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Gotta Catch’em All: Quantifying the Additional Physical Activity from Pokémon Go - Retrospective Cohort Study in
the U.S.
Journal: BMJ
Manuscript ID BMJ.2016.035580
Article Type: Christmas
BMJ Journal: BMJ
Date Submitted by the Author: 16-Sep-2016
Complete List of Authors: Howe, Katherine; Harvard T.H. Chan School of Public Health, Epidemiology; Harvard T.H. Chan School of Public Health, Social and Behavioral Sciences Suharlim, Christian; Harvard T.H. Chan School of Public Health, Center for Health and Decision Science, Department of Health Policy and Management Ueda, Peter; Harvard T.H. Chan School of Public Health, Department of Global Health and Population Howe, Daniel; n/a Kawachi, Ichiro; Harvard School of Public Health, Department of Society Human Development and Rimm, Eric; HSPH
Keywords: physical activity, augmented reality gaming, Pokemon Go
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Gotta Catch’em All: Quantifying the Additional Physical Activity from
Pokémon Go - Retrospective Cohort Study in the U.S.
Katherine B Howe, MPH1,2*; Christian Suharlim, MD MPH
3*; Peter Ueda, MD PhD
4; Daniel
Howe, BA; Ichiro Kawachi, MBChB PhD2; Eric B. Rimm, ScD
1,5,6
1. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
2. Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public
Health, Boston, MA
3. Center for Health and Decision Science, Department of Health Policy and Management,
Harvard T.H. Chan School of Public Health, Boston, MA
4. Department of Global Health and Population, Harvard T.H. Chan School of Public
Health, Boston, MA
5. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
6. Channing Division of Network Medicine, Department of Medicine, Brigham and
Women’s Hospital, Harvard Medical School, Boston, MA
*These authors contributed equally to this work.
Correspondence to: Katherine Howe [email protected]
Abstract:
Objectives To estimate the effect of playing Pokémon Go on the number of steps taken per
day up to 6 weeks after installing the game. To estimate the additional number of steps taken
by the US population due to Pokémon Go.
Design Retrospective cohort analysis using online survey data.
Participants Amazon Mechanical Turk, survey participants (n=1,182) residing in the U.S.,
aged 18 to 35 years and who used an iPhone 6 series smartphone.
Main outcome measures The number of additional daily steps taken by Pokémon players,
estimated for each week after installation of the game using a difference-in-difference
regression model (step count data automatically recorded in the Health application of the
iPhone 6 series smartphones).
Results 560 (47.4%) of the survey participants reported playing Pokémon Go and walked on
average 4,256 steps per day in the three weeks prior to installation of the game. The difference-
in-difference analysis showed that the daily average steps increased for Pokémon Go players
during the first week of installation by 955 additional steps (95% CI = 537-1,372), and then
this increase gradually attenuated over the subsequent five weeks. The effect of Pokémon Go
on daily steps was seen in various subgroups of the population including men and women, race
groups, and individuals living in areas with different levels of walkability. Of the individuals
who played Pokémon Go, 14 percent sustained an increase of at least 500 steps per day after 4
weeks compared with their pre-installation levels.
Conclusions Pokémon Go players increased their daily number of steps compared to non-
players during the first six weeks after installation, although the effect was attenuated over
time. The worldwide popularity of Pokémon Go indicates a potential of augmented reality
gaming to contribute to an increase in physical activity among young adults.
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Introduction
Pokémon Go is an augmented reality game (ARG) developed for smartphone devices. Since its
launch in July 2016, the game has been downloaded over 500 million times, is now available in
over 100 countries, and has generated substantial interest as a social phenomenon around the
globei,ii. According to Apple, a multinational technology company, this game achieved the most
downloads in a launch week ever, was the fastest to reach 50 million downloads, and at one
point, had twice the daily use of Facebook, a social media site with over 1.7 billion monthly
active usersiii,iv,v,vi
(Figure 1).
[Figure 1]vii
Pokémon are fictional creatures which players can catch and train. The smartphone game was
developed by the software development company Niantic Inc. that used an ARG mechanic (i.e.
overlaying characters on real world images) where players find Pokémon characters in their
neighborhoods. Pokémon Go capitalizes on the ubiquity of smartphones with video imaging
capabilities worldwide, and the broad based appeal of the Pokémon charactersviii.
Because Pokémon Go requires players to navigate physical environments to play the game, there
has also been considerable interest in the effects of Pokémon Go on physical activityix,x,xi,xii
.
Since supplementing the real world with computer imagery allows players to become immersed
in a videogame while capturing Pokémon, it has been suggested that the game may lead to
increased and sustained physical activity among its players.xiii On September 7, 2016, Niantic
Inc. announced that in the last 8 weeks, the over 500 million Pokémon Go players have
collectively walked 4.6 billion kilometersxiv. It is, however, not known if individuals playing
Pokémon Go increased their physical activity compared with their usual levels, and if so, by how
much.
We used a US-wide online questionnaire platform to assess the levels of physical activity among
Pokémon players and non-players using automatically recorded step count data from
respondents’ iPhone devices. We estimated the change in average number of daily steps taken by
Pokémon players in the first six weeks since installation of the game. We then used our estimates
and data on the number of Pokémon Go players in the US to estimate the total additional number
of steps taken by the US population due to Pokémon Go.
Methods
Study population We conducted an online survey using the Amazon Mechanical Turk (MTurk) platform, between
August 1 and August 31, 2016. MTurk is a website for recruitment of survey participants who
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receive a small compensation for their participation. It is widely used for research purposes as it
allows for fast recruitment of diverse study populationsxv,xvi
. The rate of compensation has been
shown to not affect the quality of the responses, and the reliability is similar to those obtained via
traditional survey methodsxvii.
We recruited survey participants who were aged 18 to 35 years, resided in the US, and used an
iPhone 6, iPhone 6 Plus, iPhone 6S, or iPhone 6S Plus (iPhone 6 series) because these devices
automatically record the number of steps taken per day while carrying the device. Of the 2,225
individuals who responded to the survey, we excluded 115 participants who had
downloaded Pokémon Go but not played it for a substantial amount of time, as indicated by not
having reached a “trainer level” of 5 or more. After reaching trainer level 5 in the game, the
player is granted access to the functions integral to the game, including joining a team for which
the player competes against other teams, completing challenges, and using certain items to
enhance the augmented reality experience. We further excluded 923 participants who did not
complete the full survey likely due to the complexities of multiple screen captures necessary for
participation. Our final study population consisted of 1,182 individuals.
Covariates Survey participants were asked about their age, location of residence (indicated by zip code),
education level (high school or less, some university or vocational school, university degree, and
graduate or professional degree), household income (
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Statistical analyses
We compared the characteristics of Pokémon Go players and non-players using chi-square test
for categorical variables, and t-test for continuous variables. We compared the average number
of steps taken per day in the four weeks prior to installing the game vs. during each of the six
weeks after the date of game installation in Pokémon players and non-players respectively. For
non-Pokémon playing participants, the daily number of steps was compared before and after the
median date of installation among Pokémon playing participants. To estimate the effect of
Pokémon Go on average daily steps, we used a regression model using average steps per day as
the dependent variable and week before or after game installation, Pokémon Go status, as well as
interaction variables between Pokémon status and each week following installation of the game
(difference-in-difference analysis). We performed these analyses for the whole study population
and by tertiles of average daily steps in the four weeks prior to installation of Pokémon Go, as
well as by quartiles of Pokémon Go trainer level. In addition, we performed analyses stratified
by sex, age group (18-24 years and 25-35 years), household income, race, weight status, and
walkability index group (Car-dependent or Somewhat walkable, and Very walkable or Walker’s
paradise). We described the characteristics of the Pokémon Go playing participants who
sustained an increase in daily steps of 500 steps or more over 4 weeks after installation of the
game and compared them with those who did not increase or sustain an increase in steps using t-
test and chi-square test.
We used data provided by Niantic Inc. on the number of downloaded Pokémon Go applications
by the trainer level reached. We extrapolated the effect of Pokemon Go on daily steps for trainer
levels higher than those observed in the survey population by fitting various model specifications
to maximize goodness of fit (more details on Technical Appendix). For each trainer level, we
applied the effect estimates from our analyses by trainer level to the number of players at that
level category. We used these estimates to estimate the total number of additional steps taken by
the US population by August 31, 2016.
This study received institutional review board exemption approval on August 1st 2016 from the
Harvard T.H. Chan School of Public Health (Protocol # IRB 16-1243). We used Stata 12 (Stata
Corp, College Town, TX) for the analyses.
Results
Of the survey participants included in our study, 560 (47.4%) played Pokémon Go at a trainer
level of 5 or above. 90% of the Pokémon players installed the game within 10 days of its release
on July 6, 2016. The median date of installation was July 8, 2016. Pokémon Go playing was
common across various subgroups of the population (Table 1); players tended to be older, more
likely to have a low education, be single, obese, have a low household income and be less likely
to be black compared with non-players (Table 1).
[Table 1]
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In the four weeks prior to installation of Pokémon Go, survey participants who played the game
took on average 4,256 (SD=2,697) steps per day. The corresponding number for non-Pokémon
Go players in the four weeks preceding July 8th (median date of Pokémon Go installation among
the players) was 4,126 (2,930). After installation of the game, the average number of steps per
day among Pokémon Go players increased sharply before gradually returning to the pre-
installation levels while the non-players remained at similar levels of daily steps throughout the
study period. Specifically, daily steps increased by 20% to 5,123 (SD=3,371) during the first
week after installation among players and was 4,994 (3,374) in week 2, 4,693 (3,104) in week 3,
4,499 (3,077) in week 4, 4,108 (2,927) in week 5, and 3,985 (2,888) in week 6 (Figure 3). The
difference-in-difference analyses which also accounted for the time trend of steps taken among
those not playing the game confirmed the pattern of a sharp rise in daily steps during the first
week (955, 95% CI 537-1,372), an effect that was gradually attenuated over the subsequent
weeks and by week 6 had gone down to 130 (-424 - 684) (Figure 2).
[Figure 2]
The effect of Pokémon Go was observed across tertiles of daily steps in the 4 weeks prior to
Pokémon Go installation. Those with lower baseline steps had a prolonged effect of daily steps
increase, although of lower magnitude (Figure 3 and Supplemental Table 2).
[Figure 3]
Stratified analyses showed that the effect of Pokémon Go on average daily steps by week could
be observed in various subgroups of the population, including men and women, race groups, and
individuals living in areas with different levels of walkability (Supplemental Figure 1 and
Supplemental Table 2).
Of Pokémon Go playing participants, 74 (14%) sustained an increase in daily steps of 500 steps
or more over 4 weeks after installation of the game. Although not statistically significant, players
who sustained the increase in daily steps tended to be Asian, have lower BMI, and have lower
levels of daily steps prior to installation of the game compared to players who did not increase or
sustain an increase in daily steps (Table 2).
[Table 2]
As expected, the cumulative effect of Pokémon Go over six weeks since installing the game was
larger among players who had reached a higher Pokémon trainer level. For example, the
additional steps among players with a Pokémon trainer level of 20 and above was 50,851,
whereas this effect was only 5,607 among those who only had reached level 5 to 9 at the time of
answering the survey. To extrapolate this estimate to those outside of our population (level under
5 and above 32), we fit a series of exponential OLS models to predict cumulative steps as a
function of level, and conducted sensitivity analyses with a series of more restrictive models.
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Niantic, Inc. provided data on the number of downloads in the US and the distribution of players
by level as of August 31, 2016. Applying this effect to the data, we estimated that the U.S.
population has taken an additional 2 trillion steps as of August 31, 2016 (Model specification
provided in technical appendix).
Discussion
In the first study on the impact of Pokémon Go on physical activity, we found that daily steps
increased by 20% in the week after download and persisted higher than baseline for the
following four weeks. 14% of players sustained an increase of 500 daily steps or more above
baseline for a month after installation. As we projected our results to the US population based on
real downloads and levels achieved, the launch of this ARG has led to 2 trillion additional steps
as of August 31, 2016. Undoubtedly, as the game has been released and continues to be released
in other countries, it will translate to many more trillions of extra steps worldwide. Further
detailed longitudinal studies are needed to quantitate and generalize the impact of this game on
obesity levels.
In recent months, researchers have published anecdotal articles on the effect of Pokémon Go
with promoting physical activity as an unintentional health interventionxxiii,xxiv
. This is the first
study to quantify the additional physical activity due to Pokémon Go. This effect size can be
translated to Pokémon Go resulting in an estimated additional 1.4 billion kilometers of walking
by the US population, equivalent to over twice the distance between Earth and Jupiterxxv,xxvi,xxvii
.
ARGs on smartphones may be a novel method to engage a large percentage of the population in
more physical activity. Due to its engagement of players with nostalgia from the popularity of
Pokémon among children in the 1990s, entertainment, and social interaction, Pokémon Go
appeals to large parts of the population indicated by its popularity across subgroups of the
populationxxviii
. Given the substantial impact of Pokémon Go on physical activity, such as its
impact on individuals with low pre-installation physical activity, ARGs such as Pokémon Go,
may have important public health effect by broadly increasing and sustaining physical activity in
populations.
Strengths of this study include the use of automatically recorded steps data from the built-in
accelerometer on the iPhone, validation of Pokémon Go trainer level and start date using player
profile screenshots, and a diverse survey population representing a wide range of socio-
demographic factors and all regions of the US. In addition, we used data from Niantic Inc. to
estimate the additional number of steps taken by US residents due to Pokémon Go.
Our study has limitations. First, physical activity was only recorded when users were carrying
their smartphone. This may lead to overestimation of the effect of Pokémon on daily steps
because physical activity could occur when not playing Pokémon whereas all Pokémon-related
activity was recorded. Second, the quality of the survey responses could not be ascertained.
However, studies show that the quality of responses on MTurk and their reliability are similar to
those obtained via traditional survey methodsxxix,xxx,xxxi
, and we did not rely on self-reported
physical activity as participants uploaded screenshots of steps recorded by their iPhone devices.
Third, we did not include participants younger than 18 years because this is the minimum age
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required to participate in surveys on MTurk. Given the alarming rates of childhood obesity, and
the strong appeal of Pokemon Go among pre-teens and teenagers, future research should study
younger populations and the game’s potential for increasing physical activity. Finally, although
Pokemon Go is a global phenomenon, we only included participants residing in the US.
We showed that Pokémon Go has increased physical activity in the U.S. ARGs on smartphones
may be a novel method to engage a large percentage of the population in more physical activity.
While the effect is short-lived for most players, it is similar to other physical activity
interventions. However, for a small minority, higher physical activity levels persist. Future work
should focus on how to make this health behavior sustainable for more of the population. There
are unintended risks of the game, such as injuries and stranger danger, particularly for children.
However, there are also potential benefits, primarily, increased social connectedness and mood
improvement from spending more time outdoors. Insights from the Pokémon Go phenomena can
be used to design physical activity enhancing applications, which may also increase both social
and mental well-beingxxxii,xxxiii,xxxiv
.
What is already known on this topic ● Pokémon Go is an augmented reality game overlaying graphics on the real world using
the video camera of smartphones.
● This game is a global phenomenon with over 500 million downloads, and it is available
in over 100 countries and regions.
● This games requires walking and may lead to increased and sustained physical activity.
What this study adds ● This is the first study to quantify the additional physical activity due to Pokémon Go.
● We estimated the effect of daily steps taken due to Pokémon Go. Before game
installation, players and non-players took a similar amount of daily steps.
● We estimated that Pokémon Go players increased their daily number of steps by 955
steps during the first week of playing the game; an increase that was attenuated with time.
14% of the individuals who played Pokémon Go sustained an increase of 500 daily steps
after 4 weeks.
● The effect of Pokémon Go on daily steps was seen in various subgroups of the population
including men and women, race groups, and individuals living in areas with different
levels of walkability.
● We estimated that the number of additional steps taken by US residents is due to
Pokemon Go is 3 trillion steps as of August 31, 2016.
Footnotes:
Contributions: KBH and CS contributed equally and are co-first authors. KBH, CS, and DH
conceived and designed the project and collected data. CS, PU, and KBH analyzed the data.
KBH, CS, PU, and DH wrote the first draft of the manuscript. All authors contributed to the
manuscript. IK and EBR provided methodological guidance and financial support for data
collection. EBR is the guarantor.
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Funding: This research received no specific grant from any funding agency in the public,
commercial, or not-for-profit sectors.
Competing interests: All authors declare: no financial relationships with any organizations that
might have an interest in the submitted work and no other relationships or activities that could
appear to have influenced the submitted work.
Ethical approval: This study received institutional review board exemption approval on August
1st 2016 from the Harvard T.H. Chan School of Public Health (Protocol # IRB 16-1243).
Transparency: The manuscript’s guarantor affirms that the manuscript is an honest, accurate, and
transparent account of the study being reported; that no important aspects of the study have been
omitted; and that any discrepancies from the study as planned have been explained
Data sharing: Statistical code and dataset are available from the corresponding author.
i Niantic Labs - Pokémon GO [Internet]. Pokémon GO. 2016. Available from: http://pokemongolive.com/en/post/headsup/ ii Goodbye Summer, Hello Fall! [Internet]. 2016. Available from: https://nianticlabs.com/blog/autumn/ iiiDillet R. Apple says Pokémon Go is the most downloaded app in a first week ever [Internet]. TechCrunch. 2016. Available from: https://techcrunch.com/2016/07/22/apple-says-pokemon-go-is-the-most-downloaded-app-in-its-first-
week-ever/ ivPokémon GO Hit 50 Million Downloads in Record Time, Now at More Than 75 Million Worldwide [Internet].
Sensor Tower. Randy Nelson [Internet]. 2016. Available from: https://sensortower.com/blog/pokemon-go-50-
million-downloads v'Pokémon GO' Claims Twice The Daily Use Of Facebook, Most First-Week Downloads On iOS [Internet]. Forbes.
Forbes Magazine. 2016. Available from: http://www.forbes.com/sites/jasonevangelho/2016/07/22/pokemon-go-
now-has-twice-the-daily-usage-time-of-facebook-eating-into-youtube-engagement/#51d08a026282 viFacebook users worldwide 2016 [Internet]. Statista. 2016. Available from: http://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/ viiPokémon GO Hit 50 Million Downloads in Record Time, Now at More Than 75 Million Worldwide [Internet].
Sensor Tower. Randy Nelson [Internet]. 2016. Available from: https://sensortower.com/blog/pokemon-go-50-million-downloads viii Experts split on what popularity of Pokemon Go means for future of gaming and entertainment [Internet].
Experts split on what popularity of Pokemon Go means for future of gaming and entertainment. 2016. Available
from: http://phys.org/news/2016-07-experts-popularity-pokemon-future-gaming.html ix'Pokémon Go' Catches High Praise from Health Experts [Internet]. LiveScience. TechMedia Network. 2016.
Available from: http://www.livescience.com/55373-pokemon-go-exercise.html x'Pokémon Go' is so addictive that people are getting way more exercise than they're used to [Internet]. The Daily Dot.
2016. Available from: http://www.dailydot.com/debug/pokemon-go-workout-exercise-perk/ xiPokemon Go leading to a ‘population-level’ surge in fitness tracker step counts [Internet]. Washington Post. The Washington Post. 2016. Available from: https://www.washingtonpost.com/news/to-your-health/wp/2016/07/15/pokemon-go-leading-to-a-population-level-
surge-in-fitness-tracker-step-counts/ xiiHealth Buzz: Pokemon GO Has Everyone Exercising [Internet]. U.S. News and World
Report. 2016. Available from: http://health.usnews.com/wellness/articles/2016-07-11/pokemon-go-has-everyone-
exercising
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xiiiCould Pokemon GO contain the secret formula to society’s chronic disease pandemic? - Exercise Right [Internet].
Exercise Right. 2016. Available from: http://exerciseright.com/au/pokemon-go-contain-secret-formula-societies-
chronic-disease-pandemic/ xivNiantic Labs - Pokémon GO [Internet]. Pokémon GO. 2016. Available from:
http://pokemongolive.com/en/post/headsup/ xvBerinsky, Adam J., Gregory A. Huber, and Gabriel S. Lenz. "Using Mechanical Turk as a subject recruitment tool
for experimental research." Submitted for review (2011). xviMason W, Suri S. Conducting behavioral research on Amazon’s Mechanical Turk. Behavior research methods.
2012 Mar 1;44(1):1-23. xviiHolden, Christopher J., Trevor Dennie, and Adam D. Hicks. "Assessing the reliability of the M5-120 on
Amazon’s Mechanical Turk." Computers in Human Behavior 29.4 (2013): 1749-1754. xviii
Walk Score Methodology [Internet]. Walk Score. 2016. Available from:
https://www.walkscore.com/methodology.shtml xix Duncan DT, Aldstadt J, Whalen J, Melly SJ, Gortmaker SL. Validation of Walk Score® for estimating
neighborhood walkability: an analysis of four US metropolitan areas. International journal of environmental
research and public health. 2011 Nov 4;8(11):4160-79. xx Carr LJ, Dunsiger SI, Marcus BH. Validation of Walk Score for estimating access to walkable amenities. British
Journal of Sports Medicine. 2010 Apr 23:bjsports69609. xxi Duncan DT, Aldstadt J, Whalen J, Melly SJ. Validation of Walk Scores and Transit Scores for estimating
neighborhood walkability and transit availability: a small-area analysis. GeoJournal. 2013 Apr 1;78(2):407-16. xxii Manaugh K, El-Geneidy A. Validating walkability indices: How do different households respond to the
walkability of their neighborhood? Transportation Research Part D: Transport and Environment. 2011 Jun
30;16(4):309-15. xxiii
McCartney M. Game on for Pokémon Go. BMJ. 2016 Aug 9;354:i4306. xxivClark AM, Clark MT. Pokemon Go and Research Qualitative, Mixed Methods research, and the
Supercomplexity of Interventions. xxvMore Women Than Men Are Playing 'Pokémon GO'- By A Lot [Internet]. Forbes. 2016. Available from:
http://www.forbes.com/sites/ryanmac/2016/07/26/more-women-than-men-are-playing-pokemon-go-by-a-
lot/#2ccbda324f16 xxvi The Average Walking Stride Length [Internet]. Live Healthy. 2016. Available from:
http://livehealthy.chron.com/average-walking-stride-length-7494.html xxvii
Distances Between the Planets of the Solar System - The Planets [Internet]. The Planets. 2016. Available from:
http://theplanets.org/distances-between-planets/ xxviii
News BBC. Pokemon and the power of nostalgia [Internet]. BBC News. 2016. Available from:
http://www.bbc.com/news/world-asia-36780797 xxixBerinsky, Adam J., Gregory A. Huber, and Gabriel S. Lenz. "Using Mechanical Turk as a subject recruitment
tool for experimental research." Submitted for review (2011). xxxMason W, Suri S. Conducting behavioral research on Amazon’s Mechanical Turk. Behavior research methods.
2012 Mar 1;44(1):1-23. xxxiHolden, Christopher J., Trevor Dennie, and Adam D. Hicks. "Assessing the reliability of the M5-120 on
Amazon’s Mechanical Turk." Computers in Human Behavior 29.4 (2013): 1749-1754. xxxii
Pimentel D. ANG 5802 Research Design Effect of Player Sex and Group Size on Collaborative Gaming
Behavior in Pokémon Go. xxxiii
Schwartz BR. Pokémon Go has been out for 4 days, and it's already changing people's lives [Internet]. Fusion. 2016. Available from: http://fusion.net/story/323694/pokemon-go-making-a-difference/ xxxiv
Is Pokemon Go a quick fix for depression and anxiety? [Internet]. Independent. 2016. Available from: http://www.independent.ie/life/health-wellbeing/is-pokemon-go-a-quick-fix-for-depression-and-anxiety- 34998029.html
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Table 1 Characteristics of Pokemon Go-playing and non-playing survey participants. Data are shown in number (%) unless
otherwise indicated.
Not Active Players (n=622) Pokemon Go Players (n=560) p
Date for Pokemon Go installation,
median (IQR) . July 8th (July 7 - 11th)
Mean age in years (SD) 27.3 (4.5) 25.6 (4.3)
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Car-Dependent 431 (69.7) 391 (70)
Somewhat Walkable 69 (11.2) 71 (12.7)
Very Walkable 63 (10.2) 52 (9.3)
Walker's Paradise 55 (8.9) 45 (8.1)
Body Mass Index in kg/m2, (SD) 26.9 (6.7) 27.9 (7.7) 0.016
Weight status
0.038
Normal weight (
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Table 2 Characteristics of Pokemon Go-players who sustained a 500 step increase in daily steps across 4 weeks following
installation of Pokemon Go and those who did not sustain such an increase. Data are shown in number (%) unless otherwise
indicated.
Not sustained (n=486) Sustained (n=74) p
Date for Pokemon Go installation, median (IQR) July 8th (July 7 - 11th) July 7th (July 7 - 9th)
Mean age in years (SD) 25.6 (4.3) 25.8 (4.4) 0.63
Age group
0.61
18-24 years 208 (42.8) 34 (46)
>=25 years 278 (57.2) 40 (54.1)
Sex
Female
Male
340 (70) 50 (67.6) 0.67
Race
0.18
Asian 30 (6.2) 8 (10.8)
White 379 (78) 51 (68.9)
Black 32 (6.6) 4 (5.4)
Other 45 (9.3) 11 (14.9)
Education
0.57
High school or less 44 (9.1) 7 (9.5)
Some university 211 (43.6) 26 (35.1)
College degree 176 (36.4) 31 (41.9)
Graduate/professional degree 53 (11) 10 (13.5)
Marital status
0.66
Single 316 (65) 49 (66.2)
Married/cohabitating 153 (31.5) 21 (28.4)
Divorced/separated/widowed 17 (3.5) 4 (5.4)
Household income
0.70
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Car-Dependent 337 (69.3) 54 (74)
Somewhat Walkable 63 (13) 8 (11)
Very Walkable 47 (9.7) 5 (6.9)
Walker's Paradise 39 (8) 6 (8.2)
Body Mass Index in kg/m2, (SD) 28.1 (7.7) 26.7 (7.2) 0.076
Weight status
0.055
Normal weight (
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Supplementary material for “Gotta Catch’em All: Quantifying the
Additional Physical Activity from Pokemon Go - Retrospective Cohort
Study in the U.S.” Howe et al.
Contents
Supplementary Table 1: Variable definitions.
Supplementary Table 2: Regression models using average steps per day as the dependent
variable and week before or after game installation, Pokemon Go status as well as
interaction variables between Pokemon status and each week following installation of the
game (difference-in-difference analysis).
Supplementary Figure 1: Average number of daily steps and standard errors by week
before and after installation of Pokemon Go by sex, age group, race, household income,
education level, urbanity, and weight status. The green line indicates non-players and the
red line indicates players.
Technical appendix for extrapolation to U.S. population estimates
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Supplementary Table 1 Variable definitions
mstepsdayw Average steps per day in a given week
_Ipweek_1 (omitted) Variable that denotes the fourth week prior to installation (Pokemon players) or prior
to 09/08 (control)
_Ipweek_2 Variable that denotes the third week prior to installation (Pokemon players) or prior to
09/08 (control)
_Ipweek_3 Variable that denotes the second week prior to installation (Pokemon players) or prior
to 09/08 (control)
_Ipweek_4 Variable that denotes the first week prior to installation (Pokemon players) or prior to
09/08 (control)
_Ipweek_5 Variable that denotes the first week following installation (Pokemon players) or
following 09/08 (control)
_Ipweek_6 Variable that denotes the second week following installation (Pokemon players) or
following 09/08 (control)
_Ipweek_7 Variable that denotes the third week following installation (Pokemon players) or
following 09/08 (control)
_Ipweek_8 Variable that denotes the fourth week following installation (Pokemon players) or
following 09/08 (control)
_Ipweek_9 Variable that denotes the fifth week following installation (Pokemon players) or
following 09/08 (control)
_Ipweek_10 Variable that denotes the sixth week following installation (Pokemon players) or
following 09/08 (control)
pokelevel5 Variable that defines Pokemon Go exposure (1=pokemon group, 0=control)
p_pweek1 An interaction term between pokelevel5 and _Ipweek_5
p_pweek2 An interaction term between pokelevel5 and _Ipweek_6
p_pweek3 An interaction term between pokelevel5 and _Ipweek_7
p_pweek4 An interaction term between pokelevel5 and _Ipweek_8
p_pweek5 An interaction term between pokelevel5 and _Ipweek_9
p_pweek6 An interaction term between pokelevel5 and _Ipweek_10
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Supplementary Table 2 Regression models using average steps per day as the dependent variable
and week before or after game installation, Pokemon Go status as well as interaction variables
between Pokemon status and each week following installation of the game (difference-in-difference
analysis).
2.1. Overall
mstepsdayw Coef. Std. Err. t P>t [95% Conf. Interval]
_Ipweek_2 59.90917 136.2998 0.44 0.66 -207.264 327.0823
_Ipweek_3 -87.77205 135.9071 -0.65 0.518 -354.1755 178.6314
_Ipweek_4 -63.80161 135.1738 -0.47 0.637 -328.7677 201.1644
_Ipweek_5 -111.0687 168.6814 -0.66 0.51 -441.7159 219.5785
_Ipweek_6 -190.1299 168.6814 -1.13 0.26 -520.7771 140.5173
_Ipweek_7 -129.8359 168.1023 -0.77 0.44 -459.348 199.6763
_Ipweek_8 -225.1486 168.8489 -1.33 0.182 -556.1242 105.827
_Ipweek_9 -552.3027 178.5123 -3.09 0.002 -902.2204 -202.385
_Ipweek_10 -424.8413 206.6329 -2.06 0.04 -829.8807 -19.80192
pokelevel5 113.6742 96.05633 1.18 0.237 -74.61429 301.9626
p_pweek1 954.9645 213.0032 4.48 0 537.438 1372.491
p_pweek2 905.5152 213.8311 4.23 0 486.3661 1324.664
p_pweek3 543.97 214.3195 2.54 0.011 123.8634 964.0766
p_pweek4 445.5244 216.3409 2.06 0.039 21.45556 869.5931
p_pweek5 381.4832 235.3069 1.62 0.105 -79.76253 842.7289
p_pweek6 130.3688 282.6927 0.46 0.645 -423.7619 684.4996
_cons 4165.374 106.3936 39.15 0 3956.822 4373.925
2.2. Pre-installation steps first tertile (lowest baseline steps)
mstepsdayw Coef. Std. Err. t P>t [95% Conf. Interval]
_Ipweek_2 18.32733 93.10116 0.2 0.844 -164.2112 200.8659
_Ipweek_3 -90.12385 92.60386 -0.97 0.331 -271.6873 91.43965
_Ipweek_4 67.59012 92.18844 0.73 0.464 -113.1589 248.3391
_Ipweek_5 298.8908 112.8196 2.65 0.008 77.69144 520.0902
_Ipweek_6 172.4076 112.5096 1.53 0.126 -48.18401 392.9992
_Ipweek_7 183.9461 112.3564 1.64 0.102 -36.34527 404.2374
_Ipweek_8 208.1131 113.1345 1.84 0.066 -13.70375 429.93
_Ipweek_9 84.31108 118.7585 0.71 0.478 -148.5325 317.1547
_Ipweek_10 290.6299 140.9265 2.06 0.039 14.3227 566.9371
pokelevel5 -11.03629 65.8223 -0.17 0.867 -140.0906 118.018
p_pweek1 870.0704 145.8135 5.97 0 584.1816 1155.959
p_pweek2 614.2075 146.3393 4.2 0 327.2878 901.1272
p_pweek3 621.3457 148.5058 4.18 0 330.1781 912.5133
p_pweek4 411.213 150.9354 2.72 0.006 115.2818 707.1441
p_pweek5 394.1259 165.9437 2.38 0.018 68.76894 719.4829
p_pweek6 -26.92996 202.7853 -0.13 0.894 -424.5204 370.6605
_cons 1730.249 72.00532 24.03 0 1589.072 1871.426
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2.3. Preinstallation steps second tertile (intermediate baseline steps)
mstepsdayw Coef. Std. Err. t P>t [95% Conf. Interval]
_Ipweek_2 64.6991 174.0123 0.37 0.71 -276.4761 405.8743
_Ipweek_3 40.33677 173.7851 0.23 0.816 -300.3929 381.0664
_Ipweek_4 128.0893 172.8893 0.74 0.459 -210.8841 467.0626
_Ipweek_5 92.70683 215.1631 0.43 0.667 -329.1501 514.5638
_Ipweek_6 89.59998 213.9141 0.42 0.675 -329.8081 509.0081
_Ipweek_7 100.2811 214.5334 0.47 0.64 -320.3413 520.9035
_Ipweek_8 271.9558 215.1631 1.26 0.206 -149.9012 693.8127
_Ipweek_9 50.5815 227.3173 0.22 0.824 -395.1054 496.2684
_Ipweek_10 413.2123 259.6849 1.59 0.112 -95.93575 922.3604
pokelevel5 25.26086 122.8027 0.21 0.837 -215.5107 266.0324
p_pweek1 838.385 272.6853 3.07 0.002 303.7478 1373.022
p_pweek2 1081.695 273.6754 3.95 0 545.1163 1618.273
p_pweek3 648.8873 274.5001 2.36 0.018 110.6919 1187.083
p_pweek4 307.0193 276.7445 1.11 0.267 -235.5765 849.615
p_pweek5 29.01386 303.4094 0.1 0.924 -565.8622 623.8899
p_pweek6 -529.3121 365.2656 -1.45 0.147 -1245.466 186.8416
_cons 3430.603 135.7474 25.27 0 3164.452 3696.755
2.4. Preinstallation steps third tertile (highest baseline steps)
mstepsdayw Coef. Std. Err. t P>t [95% Conf. Interval]
_Ipweek_2 97.07612 239.3674 0.41 0.685 -372.2365 566.3887
_Ipweek_3 -184.0094 238.8857 -0.77 0.441 -652.3775 284.3588
_Ipweek_4 -382.3325 237.3294 -1.61 0.107 -847.6493 82.98436
_Ipweek_5 -782.8152 303.7843 -2.58 0.01 -1378.426 -187.2046
_Ipweek_6 -738.9981 306.8241 -2.41 0.016 -1340.569 -137.4274
_Ipweek_7 -684.9679 303.2934 -2.26 0.024 -1279.616 -90.31958
_Ipweek_8 -1231.688 304.2795 -4.05 0 -1828.27 -635.1066
_Ipweek_9 -1807.826 323.5789 -5.59 0 -2442.247 -1173.406
_Ipweek_10 -2254.543 369.6135 -6.1 0 -2979.221 -1529.865
pokelevel5 -357.6571 168.5299 -2.12 0.034 -688.0829 -27.23124
p_pweek1 1325.242 375.5477 3.53 0 588.9295 2061.555
p_pweek2 947.3017 378.0109 2.51 0.012 206.1596 1688.444
p_pweek3 317.7127 375.5435 0.85 0.398 -418.5918 1054.017
p_pweek4 543.8067 377.1355 1.44 0.149 -195.619 1283.232
p_pweek5 370.4145 405.3498 0.91 0.361 -424.3292 1165.158
p_pweek6 739.3398 479.8827 1.54 0.123 -201.536 1680.216
_cons 7666.595 188.8693 40.59 0 7296.29 8036.899
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Supplemental Figure 1 Average number of daily steps and standard errors by week before and after
installation of Pokemon Go by sex, age group, race, household income, education level, urbanity,
neighborhood walkability, and weight status. The green line indicates non-players and the red line
indicates players.
SF1.1. by sex
SF1.2. by age group
SF1.3. by race
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Men
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Women
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Ages 18-24
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Ages 25-35
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Asian
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
White
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SF 1.4. by household income
SF 1.5. by education level
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Black
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Other races
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Houshold income
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SF 1.6. by urbanity
SF 1.7. by neighborhood walkability
SF 1.8. by weight status
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Rural
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Suburban
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Urban
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Car-dependent/somewhat walkable
2000
3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
Very walkable/Walker's paradise
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3000
4000
5000
6000
7000
Average steps per day
-4 -3 -2 -1 1 2 3 4 5 6
Week since installation
BMI/=30kg/m2
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Technical Appendix for Extrapolation to U.S. Population Estimates
Supplementary Table 3 Regression models using average steps per day as the dependent variable
and week before or after game installation, Pokemon Go status as well as interaction variables
between Pokemon status and each week following installation of the game (difference-in-difference
analysis) by quartiles of level.
ST 3.1. Among level 5-9
mstepsdayw Coef. Std. Err. t P>t [95% Conf. Interval]
_Ipweek_2 80.11255 170.1508 0.47 0.638 -253.4364 413.6616
_Ipweek_3 -39.75891 169.6804 -0.23 0.815 -372.3858 292.868
_Ipweek_4 -124.3668 168.5451 -0.74 0.461 -454.7681 206.0345
_Ipweek_5 -109.6102 179.7788 -0.61 0.542 -462.033 242.8127
_Ipweek_6 -188.6714 179.7788 -1.05 0.294 -541.0942 163.7515
_Ipweek_7 -128.3773 179.2364 -0.72 0.474 -479.737 222.9824
_Ipweek_8 -223.69 179.9357 -1.24 0.214 -576.4205 129.0405
_Ipweek_9 -550.8441 189.019 -2.91 0.004 -921.3807 -180.3075
_Ipweek_10 -423.3828 215.7344 -1.96 0.05 -846.2901 -0.4754901
pokelevel5 -456.8443 157.3768 -2.9 0.004 -765.3522 -148.3364
p_pweek1 280.5397 348.2358 0.81 0.421 -402.1119 963.1913
p_pweek2 438.5844 350.8974 1.25 0.211 -249.2847 1126.454
p_pweek3 129.7397 356.273 0.36 0.716 -568.6673 828.1467
p_pweek4 81.62078 368.2797 0.22 0.825 -640.3231 803.5647
p_pweek5 -93.0745 428.9022 -0.22 0.828 -933.8576 747.7086
p_pweek6 -36.58462 556.5694 -0.07 0.948 -1127.635 1054.466
_cons 4163.915 123.3452 33.76 0 3922.12 4405.711
ST 3.2. Among level 10-14
mstepsdayw Coef. Std. Err. t P>t [95% Conf. Interval]
_Ipweek_2 32.2073 174.2178 0.18 0.853 -309.3134 373.728
_Ipweek_3 -30.20742 173.7397 -0.17 0.862 -370.791 310.3761
_Ipweek_4 -64.4514 172.6937 -0.37 0.709 -402.9845 274.0817
_Ipweek_5 -103.6656 184.5499 -0.56 0.574 -465.4405 258.1092
_Ipweek_6 -182.7269 184.5499 -0.99 0.322 -544.5017 179.048
_Ipweek_7 -122.4328 183.9914 -0.67 0.506 -483.1128 238.2473
_Ipweek_8 -217.7455 184.7115 -1.18 0.239 -579.8372 144.3462
_Ipweek_9 -544.8996 194.0647 -2.81 0.005 -925.3264 -164.4728
_Ipweek_10 -417.4383 221.5671 -1.88 0.06 -851.7783 16.90176
pokelevel5 30.51565 159.5149 0.19 0.848 -282.1828 343.2141
p_pweek1 503.8247 353.5131 1.43 0.154 -189.1702 1196.82
p_pweek2 662.9367 354.3717 1.87 0.061 -31.74131 1357.615
p_pweek3 365.3518 355.8323 1.03 0.305 -332.1896 1062.893
p_pweek4 327.6174 359.8404 0.91 0.363 -377.781 1033.016
p_pweek5 -22.29186 396.3319 -0.06 0.955 -799.2249 754.6411
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p_pweek6 -66.30605 488.6762 -0.14 0.892 -1024.262 891.6504
_cons 4157.971 126.3927 32.9 0 3910.202 4405.739
ST 3.3. Among level 15-19
mstepsdayw Coef. Std. Err. t P>t [95% Conf. Interval]
_Ipweek_2 11.83271 172.4302 0.07 0.945 -326.1837 349.8491
_Ipweek_3 -59.18853 171.7799 -0.34 0.73 -395.93 277.553
_Ipweek_4 -98.43859 170.8648 -0.58 0.565 -433.3863 236.5092
_Ipweek_5 -124.6374 182.6422 -0.68 0.495 -482.6724 233.3977
_Ipweek_6 -203.6986 182.6422 -1.12 0.265 -561.7337 154.3365
_Ipweek_7 -143.4045 182.0894 -0.79 0.431 -500.3559 213.5469
_Ipweek_8 -238.7172 182.8022 -1.31 0.192 -597.0659 119.6314
_Ipweek_9 -565.8714 192.0601 -2.95 0.003 -942.3683 -189.3744
_Ipweek_10 -438.41 219.282 -2 0.046 -868.2703 -8.549731
pokelevel5 409.7403 157.3884 2.6 0.009 101.2105 718.2701
p_pweek1 1027.265 347.1763 2.96 0.003 346.692 1707.837
p_pweek2 587.3742 351.3765 1.67 0.095 -101.4321 1276.18
p_pweek3 326.5009 353.7408 0.92 0.356 -366.9402 1019.942
p_pweek4 274.197 356.8609 0.77 0.442 -425.3605 973.7544
p_pweek5 410.2932 388.0473 1.06 0.29 -350.3992 1170.986
p_pweek6 -487.9665 464.3265 -1.05 0.293 -1398.19 422.2567
_cons 4178.942 125.0752 33.41 0 3933.756 4424.128
ST 3.2. Among level 20+
mstepsdayw Coef. Std. Err. t P>t [95% Conf. Interval]
_Ipweek_2 18.25261 174.1755 0.1 0.917 -323.1839 359.6892
_Ipweek_3 -82.73326 173.4109 -0.48 0.633 -422.671 257.2045
_Ipweek_4 -117.7016 172.5003 -0.68 0.495 -455.8542 220.451
_Ipweek_5 -133.8788 185.0932 -0.72 0.47 -496.7173 228.9597
_Ipweek_6 -212.94 185.0932 -1.15 0.25 -575.7785 149.8985
_Ipweek_7 -152.6459 184.5312 -0.83 0.408 -514.3828 209.0909
_Ipweek_8 -247.9587 185.2558 -1.34 0.181 -611.116 115.1986
_Ipweek_9 -575.1128 194.6664 -2.95 0.003 -956.7176 -193.5079
_Ipweek_10 -447.6514 222.3304 -2.01 0.044 -883.4862 -11.81666
pokelevel5 427.0868 155.7624 2.74 0.006 121.7455 732.428
p_pweek1 1921.991 345.7821 5.56 0 1244.154 2599.829
p_pweek2 1846.496 346.5604 5.33 0 1167.133 2525.859
p_pweek3 1240.881 346.2606 3.58 0 562.1058 1919.656
p_pweek4 915.6664 345.1001 2.65 0.008 239.166 1592.167
p_pweek5 793.7437 363.5389 2.18 0.029 81.09767 1506.39
p_pweek6 545.593 417.7082 1.31 0.192 -273.2411 1364.427
_cons 4188.184 126.5303 33.1 0 3940.146 4436.221
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Supplementary Table 4 Point estimate additional steps by level categories. Model uses the full 6-
week cumulative additional steps from Supplementary Table 3, followed by a series of more
restrictive models
Categories Additional steps Sensitivity Analysis 1
5-week add’l steps*
Sensitivity Analysis 2
Somewhat restrictive**
Sensitivity Analysis 3
Most restrictive ***
Level 5-9 5605.728 5861.871 6513.392 0
Level 10-14 12397.93 12862.07 13018.11 8,167
Level 15-19 14963.65 18379.41 15507.36 11,302
Level 20+ 50850.6 47031.45 47031.45 47,031
* the biggest number of weeks where we still see statistical significance
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Supplementary Table 5 Point estimate of cumulative 6 weeks additional steps by level assuming
model specification, quantities of Pokemon Go player by level
Level Additional steps Distribution
(Niantic Inc.) Quantities | distrib
1 3754 0.785509% 860187
2 4147 0.757138% 829118
3 4581 1.182169% 1294556
4 5061 1.586680% 1737524
5 5590 2.130524% 2333071
6 6175 2.847428% 3118130
7 6822 3.112118% 3407984
8 7535 3.556573% 3894693
9 8324 3.898346% 4268958
10 9195 3.970544% 4348020
11 10157 3.996221% 4376138
12 11220 3.825737% 4189446
13 12394 3.854775% 4221245
14 13692 5.576743% 6106918
15 15124 6.289198% 6887107
16 16707 5.766386% 6314591
17 18455 5.205418% 5700293
18 20387 5.619988% 6154275
19 22520 4.563331% 4997162
20 24877 6.721020% 7359981
21 27480 7.905062% 8656589
22 30356 6.443158% 7055703
23 33533 4.321828% 4732700
24 37042 2.582156% 2827639
25 40919 1.571643% 1721058
26 45201 0.787844% 862744
27 49931 0.455164% 498436
28 55156 0.235507% 257896
29 60928 0.116487% 127562
30 67304 0.083805% 91773
31 74348 0.026618% 29148
32 82128 0.014447% 15820
33 90723 0.005346% 5854
34 100217 0.002070% 2267
35 110704 0.000975% 1068
36 122289 0.000274% 300
37 135087 0.000111% 122
38 149223 0.000017% 19
39 164840 0.000009% 9
40 182090 0.000000% 0
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Confidential: For Review O
nly
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Supplementary Table 6 Point estimate additional steps by level categories. Model uses the full 6-
week cumulative additional steps from Supplementary Table 3, followed by a series of more
restrictive models
Model Sensitivity Analysis 1
5-week add’l steps*
Sensitivity Analysis 2
Somewhat restrictive**
Sensitivity Analysis 3
Most restrictive ***
US add’l steps 2,027,547,335,158 2,058,744,240,345 2,040,547,122,913 1,713,160,698,648
%∆ from model - 1.54% 0.64% -15.51%
Distance (km)* 1,428,189,745 1,450,164,620 1,437,346,701 1,206,738,061
* assuming 63% female player2, average stride length of 26.4 inches (female) and 30 inches (male)
3
1. Source: http://heavy.com/games/2016/07/pokemon-go-xp-gained-per-level-how-much-needed-
need-to-up-advance-chart-graph-image/
2. More Women Than Men Are Playing 'Pokémon GO'--By A Lot [Internet]. Forbes. 2016.
Available from: http://www.forbes.com/sites/ryanmac/2016/07/26/more-women-than-men-are-
playing-pokemon-go-by-a-lot/#2ccbda324f16
3. The Average Walking Stride Length [Internet]. Live Healthy. 2016. Available from:
http://livehealthy.chron.com/average-walking-stride-length-7494.html
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