Gotta Ca tch’em All: Quantifying the Additional Physical ... · Gotta Catch’em All: Quantifying the Additional Physical Activity ... complete the full survey likely due to the

Confidential: For Review O

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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

https://mc.manuscriptcentral.com/bmj

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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 (<50k, 50k to <100k, and >/=100k

USD/year), marital status (unmarried, separated/widowed/divorced, married), race (Asian, Black,

White, and other race categories), and weight and height which we used to calculate body mass

index (BMI in kg/m2; categorized into normal weight [<25 kg/m2], overweight [25 to <30

kg/m2] and obese [>/=30 kg/m2]). We asked participants who reported that they played

Pokémon Go to upload a screenshot (picture of the content on a screen) of their Pokémon Go

application, which includes information on the date of installation and the Pokémon Go trainer

level that the player had reached at the time of participation in the survey. The trainer level

reflects the time spent playing the game because trainer level increases with time played. We

used the zip code of residence of the survey participants to match their location to a

neighborhood walkability index (Walk ScoreⓇ) provided by Redfin Real Estate in Bostonxviii.

This Walk Score measures the neighborhood walkability of addresses in the US from an analysis

of walking routes to nearby amenities, street connectivity, and pedestrian friendliness. The score

ranges from 0 to 100 (0 indicates that almost all errands require a car and 100 being daily errands

do not require a car), categorized into four groups (Car-Dependent [0-49], Somewhat Walkable

[50-69], Very Walkable [70-89], and Walker’s Paradise [90-100]), and has been validated in

several studiesxix,xx,xxi,xxii

.

All participants were asked to upload screenshots showing their number of steps per day while

carrying their smartphone, for each day during the two months preceding the date of study

participation. This information is recorded by default in the ‘Health’ application of iPhone 6

series, using the device’s built-in accelerometer.

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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) <0.001

Age group

<0.001

18-24 years 188 (30.2) 242 (43.2)

>=25 years 434 (69.8) 318 (56.8)

Sex

Female

Male

453 (72.8)

390 (69.6) 0.23

Race

<0.001

Asian 32 (5.1) 38 (6.8)

White 491 (78.9) 430 (76.8)

Black 68 (10.9) 36 (6.4)

Other 31 (5) 56 (10)

Education

<0.001

High school or less 29 (4.7) 51 (9.1)

Some university 208 (33.5) 237 (42.5)

College degree 267 (43) 207 (37.1)

Graduate/professional degree 117 (18.8) 63 (11.3)

Marital status

<0.001

Single 336 (54) 365 (65.2)

Married/cohabitating 256 (41.2) 174 (31.1)

Divorced/separated/widowed 30 (4.8) 21 (3.8)

Household income

0.001

<50k 240 (38.6) 277 (49.5)

50k to <100k 269 (43.3) 189 (33.8)

>/=100k 113 (18.2) 94 (16.8)

Region

0.72

Midwest 187 (30.1) 175 (31.3)

Northeast 87 (14) 74 (13.2)

South 157 (25.2) 128 (22.9)

West 191 (30.7) 183 (32.7)

Area

0.27

Rural 99 (15.9) 77 (13.8)

Suburb 294 (47.3) 290 (51.8)

Urban 229 (36.8) 193 (34.5)

Walkability score category

0.78

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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 (<25kg/m2) 295 (47.4) 246 (44)

Overweight (25 kg/m2 to <30

kg/m2) 165 (26.5) 130 (23.3)

Obese (>/=30 kg/m2) 162 (26.1) 183 (32.7)

Tertile of daily steps during three

weeks before installation of Pokemon

Go

0.21

1 (<2544 steps/day) 218 (35.2) 174 (31.4)

2 (2545 to 3505 steps/day) 209 (33.7) 182 (32.9)

3 (>/=3506 steps/day) 193 (31.1) 198 (35.7)

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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

<50k 238 (49) 39 (52.7)

50k to <100k 164 (33.7) 25 (33.8)

>/=100k 84 (17.3) 10 (13.5)

Region

0.59

Midwest 147 (30.3) 28 (37.8)

Northeast 65 (13.4) 9 (12.2)

South 114 (23.5) 14 (18.9)

West 160 (32.9) 23 (31.1)

Area

0.65

Rural 68 (14) 9 (12.2)

Suburb 254 (52.3) 36 (48.7)

Urban 164 (33.7) 29 (39.2)

Walkability score category

0.82

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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 (<25kg/m2) 204 (42.1) 42 (56.8)

Overweight (25 kg/m2 to <30

kg/m2) 118 (24.3) 12 (16.2)

Obese (>/=30 kg/m2) 163 (33.6) 20 (27)

Tertile of daily steps during three weeks before installation of

Pokemon Go 0.15

1 (<2544 steps/day) 147 (30.6) 27 (36.5)

2 (2545 to 3505 steps/day) 154 (32.1) 28 (37.8)

3 (>/=3506 steps/day) 179 (37.3) 19 (25.7)

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Confidential: For Review Only

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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


_Ipweek_7 Variable that denotes the third week following installation (Pokemon players) or


_Ipweek_8 Variable that denotes the fourth week following installation (Pokemon players) or


_Ipweek_9 Variable that denotes the fifth week following installation (Pokemon players) or


_Ipweek_10 Variable that denotes the sixth week following installation (Pokemon players) or


pokelevel5 Variable that defines Pokemon Go exposure (1=pokemon group, 0=control)

p_pweek1 An interaction term between pokelevel5 and _Ipweek_5






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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)


_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)


_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)


_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


-4 -3 -2 -1 1 2 3 4 5 6


Women

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Ages 18-24

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Ages 25-35

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Asian

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


White

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SF 1.4. by household income

SF 1.5. by education level

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Black

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Other races

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Houshold income <50,000 USD

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Houshold income 50,000 to <100,000 USD

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Houshold income >/=100,000 USD

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


High school/vocational school/some college

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


College/graduate school

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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


-4 -3 -2 -1 1 2 3 4 5 6


Rural

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Suburban

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Urban

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Car-dependent/somewhat walkable

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


Very walkable/Walker's paradise

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2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


BMI<25kg/m2

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


BMI 25 to < 30kg/m2

2000

3000

4000

5000

6000

7000


-4 -3 -2 -1 1 2 3 4 5 6


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


_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



_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



_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+


_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**


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 <0.05

** 5-week for 20+, 4 weeks for the rest removing the week 5 & 6 uncertainties

*** point estimate calculated until the biggest number of weeks where we still see statistical

significance <0.1

Supplemental Figure 2 Model fit

SF 2.1. Between total experience points (time spent) and level1

SF 2.2. Between additional steps to level, assuming similar model functional form (exponential)

Model specification: y = c*e^(b*x)

Y = 6-week cumulative additional steps taken

X = Pokemon Go trainer level

c = 3398.690925

b = 0.099527756

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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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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*


Somewhat restrictive**


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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