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Research Article

Active Video Games and Health Indicators in Children and Youth: A Systematic Review

  • Allana G. LeBlanc equal contributor,

    equal contributor Contributed equally to this work with: Allana G. LeBlanc, Jean-Philippe Chaput

    Affiliation: Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada

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  • Jean-Philippe Chaput equal contributor mail,

    equal contributor Contributed equally to this work with: Allana G. LeBlanc, Jean-Philippe Chaput

    jpchaput@cheo.on.ca

    Affiliations: Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada, Department of Pediatrics, University of Ottawa, Ottawa, Ontario, Canada

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  • Allison McFarlane,

    Affiliation: Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada

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  • Rachel C. Colley,

    Affiliations: Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada, Department of Pediatrics, University of Ottawa, Ottawa, Ontario, Canada

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  • David Thivel,

    Affiliation: Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada

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  • Stuart J. H. Biddle,

    Affiliation: School of Sport, Exercise & Health Sciences, Loughborough University, Loughborough & The NIHR Leicester-Loughborough Diet, Lifestyle and Physical Activity Biomedical Research Unit, United Kingdom

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  • Ralph Maddison,

    Affiliation: National Institute for Health Innovation, University of Auckland, Auckland, New Zealand

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  • Scott T. Leatherdale,

    Affiliation: School of Public Health and Health Systems, University of Waterloo, Waterloo, Ontario, Canada

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  • Mark S. Tremblay

    Affiliations: Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada, Department of Pediatrics, University of Ottawa, Ottawa, Ontario, Canada

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  • Published: June 14, 2013
  • DOI: 10.1371/journal.pone.0065351

Abstract

Background

Active video games (AVGs) have gained interest as a way to increase physical activity in children and youth. The effect of AVGs on acute energy expenditure (EE) has previously been reported; however, the influence of AVGs on other health-related lifestyle indicators remains unclear.

Objective

This systematic review aimed to explain the relationship between AVGs and nine health and behavioural indicators in the pediatric population (aged 0–17 years).

Data sources

Online databases (MEDLINE, EMBASE, psycINFO, SPORTDiscus and Cochrane Central Database) and personal libraries were searched and content experts were consulted for additional material.

Data selection

Included articles were required to have a measure of AVG and at least one relevant health or behaviour indicator: EE (both habitual and acute), adherence and appeal (i.e., participation and enjoyment), opportunity cost (both time and financial considerations, and adverse events), adiposity, cardiometabolic health, energy intake, adaptation (effects of continued play), learning and rehabilitation, and video game evolution (i.e., sustainability of AVG technology).

Results

51 unique studies, represented in 52 articles were included in the review. Data were available from 1992 participants, aged 3–17 years, from 8 countries, and published from 2006–2012. Overall, AVGs are associated with acute increases in EE, but effects on habitual physical activity are not clear. Further, AVGs show promise when used for learning and rehabilitation within special populations. Evidence related to other indicators was limited and inconclusive.

Conclusions

Controlled studies show that AVGs acutely increase light- to moderate-intensity physical activity; however, the findings about if or how AVG lead to increases in habitual physical activity or decreases in sedentary behaviour are less clear. Although AVGs may elicit some health benefits in special populations, there is not sufficient evidence to recommend AVGs as a means of increasing daily physical activity.

Introduction

The majority of children and youth around the world do not meet current physical activity guidelines and are considered to be inactive [1]. Self-reported measures of physical activity (PA) from the Global School-based Student Health Survey and the Health Behaviour in School-Aged Children Study (HBSC) show that 80% of 13–15 year olds do not participate in at least 60 minutes of moderate- to vigorous-intensity physical activity (MVPA) daily [2]. Further, it is now understood that children and youth spend a significant part of their day being sedentary. International data from the HBSC study show that 66% of girls and 68% of boys watch more than two hours of television per day [2], and data from a Canadian study show that youth accumulate an average of 7.8 hours of screen time daily [3].

High levels of habitual sedentary time (especially via screen-based activities) are associated with a range of negative health and behavioural indicators including poorer measures of body composition, fitness, self-esteem, self-worth, pro-social behaviour, and/or academic achievement [4]. Thus, population health researchers have started to develop novel interventions that use screen-based technology as part of the solution rather than part of the problem. One such intervention is the use of active video games (AVGs), or screen-based activities that require increased PA to play the game compared to conventional sedentary, or passive, video games (see Table 1).

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Table 1. Definitions used to guide the systematic review.

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AVGs have the potential to increase habitual PA and improve measures of cardiometabolic health among children and youth who would otherwise be spending time in sedentary, screen-based activities. Manipulating the gaming environment as an intervention tool for increasing PA is reinforced by recent findings showing that playing AVGs acutely increases EE compared to sedentary video games [5][10]. However, there is evidence to suggest that both children and adults may compensate for exercise interventions by decreasing spontaneous PA for the remainder of the day such that the net PA remains unaffected [11], [12]. Thus, from a public heath standpoint, it is important to examine the habitual and long-term impact of AVGs on a range of health and behaviour indicators to better appreciate the potential benefits (and potential risks) of AVGs. The objective of this systematic review is to present current evidence on the relationship between AVGs and several health and behavioural indicators in children and youth aged 0–17 years.

Methods

Quality Assessment

The GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework was used to guide our review including a-priori ranking of health indicators and quality assessment of the evidence. Quality of evidence for each health indicator was assessed based on study design, risk of bias, consistency of results, directness of the intervention, precision of results, and possibility of a dose-response gradient. Details on data extraction are presented in the following sections. Details on GRADE methodology can be found elsewhere [13].

Study Inclusion Criteria

To be included, studies needed to have a specific measure of time spent using AVGs using direct (e.g., accelerometer, pedometer or computer memory) or indirect (e.g., self- or parent-report) measurement, and a measure of at least one relevant health or behaviour indicator. Relevant health and behaviour indicators were chosen a priori by an expert panel (paper authors) and prioritized based on group consensus (Table 2).

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Table 2. A priori consensus rankings assigned by the Guideline Development and Research Committee for each health indicator by age group.

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Study Exclusion Criteria

All published, peer-reviewed studies were eligible for inclusion; no date limits were imposed, but due to feasibility, studies in languages other than English or French were excluded. Studies were excluded if the mean age of participants was greater than 17.99 years; if the study examined only passive video games; if there was more than one aspect to the intervention that may have confounded the results (e.g., an intervention that included both AVG and diet components); or if the outcome of interest was not included in our list of relevant health and behavioural indicators.

Search Strategy

The following electronic bibliographic databases were searched: MEDLINE, EMBASE, psycINFO, SPORTDiscus and Cochrane Central Database. The search strategy was created and run by AGL (see Appendix S1). Database searches were limited to studies involving children and youth aged 0–17 years. References were extracted from the OVID, EBSCO and Cochrane interfaces and imported into Reference Manager Software (Version 11, Thompson Reuters, San Francisco, CA).

Titles and abstracts of potentially relevant articles were screened by two independent reviewers (AM, and one of JPC, RCC, AGL, or DT), and full text copies were obtained for articles meeting initial screening criteria. Full text articles were screened in duplicate for inclusion in the review (AM and one of JPC, RCC, AGL or DT); any discrepancies were discussed, and resolved by the reviewers. In addition to our search, seven key content experts were contacted and asked to identify what they deemed important papers in the field.

Data Extraction and Analysis

Data extraction was completed by one reviewer and checked by another for accuracy (one of JPC, AGL or AM). One reviewer (AGL) independently assessed the quality of evidence for all studies [13]. Reviewers were not blinded to the author names or journal titles when extracting data. Studies were divided by health or behavioural indicator (some studies examined more than one indicator) and by study design.

Results

Figure 1 shows the PRISMA flow diagram for study inclusion and exclusion. Table 3 provides a summary of all studies included in the review. Quality of evidence, by health or behaviour indicator, can be found in Tables 410. The indicators of interest represented in the included studies were energy expenditure (n = 35), adherence and appeal (n = 18), opportunity cost (n = 2), adiposity (n = 9), cardiometabolic health indicators (n = 3), energy intake (n = 2), and learning and rehabilitation (n = 9). No studies examining the relationship between AVG play and adaptation, or evolution of video games, were found. Many studies included results for more than one health indicator and were presented accordingly. Due to heterogeneity in AVGs used in the included studies (e.g., brand of gaming consoles, game type, playing time), a meta-analysis was not possible. Qualitative synthesis was conducted for all included studies.

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Figure 1. Prisma flow diagram of included studies.

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Table 3. Descriptive characteristics of included studies.

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Table 4. Association between active video games and energy expenditure in children and youth.

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Table 5. Association between active video games and adherence and appeal in children and youth.

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Table 6. Association between active video games and opportunity cost in children and youth.

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Table 7. Association between active video games and adiposity in children and youth.

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Table 8. Association between active video games and cardiometabolic health indicators in children and youth.

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Table 9. Association between active video games and energy intake in children and youth.

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Table 10. Association between active video games and learning and rehabilitation in children and youth.

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Data Synthesis

Physical Activity and Energy Expenditure

Studies were grouped depending on if they examined habitual activity (i.e., if AVG was associated with increased PA, decreased sedentary behaviour, or change in fitness), or acute EE (i.e., measured EE during a single bout of AVG play) (Table 4).

Changes in habitual physical activity

Eleven randomized controlled trials (RCTs), and five observational studies examined the relationship between AVG play and habitual PA. The majority of the `RCTs reported that an AVG intervention had no effect on time spent engaging in total PA [14][19], MVPA [15], [18], [20], [21], or physical fitness (estimated via shuttle run test) [21]. Maloney et al. [15] suggested that a Dance Dance Revolution (DDR) intervention increased self-reported levels of PA (measured via self-report) but not objectively measured PA (measured via accelerometer). Baranowski et al. [20] found no difference in objectively measured PA between children who were given a passive video game or those who were given AVGs. Ni Mhurchu et al. [18] showed increased PA at 6 weeks but not at 12 weeks in those who received an AVG intervention compared to those who continued playing passive games. The remaining RCTs suggest AVGs do have an effect on habitual EE [22][24]. Errickson et al. [22] reported increases in weekly MVPA in the intervention group after a 10-week DDR intervention but statistical significance was not reported; Maloney et al. [23] reported increased vigorous PA (hours/week) after a 10-week DDR intervention; and Murphy et al. [24] reported increases in aerobic fitness (peak VO2) after a 12-week DDR intervention.

The observational studies provided inconsistent results. Bethea et al. [25] reported increased aerobic fitness (VO2max) after a 30-week DDR intervention; however, Owens et al. [26] reported no change in either aerobic or muscular fitness after three months of Wii Fit use. Finally, there were inconclusive results comparing AVGs to traditional PA. Fogel et al. [27] reported higher levels of PA when playing AVGs compared to physical education class; whereas Gao et al. [27] reported that students spent more time in MVPA during fitness class and playing football, than when playing DDR.

Changes in acute energy expenditure

Two RCTs examined the effect of AVG on acute EE. The first reported no significant difference in average time spent pedaling (min/session), EE (kcal/session), time spent in MVPA (60–79% peak heart rate/session), or average distance pedaled (km/session) between a GameBike intervention group and music only exercise group [29]. However, the second study reported higher measures of oxygen consumption (VO2), heart rate, and rating of perceived exertion while playing Wii boxing than when compared to rest or light treadmill walking (1.5 mph) [30].

Seven intervention studies and 12 cross-sectional studies examined the EE of AVGs compared to rest or to sedentary video games and all reported significant increases in EE [31][48]. Three of these studies suggested that although AVGs increased EE above rest, and while playing sedentary video games, EE is still less than when participating in traditional PA [34], [47], [48].

Adherence and appeal

Studies were grouped depending on if they examined adherence to playing AVGs (i.e., children continued to use AVG in the long term, or if it dropped off quickly), or appeal of AVG (i.e., if children and/or their parents enjoyed AVGs) (Table 5).

Adherence to active video games

Of the eight RCTs that assessed adherence to AVG play, four reported high levels of adherence at the midpoint of the study, but significantly lower levels by the end of the interventions (interventions ranged from 10–12 weeks) [15][17], [35]. One study reported that adherence was lower at the end of the study but the difference did not reach statistical significance [49]. Paez et al. [50] were unable to determine any significant predictors of time spent playing DDR at the end of a 10-week intervention. Finally, two studies reported that although both groups played fewer sedentary video games by the end of the study, there was a trend towards less sedentary play in the AVG intervention group compared to the control group [18], [21].

Two intervention studies and one cross-sectional study reported on adherence to AVG play. Bethea et al. [24] reported that children decreased time spent playing AVGs by the end of the study. Sit et al. [44] reported that although there was no significant difference in time spent playing interactive versus online bowling or running game, normal-weight children spent more time on both interactive bowling (p<0.05) and running (p<0.01) than overweight participants. Finally, Dixon et al. [51] provided qualitative data saying that overall, both parents and children supported the idea of AVGs, but not at the expense of traditional PA.

Appeal of active video games

One RCT presented qualitative data reporting that in general, children like AVGs, and things they did not like were game-specific [20]. Of the six intervention and one cross-sectional studies, the majority reported that in general, children and youth enjoyed AVGs [27], [28], [31], [35], [47]. Children enjoyed Wii Balance, Wii Aerobics and Wii Boxing more than treadmill walking or running [30], [34], and Wii Golf more than traditional mini golf [47]; however, they enjoyed indoor mini basketball more than the video game version [46] and showed higher intrinsic motivation to fitness class than to DDR [28]. They also enjoyed DDR (even when using a handheld controller) more than dancing with music or an instructional video [52]. Bailey et al. [31] reported that boys enjoyed Wii Boxing and Xavix J-mat more than girls. Finally, Roemmich et al. [47] reported that children spent an average of 87% more time in free play when given access to AVGs compared to indoor versions of traditional PA.

Opportunity cost

This review identified one RCT and two observational studies reporting on adverse events associated with AVGs. The RCT reported that none of the adverse events that occurred during the study period were related to the AVG intervention (EyeToy) [21]. Two observational studies reported some injuries associated with AVG use (e.g., back pain, fractures, bruises) [53], [54]. No studies reported on the financial opportunity cost (e.g., spending money on AVGs instead of on more traditional PA such as sports equipment or swimming lessons) or behavioural opportunity cost (e.g., AVGs displacing traditional PA) (Table 6).

Adiposity

Six RCTs (from seven papers), and three intervention studies were included. Results of the RCTs seemed to depend on weight status of the participants included in the study. Three of the RCTs included only overweight or obese participants and reported that AVGs helped to attenuate weight gain [21], [29], [55]; however, of the three RCTs that included normal-weight participants, only one reported attenuated weight gain in the intervention group [18]. The three intervention studies reported that AVG had no effect on attenuating weight gain or promoting weight loss in normal weight [25], [26] or overweight [56] participants (Table 7).

Cardiometabolic health indicators

Two RCTs and one prospective cohort study reported on the relationship between AVGs and cardiometabolic health. After a 12-week DDR intervention with overweight children, Murphy et al. [24] reported a significant decrease in mean arterial pressure in the exercise intervention group, but no changes in blood pressure, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, or measures of insulin sensitivity (HOMA, fasting insulin); however, Adamo et al. [29] reported a decrease in total cholesterol after a 10-week GameBike intervention in obese children but no changes in high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, fasting blood glucose, fasting insulin or triglycerides (they did not report on mean arterial blood pressure). Finally, a 30-week prospective cohort study found no effect of DDR use on blood pressure, fasting glucose, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, or triglycerides post intervention [24] (Table 8).

Energy intake

Two studies examined energy intake during AVG play [21], [41]. One RCT reported that over a 24-week AVG intervention (EyeToy), average self-reported daily total energy consumed from snack food decreased in the intervention group (567±684 kcal/day) compared to the passive video game control group (708±948 kcal/day), but the change was not statistically significant [21]. The other study (4 sessions using X-box 360 on an adapted treadmill) reported no significant difference in energy intake between the AVG session (383±266 kcal/h) versus the seated gaming session (374±192 kcal/h) [41] (Table 9).

Learning and rehabilitation

This review included two RCTs and seven observational studies examining the relationship between AVG and learning and rehabilitation. The first RCT used Nintendo Wii along with standard physiotherapy to treat those with cerebral palsy (compared to standard physiotherapy alone), and saw significant improvements in upper limb function [57]. The second RCT also reported significant improvements in motor proficiency after a Wii intervention in those with Down's syndrome [58]. All seven observational studies showed improvements in learning and rehabilitation after an AVG intervention (using Nintendo Wii, DDR or Microsoft Kinect). This included improvements in manual and body coordination [59], following movement cues and directions [60][62], functional mobility [63], and length of time spent at higher intensity of PA [64], [65] (Table 10).

Interpretation

This systematic review is the first to provide a comprehensive understanding of the influence of AVGs on multiple health and behavioural indicators in children and youth. Existing evidence suggests that AVGs are able to increase EE above rest and when compared to playing passive video games. The studies included in the systematic review also showed that AVGs do not make a significant contribution to enable children and youth to meet guidelines of 60 minutes of moderate- to vigorous-intensity physical activity on a daily basis [1]; however, AVGs may increase light- to moderate-intensity physical activity at the expense of some sedentary behaviours (including sedentary video games). The appeal of AVGs is high for some children, but there is a lack of evidence suggesting long-term adherence. In overweight and obese children and youth, AVGs may attenuate weight gain whereas evidence in normal-weight children is inconclusive. Evidence for energy intake and AVG play is also inconclusive as is the effect of AVG interventions on cardiometabolic health indicators or opportunity cost. Finally, there is evidence to suggest that AVGs can be beneficial to improve motor skill proficiency and movement cues in populations with movement difficulties.

Strengths and limitations

The main strength of this study is the use of high, international standards of developing and conducting a systematic review. As many decisions as possible were made a priori which helps to limit potential bias throughout the review. Furthermore, all steps of the review (i.e., inclusion criteria, exclusion criteria, data extraction, GRADE tables) were done in duplicate to minimize error. Further, the systematic review has been completed as per PRISMA guidelines (Appendix S2). Finally, we focused on many health and behavioural indicators (i.e., not just EE) with the hope of providing a thorough understanding of the relationship between AVGs and health in children and youth.

The main limitation to our study, and an area for future research, relates to the relatively low quality of studies in this field of research. Most studies included in this review had small sample sizes and short intervention periods, making it difficult to elucidate the true effects of these technologies on health and behavioural outcomes. Further, since many studies were underpowered, some results were not statistically significant (and therefore not reported here) but showed a trend towards significance. Future work should aim to use larger sample sizes to avoid being underpowered, and focus on using both direct (e.g., accelerometer, pedometer, heart rate) and indirect (e.g., self-, parent-, caregiver-report) measures to assess total AVG use. Both measures are needed to reflect the nuances associated with capturing AVG play such as body position or intensity of play. Moreover, multiple follow-up measurements over longer time periods are required so the longitudinal effects of AVG use can be better understood. It is also important that future work aims to harmonize methods for data collection and analysis so that meta-analyses can be performed. Moreover, the review included studies that were largely based on what could be deemed “first generation” AVGs, as such there will be a need to re-evaluate the evidence in the future as AVGs evolve (and the quality of the research designs improve).

Future directions

Other reviews in this area have shown similar results to ours in that some AVGs are able to acutely increase light- to moderate-intensity PA in some children and youth but unable to elicit PA of high enough intensity, or volume to enable children to meet physical activity guidelines [5][10], [66]. More high quality, robustly designed and well powered studies are needed comparing AVGs to traditional PA (not just to rest or other sedentary games); comparing different types of video game consoles; measuring energy intake while playing AVGs (compared to a variety of both active and sedentary behaviours); assessing AVG use in limited areas that may be unsafe; assessing the ability of AVGs to displace sedentary time; examining the opportunity cost of AVGs (i.e., both time and financial considerations); and assessing behavioural compensation throughout the entire day.

Conclusion

While controlled laboratory studies clearly demonstrate that a motivated player can obtain some light- to moderate-intensity PA from most AVGs, the findings are inconsistent about whether, or the circumstances under which, having an AVG results in sustained PA behaviour change, or for how long the behaviour change persists. Some of these games offer nuances on game play that could be related to increased PA or decreased sedentary behaviour. AVG technology is innovating at a rate that outpaces the related research. Higher quality research is needed that tests conceptual models of how different AVGs may relate to the initiation and maintenance of increased PA or decreased sedentary behaviour and understand their effects on health outcomes to resolve these inconsistencies.

Supporting Information

Appendix S1.

Search strategy.

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(DOC)

Appendix S2.

PRISMA presubmission checklist.

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(DOC)

Acknowledgments

The authors are grateful to Dr. Margaret Sampson at the Children's Hospital of Eastern Ontario for her contributions to developing the search strategy for this project.

Author Contributions

Conceived and designed the experiments: MST AGL JPC RCC RM SJHB SL. Performed the experiments: MST AGL JPC AM DT RCC RM SJHB SL. Analyzed the data: MST AGL JPC AM DT RCC RM SJHB SL. Wrote the paper: MST AGL JPC AM DT RCC RM SJHB SL.

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