AUTHORS: Tom
Baranowski, PhD,a Dina
Abdelsamad, BA,a Janice
Baranowski, MPH, RD,a Teresia
Margareta O’Connor,
MD, MPH,a Debbe
Thompson, PhD, RD,a Anthony
Barnett, PhD,b Ester
Cerin, PhD,b and
Tzu-An Chen, PhDa aChildren’s Nutrition Research Center, Department of
Pediatrics,Baylor College of Medicine, Houston, Texas; and bInstitute of Human Performance,
University of Hong Kong, Hong Kong SAR
Although young childrenget reasonable amounts of physical
activity (PA), levelsof PA decline throughout childhood,1 dropping well below recommendedlevels.2–4 The risk of being an obese adult from being obese as a child increases
enormously at 10 years ofage,5 suggesting that 10 years of age isa critical period for
increasing PA toprevent child and adult obesity.
Laboratory studies have demonstrated that the right person can
engage inmoderate (3+ metabolic equivalents),6,7 and even vigorous (6+ metabolic equivalents),8 levels of PA with active videogames. Among
studies under morenaturalistic circumstances, 2 studiesshowed some increase in
PA from active video games,9,10 one showed a small change in adiposity, but not activity,11 and a fourth showed no changes.12 An experimental design with randomization is
needed, addressing the duration of how long increased PA was sustained with the
use of objective measures.13
The present randomized trial assessed whether 9- to 12-year-old
childrenwould increase their level of PA,measuredwith accelerometry, with the
acquisition of a new (to them)Wii console and a choice of 2 (of 5) active video
games with all necessary peripherals, compared with children receiving a new Wii
console and choice of 2 (out of 5) inactive video games and all the necessary
peripherals. The hypothesis was that children receiving the active video games
would increase their levels of PA.
METHODS
Participants The
inclusionary criteria were an age of 9 to 12 years; BMI between the 50th and 99th
percentiles (at risk for adult obesity); ability of the child and family to speak,
understand, read, and write English (because of the limits of the available
games and the parental reporting of some data); permission by the parent
allowing the child to play the provided video game (active or inactive); and
the presence of a television in the household to which the Wii console could be
attached. Children were excluded if they had a medical problem (including
epileptic seizures) that would prevent them from being physically active or
playing video games; if they had a family history of epileptic seizures
(because of the risk of seizures from video screens)14; if they already had a Wii game console in
the home (and, thereby, not being “new” to
the child); if they did not provide at least 5 of 7 complete days of accelerometry
data at baseline (a “break-in
period” because
of concerns about difficulties
in obtaining 5 weeks of accelerometry data over the course of the study); and if
they lived beyond 15 miles from the Children’s Nutrition Research Center (CNRC) (because of concerns about getting
the family to data collections and delivering the Wii consoles on several
occasions).
Design
Children were randomly assigned, after baseline assessment, to
treatment or control groups. Random assignment was conducted by using a random number
generator (generated by the statistician) and randomly allocating sequential
positions in the enrollment book to treatment or control conditions.
Children were entered sequentially as they met inclusionary
criteria. The project manager assigned participants to sequential positions and
informed staff of conditions. All children were provided Wii game consoles.
Children in the treatment group were offered a selection of one active, and the
control group of one inactive, video game at the beginning of week 1 and another
at beginning of week 7. PA was monitored by using accelerometry at baseline,
and weeks 1, 6, 7, and 12. Height, weight, and self-reportedmeasureswere obtained
at baseline, between weeks 6 and 7 (midassessment), and after week 12 (postassessment).
Intervention
and Control Conditions
Each participating child was provided a Wii console.
Self-determination theory posits that providing choice enhances intrinsic
motivation to perform a behavior. 15
The treatment group was given a choice of 1
active video game with all necessary peripherals to
play that game at the beginning of week 1 and of another at the beginning of
week 7. To remain true to naturalistic circumstances, no prescription was
provided on when or how to play the video games, and no prohibitions were
provided against purchasing and/or using other video games. The control group was given a
choice of 1 inactive video game with all necessary
peripherals to play that game at the beginning of week 1 and of another at the
beginning of week 7. All but one of the video games offered were rated E
(Everyone) by the Entertainment Software Rating Board (ie, content suitable for
ages 6 and older). Dance Dance Revolutionwas rated E10+, and parents had to agree
that it was acceptable to offer that game to their child. The Wii console was
chosen because it was the primary platform for most active video games at the
time of the start of the study, and it automatically electronically stored in
the console the name and duration of the games played each day. The selection of the video games was based on
game sales data of those most purchased for the Wii console at the time of the
start of the study. All possible Wii video games were tested by staff and rated
as either active or inactive. The 5 selected active games were considered the most active E-rated ones available at the time
of the study. The 5 inactive games were the most popular at the time of the
study.
Recruitment
Participants were recruited (in 2010) from multiple sources. The
professional recruiter of the CNRC identified candidates in the CNRC recruitment database (.9800 names in 2010) who met age criteria
and called the parent to preliminarily orally assess inclusionary criteria and
interest. The Baylor College of Medicine Public Relations office distributed press releases soliciting participants to local
media and via the CNRC “Nutrition
and Your Child” quarterly
newsletter. Recruitment fliers
with tear-away tabs and call numbers were posted around the Texas Medical Center
and Rice University campuses, the Harris County Hospital District Pediatric Clinic,
and local public libraries and museums.
Prospective parents were sent a cover letter, parental consent
form, family demographic form, and information on TV inputs and images to confirm eligibility. The research protocol was approved by the Baylor
College of Medicine Institutional Review Board. All participants provided
parent-signed consent and child-signed assent. Children were allowed to keep
the Wii console, 2 selected video games, and enabling peripherals, if they
completed all data collection to acceptable minimum standards (eg, 5 days of
accelerometry at each time interval).
Measures
Parents completed the demographics (child gender, child age,
child ethnic group, highest educational attainment in the household, parent
perception of neighborhood safety) at baseline with commonly used questions
from our previous studies.
Neighborhood safety was reported by the parent at baseline by a
validated 12-item questionnaire (4 response categories from "strongly disagree” to “strongly agree”) that assessed parentperceived neighborhood safety in regard to
traffic,
lighting, crime, and access to parks.16
The Cronbacha
in the present sample was 0.82.
Children’s
height was measured by using the Perspective Enterprise’s stadiometer PE-AIM-101 (Portage, MI) with
shoes removed according to standard protocol.17
Two assessments were recorded to the
nearest 0.1 cm and averaged. Children’s weight was measured using the SECA a 882 digital scale (Hamburg, Germany) with
shoes, outer wear, and objects from pockets removed, with feet placed in the
center of the scale and eyes looking straight ahead, according to standard
protocol. 17 The
scale was calibrated by using standard weights any time the scale was moved.
Weight was measured once to minimize burden because 2 measures rarely varied.
All data collectors were trained to minimum acceptable standards.
PA was assessed with the use of Actigraph GT33 accelerometers (Pensacola, FL). The
accelerometer was placed on an elastic belt; the beltwas fit tobesnug but comfortable for the child; and the accelerometer
was placed above the right hip. The child was instructed to wear the
accelerometer for 7 consecutive days, and remove it only when going in the
water (eg, bathe, swim) or when playing contact sports. A log was provided, and
participants were instructed to record when they slept or removed the
accelerometer. The monitors were fully charged before they were given to participants.
If ,7
days were provided, the child was asked to rewear the monitor to complete the
number of days. (High compliance was obtained because childrenwanted to keep
the Wii game equipment.) Actigraphs were programmed to start at midnight at the
end of the day on which it was provided. The epoch was set to 10 seconds.
Values above 17 000 cpm were considered errors and removed, as suggested by the
manufacturer. Intervals of 60 continuous minutes or more of recorded zeros were
taken as periods of not wearing the monitor. The minimal acceptable period at
each data collection time interval was 5 days of 600 minutes per day. The
Evenson cut points18,19 were
used to define
levels of moderate or vigorous, light and sedentary behaviors. After week 12,
the parent returned the Wii console. Staff then transcribed the full file, including machine-recorded date, name, and duration of each game
recorded in the console. Children and parents were asked to keep a diary of
game play on the Wii console for each week the child wore an activity monitor. The
diary included what game was played at what time for each day, and who played
it.
Interviews
Children were interviewed at the midand postassessments by using
qualitative methods. The interview was designed to take 15 minutes and assessed
reasons the child selected the games s/he did, what the child liked and did not
like, and with whom the games were played. The interviewers were trained in
open-ended interview procedures. The responses were independently double coded
by using thematic analysis procedures.20
Differences were reconciled by consensus among
the investigators.
Power
Power analysis fora repeated-measures analysis of covariance to
test whether PA varied by group by time showed that, with the final sample size of 78, 2 groups (intervention, control), 5
repeated measures, a correlation over time of 0.66 and an a of 0.05, there was 80% power to detect a
moderate effect size (Cohen’s d =
0.21). To test all the post hoc contrasts of interest, independent t tests were used with an a of 0.01 per pair. Therefore, there was 80%
power to detect large effects (Cohen’s d = 0.79).
Data Analyses
Linear mixed models were used to investigate differences in PA
between groups (intervention, control), time (baseline, week 1, week 6, week 7,
and week 12), and group by time. Four separate analyses in which either minutes
of sedentary, light, ormoderate to vigorous PA per day and counts per minute
were treated as the dependent variables were run. To test a differential intervention
effect on children’s
PA by parents’ perceived
neighborhood safety, parents’ socio economic status, number of video games available in the home,
or child BMI z score,
all analyses included a group by time by covariate interaction term and all the
imbedded 2-way interaction terms. All the analyses were conducted by using the
Proc Mixed procedure21 in
Statistical Analysis Systems (version 9.2, 2009, SAS Institute Inc., Cary, NC).
For nonnormally distributed data (ie, moderate to vigorous PA), generalized
linear mixed models with gamma distribution and a log link function was
performed by using PROC GLIMMIX in SAS. a was set at 0.05.
RESULTS
The study began with 84 participants completing baseline
assessment and being randomly assigned to the study. Six participants were
dropped from the control group for the reasons shown in Fig 1. Of the 78
remaining in the analyses, 41% reported being African American, 14%white,
13%Hispanic, 4% other, and 28% mixed ethnic heritage. Boys composed 51% of the
sample. The average age was 11.361.8 years, and average BMI percentile was 81.7%. Sixty-four
percent of children reported that the Wii console was kept in the living room,
and 19% reported that it was kept in the child’s bedroom; 49% had a Play Station 2, but only 15% had a Play
Station 3; 10% reported having an Xbox and 17% had an Xbox 360; and 58%
reported having a TV and 36% a video game console in their bedroom. The average
minutes of moderate to vigorous and light PA, sedentary behavior, and counts per
minute for the treatment and control groups appear . There was no
evidence of treatment-control group, or treatment control group by time
differences in any of these variables over all, or at any time. There was a
significant timerelated difference in sedentary behavior in week 6,
only. There was no evidence of moderation of these effects by neighborhood safety,
child BMI z score, highest educational attainment in
the home, family income, number of video games, or number of active video games
in the home.
The interviews, diaries, and console records all indicated
substantial active video game use. Although it is clear that there was
substantial crossover in types of games used, the time spent playing games
opposite to that assigned was small in comparison with
the time spent playing the type of game assigned.
Child responses to the interview questions were diverse, but
indicated that children in both groups enjoyed the active video games, and this
was comparable after weeks 6 and 12. What treatment group children “liked best”
usually referred to specific PA in the game they selected, eg, boxing or bowling, but also
included “didn’t have to go outside” and “doing activities that you wouldn’t normally be able to do.”
When asked what they did not like, some reported
difficulties
with specific
games, eg, “computer
competitor would scream things,” “I couldn’t
understand a character,” but
there was also “didn’t have anyone to play with” and “didn’t
like difficulty
level.” What
control group children liked best included “beating the high score/getting points” and “challenging.” Approximately equal percentages of children in the treatment and
control groups reported playing each game with someone else (Table 4). Siblings
(79%in both groups) were the most commonly reported coplayers, followed by
parents (55%, 49%, respectively) and cousins (35%, 38%, respectively)
DISCUSSION
There was no evidence that children receiving 2 active video
games and the peripherals necessary to run them were any more active over a
12-week period than those receiving 2 inactive video games. Thus, although
children can do moderate or vigorous PA with active video games in laboratory
settings, 6,8,22 they
either did not elect to play the provided games at that level of intensity, or
compensated for the increased intensity by being less active at other times in the day. The
attempt in this study was to simulate a family receiving a new active video
game and assessing the naturalistic spontaneous activity from that acquisition.
These findings
are consistent with 1 other naturalistic study12
and suggest that simply acquiring a new
active video game does not automatically lead to increased PA, thereby
minimizing the public health value of simply having active video games
available for children to play. Providing explicit instructions to use the
active video game appears to lead to increased activity,9,11,23 which may make active video games useful as part of interventions that prescribe some minimal use.
None of the active video games had a narrative or story; wrapping an engaging
narrative around the activity in active video games may motivate more intense
and maintained PA.13
An attempt was made to match the days, games, and play duration
recorded on the Wii console file with the days and times of starting game play from the diary,
and then identifying the corresponding intervals on the accelerometers to
identify specific
game play PA. This effort was abandoned, because the console-recorded days were
not in synchrony with days in the diary; the durations on the console were at
times excessive (eg,upto24hours) suggesting that players left the console on
with the game in the console, even when not playing; and more than half the
names of the games in the diary and the console did not match for the same day and
times (when this could be established). The records, however, did reveal that
some children receiving the active video games obtained and played inactive
games, and vice versa, thereby somewhat “contaminating” the effect, but most of the game play time was consistent with
the type of game provided to the child. There was substantial social
involvement in game play in both conditions , but the Wii console log
could not differentiate game play by target child, friend(s), family member (s),
or others.
The strengths of the current research were the experimental
design with random assignment of participants to groups; restriction of the
sample to families without a Wii console to simulate acquisition of a new (to
them) active video game; the use of objective monitors of activity over
week-long intervals at 5 times in the design; and obtaining complete data on .90% of the sample. The limitations included
a modest sample size (the study was not powered to detect equivalence); there
was some cross-game contamination, but this was expected in a naturalistic study,
and was reasonably low, but we could not assess game play on consoles other
than the Wii; we were not able to assess activity during active game play; and
the study was conducted only with 9- to 12-year-olds in one city, and thereby
may not generalize to children of other ages, in other cities, or using other video
games and systems.
CONCLUSIONS
Children (9- to 12-years-old) in a naturalistic setting did not
participate in higher levels of PA after receiving a new (to them) video game
console and 2 active video games in comparison with those receiving the same
console and 2 inactive video games.
REFERENCES
1. Sallis JF. Age-related decline in physical activity: a
synthesis of human and animal studies. Med
Sci Sports Exerc. 2000;32(9): 1598–1600
2. Troiano RP, Berrigan D, Dodd KW, Mâsse LC, Tilert T, McDowell
M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc.
2008;40(1):181–188
3. Molnar BE, Gortmaker SL, Bull FC, Buka SL. Unsafe to play?
Neighborhood disorder and lack of safety predict reduced physical
activity among urban children and adolescents. Am J Health Promot.
2004;18 (5):378–386
4. Baranowski T, Thompson WO, DuRant RH, Baranowski J, Puhl J.
Observations on physical activity in physical locations: age,
gender, ethnicity, and month effects. Res Q Exerc Sport.
1993;64(2):127–133
5. Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH.
Predicting obesity in young adulthood from childhood and parental
obesity. N Engl J Med. 1997;337(13):869–873
6. Graves LE, Ridgers ND, Williams K, Stratton G, Atkinson G,
Cable NT. The physiological cost and enjoyment of Wii Fit in adolescents, young
adults, and older adults. J Phys Act Health. 2010;7(3):393–401
7. Howe CA, Freedson PS, Feldman HA, Osganian SK. Energy
expenditure and enjoyment of common children’s games in a simulated free-play environment. J Pediatr. 2010;157(6):936–942.e1–2
8. Bailey BW, McInnis K. Energy cost of exergaming: a comparison
of the energy cost of 6 forms of exergaming. Arch
Pediatr Adolesc Med. 2011;165(7):597–602
9. Madsen KA, Yen S, Wlasiuk L, Newman TB, Lustig R. Feasibility
of a dance videogame to promote weight loss among overweight children and
adolescents. Arch Pediatr Adolesc Med. 2007;161(1):105–107
10. Mhurchu CN, Maddison R, Jiang Y, Jull A, Prapavessis H,
Rodgers A. Couch potatoes to jumping beans: a pilot study of the effect of
active video games on physical activity in children. Int J Behav Nutr Phys Act.
2008; 5(8)
11. Maddison R, Foley L, Ni Mhurchu C, et al Effects of active
video games on body composition: a randomized controlled trial. Am J Clin Nutr. 2011;94(1):156–163
12. Maloney AE, Bethea TC, Kelsey KS, et al. A pilot of a video
game (DDR) to promote physical activity and decrease sedentary
screen time. Obesity
(Silver Spring). 2008; 16(9):2074–2080
13. Barnett A, Cerin E, Baranowski T. Active video games for
youth: a systematic review. J Phys
Act Health. 2011;8(5):724–737
14. Fisher RS, Harding G, Erba G, Barkley GL, Wilkins A;
Epilepsy Foundation of America Working Group. Photic- and pattern-induced seizures:
a review for the Epilepsy Foundation of America Working Group. Epilepsia. 2005;46(9):1426–1441
15. Fortier MS, Sweet S, O’Sullivan T, Williams G. A self-determination process model of physical
activity adoption in the context of
a randomized controlled trial. Psychol
Sport Exerc. 2007;8:741–757
16. Timperio A, Crawford D, Telford A, Salmon J. Perceptions
about the local neighborhood and walking and cycling among children. Prev Med.
2004;38(1):39–47
17. Lohman TG, Roche AF, Martorell R. Anthropometric Standardization Reference Manual. Champaign, IL: Human Kinetics Books; 1988
18. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of
accelerometer cut-points for predicting activity intensity in youth. Med Sci Sports Exerc.
2010;43(6):1360–1368
19. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG.
Calibration of two objective measures of physical activity for children. J Sports Sci.
2008;26(14):1557–1565
20. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol.
2006;3:77–101
21. Littell, RC, Milliken, GA, Stroup, WW, and Wolfinger, RD. SAS system for mixed models. Cary: NC: SAS Institute, Inc; 1996
22. Penko AL, Barkley JE. Motivation and physiologic responses
of playing a physically interactive video game relative to a sedentary
alternative in children. Ann Behav Med. 2010;39(2):162–169
23. Utter J, Scragg R, Schaaf D, Mhurchu CN. Relationships
between frequency of family meals, BMI and nutritional aspects of the
home food environment among New Zealand adolescents. Int J Behav Nutr Phys Act.
2008;5:50
Source :
Downloaded from pediatrics.aappublications.org at
Indonesia: AAP Sponsored on April 30, 2012
Note
:
Originally
published online February 27, 2012
Tidak ada komentar:
Posting Komentar