Experience level and social condition influences on heart rate, perceived exertion, and mood from interactive video game boxing.

Russell, William D. ; Kraft, Justin A. ; Bergman, Randall J. 等

Sedentary behavior is a modifiable risk factor for lifestyle related diseases (Blair & Connelly, 1996), and finding healthier physical activity options is important to improving health. Many individuals base physical activity decisions on enjoyment (Kahneman, 1999) and when people derive pleasure from exercise, adherence rates increase (Carels, Berger, & Darby, 2006; Williams, Dunsinger, Ciccolo, Lewis, Albrecht, & Marcus, 2008). Unfortunately, activities such as television watching or video games are increasingly replacing more physically active options (Gortmaker, Must, Sobol, Perterson, Colditz, & Dietz, 1996; Janz & Mahoney, 1997). Therefore, identifying enjoyable activities capable of yielding physiological benefits is a primary health objective. Movement-based, interactive video games (IVGs) that promote greater activity (Graves, Ridgers, & Statton, 2008) may provide a more physically active alternative to traditionally sedentary behavior (Trout & Christie, 2007).

Participation in IVGs has shown to increase energy expenditure compared with sedentary video games (Graves et al., 2008; Graves, Stratton, Ridgers, & Cable, 2007; Graves, Ridgers, Williams, Stratton, Atkinson, & Cable, 2010; Lanningham-Foster et al., 2006; Maddison, Mhurchu, Jull, Jiang, Prapavessis, & Rodgers, 2007; Mellecker & McManus, 2008; Straker & Abbott, 2007), suggesting that some applications may be viable alternatives to traditional exercise. Interactive dance games are capable of raising heart rate above the minimal American College of Sports Medicine (ACSM) intensity recommended for developing and maintaining cardiorespiratory fitness (Unnithan, Houser, & Fernhall, 2006; Kraft, Russell, Bowman, Selsor, & Foster, 2011). Results examining Wii Sports boxing have reported HR between 111 bpm (Lee & Pitchford, 2009) and 134 bpm (Welch, White, & Nixon, 2009). Wii Sports boxing has been shown to elicit a higher energy expenditure and HR than Wii Tennis or Bowling (Graves et al., 2008; Lee & Pitchford, 2009). Certain IVGs produce intensities similar to light and moderate traditional physical activities such as walking and jogging (Graves et al., 2010; Maddison et al., 2007; Miyachi, Yammamoto, Ohkawara, & Tanaka, 2010; Tan, Aziz, Chua, & Teh, 2002). Other research, however, has concluded that not all applications are strenuous enough to contribute to recommended daily amounts of exercise (Graves et al., 2007).

If IVGs are capable of promoting physiological benefits, it is reasonable to ask whether they promote psychological benefits similar to traditional exercise (Berger, Pargman, & Weinberg, 2002). In their mood-enhancement taxonomy for exercise, Berger and Motl (2001) noted that for exercise to improve mood, it needed to be a closed and predictable activity, involve rhythmic and repetitive movements, be performed at a moderate intensity, and be perceived as enjoyable. Previous research has demonstrated that some modes of IVG play can fulfill these criteria (Legrand, Philippe, Bertucci, Soudain-Pineau, & Marcel, 2011 ; Plante, Aldridge, Bogden, & Hanelin, 2003; Plante, Aldridge, Su, Bogden, Belo, & Kahn, 2003; Russell & Newton, 2008; Russell, Kraft, Selsor, Foster, & Bowman, 2010). For example, Barkley and Penko (2009) examined affective responses of adults after ten minutes of Nintendo Wii activity, compared to ten minutes of rest, treadmill walking at a moderate pace, or playing a sedentary video game, and found that IVG enjoyment was significantly greater than all other conditions. Plante, Aldridge, Bogden, & Hanelin (2003) found that although both traditional and IVG cycling elicited significant mood benefits, higher feelings of enjoyment and energy were reported when IVG activity was combined with exercise. Russell & Newton (2008) found similarly positive mood improvements after 30 min of IVG cycling vs. regular stationary bicycle at 60-70% of maximal heart rate. Russell et al (2010) showed that IVG exercise produced acute psychological benefits similar to traditional exercise when performed at a self-selected intensity. Therefore, if performed at a sufficient volume to yield minimal physiological benefits, IVGs may also contain necessary elements to yield affective benefits. However, physiological and psychological IVG benefits may vary from mode to mode.

Recently, it has been suggested that physiological and psychological responses to IVGs may be a function of users' experience level (Legrand, Philippe, Bertucci, Soudain-Pineau, & Marcel, 2011; Sasser, Eller, Dragoo, Ulbright, Robinson, & Silvers, 2009; Sell, Lillie, & Taylor, 2008) and whether users perform IVGs alone or with another user (Chin A Paw, Jacobs, Vaessen, Titze, Van Mechelen, 2008). Experience level may influence physiological demands of interactive gaming, as experienced players have exhibited higher energy expenditure, HR, RPE, oxygen consumption, and step count during Dance Dance Revolution (DDR) game play compared to inexperienced players (Sell et al., 2008). Although experience level of participants was not controlled, Worley, Rodgers, & Kraemer (2011) reported higher energy expenditures for two Wii fitness games (aerobic step and hula) when played at the intermediate level rather than the beginner level. Legrand et al (2011) noted that experience level could represent a separate explanation for certain affective changes from IVG exercise.

Variation in movement patterns based on experience level may directly impact the ability of IVGs to elicit activity capable of meeting physical activity guidelines. If exercise demands increase as player skill and experience increases, IVGs may provide a viable routine exercise strategy. On the other hand, if skill improvements that accompany experience cause reductions in bodily motion, exercise demands may decrease over time due to a reduction in movement. To date, research has not examined the influence of users' experience level and social condition (paired vs. alone) on physiological and psychological responses to IVGs. Social condition is important to consider in IVG participation as home-based IVGs are created and marketed to be played alone or in multi-player modes. Companionship is

associated with positive affect during physical activity and is associated with increased physical activity among adolescents (De Bourdeaudhuij et al., 2005; Duncan et al., 2005). Peer influence has also been shown to positively influence activity rate, liking of physical activity, and motivation (Rittenhouse, Salvy, & Barkley, 2011; Salvy et al., 2009).

The purpose, then, of this study was to determine the ability of a novel game, the interactive Wii Punchout boxing game, to promote self-selected intensities sufficient to meet ACSM exercise guidelines. Additionally, since the presence of a peer may influence motivation to be physically active, this presence may influence self-selected exercise intensity during interactive video gaming, as well as mood changes. Therefore, this study further examined the effects of 1) experience level and 2) social condition on self-selected exercise intensity and changes in mood resulting from interactive boxing.

Methods

Participants. Forty-eight college age volunteers (29 males and 19 females: mean age males: 22.4 [+ or -] 5.7 years; females 21.4 [+ or -] 5.6 years), height (males: 179 [+ or -] 8.5 cm; females: 167 [+ or -] 6 cm), body mass (males: 86.3 [+ or -] 17.2 Kg; females: 71.3 [+ or -] 15.7 Kg), and body fat measured via Omron (Bannockburn, IL) body fat analyzer (males: 16.8 [+ or -] 6.1%; females: 25.5 [+ or -] 6.6%) with no previous experience playing the interactive boxing video game were recruited. The final sample of 48 participants included 24 randomly assigned to an experienced group (19 males, 5 females) and 24 randomly assigned to an inexperienced group (10 males, 14 females). All participants were screened for conditions contraindicating physical activity (Physical Activity Readiness Questionnaire; PAR-Q) (Thomas, Reading, & Shephard, 1992). The procedures were approved a priori by the university Institutional Review Board for the protection of human subjects. Participants were asked to refrain from exercise and caffeine the day of their sessions, and adherence to these instructions was verbally confirmed.

Protocol. Participants reported to the lab for an initial familiarization session in which descriptive data was recorded. Participants sat quietly for 10 min while wearing a HR monitor (Port Washington, NY, Polar Inc.) and resting HR was recorded and utilized to calculate a target heart rate (THR) via the Karvonen heart rate reserve (HRR) method (ACSM, 2006; Karvonen, Kentala, & Mustala, 1957). This THR was used to determine minutes spent exercising above THR in the experimental trials. THR was defined as HR [greater than or equal to] 40% of HRR as this is the minimum exercise intensity necessary to bring about improvements in cardiovascular fitness (Pollock et al., 1998). Participants were then introduced to the Wii Punchout (Nintendo, Sony, San Diego, CA) game, and basic game strategies, rules, and controller commands were explained. This was followed by 15 min of game play, with familiarization time equally divided between solo and paired game play. Participants were then randomly assigned to an inexperienced (n = 24) or experienced (n = 24) group. Experience level was operationally defined and controlled by requiring participants assigned to the experienced group to complete two hours of supervised game play, one hour in the alone condition and one hour in the paired condition, prior to their first session of data collection. Participants assigned to the inexperienced group received no supervised game play time other than the 15 min familiarization session.

This study implemented a mixed-model design, in which user experience with the IVG used in this study served as the between-groups variable and social condition of game play was the repeated-subjects variable, in that all participants (in both experience groups) were exposed to both social conditions; (1) playing alone and (2) paired against a peer. Trials were counterbalanced and consisted of 30 min of game play. Throughout each session, participants were fitted with a HR monitor and an ankle-mounted StepWatch 3 Step Activity Monitor (SW) (Orthocare Innovations, Seattle, WA) (r [greater than or equal to] 99) (Karabulut, Crouter, & Bassett, 2005; Foster et al., 2005) on each leg. Heart rate was recorded every minute throughout the exercise session and peak HR (PkHR) and minutes above THR were calculated and recorded. Rating of perceived exertion (RPE; Borg's modified 10 point scale; Robertson, 2004) was estimated throughout the session by asking participants to respond to the following question, "Using the following scale and verbal anchors; overall, how hard are you working right now?" RPE was recorded every five minutes. After the session, participants rested for 15 min and a 15 min post exercise recovery HR (RecHR) and post exercise session RPE (SeRPE) were recorded. SeRPE was used to provide an estimate of the global difficulty of the exercise session and was estimated by asking participants to view Borg's scale and respond to the question, "How was your workout?" (Foster, 1998; Foster, Daines, Hector, Snyder, & Welsh, 1996).

Instruments. The Wii Punchout video game provides two gaming modes. The single player (solo) mode engages the game player in direct competition against the video game. In this mode, the player competes against a series of video-game generated and controlled opponents which progressively increase in difficulty. The paired mode engages two players who compete directly against one another in a simulated boxing match. Matches consist of three rounds (unless there is a knockout) after which a winner is declared and a new match is begun.

The SW pedometers used in this study were sealed microprocessor-controlled step counters. The StepWatch Analysis Software programs the SW monitor prior to deployment, and downloads data directly to the computer for viewing. Instrument sensitivity is optimized for each subject's gait characteristics by programming the subject's height and answering questions that describe the subject's gait. Data was collected in one minute time intervals.

The Profile of Mood States (POMS) (McNair, Lorr, Dropplemann, 1971) was used to assess mood change from pre- to post-activity within each experimental session. The POMS is comprised of 65 adjectives formatted on a 5-point scale to measure six mood or affective states (tension, depression, anger, vigor, fatigue, and confusion) and a total mood disturbance score (TMD). The POMS has been shown to be suitable for individuals age 18 years to adulthood and internal consistency reliability has ranged from .84 to .95 (McNair et al., 1971). Test-retest reliability has ranged from .65 to .74. The immediate "how do you feel right now" response set was used for this study. In accordance with recommendations on calculating a single overall mood (TMD) score (McNair et al., 1971), the total for the individual's positive mood score (vigor) was subtracted from the total of an individual's negative mood states (tension, depression, anger, fatigue, and confusion) and a constant of 100 was then added to this value to create a TMD score. Upon entering the lab and after being fitted with a heart rate monitor and pedometers, participants sat quietly for 10 minutes after which they completed the pre-session POMS. At five-minutes post-session, participants completed the POMS for a second time (post 1). At 15 minutes post session (10 minutes after completing the first post-session POMS), participants completed the POMS for a second post-session (post 2) measure of overall mood. Temporal patterning of mood change was assessed at five and 10-minutes post session because previous research has shown affective states are either more positive or less negative in the time period shortly after bouts of aerobic exercise (Petruzzello & Landers, 1994; Petruzzello, Landers, Hatfield, Kubitz, & Salazar, 1991; Petruzzello & Tate, 1997; Yeung, 1996).

Statistical Analysis. Analyses were conducted using SPSS 17.0 for Windows (SPSS Inc., Chicago, IL). A repeated measures mixed model ANOVA with social interaction (alone versus paired) as the within subjects variable, and experience level as the between subjects variable was applied to mean HR, RPE, PkHR, minutes above THR, RecHR, SeRPE, and total steps. Bonferroni post hoc tests were applied where appropriate. A paired t-test was applied to baseline resting HR data to ensure that resting HR was similar between experience groups. All differences were considered significant at p [less than or equal to] 0.05 level. A 3-way, mixed-design ANOVA was used to examine mood change from pre-session mood to post-session mood, across conditions. Experience level (experienced, inexperienced) served as the between-subjects factor, while social condition (alone, paired) and time (pre-session, post-session) served as within-subjects factors. In this analysis, TMD change scores (difference between pre-session TMD and 5-min post-session TMD score, as well as difference between pre-session TMD and 15-min post-session TMD score) were used as dependent variables.

Results

Physiological Measures. No difference in resting HR at baseline was observed between experience groups (inexperienced: 73.3 [+ or -] 8 bpm and experienced: 71.4 [+ or -] 8 bpm). Mean HR and RPE were 103.2 [+ or -] 21 bpm vs. 94.7 [+ or -] 21 bpm (p = .06) and 2.8 [+ or -] 1.2 vs. 2.4 [+ or -] 1.2 (p =. 14) in the inexperienced and experienced groups respectively. Mean HR and mean RPE separated by condition and group are reported in Table 1. No differences between experience groups were observed for peak HR, recovery HR, or session RPE (Table 2). Peak HR was significantly higher in paired condition versus the solo condition (solo: 111.5 [+ or -] 21 bpm versus paired: 118.6 [+ or -] 21 p = 0.03). No difference for social condition was observed for any other variable. Less than 1% of game play exceeded ACSM recommended target HR. Steps in the inexperienced groups were 90 [+ or -] 173 steps versus 59 [+ or -] 49 steps in the experienced condition. Steps in the solo condition were 62 [+ or -] 85 steps compared to 87 [+ or -] 168 steps in the paired condition. No significant differences in steps were observed for either experience level or social condition.

Mood A three-way ANOVA (experience level x social condition x time) was conducted to determine the influence of users' experience level and social condition on the two measures of mood change (pre-post 1 TMD change and pre-post-2 TMD change). Overall ANOVA results yielded a nonsignificant 3-way interaction (F(2,46) =1.23, p>.05). Change in mood scores representing the experience level by time interaction were (TMD change) 3.5 [+ or -] 12.56 at 5-min post session and 4.5 [+ or -] 13.07 at 15-min post session in the inexperienced group vs. -.60 [+ or -] 11.16 at 5-min post session and 3.75 [+ or -] 9.66 at 15 min post-session in the experienced group (p=.06). Table 3 presents mean POMS TMD change means and standard deviations across experience level and social condition.

Discussion

The purpose of this study was to determine the ability of the Wii Punchout boxing game to promote self-selected intensities sufficient to meet ACSM exercise guidelines and to examine the influence of 1) experience level and 2) social condition on self-selected exercise intensity and mood changes. The current IVG provided only a minimal physiological stimulus which was not sufficient to meet ACSM exercise guidelines (<1% of game play exceeded ACSM recommended target HR). The observed HR (inexperienced: 103.2 [+ or -] 21 bpm and experienced: 94.7 [+ or -] 21 bpm) during Wii punchout was lower than to the HR observed during Wii sports boxing (111 [+ or -] 13.0bpm) (Lee & Pitchford, 2009), (121 [+ or -] 12bpm) (Barkley & Penko, 2009) or (134 [+ or -] 21bpm) (Welch et al., 2009). The observed HR was also lower than previously reported values during other IVG modes. Studies have reported mean HR during DDR play ranging from 114 [+ or -] 18 bpm to 137 [+ or -] 22 bpm (Unnithan et al., Kraft et al., 2011; Tan et al., 2002; Sasser et al., 2009). Additionally, Kraft et al. (2011) reported HR of 144 [+ or -] 22 bpm during IVG bicycling exercise. The lack of physiological stimulus during Wii Punchout may be the result of limited total body movement demands, as evidenced by the lack of steps taken during game play. While step count results were nonsignificant, their inclusion in this design was important as no research we are aware of has examined step counts during IVG activity and the resultant utility of IVGs in meeting daily step-goal recommendations (US Department of Health and Human Services, 2008; Centers for Disease Control, 2010; Hatano, 1997). These results support the notion that involving more muscle mass (.lower body or whole body versus upper body) leads to greater exercise stimulus (Graves et al., 2008; Ridley & Olds, 2001) and is a critical consideration if IVGs are to be considered a viable exercise option. Future research may consider assessing overall body energy expenditure during IVG participation by use of accelerometers. The current results also suggest that continuous IVG modes (e.g. Game bike) may provide more stimulus to provide greater physiological and affective benefits.

A trend indicating higher mean HR (inexperienced: 103.2 [+ or -] 21 bpm and experienced: 94.7 [+ or -] 21 bpm, p = .06) was observed in inexperienced players. This trend was supported by a similar pattern in reported RPE (inexperienced: 2.8 [+ or -] 1.2 and experienced: 2.4 [+ or -] 1.2, p = 0.14). While not statistically significant, this difference (8.5 bpm) may constitute practical significance especially given the minimal exercise stimulus provided by the game. The mean increase in HR from pre-exercise (peak HR - HR immediately prior to game play) was 29.6 bpm in the inexperienced group and 23.5 bpm in the experienced group. As such, 8.5 bpm represents a substantial proportion of the increase in HR and comprises a 26% greater increase in HR in the inexperienced group. Thus, experience level may influence the physical demands of IVGs and this relationship warrants further investigation. Additionally, potential exercise benefits may rely on technological advances to a point at which IVGs can be individually adjusted to meet one's skill, experience, and fitness level, as would be the case with traditional exercise equipment which allows aspects such as grade, speed, and resistance to be modified by the user.

The presence of a peer has been shown to be reinforcing and to increase motivation during IVG bike exercise in adolescents, in that participants biked a greater distance on the IVG bike in the presence of a peer than when alone (Salvy et al., 2009). Social condition did not influence mean HR or RPE in the current study. Lack of observed differences may have resulted from the small scale of the exercise stimulus provided by the current game under either condition. Additionally, a significantly higher peak HR (Table 2) was observed in the paired condition which may correspond with the previous findings and indicate that this variable warrants further study.

Unlike previous research examining IVGs and affective benefits, (Legrand et al., 2011; Plante et al., 2003a; Russell et al., 2010) current results showed no evidence of mood benefits from this interactive boxing game. Moreover, neither experience level nor social condition was a statistically significant factor. A trend in the mood analysis suggested a tendency for experienced participants to have more improved moods at 5 min post-session, compared to inexperienced participants, but not at 15 min post-session. This trend is consistent with the HR and RPE trends, in which inexperienced participants were observed to have slightly higher HR and RPE values than experienced participants. Thus, the additional practice at the IVG for the experienced group may have resulted in less extraneous movements during their 30 minute session, combined with a greater relative skill level at the game compared to the inexperienced group. The end result, related to mood, may have been that the 30 minute session may have seemed more like 'play' to experienced participants and more like 'work' to inexperienced participants. This conclusion is tenuous because a direct measure of enjoyment during the activity was not included in the current design.

It should be noted that the lack of significant mood changes may have also been directly related to lack of significant overall physiological stimulus from the current game. Previous IVG research indicates minimal intensity thresholds appear necessary to facilitate affective benefits. For example, Plante et al. (2003a) found mood was enhanced from a virtual reality bicycle game in which participants exercised at a moderate-intensity (60-70% of MHR). More recently, Russell et al (2010) showed that exergames displayed similar acute psychological benefits to traditional exercise at self-selected intensities. Specifically, mean HR for 30 min of activity corresponded to 144 bpm (Gamebike) and 119 bpm (Dance Dance Revolution). Recently, in-task and pre-post exercise affective changes in IVG exercise (Wii Fit jogging and TacX 1-magic Fortius) were examined and significant pre-post exercise mood improvements were found in both self-selected and externally-imposed IVG exercise (Legrand et al., 2011), with the highest ratings of pleasure reported in the self-selected IVG exercise. Of note is that while Legrand et al. (2011) examined affective responses between an imposed vs. self-selected IVG environment, exercise was adjusted during sessions to maintain exercise intensities to 60-70% of max HR, as in other designs (Plante et al., 2003a; Russell et al., 2010). Since the HR values observed in the present study were lower than in previous studies, it appears that minimal physiological intensity thresholds may be necessary to achieve acute affective benefits from IVGs.

Berger & Motl (2001) noted that mood benefits from physical activity are not automatic. In establishing a taxonomy for exercise-mediated psychological benefits, Berger and Owen (1992) indicated a key requirement for mood alteration through exercise is enjoyment. Since no direct measure of activity enjoyment was used in this study, future research may incorporate a direct measure of participants' perceptions of how enjoyable the IVG is perceived during the activity. Also included within this taxonomy are mode and training requirements associated with the exercise-mood relationship. Mode requirements include 1) abdominal, rhythmical breathing, 2) absence of interpersonal competition, and 3) repetitive and rhythmical movements (Berger & Motl, 2001). Training requirements within this taxonomy include 1) a moderate intensity and 2) a minimal duration of 20-30 minutes (Berger & Owen, 1992). Upon examination of the current IVG, certain taxonomy requirements may have been absent. Specifically, due to the game's intermittent nature, it lacked a repetitive and rhythmic aerobic-like mode requirement. In addition, the current IVG did not meet a moderate intensity training requirement, as was observed from HR in both experience groups. Until IVG technology allows users to individualize game play based on their skill, experience and current fitness level, practitioners may need to carefully consider which applications may best yield physiological and psychological benefits.

References

American College of Sports Medicine (2006). ACSM's Guidelines for Exercise Testing and Prescription. Philadelphia, PA: Lippincott Williams & Wilkins.

Barkley, J.E., & Penko, A. (2009). Physiologic responses, perceived exertion, and hedonics of playing a physical interactive video game relative to a sedentary alternative and treadmill walking in adults. Journal of Exercise Physiology, 12, 12-22.

Berger B.G., & Motl R.W. (2001). Physical activity and quality of life. In: Singer R.N., Hausenblas H.A. &, Janelle, C.M. eds. Handbook of sport psychology. (2nd ed.) New York: John Wiley and Sons. 636-671.

Berger B,. & Owen, D. (1992). Preliminary analysis of a causal relationship between swimming and stress reduction: Intense exercise may negate the effects. International Journal of Sport Psychology, 23, 70-85.

Berger B.G., Pargman, D., & Weinberg R.S. (2002). Foundations of Exercise Psychology. Morgantown, WV: Fitness Information Technology.

Blair S.N., & Connelly, J.C. (1996). How much physical activity should we do? The case for moderate amounts and intensities of physical activity. Research Quarterly for Exercise & Sport, 67, 193-205.

Carels R.A., Berger B., & Darby L. (2006). The association between mood states and physical activity in postmenopausal, obese, sedentary women. Journal of Aging and Physical Activity, 14, 12-28.

Center for Disease Control and Prevention. Physical activity. Retrieved August, 2010 from: www.cdc.gov/physicalactivity/index.html

Chin A Paw, M.J., Jacobs, W.M., Vaessen, E.R, Titze, S., & Van Mechelen, W. (2008). The motivation of children to play and active video game. Journal of Science & Medicine in Sport, 11, 163-166.

De Bourdeaundhuij, I., Philippaerts, R., Crombez, G., Matton, L., Wijndaele, K., Balduck, A.L., & Lefevre, J. (2005). Stages of change for physical activity in a community sample of adolescents. Health Education Research, 20, 357-366.

Duncan, S.C., Duncan, T.E., & Strycker, L.A. (2005). Sources and types of social support in youth physical activity. Health Psychology, 24, 3-10.

Foster, C. (1998). Monitoring training in athletes with reference to overtraining syndrome. Medicine and Science in Sports and Exercise, 30, 1164-1168.

Foster, C., Daines, E., Hector, L., Snyder, A.C., & Welsh, R. (1996). Athletic performance in relation to training load. Wisconsin Medical Journal, 95, 370-374.

Foster, R., Lanningham-Foster, L., Manohar, C., McCrady, S., Nysse, L., Kaufman, K., Padgett, D., & Levine, J. (2005). Precision and accuracy of an ankle-worn accelerometer-based pedometer in step counting and energy expenditure. Preventive Medicine. 41, 778-783.

Gortmaker, S., Must, A., Sobol, A., Peterson, K., Colditz, G., & Dietz, W. (1996). Television viewing as a cause of increasing obesity among children in the United State, 1986-1990. Archives of Pediatric and Adolescent Medicine, 150, 356-362.

Graves, L.E., Ridgers, N.D., & Stratton, G. (2008). The contribution of upper limb and total body movement to adolescents' energy expenditure whilst playing Nintendo Wii. European Journal of Applied Physiology, 104, 617-623.

Graves, L., Ridgers, N.D., Williams, K., Stratton, G., Atkinson, G., & Cable, N.T. (2010). The physiological cost and enjoyment of Wii Fit in adolescents, young adults, and older adults. Journal of Physical Activity & Health, 7, 393-401.

Graves, L., Stratton G., Ridgers, N.D., & Cable, N.T. (2007). Energy expenditure in adolescents playing new generation computer games. British Medical Journal, 335, 1282-1284.

Hatano, Y. (1997). Prevalence and use of the pedometer. Research Journal in Walking. 1, 45-54.

Janz, K., & Mahoney, L. (1997). Maturation, gender, and video game playing are related to physical activity intensity in adolescents: the Muscatine study. Pediatric Exercise Science, 9, 353-363.

Kahneman, D. (1999). Objective happiness. In: Kahneman, D., Diener, E., & Schwartz, N.eds. Well-being: the foundation of hedonic psychology. (pp. 3-25). New York: Russell Sage Foundation.

Karabulut, M., Crouter, S, & Bassett, D. (2005). Comparison of two waist-mounted and two ankle-mounted electronic pedometers. European Journal of Applied Physiology, 95, 335343.

Karvonen, M.J., Kentala, K., & Mustala, O. (1957). The effects of training on heart rate: a longitudinal study. Annales Medicinae Experimentalis Et Biologiae Fenniae, 35, 307-315.

Kraft, J.A., Russell, W.D., Bowman, T., Selsor, C., & Foster, G. (2011). Heart rate and perceived exertion during self-selected intensities for exergaming compared to traditional exercise in college-age participants. Journal of Strength and Conditioning Research, 25, 1736-1742.

Lanningham-Foster L., Jensen, T.B., Foster, R.C., Redmond, A.B., Walker, B.A., Heinz, D., & Levine JA. (2006). Energy expenditure of sedentary screen time compared with active screen time for children. Pediatrics, 118, 1831-1835.

Lee, M., & Pitchford, E.A. (2009). Energy Expenditure of and interactive video game: a preliminary study. Medicine and Science in Sports & Exercise, 41, S551 [abstract].

Legrand, F.D., Philippe, M.J., Bertucci, W.M., Soudain-Pineau, M.A, & Marcel, J. (2011). Interactive-virtual reality (IVR) exercise: An examination of in-task and pre-to-post exercise affective changes. Journal of Applied Sport Psychology, 23, 65-75.

Maddison, R., Mhurchu, C.N., Jull, A., Jiang. Y., Prapavessis, H., & Rodgers, A. (2007). Energy expended playing video console games: An opportunity to increase children's physical activity? Pediatric Exercise Science, 19, 334-343.

McNair, D.M., Lorr, M., & Dropplemann, L.F. (1971). Profile of Mood States manual. Educational and Industrial Testing Service, San Diego, CA.

Mellecker, R.R., & McManus, A.M. (2008). Energy expenditure and cardiovascular responses to seated and active gaming. Archives of Pediatric & Adolescent Medicine, 162, 886-891.

Miyachi, M.K., Yammamoto, K., Ohkawara, K., & Tanaka, S. (2010). METs in adults while playing active video games: A metabolic chamber study. Medicine and Science in Sports & Exercise, 42, 1149-1153.

Petruzzello, S.J., & Landers, D.M. (1994). State anxiety reduction and exercise: Does hemispheric activation reflect such changes? Medicine and Science in Sport and Exercise, 26, 1028-1035.

Petruzzello, S.J., Landers, D.M., Hatfield, B.D., Kubitz, K.A., & Salazar, W. (1991). A meta-analysis on the anxiety-reducing effects of acute and chronic exercise. Sports Medicine, 11, 143-182.

Petruzzello, S.J., & Tate, A.K., (1997). Brain activation, affect, and aerobic exercise: An examination of both state-independent and state-dependent relationships. Psychophysiology, 34, 527-533.

Plante, T.G., Aldridge, A., Bogden, R., & Hanelin, C. (2003). Might virtual reality promote the mood benefits of exercise? Computers in Human Behavior, 19, 495-509.

Plante T.G., Aldridge, A., Su, D., Bogden, R., Belo, M., & Kahn, K. (2003). Does virtual reality enhance the management of stress when paired with exercise? An exploratory study. International Journal of Stress Management, 10, 203-216.

Pollock, M.L., Gaesser, G.A., Butcher, J.D., Despres, J.R, Dishman, R.K., Franklin, B.A., & Garber, C.E. (1998). ACSM Position Stand: The recommended quantity and quality of exercise for developing and maintaining cardiorespiratory and muscular fitness, and flexibility in health adults. Medicine and Science in Sports & Exercise, 30, 975-991

Ridley, K., & Olds, T. (2001). Video center games: energy costs and children's behaviors. Pediatric Exercise Science, 13, 413-421.

Rittenhouse, M., Salvy, S.J., & Barkley, J.E. (2011). The effect of peer influence on the amount of physical activity performed in 8-to 12-year old boys. Pediatric Exercise Science, 23, 49-60.

Robertson, R.J. (2004). Perceived exertion for practitioners: rating effort with the omni picture system. Champaign, IL: Human Kinetics.

Russell, W.D., & Newton, M. (2008). Short-term psychological effects of interactive video game technology exercise on mood and attention. Educational Technology & Society, 11, 294-308.

Russell, W.D., Kraft, J.A., Selsor, C., Foster, G., & Bowman, T. (2010). Comparison of Acute Psychological Effects from "Exergames" vs. Traditional Exercise. Athletic Insight, 12, online publication.

Salvy, S.J., Roemmich, J.N., Bowker, J.C., Romero, N.D., Stadler, P.J., & Epstein, L.H. (2009). Effect of peers and friends on youth physical activity and motivation to be physically active. Journal of Pediatric Psychology, 34, 217-225.

Sasser, K., Eller, S., Dragoo, K., Ulbright, J., Robinson, T., & Silvers, W.M. (2009). Heart rate responses with various modes of video game interaction. Medicine and Science in Sports & Exercise, 41, S552-S553 [Abstract].

Sell, K., Lillie, T., & Taylor, J. (2008). Energy expenditure during physically interactive video game playing in male college students with different playing experiences. Journal of American College Health, 56, 505-511.

Straker, L., & Abbott, R. (2007). Effect of screen-based media on energy expenditure and heart rate in 9- to -12 year old children. Pediatric Exercise Science, 19, 459-471.

Tan, B., Aziz, A.R., Chua, K., & Teh, K.C. (2002). Aerobic demands of the dance simulation game. International Journal of Sports Medicine, 23, 125-129.

Thomas, S., Reading, J., & Shephard, R.J. (1992). Revision of the Physical Activity Readiness Questionnaire (PAR-Q). Canadian Journal of Sport Sciences, 17, 338-345.

Trout, J, & Christie, B. (2007). Interactive video games in physical education. Journal of Physical Education, Recreation, and Dance, 78, 29-45.

United States Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans: Be Active, Healthy, and Happy. Retrieved August, 2010 from: www.health/gov/paguidelines

Unnithan, V.B., Houser, W., & Fernhall, B. (2006). Evaluation of the energy cost of playing a dance simulation video game in overweight and non-overweight children and adolescents. International Journal of Sports Medicine, 27, 804-809.

Welch, J.M., White, J., & Nixon, N.A. (2009). Physiological cost of an active video game versus other exercise modes in university students. Medicine and Science in Sports and Exercise, 41, S609-S551, [Abstract].

Williams, D.M., Dunsinger, S., Ciccolo, J.T., Lewis, B.A., Albrecht, A.E., & Marcus, B.H. (2008). Acute affective response to a moderate-intensity exercise stimulus predicts physical activity participation 6 and 12 months later. Psychology of Sport & Exercise, 9, 231-245.

Worley, J.R., Rogers, S.N., Kraemer, R.R. (2011). Metabolic responses to Wii Fit[TM] video games at different game levels. Journal of Strength and Conditioning Research, 25, 689-693.

Yeung, R.R. (1996). The acute effects of exercise on mood state. Journal of Psychosomatic Research, 40, 123-141.

William D. Russell and Justin A. Kraft

Missouri Western State University

Randall J. Bergman

Lenoir-Rhyne University

Justin Spellman and Nicolas W. Barnes

Missouri Western State University

Address correspondence to: William D. Russell, PhD. Missouri Western State University, 4525 Downs Drive, Dept. of Health, Physical Education, and Recreation, Looney Complex 214, St. Joseph, MO 64507. Email: [email protected].

Table 1.

Mean HR and RPE by social condition and experience group.

                         Inexperienced         Experienced

Mean HR Solo (bpm)     101.4 [+ or ] 18.0   93.4 [+ or ] 15.3
Mean HR Paired (bpm)   105.1 [+ or ] 18.3   96.2 [+ or ] 15.2
Mean RIDE Solo           2.9 [+ or ] 1.1     2.5 [+ or ] 0.7
Mean RPE Paired          2.7 [+ or ] 1.2     2.4 [+ or ] 0.9

Values are means and standard deviations.

Table 2.

Peak HR, Recovery HR (RecHR), and Session RPE by condition and
experience group.

Social Condition       Peak HR (bpm)          RecHR (bpm)

Solo               111.5 [+ or -] 21.5     74.9 [+ or -] 9.7
Paired             118.6 [+ or -] 24.6 *   76.1 [+ or -] 15.8
Experience Group
inexperienced      118.5 [+ or -] 28.6     75.3 [+ or -] 15.9
Experienced        111.5 [+ or -] 28.6     75.7 [+ or -] 15.9

Social Condition      Session RPE

Solo               2.83 [+ or -] 1.3
Paired              2.6 [+ or -] 1.1
Experience Group
inexperienced       2.8 [+ or -] 1.4
Experienced         2.5 [+ or -] 1.4

Values are means and standard deviations.

* indicates peak HR significantly higher in paired condition than
solo condition (p < 0.05).

Table 3.

Mean POMS TMD change scores by social condition and experience group.

                    Pre-Post 1            Pre-Post 2
                       Solo                  Solo

Inexperienced   2.17 [+ or -] 2.17    1.92 [+ or -] 1.98
Experienced     -.21 [+ or -] 2.28    4.67 [+ or -] 1.98

                    Pre-Post 1            Pre-Post 2
                      Paired                Paired

Inexperienced    4.83 [+ or -] 2.57   6.67 [+ or -] 2.70
Experienced     -1.00 [+ or -] 2.57   2.83 [+ or -] 2.69

Values are means and standard deviations.

* Negative scores indicate mood improvement as indicated by POMS TMD
change scores.