Content uploaded by Jiyoung An
Author content
All content in this area was uploaded by Jiyoung An on Feb 10, 2017
Content may be subject to copyright.
Pok´
emon GO May Increase Physical
Activity and Decrease Sedentary
Behaviors
Regular physical activity
contributes to the prevention of
obesity and chronic diseases
1
;
however, fewer than half of US
adults are regularly active. Video
games, computers, television,
mobile devices, and sedentary
occupations have all contributed
to the growth in sedentary
behavior and obesity. More
recently, technology-based
interventions have focused on
mobile devices to promote
physical activity.
2
About 90% of
American adults have a mobile
phone,
3
with 64% owning
a smartphone. Advantages of
technology-based interventions
include continual self-
monitoring and access, de-
creasing barriers of transportation
and time, and portability (e.g.,
smartphone interventions), and
they may be more cost-effective,
accessible, and convenient.
Gaming technology has
attempted to promote physical
activity but with limited success
regarding uptake or effective-
ness.
4
On July 6, 2016, Pok´emon
GO
5
was released. It is a mobile
application that uses a global
positioning system to allow users
to walk around or travel to catch
nearby “Pok´emon,”which are
creatures that the player captures
and trains to fight other such
creatures. The augmented reality
feature places the Pok´emon in
the real-world setting by using
the mobile device’s camera,
which makes players feel like
real-life Pok´emon Trainers. The
map in the application is based on
real-world streets and pathways,
featuring Pok´e Stops (where
one can collect items, such as the
Pok´eballs used to capture the
Pok´emon, and Pok´emon eggs)
and Gyms (where battles against
other Pok´emon Trainers and
their Pok´emon occur). The
three types of Pok´emon eggs,
2 kilometers, 5 kilometers, and
10 kilometers, are hatched by
walking the corresponding dis-
tances, and rarer Pok´emons tend
to emerge from 10-kilometer
eggs. Furthermore, nostalgia is
incorporated by featuring first-
generation Pok´emon and
a Pok´edex to track Pok´emons
captured.
A PILOT STUDY
In the absence of a formal
research evaluation of Pok´emon
GO, the University of Hawaii
institutional review board
exempted a retrospective
pre–post design study to in-
vestigate if playing Pok´emon GO
increased physical activity and
decreased sedentary behaviors.
We distributed the Survey-
Monkey link through social
media, e-mail, e-mail lists, and
Web sites requesting recipients to
further post the link on their
social networking sites. Partici-
pants provided consent, and
surveys (open from July 28, 2016,
to August 31, 2016) took about 5
to 10 minutes to complete.
We excluded 4 of 633 surveys
that only had one demographic
variable and that of one in-
dividual who noted 0 days of
playing Pok´emon GO. Of the
remaining 628, 82 (13.1%)
completed only demographics
and 60 (9.6%) individuals com-
pleted only the pre–Pok´emon GO
survey portion. These individuals
were not significantly different
from survey completers on de-
mographics and the prebehavior
variables (all P>.05) and we also
excluded these from the analy-
ses. Thus, we analyzed 486 of
633 surveys (76.8% completion
rate; 57.8% female; 59.9%
White, 28.5% Asian; mean
age = 28.6 [SD = 8.5] years;
mean body mass index [BMI] =
26.4 [SD = 6.8] kg/m
2
;playing
Pok´emon GO an average of 23.3
[SD = 10.0] days).
A revised Godin Leisure-
Time Exercise Questionnaire
assessed days per week (0–7) and
minutes per day (10-minute in-
tervals from 0 to ‡60) spent in
strenuous, moderate, and mild
physical activity before and after
beginning to play Pok´emon GO.
We defined strenuous physical
activity as an activity causing
a rapid heart rate and sweating
(e.g., soccer, vigorous swim-
ming). We defined moderate
physical activity as not exhausting
with light sweating (e.g., fast
walking, volleyball). Mild
physical activity included mini-
mal effort without sweating
(e.g., easy walking, fishing). The
Godin Leisure-Time Exercise
Questionnaire demonstrated
adequate test–retest reliability
and validity.
6
Three questions assessing
hours of daily sedentary behavior
(0 to ‡10 hours) before and after
beginning to play Pok´emon GO
addressed television, video, or
DVD watching; video game
playing; and Internet surfing and
playing online games. This
measure displayed adequate
test–retest reliability.
7
PHYSICAL ACTIVITY
AND SEDENTARY
BEHAVIOR
Playing Pok´emon GO increased
moderate to vigorous physical
activity by about 50 minutes per
week and reduced sedentary be-
havior by about 30 minutes per
day. Figure 1 presents the
pre–post physical activity and
sedentary behavior results. We
saw significant increases for all
three physical activity indicators
with the largest change in the
mild-intensity physical activity
(approximately +47 minutes per
week; P<.008), followed by
moderate physical activity (ap-
proximately +38 minutes per
week; P<.008) and strenuous
physical activity (approximately
+14 minutes per week; P<.008).
For sedentary behavior indica-
tors, TV, video, or DVD
watching (approximately –30
minutes per day; P<.008) and
Internet surfing (approximately
–12 minutes per day; P<.008)
decreased significantly, whereas
video game playing did not
change (P= .05). Note that
missing data (0%–1.5%) appeared
at random and we deleted it
ABOUT THE AUTHORS
All of the authors are with the Office of Public Health Studies, University of Hawaii at Manoa.
Correspondence should be sent to Claudio R. Nigg, PhD, FSBM, 1960 East-West Road,
Honolulu, HI 96822 (e-mail: cnigg@hawaii.edu). Reprints can be ordered at http://www.ajph.
org by clicking the “Reprints”link.
This editorial was accepted October 16, 2016.
doi: 10.2105/AJPH.2016.303532
AJPH PERSPECTIVES
January 2017, Vol 107, No. 1 AJPH Nigg et al. Editorial 37
pairwise and applied a Bonferroni
correction for multiple com-
parisons (P<.05/6 = .008).
We found no sex or race/
ethnicity interaction for any be-
havioral indicator (all interaction
P>.008), but there was some
indication that the game may
benefit the more-overweight
participants. The BMI was posi-
tively related to strenuous, mod-
erate, andmild physical activity (all
r= 0.2; P<.01). The number of
days playing Pok´emon GO was
positively related to moderate and
mild physical activity (both
r = 0.1; P<.05).
CAVEATS
The weak but significant
physical activity dose–response
result is likely attributable to the
short time frame of data col-
lection. It is unclear why there
was no BMI or dose–response
effect for sedentary behavior;
however, the Pok´emon GO
sedentary behavior effect seems
to appear early when starting
to play and applies across the
BMI range.
The retrospective self-report
design is associated with po-
tential social desirability and
recall bias. The lack of a control
group also limits the ability to
make causal inferences. Long-
term, rigorously designed
studies should look at mecha-
nisms of effective Internet-
based interventions such as
cooperation, competition,
nostalgia, intermittent re-
inforcement, sense of control,
andaugmented reality. Fur-
thermore, future research
should also document possible
negative consequences such
as game or Internet addiction
or accidents.
PRECISION PUBLIC
HEALTH
This study supports the po-
tential of Internet games being
able to promote health behav-
iors, which has implications
for mostly sedentary people, es-
pecially when, such as with
Pok´emon GO, they can potentially
reach large populations. Pok´emon
GO individually tailors its char-
acter (avatar) and augmented
reality of the game both moti-
vationally and geographically,
maximizing uniqueness for each
player, and may be providing
a way to individualize
interventions.
Claudio R. Nigg, PhD
Desiree Joi Mateo
Jiyoung An, PhD
CONTRIBUTORS
C. R. Nigg was the principal in-
vestigator, conceptualized the study,
oversaw the data collection, ran the
analyses, and wrote the “Physical Ac-
tivity and Sedentary Behavior,”“Ca-
veats,”and “Public Health Precision”
sections.D.J.Mateowrotethefirst draft
of the introduction and pilot description
and conducted the data collection. J. An
provided input on the study design,
measures, procedures, and discussion. All
authors revised draftsandapprovedthe
final version.
ACKNOWLEDGMENTS
The authors would like to acknowledge
the Health Behavior Change Research
Workgroup members who assisted with
recruitment: Nikki Cablay, Maddison
Chai, Anna Lena Eckert, Codie Garza,
Robin Mehl, Zoe Nigg, Brandon Sakka,
and Julia Schneider.
REFERENCES
1. US Department of Health and Human
Services, Office of Disease Prevention
and Health Promotion. Physical Activity
Guidelines for Americans 2008.Available
at: http://www.health.gov/
paguidelines/guidelines. Accessed
August 31, 2016.
2. Bort-Roig J, Gilson ND, Puig-Ribera
A, Contreras RS, Trost SG. Measuring
and influencing physical activity with
smartphone technology: a systematic
review. Sports Med. 2014;44(5):
671–686.
3. Pew Internet. Mobile technology fact
sheet 2014. Available at: http://www.
pewinternet.org/fact-sheets/mobile-
technology-fact-sheet. Accessed August 28,
2016.
4. Middelwe erd A, Mollee JS,
VanDerWalN,BrugJ,teVeldeSJ.
Apps to promote physical activity
among adults: a review and content
analysis. Int J Behav Nutr Phys Act. 2014;
11:97.
5. Pok´emon Go. 2016. Available at:
http://www.pokemongo.com/en-us.
Accessed September 2, 2016.
6. Jacobs DR, Ainsworth BE, Hartman TJ,
Leon AS. A simultaneous evaluation of 10
commonly used physical activity ques-
tionnaires. Med Sci Sports Exerc. 1993;
25(1):81–91.
7. Wallace LS, Buckworth J, Kirby TE,
Sherman WM. Characteristics of exercise
behavior among college students: appli-
cation of social cognitive theory to pre-
dicting stage of change. Prev Med. 2000;
31(5):494–505.
250
200
150
100
50
0
Strenuous
PA (min/wk)
Moderate
PA (min/wk)
Mild PA
(min/wk)
Internet
surng
(min/d)
Video game
playing
(min/d)
TV
watching
(min/d)
Behavior
Time
Pre
Post
FIGURE 1—Average Physical Activity (PA; in Minutes per Week), Sedentary Behavior (in Minutes per Day),
and 95% Confidence Intervals Before (Pre) and After (Post) Starting to Play Pok ´
emon GO
AJPH PERSPECTIVES
38 Editorial Nigg et al. AJPH January 2017, Vol 107, No. 1
