470747 ournal of Applied GerontologyBleakley et al.

JAG34310.1177/0733464812470747J

Original Article

Gaming for Health: A Systematic Review of the Physical and Cognitive Effects of Interactive Computer Games in Older Adults

Journal of Applied Gerontology 2015, V   ol. 34(3) NP166­–NP189 © The Author(s) 2013 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0733464812470747 jag.sagepub.com

Chris M. Bleakley1, Darryl Charles1, Alison Porter-Armstrong1, Michael D. J. McNeill1, Suzanne M. McDonough1, and Brendan McCormack1

Abstract This systematic review examined the physical and cognitive effects of physically based interactive computer games (ICGs) in older adults. Literature searching was carried out from January 2000 to June 2011. Eligible studies were trials involving older adults (>65 years) describing the effects of ICGs with a physical component (aerobic, strength, balance, flexibility) on physical or cognitive outcomes. Secondary outcomes included adverse effects, compliance, and enjoyment. Twelve trials met the inclusion criteria. ICG interventions varied in terms of software, game type, and nature of the computer interaction. Although there was preliminary evidence that ICG is a safe and effective exercise intervention for older adults, the dearth of high-quality evidence limits this finding. No major adverse effects were reported and two studies reported minor events. ICG could be improved further by tailoring interventions for older adults; in particular, they should aim to optimize participant safety, motivation, and enjoyment for this population. Manuscript received: January 13, 2012; final revision received: October 10, 2012; accepted: November 10, 2012. 1

University of Ulster, Newtownabbey, UK

Corresponding Author: Suzanne M. McDonough, University of Ulster, Shore Road, Newtownabbey, BT370QB, UK. Email: [email protected]

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Keywords older adults, physical activity, interactive computer gaming The average age of the population is increasing, with many adults living with chronic disease, sensory and motor impairments, reduced physiological reserve, and frailty. Such age-related changes affect function, independence, and quality of life, generating a significant burden on health care systems. The health benefits of undertaking regular physical activity (PA) are extensive, and public health guidelines (Haskell et al., 2007) advise at least 30 minutes of PA each day (Nelson et al., 2007). Refined guidelines (Chodzko-Zajko et al., 2009; Nelson et al., 2007) for older adults advise a combination of aerobic, strengthening, balance, and flexibility training. There is a large body of evidence that PA improves muscle strength (Latham, Bennett, Stretton, & Anderson, 2004), balance (Bulat et al., 2007), fall risk (Weerdesteyn et al., 2006), mental health (Lee & Park, 2007), and cognitive functioning (Colcombe & Kramer, 2003) in older adults. In spite of this, few older adults engage sufficiently in PA, particularly those aged 80 years and older (Baert, Gorus, Mets, Geerts, & Bautmans, 2011). The decision to undertake PA can be complex and a number of motivators and barriers may exist. Important barriers to PA in older adults include insufficient guidance, lack of role models, fears, individual preferences, social support, and constraints related to the physical environment (Allender, Cowburn, & Foster, 2006; Baert et al., 2011). Increasing or maintaining PA levels in older adults is a priority for preventing age-related physiological decline, functional losses, and frailty. Developing methods to overcome barriers to PA and promote adherence to current guidelines is an increasing challenge for public health. Interactive computer games (ICGs) are increasingly used to promote fitness training and rehabilitation. Although traditionally reserved for younger children, gaming software can be used to create a stimulating and engaging environment for all ages. Recently ICG rehabilitation strategies have been adapted for the older user. The rationale is that ICG offers older people an opportunity to be active and independent in activities which are otherwise difficult to engage in. ICG is also enjoyable and can usually be performed safely, and with minimal supervision. An added advantage for older adults is that programs can include exercises and movements which integrate cognitive processes (e.g., attention and motivation) and various motor control challenges. ICG has been shown to be an effective rehabilitation tool for younger clinical populations (Sandlund, McDonough, & Häger-Ross, 2009). Others (Wiemeyer & Kliem, 2012) have considered the theoretical benefits of serious gaming in the elderly and provided a general overview of its effects in various populations. Our

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aim is to systematically review the evidence base and examine the physical and cognitive effects of physically based ICG in an older adult population. We also consider how it affects user’s compliance, enjoyment, and safety during exercise.

Method Search Strategy We searched the Cochrane Central Register of Controlled Trials (CCTR), MEDLINE, and EMBASE by combing a range of subject headings (MeSH) and key words [Aging; Aged; Aged, 80 and over; Geriatrics; older adults.mp; Computer-Assisted Instruction; Computers; User-Computer Interface; Computer Simulation; interactive computers.mp; Software; Video Games; Games; Experimental; games.mp; virtual reality.mp; serious gam$.mp; Computers; Therapy, Computer-Assisted; video capture.mp; Software; web cam.mp; balance.mp; Postural Balance; Hand Strength; Muscle Strength Dynamometer; strength.mp; Muscle Strength; Motivation; adherence.mp; Mental Health; flexibility.mp; Pliability; Heart Rate; Obesity; Exercise; Physical Fitness; aerobic fitness.mp.]. Each database was searched from January 1, 2000 to June 30, 2011. We also undertook a related articles search using PubMed and read reference lists of all incoming articles.

Inclusion Criteria Studies must have used an ICG intervention on older adults (aged >65 years). ICG was defined as any kind of computer game or virtual reality technique where the participant could interact with virtual objects in a computer-based environment (Sandlund et al., 2009); the participants’ interaction must have involved at least one of the following physical components: aerobic, strength, balance, or flexibility. Studies using ICG for specific rehabilitation after injury were excluded. We were primarily interested in outcomes relating to physical or cognitive functioning. Secondary outcomes were compliance, enjoyment, and adverse events. Case reports or small case series (n < 3) were excluded but there were no other restrictions placed on study design.

Selection of Studies and Risk of Bias Two authors independently selected trials for inclusion. Titles and abstracts of publications obtained by the search strategy were screened. All trials classified as relevant by either of the authors were retrieved. Based on the information

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within the full reports, we used a standardized form to select the trials eligible for inclusion in the review. Disagreement between the authors was resolved by consensus, or third-party adjudication. Randomized controlled trials (RCTs) were assessed for risk of bias using the Cochrane risk of bias tool (Higgins & Altman, 2009). Two authors independently assessed studies for risk of bias using four criteria: randomization, allocation concealment, blinded outcome assessment, incomplete follow-up. Two independent assessors graded each criterion as having high, low, or unclear risk of bias.

Data Extraction and Measures of Treatment Effect Data were extracted independently by two review authors using a customized form. When adequate data were available, RevMan software was used to calculate mean differences (MDs) and 95% confidence intervals (95% CIs) for continuous data, and risk difference (95% CI) for dichotomous data. MDs in controlled studies were based on between-group comparisons (e.g., mean ICG group − mean control group). In observational studies where no control group was used, MDs were calculated based on within-group comparisons (mean score post-ICG − mean score pre-ICG [baseline]).

Results Figure 1 provides a summary of the search results and study selection process.

Study Design and Participants Twelve studies were eligible for inclusion. Study designs were either observational (Graves et al., 2010; Rosenberg et al., 2010; Studenski et al., 2010; Suárez, Suárez, & Lavinsky, 2006; Young, Ferguson, Brault, & Craig, 2011), controlled trials (Bisson, Contant, Sveistrup, & Lajoie, 2007; Lajoie, 2004), or RCTs (Buccello-Stout et al., 2008; Hagedorn & Holm, 2010; Heiden & Lajoie, 2010; Sohnsmeyer, Gilbrich, & Weisser, 2010; Wolf et al., 2003). All studies included participants with a mean age >65 years, with three aged >80 years (Hagedorn & Holm, 2010; Studenski et al., 2010; Young et al., 2011). At the time of the study, the majority of participants were living in the community (Bisson et al., 2007; Heiden & Lajoie, 2010; Wolf et al., 2003), senior living or retirement centers (Rosenberg et al., 2010; Sohnsmeyer et al., 2010; Studenski et al., 2010), or a combination of both (Lajoie, 2004). Relevant comorbidities reported were subsyndromal (mild) depression (Rosenberg et al., 2010), balance disorders (Suárez et al., 2006), and history of falls (Hagedorn & Holm, 2010). Participants were

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ELECTRONIC SEARCH Medline/CCTR/EMBASE (n=705 titles) Related articles Pubmed (n=258 titles) Full text studies screened for eligibility: n=47

INCLUDED (N=12) Observational (n=5) Controlled trial (n=2) RCT (n=5)

EXCLUDED WITH REASONS (N=36) Study design not relevant (n=4) Non English Lanuage (n=1) Not older population (n=14) Intervention not relevant (n=6) Outcomes not relevant (n=11)

Figure 1. Summary of search results and selection of studies. Note. RCT = randomized controlled trial

generally healthy, and most studies (Buccello-Stout et al., 2008; Heiden & Lajoie, 2010; Lajoie, 2004; Wolf et al., 2003) specified that individuals with uncontrolled orthopedic, neurological, cardiovascular problems, or other debilitating conditions were not included. In others, exclusion criteria were lack of ability to stand and poor visual acuity (Hagedorn & Holm, 2010).

Details of ICG interventions The majority of studies (Bisson et al., 2007; Buccello-Stout et al., 2008; Graves et al., 2010; Hagedorn & Holm, 2010; Heiden & Lajoie, 2010; Lajoie, 2004; Rosenberg et al., 2010; Studenski et al., 2010; Suárez et al., 2006; Wolf et al., 2003; Young et al., 2011) used an ICG intervention incorporating weight bearing and various forms of postural stability training. Four involved Exergames based on commercial computer systems (Graves et al., 2010; Rosenberg et al., 2010; Sohnsmeyer et al., 2010; Young et al., 2011) or similar proprietary programs (Hagedorn & Holm, 2010). In others, interaction was facilitated through a dance mat (Studenski et al., 2010), virtual reality (VR) headsets, or projections (Bisson et al., 2007; Buccello-Stout et al., 2008; Suárez et al., 2006; Young et al., 2011). In three studies (Heiden & Lajoie, 2010; Lajoie, 2004; Wolf et al., 2003) the “gaming” component was limited to graphical feedback during balance exercises.

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The amount of exposure to ICG varied across studies. In one study (Young et al., 2011) participants undertook 10 sessions over 4 weeks. In the remainder, we were able to calculate an aggregate number of hours of ICG exposure, which ranged from 2.5 (Buccello-Stout et al., 2008) to 36 (Hagedorn & Holm, 2010). Full details of included studies are presented in Table 1. The majority of studies had selection bias with two (Buccello-Stout et al., 2008; Heiden & Lajoie, 2010) failing to report adequate methods of randomization and, no study used allocation concealment or blinded outcome assessment. There was also high risk of attrition bias, with one study (Wolf et al., 2003) adequately reporting details of incomplete outcome data. Two (Buccello-Stout et al., 2008; Heiden & Lajoie, 2010) provided insufficient details on dropouts, exclusions, missing data, or approach to analysis; the remainder limited their analysis to adherence only (participants attending 45 on Berg Balance test

  Buccello-Stout et al. (2008)

Interventions II. Tai Chi

Participants

 

Study

Table 1. (continued)

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N = 16 community-dwelling older adults; score > 25 on Folstein Mini-Mental State Exam; absence of diabetes, neurological, cardiovascular, orthopedic disorders Mean age: 77 years

Participants

Participants stood on two pressure pads (NeuroGym Technologies) that were used to move a virtual paddle and control a tennis game (Pong); there were 5 postures (akin to gestures) and stepping routine. Game play and game design details are not fully discussed, and no detailed comments on the associated motivational and fun aspects II.  Chair exercise class only (upper and lower body)

Both groups received progressive muscle strength and physical fitness training (2 times/week) I. Chair exercise class (upper and lower body) plus computer based balance biofeedback [30-minute sessions, ×2 per week over 8 weeks; 8 hours in total]

Interventions

•  6-minute walk test [Weeks 8 and 10]e

• Community Balance and Mobility Scalea (Weeks 8 and 10) •  Postural sway

• Reaction timea (Weeks 8 and 10)

[Week 12]

Summary of outcomes and resultsa,b,c (follow up)d

Note. PACES = Physical Activity Enjoyment Scale; METs = metabolic equivalents; QIDS = Quick Inventory of Depressive Symptoms Scale; RBANS = Repeatable Battery for Assessment of Neurocognitive Status; COP = Center of pressure; RCT = randomized controlled trial; ICG = interactive computer game. a. ICG significantly improved from baseline. b. Significant between-group differences in favor of ICG. c. Significant between-group differences in favor of control. d. Follow-ups depict the time since the start of the intervention. e. Insufficient data for between-group effect size calculation.

   

 

RCT

Heiden and Lajoie (2010)

 

Study

Table 1. (continued)

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In a related study (Studenski et al., 2010), participants used an interactive dance mat in a senior living center. After 3 months, there were improvements from baseline in walking time (decreased by 0.5 seconds [SD = 1.6] vs. baseline), physical performance (0.7 points on short physical performance battery [SD = 1.1]), balance (4.9 points on a balance confidence scale [SD = 10.1]), and selfreported health based on SF 36 (Short Form Health Survey) scores in physical (0.9 points [SD = 5.6]) and mental components (3.9 points [SD = 8.2]). Suárez et al. (2006) recruited a group of older participants with balance disorders to undertake a balance rehabilitation program using a VR system which changed sensory information to elicit changes in postural response. Although details on the game play were limited, the primary focus of the intervention was on vestibular rehabilitation. After a 6-week intervention, participants’ postural control was significantly improved during a bipedal balance test on a force platform; this was evidenced by significant decreases in center of pressure distribution area (MD = 12.2 cm2; 95% CI = [9.89, 14.51] vs. baseline) and sway velocity (MD = 1.97 cm/s; 95% CI = [1.42, 2.52] vs. baseline) throughout the treatment period. Controlled trials. In a nonrandomized study, Bisson et al. (2007) trained one group of participants using balance exercises within a virtual environment (juggling game), with comparisons made with a control group undertaking balancing exercises with minimal visual feedback from a computer screen. At Weeks 1 and 4 postintervention, both groups showed significant improvements in functional balance and mobility, with ratings on the Community Balance and Mobility Scale increasing by more than 6 points in each group throughout the study; reaction time (saying “top” in response to an auditory cue) was also improved in both groups, but there were no significant between-group differences. A small controlled trial by Lajoie (2004) used an ICG intervention based on balance exercises with visual feedback from a cursor. This was undertaken over an 8-week period with comparisons to an untreated control. There were no between-group differences in postural sway or Berg Balance score at 8- and 10-week follow-up. However, there were significant differences in favor of the ICG group in terms of Activity Specific Balance Scale and in dual task performance (verbal response to an auditory stimulus) during balancing. Randomized controlled trial. Hagedorn and Holm (2010) recruited 35 older adults (mean age = 81.3 years; SD = 6.9 years) with a history of falls. The ICG intervention involved a series of balancing games within a virtual environment and was compared with a traditional balance training control. The traditional balance training consisted of balancing on different surfaces (eyes open and closed), walking on a line, and obstacle courses. Follow-ups were undertaken at the end of the 12-week intervention period, with both groups showing improvements from baseline. The ICG group had increased lower limb muscle strength (MD = 4.3 kg; 95% CI = [−0.63, 9.23] vs. baseline) and aerobic fitness based on a 6-minute walk test

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(MD = 35 meters; 95% CI = [−23.95, 93.95] vs. baseline); the control also showed improved strength (MD = 3.3; 95% CI = [−3.86, 10.46] vs. baseline) and balance (MD = 7 seconds; 95% CI = [−2.2, 16.22] vs. baseline). There were no significant between-group differences in terms of muscle strength (MD = 1.3 kg; 95%CI = [−4.96, 7.56]), balance (4.9 seconds; 95% CI = −3.83, 13.63]), aerobic capacity (MD = 85 meters; 95% CI = [−24.98, 145.02]), or fear of falling (MD = 2.9 points; 95% CI = [−2.73, 8.53] based on a 64-point questionnaire). Heiden and Lajoie (2010) used a similar ICG intervention in a sample of community-dwelling older adults. Comparisons were made with a control group undertaking 8 weeks of chair-based exercises only; there were insufficient data to calculate between-group effect sizes. Reaction time (p < .05) and balance (p < .05) were significantly improved from baseline in the ICG group only. However, 6-minute walk distance was significantly reduced in both groups. Sohnsmeyer et al. (2010) performed an RCT with 40 subjects aged 70 years and older; ICG intervention was based on a commercial computer system game (Wii Bowling). After a 6-week intervention period, the ICG group had a significant increase in isometric quadriceps strength compared with an untreated control group. In a large RCT (Wolf et al., 2003), the ICG intervention was limited to balance exercises facilitated with visual feedback from a cursor on a computer screen (using four transducers embedded in two movable pylons upon which subjects stood). Comparisons were made with Tai Chi or advice groups, over a 15-week intervention period. The Tai Chi intervention was group based, with participants encouraged to undertake 30 minutes of home exercises each day. Tai Chi resulted in a significantly lower incidence of falls compared with ICG (risk difference = 0.28; 95% CI = [0.12, 0.45]), but there were no significant between-group differences in flexibility, strength (MD = 1.30 kg; 95% CI = [−1.81, 4.41]), or walking capacity (MD = 0.02 miles; 95% CI = [−0.01, 0.05]). In a study by Buccello-Stout et al. (2008), two groups (aged 66-81 years) undertook treadmill walking while interacting with a three-dimensional virtual screen. In one group, the VR environment was rotating to create an increased sensorimotor challenge. After eight sessions, there were significant betweengroup differences in favor of the sensorimotor group (rotating environment) in speed (mean decrease of 3.7 seconds in the experimental group) and accuracy (mean decrease of 5.3 penalties in the experimental group) during a walking obstacle course. Between-group differences were retained over a 4-week period.

ICG and Cognitive Functioning Observational. Rosenberg et al. (2010) recruited older adults with subsyndromal depression. They used an “Exergame” (Nintendo Wii), whereby participants play different sports (golf, tennis, bowling, baseball, and boxing), using a

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remote wireless device. This had a positive impact on symptoms over a 12-week period; follow-up showed significant improvements from baseline in depressive symptoms based on the Quick Inventory of Depressive Symptoms Scale (MD = 2.7 points; 95% CI = [0.56, 4.84]), cognitive functioning based on the Repeatable Battery for Assessment of Neurocognitive Status (MD = 4.6 points; 95% CI = [−6.5, 15.7]), and quality of life (SF 36 mental composite; MD = 3.2 points; 95% CI = [−2.87, 9.27]). Studenski et al. (2010) also found positive changes in cognitive performance after 3 months of ICG using an interactive dance mat program (decrease from baseline of 0.7 points [SD = 5.5] on a digital substitution test).

Enjoyment, Compliance, and Adverse Events A small number of studies reported relevant secondary outcomes. Graves et al. (2010) found ICG games (Wii Balance, Wii Yoga, Wii Muscle Conditioning, Wii Aerobics) scored well on a Physical Activity Enjoyment Scale (PACES); the highest PACES scores were with Wii Balance which equated to a percentage enjoyment score of 85.5 (SD: 14.2%). Rosenberg et al. (2010) reported good compliance with 85% of participants completing a 12-week intervention (Wii Sports). Qualitative feedback from this study was also positive with the intervention described as being fun, varied, motivating, challenging to improve, and provided good feedback on progress. Positive qualitative feedback on Wii Balance exercises was also reported by Young et al. (2011); their small sample of participants stated that they enjoyed the intervention, and would “definitely” continue to use it over a longer period of time. Studenski et al. (2010) reported noncompliers with 11 out of 36 participants failing to complete a 12-week dance mat intervention; three expressed a lack of interest and four suffered musculoskeletal pain due to weight bearing during or after the intervention. Rosenberg et al. (2010) also recorded two incidences of minor pain with Wii Sports. No study reported any serious adverse side effects.

Discussion Summary of Results This is the first study to systematically examine use of ICG in older adults and consider its potential health benefits. We included data from 12 studies on older adults, of which 3 used participants with a mean age of >80 years. We found preliminary evidence that ICG is a safe and effective medium to promote PA in an older population, and may be associated with a range of physical and cognitive benefits. Findings from some of the studies are restricted due to small sample size,

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high risk of bias, and observational study design. There was a wide range of ICG interventions used; some were limited to basic computer interaction, including the largest RCT (Wolf et al., 2003) and may not have maximized the potential for motivation and gaming. There was no evidence of an optimal exercise dose in terms of exercise type, duration, or intensity and, there were insufficient data to investigate potentially important subgroup effects based on age, gender, or baseline activity levels. In studies using observational designs, effect sizes were calculated based on within-group comparisons; these should be interpreted with some degree of caution as retest or practice effects have been shown to be comparable with treatment effects in an elderly population (Colcombe & Kramer, 2003).

ICG and Physical Fitness A decline in physical fitness is a common feature of old age. PA can help to slow, reduce, or even reverse age-related decreases in aerobic capacity, strength, balance, and flexibility. Public health guidelines for PA have been refined for older adults, and include aerobic, strengthening, balance, and flexibility components. It is estimated that only 12% of older adults aged between 65 and 74 years, and 10% aged >74 years, regularly undertake muscle strengthening activity (U.S. Department of Health and Human Services, 2004). Progressive muscle weakness and bone loss are primary causes of mobility loss and independence in old age (Narici & Maffulli, 2010). Three RCTs (Hagedorn & Holm, 2010; Wolf et al., 2003) in the current review assessed muscle strength. Sohnsmeyer et al. (2010) reported significant increases in lower limb strength after a 6-week intervention period; however, this was compared with an untreated control group. In the others, ICG resulted in within-group increases in strength over a 12- (Hagedorn & Holm, 2010) and 15-week (Wolf et al., 2003) intervention period. However, changes were comparable with groups using other forms of exercise. Most ICG interventions in the current review were designed primarily to challenge participants’ balance and postural control, rather than muscle strength. Indeed, there were clear trends from observational studies that ICG interventions could reduce postural sway, improve standing stability (Suárez et al., 2006; Young et al., 2011), and balance confidence (Studenski et al., 2010; Young et al., 2011). Furthermore, the majority of RCT showed ICG is more effective than chair-based exercise and is equally effective as other forms of balance training exercises (Bisson et al., 2007; Hagedorn & Holm, 2010). Improving balance and postural control in older people could have significant benefit in terms of gait performance, stability, and risk of falling. Future research should determine the clinical and economic significance of the observed changes. Only one RCT monitored fall occurrence; the ICG intervention in this study was

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Table 2. Recommendations for Future Trials Investigating the Effectiveness of Interactive Computer Games (ICGs). Recommendations Selection/inclusion criteria Methodology     ICG intervention

   

 

Comparison group       Outcomes and follow-up    

•  Elderly adults with particular focus on participants aged > 80 years •  Randomized controlled design (predetermined randomization schedule and allocation concealment) •  Blinded outcome assessment •  Minimize attrition bias through active tracking of dropouts/ intention to treat analysis •  Game design or accessories developed to challenge a specific component of fitness, for example, strengthening or falls prevention •  User-friendly software tailored to elderly population •  Maximize enjoyment, engagement, and motivation during exercise by ensuring ICG themes correspond to the interests of the elderly population •  Maximize programmable game features, for example, incorporating baseline calibration to tailor game features to individuals’ ability/fitness levels •  Nongame exercise •  Optimal exercise dose (duration intensity) •  Subgroup effects (gender, baseline physical, or cognitive ability) •  Active control group recognized as a necessity for cognitive intervention studies •  Physical and cognitive-based outcomes •  Mechanistic and clinically relevant •  Active follow-up of predefined adverse events

somewhat limited, but the superiority of Tai Chi as a fall-prevention strategy may be an important finding.

ICG and Cognition Aging is associated with negative plastic changes in the brain. Although cognitive decline can be prevented by ensuring interaction with challenging or new environments, this becomes increasingly difficult to achieve with increasing age. There was some evidence that ICG has a positive influence on cognition (Rosenberg et al., 2010; Studenski et al., 2010), depressive symptoms (Rosenberg et al., 2010), and quality of life (Rosenberg et al., 2010); these findings were largely based on older participants (aged 63-96 years) with existing subsyndro-

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mal depression (Rosenberg et al., 2010). We found no randomized controlled studies investigating the effect that physically based ICGs have on cognitive function. This should be addressed in future research to more rigorously differentiate between interventional effects and retest effects, when assessing cognitive measures in this population. Cognitive activity or stimulation associated with ICG could be a protective factor against the cognitive functional losses associated with aging (de Bruin, Schoene, Pichierri, & Smith, 2010). There is a growing body of evidence that ICGs with no physical component (e.g., strategy games, personalized cognitive training programs, or classic computer games; Basak, Boot, Voss, & Kramer, 2008; Peretz et al., 2011; Smith et al., 2009) produce positive changes in cognitive function including enhanced executive function, memory, and focused attention.

ICG and Overcoming Barriers to PA Physical inactivity is a major public health challenge in the developed world. Only 37% of men and 24% of women in the United Kingdom meet the minimal recommendations for PA (Allender, Peto, & Scarborough, 2006). Older adults are particularly inactive which may relate to a combination of personal, environmental, cultural, and social factors. In a review of qualitative studies, Allender, Cowburn, et al. (2006) suggest that in older adults, unclear guidance and lack of role models are the greatest barriers to PA; and there is further evidence that social support, health benefits, and enjoyment are the most important motivators (Allender, Cowburn, et al., 2006; Stathi, McKenna, & Fox, 2003). PA should be one of the highest priorities for preventing and treating disease and disablement in older adults (Chodzko-Zajko et al., 2009). Developing effective methods to promote PA and improve adherence is therefore a priority in this population. ICG can incorporate play and enjoyment, which are important motivators for PA. Two studies (Graves et al., 2010; Young et al., 2011) included qualitative analysis of patients’ experience during ICG and there were clear trends that commercial interventions were well tolerated and enjoyable. Fear can be a significant barrier to PA. In older adults this can relate to fear of a different situation, a fear of falling or injury. Some of the ICG interventions involved simulation of boxing, golf, and bowling, which were well tolerated. Exposing older adults to environments and experiences such as these, which are otherwise inaccessible or dangerous, is a unique advantage of ICG.

ICG and Safety A small number of minor adverse events associated with ICG were reported (Rosenberg et al., 2010; Studenski et al., 2010). These were generally muscu-

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loskeletal complaints and are likely to be related to muscle soreness from unaccustomed movements or weight bearing. A potential limitation of included studies is that the majority did not seem to undertake active surveillance of predefined adverse events. Although this may have been an oversight during reporting, the short- and long-term safety of ICG requires further investigation. We must consider that included studies were largely based on physically healthy groups of older adults, with few existing comorbidities. ICG is not suitable for every older adult. Little information is available concerning its use on very frail older adults, or those presenting loss of functional independence. The introduction of computer-based exercises should follow the same reasoning and dose selection as any other form of PA. This is particularly applicable to older adults accustomed to inactivity. A related advantage of ICG is the capacity for programs to record data on participants’ exercise intensity and performance. This could facilitate optimal progression and ensure that exercise prescription is suitable to the users’ fitness levels. There have been a number of cases reporting injuries relating to ICG within younger user populations (Baxter & Madhok, 2011; Razavi & Lam, 2011; Robinson, Barron, Grainger, & Venkatesh, 2008; Sparks, Chase, & Coughlin, 2009), including eye trauma and acute or overuse musculoskeletal injuries involving the arm and knee. Future studies within an elderly population must use an extensive and active follow-up on predefined adverse events.

Game Type and Suggestions for Future Designs There were variations across studies in terms of the software, game design, and application of ICG into each rehabilitation strategy. In many of the studies containing bespoke games, their game design within the ICG interventions was rudimentary and game-play mechanics were either limited or not discussed adequately to be fully understood. There was also limited emphasis on game play within the commercial Wii game studies. The design of the ICG program is a key factor determining participant usability and enjoyment; structured game play, constructed through staged challenges, is an important motivational aspect of game design. Future studies should try to take full advantage of the positive impact game design can have on play, enjoyment, engagement, and motivation during exercise (Table 2). Not all participants were able to complete the ICG interventions, and two studies found that between 10% (Studenski et al., 2010) and 15% (Rosenberg et al., 2010) of participants failed to complete the intervention; one study clarified that dropout was due to lack of interest (Studenski et al., 2010). There is currently a limited selection of ICG interventions adapted for older users. Many off-the-shelf games are too

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complex or difficult, and do not correspond with the interest sets of an older population. Game design must be tailored more toward the older people, and should find ways to optimize motivation, enjoyment, and safety within this population. The clinical effectiveness of ICG in older adults could be ameliorated by designing interventions to target particular elements of physical or cognitive function. For example, game designs or accessories could be developed to provide more of a strength challenge in order to combat sarcopenia and weakness in old age. ICG interventions could also be manipulated to target specific components of sensorimotor control or even challenge dual tasking. ICG also provides an optimal medium to simultaneously train balance, coordination, attention, and visual–spatial ability and provide real-time feedback on performance, gait, physical function, and fall prevention.

Conclusion There is preliminary evidence that ICG is a safe and effective exercise intervention for an older population, and may be associated with a range of physical and cognitive benefits. Future ICG interventions should be tailored toward older people, and should aim to optimize motivation, enjoyment, and safety within this population. Study methodology should incorporate randomized, parallel group designs with lower risk of selection, detection, and attrition bias.

Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.

References Allender, S., Cowburn, G., & Foster, C. (2006). Understanding participation in sport and physical activity among children and adults: A review of qualitative studies. Health Education Research, 21, 826-835. Allender, S., Peto, V., & Scarborough, P. (2006). Coronary heart disease statistics. London, England: British Heart Foundation. Baert, V., Gorus, E., Mets, T., Geerts, C., & Bautmans, I. (2011). Motivators and barriers for physical activity in the oldest old: A systematic review. Ageing Research Reviews, 10, 464-474.

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Author Biographies Chris M. Bleakley is a Lecturer at the Faculty of Life and Health Science. He is a graduate of the University of Ulster, obtaining a BSc in Physiotherapy in 2000, and a PhD in 2004. Darryl Charles is a Senior Lecturer in Computing and a member of the Computing Research Institute at the University of Ulster. He obtained his B.Eng. in Electrical and Electronic Engineering from Queens University, Belfast, in 1988, his MSc in Microelectronics and Microcomputer Applications from the University of Ulster,

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Coleraine, in 1995, and his PhD on Unsupervised Artificial Neural Networks from the University of Paisley, Scotland, in 1999. He specialises in games research and development, and is is currently Chief Technical Advisor at the game based learning specialist company, SilverFish Studios. Alison Porter-Armstrong is a Senior Lecture and a member of the Centre for Health and Rehabilitation Technologies in the Institute of Nursing and Health Research. She received her occupational therapy degree in 1993 and her DPhil in 1999 from the University of Ulster. Her research interests are in physical activity and risk of pressure ulceration and use of assistive technologies. Michael D. J. McNeill recently retired as Senior Lecturer in Computer Science from the University of Ulster. He holds a DPhil in 3D graphics from the University of Sussex and a BSc (Hons) in Mathematics from the University of Bath. He has experience in computer graphics, virtual reality and in computer game design for people with stroke. Suzanne M. McDonough is a Professor of Health and Rehabilitation at the University of Ulster, and leads up the Centre for Health and Rehabilitation Technologies in the Institute of Nursing and Health Research. In 1989 she gained her B. Physiotherapy in UCD, Dublin, Ireland and her PhD in 1995 from the Medical School, Newcastle University, UK. Suzanne has expertise on gaming for rehabilitation in children with cerebral palsy and adults with stroke. Brendan McCormack is Director of the Institute of Nursing and Health Research and Head of the Person-centred Practice Research Centre at the University of Ulster. He has a professional background in mental health and gerontological nursing. His writing and research work focuses on gerontological nursing, person-centered practice and practice development. He is the Editor of the “International Journal of Older People Nursing”. Brendan obtained his Doctorate in Philosophy from the University of Oxford in 1997.