
Completed 12 month follow-up on falls surveillance (n=27) Did not complete (n=3) Illness (n=2) Death (n=1)
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6.00
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4.00
Group
3.00
Conventional Wii
2.00
1.00
1.00
2.00
3.00
4.00
5.00
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0.00 0.00
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PPA score Post Intervention
5.00
6.00
PPA score Pre Interventiion
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Figure 2. A scatter plot showing the PPA z-scores pre and post-intervention between the Wii Fit balance and conventional balance training groups