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Assessment of a Mobile Game (“MobileKids Monster Manor”) to Promote Physical Activity Among Children


Abstract and Figures

Objective: The majority of children in North America are not meeting current physical activity guidelines. The purpose of this study was to evaluate the impact of a mobile phone game (“MobileKids Monster Manor”) as a tool to promote voluntary physical activity among children. Materials and Methods: The game integrates data from an accelerometer-based activity monitor (Tractivity®; Kineteks Corp., Vancouver, BC, Canada) wirelessly connected to a phone and was developed with the involvement of a team of young advisors (KidsCan Initiative: Involving Youth as Ambassadors for Research). Fifty-four children 8–13 years old completed a week of baseline data collection by wearing an accelerometer but receiving no feedback about their activity levels. The 54 children were then sequentially assigned to two groups: One group played “MobileKids Monster Manor,” and the other received daily activity feedback (steps and active minutes) via an online program. The physical activity (baseline and intervention weeks) was measured using the activity monitor and compared using two-way repeated-measures analysis of variance (intervention×time). Results: Forty-seven children with a body mass index (BMI) z-score of 0.35±1.18 successfully completed the study. Significant (P=0.01) increases in physical activity were observed during the intervention week in both the game and feedback groups (1191 and 796 steps/day, respectively). In the game group, greater physical activity was demonstrated in children with higher BMI z-score, showing 964 steps/day more per BMI z-score unit (P=0.03; 95 percent confidence interval of 98 to 1829). Conclusions: Further investigation is required to confirm that our game design promotes physical activity.
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Assessment of a Mobile Game
(‘‘MobileKids Monster Manor’’) to Promote
Physical Activity Among Children
Ainara Garde,
Aryannah Umedaly,
S. Mazdak Abulnaga,
Leah Robertson,
Anne Junker,
Jean Pierre Chanoine,
J. Mark Ansermino,
and Guy A. Dumont
Objective: The majority of children in North America are not meeting current physical activity guidelines. The
purpose of this study was to evaluate the impact of a mobile phone game (‘‘MobileKids Monster Manor’’) as a
tool to promote voluntary physical activity among children.
Materials and Methods: The game integrates data from an accelerometer-based activity monitor (Tractivity
Kineteks Corp., Vancouver, BC, Canada) wirelessly connected to a phone and was developed with the involvement
of a team of young advisors (KidsCan Initiative: Involving Youth as Ambassadors for Research). Fifty-four children
8–13 years old completed a week of baseline data collection by wearing an accelerometer but receiving no feedback
about their activity levels. The 54 children were then sequentially assigned to two groups: One group played
‘‘MobileKids Monster Manor,’’ and the other received daily activity feedback (steps and active minutes) via an
online program. The physical activity (baseline and intervention weeks) was measured using the activity monitor and
compared using two-way repeated-measures analysis of variance (intervention ·time).
Results: Forty-seven children with a body mass index (BMI) z-score of 0.35 1.18 successfully completed the
study. Significant (P=0.01) increases in physical activity were observed during the intervention week in both
the game and feedback groups (1191 and 796 steps/day, respectively). In the game group, greater physical
activity was demonstrated in children with higher BMI z-score, showing 964 steps/day more per BMI z-score
unit (P=0.03; 95 percent confidence interval of 98 to 1829).
Conclusions: Further investigation is required to confirm that our game design promotes physical activity.
Obesity is among the most urgent health problems
faced by children today. Over the past three decades, the
proportion of children who are classified as overweight or
obese has increased substantially. Globally, an estimated 170
million children and youth under 18 years of age are now
estimated to be overweight.
Being overweight or obese has
highly negative social
and health
consequences in children
and youth. Greater body mass index (BMI) is associated with
increased incidence of diseases such as diabetes, high blood
pressure, and stroke and is directly related to a reduced
quality of life and greater risk of being teased, bullied, and
social isolation.
Because of the increasing prevalence and
associated health consequences, obesity has been considered
one of the most serious health challenges of this century.
The increased prevalence of obesity has been reported to
be due to both an increase in the consumption of unhealthy
foods and a decrease in physical activity.
Globally, the
majority of children and youth do not meet current physical
activity guidelines and are considered to be physically hy-
There is a pressing need for interventions that
increase physical activity in children; understanding the
factors that influence their activity is essential to designing
such interventions.
The growing inclination of youth toward
sedentary forms of entertainment such as television,
media, and electronic games is listed as a leading cause of the
reluctance in children and youth to engage in and maintain
Electrical and Computer Engineering in Medicine Group,
Endocrinology and Diabetes Unit, Department of Pediatrics, and
Anesthesiology, Pharmacology and Therapeutics, The University of British Columbia and BC Children’s Hospital, Vancouver, British
Columbia, Canada.
Clinical and Population Studies at the Child & Family Research Institute, Vancouver, British Columbia, Canada.
GAMES FOR HEALTH JOURNAL: Research, Development, and Clinical Applications
Volume 4, Number 2, 2015
ªMary Ann Liebert, Inc.
DOI: 10.1089/g4h.2014.0095
appropriate levels of physical activity.
Thus, a possible
solution to promote physical activity among youth could be
to engage them using tools and technology that they volun-
tarily choose, such as mobile devices and games.
Several studies have been conducted to investigate the
ability of active videogames (exergames) to promote physi-
cal activity in children.
In some cases it has been found
that energy expenditure increases while playing active vi-
deogames, indicating a possible benefit.
However, ran-
domized controlled trials studying exergames have produced
mixed results.
Although some show an increase in
physical activity, others have shown no significant differ-
ence. More research on the long-term effects of playing
exergames is needed.
Exergaming is expanding as an option for reducing sed-
entary behavior in children. However, the time spent playing
indoors, on screens (television, computer, phone, video-
games), is one of the known factors inhibiting children from
being physically active.
Exergaming applied to mobile
phones may provide a fun way of promoting indoor and
outdoor physical activity that is not constrained by a home
console environment. Therefore, we designed a mobile ex-
ergame called ‘‘MobileKids Monster Manor’’ (MKMM)
with the direct involvement of a group of youth advisors to
encourage voluntary physical activity among children. In
order to increase the user’s awareness of his or her own level
of physical activity, the game integrates data from an activity
monitor wirelessly connected to the phone into a reward
The aim of this study was to assess the effectiveness of the
MKMM game in increasing physical activity. We also in-
vestigated the effect of providing feedback to children re-
garding their daily physical activity using software provided
by the activity monitor. First, we assessed the hypothesis that
although both interventions would raise physical activity
above baseline, playing the MKMM game would motivate a
greater increase among children. Second, we hypothesized
that the children would find the game highly enjoyable as it
was developed with the direct involvement of youth.
Development and design
The MKMM game was developed by Ayogo Games Inc.
(Vancouver, BC, Canada), a company focused on gaming
psychology and patient self-care. The chosen activity
monitor, Tractivity
, is a commercially available device
manufactured by Kineteks Corp. (Vancouver). Tractivity is
an accelerometer-based activity monitor that measures the
number of steps per minute. Through a wireless connection,
the data from the sensor is transmitted to the phone and
converted into points within the MKMM game (Fig. 1).
Real-world physical activity thereby generates gaming
currency that grants the user playtime in the MKMM game.
The physical activity measurements are also used to gen-
erate interpersonal competition and encourage peer support
among young users, with the aim of instilling healthy
habits. The MKMM game incorporates several theoretical
models of motivation to appeal to children between 8 and
13 years of age, based on the Self-Determination Theory
suggested by Deci and Ryan
through competence, relat-
edness, and autonomy.
MKMM players are able to receive
positive feedback from the environment and visualize their
achievements and progress within the game. They have
autonomy within the game, but also achieve milestones with
their peers. MKMM uses a monster character theme for its
graphics and rewards players with ‘‘gold’’ tokens to en-
courage them to venture through the game’s ascending
Game description
The overall goal of the MKMM game is to set the monsters
free from a number of mansions (Fig. 1.3). Players achieve this
by completing active games or challenges (Fig. 1.2), winning
˜atas’’ based on their performance and, in turn, earning
‘‘beanz,’’ the currency they need to buy ‘‘monsterrific’’ ingre-
dients. Once the players have collected all of a monster’s re-
quired ingredients, the monster will be set free, and the player can
FIG. 1. Some screen shots of the ‘‘MobileKids Monster Manor’’ (MKMM) game: (1) Loading ‘‘MobileKids Monster
Manor’’; (2) starting a challenge; (3) monster rooms; and (4) encouraging your teammates.
collect his or her ‘‘gold’’ and propel his or her team up the
leaderboards (Fig. 1.3). These aspects of choice, challenge, cu-
riosity, fantasy, and structural features are suggested by the
Theory of Motivation in Videogames
as important factors
for motivation within gaming.
As teams compete, players can see the overall team rankings
collected that day (Fig. 1.3). Players are provided an encour-
agement mechanism to provide positive support and motivation
between teammates by stimulating healthy competition, as well
as to keep players engaged over the long term (Fig. 1.4). Table 1
at the Appendix of this article provides a detailed description of
the MKMM game.
KidsCan: Involving Youth as Ambassadors for Research
Clinical research is changing, with researchers acknowl-
edging the need for direct input from the people they are
studying. This can help identify research issues and questions
that may be otherwise missed by professionals.
To involve
young people in research, a youth research advisory group,
KidsCan, has been established at the Child and Family Re-
search Institute (CFRI) in Vancouver, according to a proto-
col approved by the University of British Columbia and the
Children’s and Women’s Health Centre of British Columbia
Research Ethics Board (protocol number H13-00448). In
2013, its inaugural year, this advisory group enrolled 17
members 14–18 years of age. The aim of this initiative is to
engage youth in pediatric research not only as clinical sub-
jects, but as partners in research related to their demographic.
The KidsCan advisors played a role in several stages of the
MKMM development. They called on their social networks
and community connections to increase awareness of the
study and were part of the beta testing of the game, offering
feedback in the technical and operational details to be im-
proved prior to the study participants’ use.
Materials and Methods
A convenience sample size of 54 subjects was recruited for the
study. Subjects were recruited through poster advertisements in
local schools and community centers and through our KidsCan
young advisors.
Subjects 8–13 years of age and fluent in En-
glish were recruited according to a protocol as described above.
In addition to obtaining written informed consent from a parent/
guardian for every subject, written assent was also sought from
participants on an assent form, which described the study in an
appropriate way for the child’s age and learning abilities. Sub-
jects with a medical history that included respiratory, cardio-
vascular, and/or neurological problems were excluded from
participation. Screening for exclusion criteria was completed by
the research assistant before enrollment of the subject in the
The weight, height, and age values, reported by the chil-
dren’s parents, were used for calculating the BMI. Each BMI
value was standardized by conversion to a z-score (BMI
z-score) in groups defined by age and gender, using the World
Health Organization child growth standards.
From the 54
subjects,47(16boysand31girls)of10.21.2 (mean
standard deviation) years of age successfully completed the
study (all attrition was due to broken/lost sensors). The study
was conducted in two cohorts, during July and August 2013, at
the CFRI in Vancouver. The staged design was used to limit the
number of mobile devices required for the study.
Study design
Subjects were sequentially allocated into either the ‘‘Game’
or ‘‘Feedback’’ group (Fig. 2 and Table 2). The participants and
the research assistant were blinded to the allocation until the
beginning of the intervention. Siblings were allowed to par-
ticipate and were assigned to the same group. No systematic
bias was involved in the allocation process.
Both groups performed the same tasks in the first 7 days of
the study (baseline activity): Subjects were given the Trac-
tivity sensor and were required to wear the sensor around
their ankle at all times, apart from when in water. We applied
a within-subject study design in parallel to assess the effect
of the two different interventions (Fig. 2):
a. Intervention 1: ‘‘Game’’ group (MKMM game pro-
vided). In the second week of the study, the game
group was given an Apple (Cupertino, CA) iPhone
3GS, 4, or 4S with an installation of the MKMM game.
The iPhones were restricted to allow access only to the
game. Subjects were divided into three in-game teams
that competed remotely by having individual players’
scores accumulate into a total team score (Fig. 1.3).
b. Intervention 2: ‘‘Feedback’’ group (activity feedback,
through Tractivity online software provided). In the
second week of the study, the feedback group was
given access to the Tractivity online software and re-
ceived quantitative physical activity feedback via a
Web-based interface. The software provided subjects
with a count of total steps taken in hourly, daily, and
weekly formats. The subjects were required to check
their physical activity at least once every day.
Data collection
We recruited 54 subjects in this study. After finalizing en-
rollment, weight, height, and other demographic information
including gender and age was collected from each subject.
Physical activity was recorded in terms of steps walked and
active minutes, using the Tractivity activity monitor.
tivity software considers a minute to be active only if it con-
tains at least 20 steps and it is within a window of 7 active
minutes. Both groups were required to wear the sensor con-
tinuously for 2 weeks. The first week served as the baseline
data collection, and the second week evaluated the effect of
the intervention on their activity pattern. The data, which were
collected after the second week of the study, were saved on
password-protected servers at the CFRI.
To assess the response of the study participants’ experi-
ence with MKMM and activity monitoring, an eight-question
survey was distributed electronically to participants in the
game group. The survey was developed based on a validated
survey instrument, called the Fun Toolkit, devised to assist
researchers and developers in gathering opinions from chil-
dren about technology.
This survey posed key questions
unveiling information about players’ attitudes toward the
activity sensor, the game, the social encouragement within
gameplay, the requirement of being active to earn points, and
if the game encouraged more physical activity overall.
Data analysis
Data are summarized as mean and standard deviation.
After applying the Shapiro–Wilk normality test, a two-way
repeated-measures analysis of variance was used to inves-
tigate the hypothesis that playing the MKMM game or
having daily activity feedback increases physical activity in
children. The differences between interventions and across
weeks, in both total steps taken and total active minutes,
were studied. In addition, a linear regression model was
applied to investigate the relationships between physical
activity (steps and active minutes) and gender, age, and
BMI z-score. A probability of P<0.05 was considered
significant. All analyses were performed using IBM (Ar-
monk, NY) SPSS Statistics version 19 software.
The compliance, or ‘‘wear time,’’ is defined as the
number of hours the sensor was worn and was calculated by
subtracting ‘‘non-wear time’’ from total daily time. As
suggested by adolescent accelerometer methods, guide-
lines, and definitions,
a consecutive 60 minutes with zero
steps is considered a ‘‘non-wear time.’’ Only days with
more than 10 hours of ‘‘wear time’’ were considered, and a
minimum of 5 wearing days was required for inclusion in
the final dataset. The data were normalized with respect to
the compliance to avoid the bias introduced by the ‘‘wear
From the 54 recruited subjects, 47 successfully completed
the study. From the 29 subjects allocated to the game group,
three discontinued the study because they lost or broke their
sensor. The remaining 26 children finished the game-based
study, but three subjects were excluded from further analysis
because they did not meet the ‘‘wear time’’ criteria. From the
25 subjects allocated to the feedback group, four dis-
continued the study because they lost or broke their sensor,
and the remaining 21 subjects successfully finished the study
and met the established ‘‘wear time’’ criteria. The BMI
z-score (mean standard deviation) was 0.35 1.18 (Fig. 3).
Based on the World Health Organization guidelines, 9 per-
cent were classified as obese, 19 percent as overweight,
70 percent as normal, and 2 percent as underweight,
which represents the current BMI distribution of children in
The primary outcome of the study was the impact of each
intervention on children’s physical activity, and the sec-
ondary outcome was the MKMM game enjoyment.
Primary outcome: Intervention effect in activity
The average numbers of steps and active minutes per day
during the baseline week and during the intervention week
were calculated for each subject within the game and feed-
back group (Fig. 4). Both groups experienced a significant
increase in activity during the intervention period compared
with their baseline: The game group had an average indi-
vidual daily increase of 1191 steps and 25 active minutes,
and the feedback group averaged 796 more steps and 6 more
active minutes per day, per subject. The horizontal lines in
Figure 4a and 4b illustrate this increased tendency in steps
and active minutes during both interventions. A steeper in-
crease is reflected in the game group compared with the
feedback group, especially in active minutes.
FIG. 2. The protocol of the study for each intervention. The baseline activity of both the game group and the feedback
group was recorded during the first week and compared with the second week to evaluate the effect of both interventions.
The difference between both interventions was that during the second week, the game group was given the ‘‘MobileKids
Monster Manor’’ game with which to play, whereas the feedback group was given an online-based program to track their
daily activity (steps and active minutes). Color images available online at
Table 2. Background Information for the
Children in the Game and Feedback Groups
Game Feedback
Number (female, male) 26 (17, 9) 21 (14, 7)
Age (years) 10.2 2.5 10.3 1.3
BMI (z-score) 0.40 1.30 0.34 1.03
BMI, body mass index.
The two-way repeated-measures analysis of variance ap-
plied to steps and active minutes showed a significant in-
crease during the intervention week (F=7.8, P=0.01 and
F=6.0, P=0.03, respectively). Although the physical activity
increase was higher in the game group than in the feedback
group, the interaction between intervention (game versus
feedback) and time (Week 1 or baseline versus Week 2) was
not significant. The feedback group was more compliant and
wore the sensor significantly longer than the game group
(F=11.4, P=0.003) (Fig. 4c), which showed the require-
ment of data normalization.
A linear regression model showed that within the game
group, subjects with a higher BMI z-score had a significantly
greater increase in activity while playing the game. This effect
was reflected by an increase of 963 more steps (P=0.03; 95
percent confidence interval of 98 to 1829) and 15 more active
minutes (P=0.05; 95 percent confidence interval of 0.2 to 31)
per day for children with each unit higher BMI z-score. The
feedback group showed no significant correlation between the
BMI and the increase in physical activity.
Secondary outcome: Survey answers
Upon completion of the second week of the study, subjects
in the game group filled out a survey based on their experi-
ence playing the game and wearing the sensor. Eighty-one
percent of subjects reported liking the game, whereas 19
percent reported not enjoying it (Fig. 5). The reasons given
by the children for not liking the game were mainly related to
exercise suggestions provided by the game, namely, that the
younger children misunderstood and thought that they had to
perform the suggested activities, rather than any physically
active behavior of their choice. These children stopped
playing the MKMM early during the intervention week. By
selecting only the children who liked the game (n=22), the
results showed a greater increase reflected by 1845 more
steps per day (F=10.4, P=0.005) and 36 more active min-
utes per day (F=7.5, P=0.01) during the intervention week.
The survey also showed that 89 percent of the children
liked having to be active to score points in the MKMM game
and that 85 percent enjoyed comparing their score with the
scores of other players. In addition, 85 percent liked being
able to send and receive messages with teammates, and 93
percent of the children found the sensor easy to wear.
The aim of this study was to assess the effectiveness of
the MKMM game in increasing physical activity among
children. The goal of our MKMM game, designed for
FIG. 3. Body mass index (BMI) z-score histogram for the
47 subjects who successfully completed the study. Color
images available online at
FIG. 4. Mean and standard deviation of (a) the steps walked per day, (b) active minutes per day, and (c) compliance or
‘‘wear time’’ per day for both interventions, during baseline (Week 1) and intervention week (Week 2). The feedback group
is represented by a solid line, and the game group is indicated by a dot-dash line. The error bars reflect the standard
deviation of the steps, active minutes, and compliance within each intervention during Week 1 and Week 2. Color images
available online at
children, using advice from other young people, was to
promote voluntary physical activity by rewarding higher
levels of activity with motivational features and prizes.
Despite having advice from our KidsCan young advisors to
develop the game, the mobile-gaming intervention did not
have universal appeal among children as confirmed from
our poststudy participant survey. A statistically significant
increase was observed in physical activity during the in-
tervention week. Overall, the game had a positive outcome
because it significantly raised physical activity above
baseline, and the increase was greater than in the feedback
group. The children who reported liking the game (81
percent) showed a much greater increase than children who
reported not liking it (n=4). These results are particularly
promising, but similar to all behavioral interventions, the
MKMM game is unlikely to apply to all people with equal
success. In addition, children with a higher BMI z-score
showed a significantly greater increase in physical activity
while playing the game.
We also studied the impact of providing children with
feedback about their daily activity. For the feedback group, a
significant increase in activity between the baseline and in-
tervention weeks was also observed. Although the increase in
the game group was greater than that seen in the feedback
group (increases of 1191 versus 796 steps per day), this
difference was not significant. This reflects the fact that al-
though the knowledge of their daily activity level enhanced
the children’s activity level, more gaming features such as
social messaging and healthy competition may further mo-
tivate children to increase and sustain this behavior. The
MKMM game introduces a fun way to convert active be-
havior into points that children may find more appealing than
steps or active minutes. However, both interventions may be
favorably used to encourage a healthier lifestyle among
Self-reported physical activity has been described as an
unreliable measure of physical activity owing to recall bias
and/or its susceptibility to reporting bias by social desir-
An advantage of the MKMM game is that it is
synchronized with an activity monitor, providing objective,
real-time physical activity information to the game. The
Tractivity sensor was found to be the optimal activity mon-
itor for this study as it introduces minimal inconvenience to
the participant
and permits wireless communication with
the phone. The Tractivity device can record and store data for
long continuous periods, creating an accurate representation
of habitual activity patterns.
Implementing exergames on mobile phones, in compar-
ison with Internet- or computer-based games, has the ben-
efit of providing the ability to play while away from a
computer. MKMM is a smart mobile game in which the
players have to earn their playtime through physical ac-
tivity, thus reducing screen time relative to other games.
MKMM takes advantage of the affinity of children toward
mobile technology and gaming and is not restricted to in-
door sedentary play.
Several studies have been conducted to evaluate the
ability of active computer and video-console games to
promote physical activity among children.
active videogames often include multiplayer aspects, both
competitive and cooperative, and variable rewards.
systematic review of randomized controlled trials studying
the effect of active computer and video-console games has
shown that exergames have mixed results.
In general,
energy expenditure increased while playing active video-
games (measured by BMI changes, step count, or minutes
of daily physical activity), indicating a possible benefit to
playing active games. ‘‘MetaKenkoh,’’ for example, is an
Internet-based game for children to promote physical ac-
tivity using a pedometer to relate a player’s daily step count
to their game progress.
A pilot study on children 9–11
years of age found that using ‘‘MetaKenkoh’’ increased
physical activity by 10 percent.
However, some studies
showed no significant difference.
Baranowski et al.
reported a study of 133 participants randomized into in-
tervention and control groups where the intervention group
played two videogames designed to promote physical ac-
tivity and nutrition, whereas the control group had an In-
ternet learning experience in two parts. Although 80–90
percent of the children reported enjoying the game, physical
activity measured via accelerometry showed no significant
difference between the groups immediately after playing
the game and 2 months later. The researchers reported that
more work is needed in active game design to produce ef-
fective games conditional on behavior change, such as
MKMM. They hypothesized that there might be a greater
effect in children with a higher BMI.
Therefore, we
should remain cautious about the ability of exergames to
enhance children’s health.
One of the challenges of using games as tools to promote
activity is that the game enthusiasm decreases with time,
especially in children. A similar study found that the ma-
jority of participants increased their awareness of physical
activity levels through playing the game. However, interest
in the game faded after 2 weeks.
To further evaluate
children’s sustained interest
in the MKMM game, longer
studies will be required. The active involvement of youth in
the design and iterative improvement process will help to
find innovative ways of sustaining youth interest in the
MKMM game. However, we are hopeful that playing the
game, even for a short time period, may increase physical
FIG. 5. The answers obtained to the question, ‘‘How did
you like the MKMM [‘MobileKids Monster Manor’]
game?’’ Eighty-one percent of the subjects reported liking
(good, really good and brilliant) the game versus 19 percent
who did not find it appealing (not very good, awful). Color
images available online at
Limitations and future studies
Despite the promising results of the study, further inves-
tigation of the MKMM game is needed with an appropriately
powered randomized, controlled trial.
The high variability
in physical activity shown by children in both groups indi-
cates that a higher sample size is required to improve the
significance of the results. Therefore, to evaluate the effec-
tiveness and sustainability of the MKMM game as well as its
ability to positively affect children’s health, we plan to
perform a larger scale follow-up study that includes children
at schools in our region. This will allow us to evaluate the
game in a school-based environment to determine the ef-
fectiveness of game use in an educational setting.
The primary limitation of using activity monitors is the
reliance on the participant wearing them as directed and the
inability to verify who is wearing them. Not being able to
control compliance or ‘‘wear time’’ was a limitation of the
study because, as is illustrated in Figure 4c, the feedback
group showed higher compliance than the game group. A
possible explanation of this effect could be that although the
children in both groups were instructed to wear the sensor at
all times, the children in the game group were more focused
on the additional equipment (iPhone with MKMM) pro-
vided. In this relatively young population, the presence of the
equipment may have removed the emphasis of wearing the
activity monitor continuously, thus resulting in reduced
‘‘wear time.’’ The children of the feedback group however
were more focused on wearing the sensor at all times because
it was the sole component of their trial.
Another limitation of the study is the use of parent-
reported weight and height values rather than an objective
measurement. This makes our observation that children with
higher BMI z-score respond better to the game less reliable.
To further evaluate the results obtained in this study, showing
greater physical activity in children with a higher BMI z-score,
we aim to incorporate MKMM into the Shapedown BC obe-
sity management program (www.childhoodobesityfoundation
.ca/shapedownbc), at BC Children’s Hospital, as this cohort
consists primarily of children who are at or above the 95th
percentile for BMI. Children with higher BMIs may be more
inclined to sedentary activity using TV/smartphones, so this
game presents an opportunity to improve their physical ac-
tivity by taking advantage of their high affinity/reliance to-
ward technology. Another potential advantage of the game is
that it allows for activity within the privacy of the home, as
children in this type of program have reported embarrassment
exercising in traditional settings.
Our MKMM game, designed for children with input from
youth, enhanced physical activity, especially in children who
reported liking the game. Increasing awareness of the im-
portance of maintaining sufficient activity levels among
young people has the potential to reduce the impact of
obesity-related diseases in children and adults, thus reducing
the impact on families and the healthcare system.
This research was funded by grants from the Peter Wall
Institute for Advanced Studies under the Peter Wall Solu-
tions Initiative program (number PW-11-029) and the
Michael Smith Foundation for Health Research (number KT-
KTA-00001-112). The game developer Ayogo Games Inc.
was paid as a contractor with funds from the Peter Wall
Institute for Advanced Studies. The authors would like to
thank Ayogo Games Inc. and Kineteks Corp. for their col-
laboration and continuous feedback, Guohai Zhou for his
advice regarding statistical analyses, and Mika Johnson for
helping to revise this manuscript. The authors would also like
to especially thank the Pediatric Anesthesia Research Team
at the BC Children’s Hospital.
Author Disclosure Statement
The authors declare no competing financial interests exist.
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Address correspondence to:
Ainara Garde Martinez, PhD
Electrical and Computer Engineering in Medicine Group
BC Children’s Hospital
Clinical Support Building, Room V3-351
950 West 28th Avenue
Vancouver, BC V5Z 4H4, Canada
(Appendix follows/)
Table 1. Characteristics of a Videogame for Health: ‘‘MobileKids Monster Manor’
Characteristic Description
Health topic(s) Promoting physical activity
Targeted age group(s) Children 8–13 years of age
Other targeted group
Short description
of game idea
Physical activity captured through a biometric device advances the player’s
in-game economy, which increases the player’s virtual collections and
raises his or her team’s standing.
Target player(s) Individuals and a small group
Guiding knowledge
or behavior change
theory (or theories), models,
or conceptual framework(s)
The game builds relatedness, competence, and autonomy, consistent with
Self-Determination Theory.
Elements of challenge, curiosity, and
fantasy found in the game reflect the influence of the theory of motivation
in videogames,
which is built on attribution theory.
Intended health behavior
Increase in voluntary physical activity
Knowledge element(s)
to be learned
Awareness of the progressive benefit of daily physical activity
Behavior change procedure(s)
(taken from Michie inventory)
or therapeutic procedure(s) used
Feedback and discrepancy assessment: Individuals compare data on their
behavior with goals and standards.
Clinical or parental
support needed?
Data shared with parent
or clinician
No, but possible if required
Type of game Active
Story (if any)
synopsis (including
story arc)
The goal of the MKMM game is to unlock all of the hidden monsters in
four multilevel mansions. A secondary goal is to help your team compete
by participating in the team-to-team activity challenges. Players advance
by completing timed activity challenges, therefore earning pin
˜atas. The
˜ata releases ‘‘beanz,’’ the currency they need to buy ‘‘monsterrific’’
ingredients, which when thrown into a cauldron generate the pieces
needed to build a monster. Building a collection of monsters, mansion
furnishings, and pets generates additional ‘‘gold’’ that the player can
spend in the pin
˜ata minigame. Pin
˜atas provide variable rewards of both
‘‘beanz’’ and rare items, but the economy must be continuously
recharged by doing more exercise.
How the story relates
to targeted behavior
The story is about progression. As the player’s fantasy collection grows, the
player can relate his or her progress to healthy activity progress. Players
associate in-game progress with their increase in ability to complete
increasingly difficult physical activity challenges.
Game components:
Player’s game
By doing daily activity, players advance their team and unlock currency to
create a complete collection of monsters (and their pets and furnishings)
and manors.
Rules An activity-monitoring device must be worn by the player to participate
and earn currency. Players set personal challenges, and as they move,
data from the monitoring device prove their completion of the challenge.
Players must unlock all the monsters in one house before being able to
unlock the next house.
Game mechanic(s) Progression: To advance levels (houses), gain currency, and enrich the
economy, the player must exercise. When an activity challenge is in
progress, the player receives a countdown on progress toward his or her
activity goal.
Collection: A player builds a collection of virtual goods, including
monsters, furnishing, and pets.
Chance/variable rewards: A player purchases pin
˜atas, which the player
taps to pieces, resulting in unpredictable rewards of currency and rare
Table 1. (Continued)
Characteristic Description
Social: Players are allied on teams. The competition between teams is
based on which team collectively accumulates the most gold (through
collection and through activity). Players support each other through
positive encouragements. Team members see the team’s relative standing
on the team leaderboard.
Scheduling: The player’s collection will produce gold over time, but the
economy slows and falters without the input of physical activity.
Procedures to generalize
or transfer what’s
learned in the game
to outside the game
The game’s goal of increasing physical activity is tied to the biometric
activity monitor, which automatically synchronizes data from the device
with the app, turning those data into real-time inputs to the MKMM
The device measures the player’s actual steps and movement as the player
completes a challenge. Once complete, the player receives a pin
valued at a fixed value in gold.
Once a challenge has been completed, the gold is also attributed to the
team’s progress, advancing the team’s standing on the team leaderboard.
The app interprets data from the device and provides players with instant
feedback on their progress on a challenge.
As players successfully attempt novel physical challenges and experience
their physical abilities improving, they are expected to repeat those
activities outside of the game.
Virtual environment:
Setting A street of spooky old mansions where the player moves from mansion to
mansion as they complete their collection of monsters. Each floor of the
mansion takes on the personality of the inhabiting monster. The male and
female monsters have their own ideas of what is appealing, so they like
you to furnish their rooms with customized humorous, quirky, and not-
very-scary items.
Characteristics The individual player is identified by his or her username only and his or
her team’s identity. The characters in the game are the animated
monsters—All have a unique personality as shown by their names,
physique, mannerisms, clothing, and furniture.
Abilities Each monster is built from items that the player has purchased. Once
unlocked, they stroll around the mansion.
Game platform(s) needed
to play the game
Smartphone, iPod, or tablet
Sensors used Tractivity (real-time activity monitor)
Estimated play time 30 minutes of physical activity is required to be able to play 5–10 minutes
app, application; MKMM, ‘‘MobileKids Monster Manor’’; NA, not applicable.
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... The κ value of agreement for the screening phase was 0.64 between the 2 authors, reflecting good agreement [53]. [21][22][23][24]26,27,29,[32][33][34]36,51,52]), levels (9/18, 50%; [22,26,27,29,33,35,36,51,52]), points or scores (7/18, 39%; [22,26,27,29,30,35,36]), or the presence of a leaderboard (7/18, 39%; [22,29,30,33,34,51,52]). Almost all studies included social incentives such as team collaboration, social networking, and messaging facilities in their intervention (15/18, 83%; all except Nishiwaki et al [25], Direito et al [31], and Höchsmann et al [35]). Studies comparing gamified interventions with active control groups used a similar intervention without game elements (ie, an equivalent nongamified app [30][31][32] or a self-monitoring intervention with wearables or activity monitors [25][26][27]34,36]). ...
... The κ value of agreement for the screening phase was 0.64 between the 2 authors, reflecting good agreement [53]. [21][22][23][24]26,27,29,[32][33][34]36,51,52]), levels (9/18, 50%; [22,26,27,29,33,35,36,51,52]), points or scores (7/18, 39%; [22,26,27,29,30,35,36]), or the presence of a leaderboard (7/18, 39%; [22,29,30,33,34,51,52]). Almost all studies included social incentives such as team collaboration, social networking, and messaging facilities in their intervention (15/18, 83%; all except Nishiwaki et al [25], Direito et al [31], and Höchsmann et al [35]). Studies comparing gamified interventions with active control groups used a similar intervention without game elements (ie, an equivalent nongamified app [30][31][32] or a self-monitoring intervention with wearables or activity monitors [25][26][27]34,36]). ...
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Virtual learning objects represent an alternative to face limitations related to access, attention, or motivation that hinder effective learning when teaching healthcare. This study aims to design and validate virtual learning objects as technological tools to promote healthy lifestyles among school students. A quantitative-descriptive methodology is applied with a population sample of 224 students (9 to 11 years old) attending elementary school‟s fourth and fifth grades. The “questionnaire for healthy life habits and physical activity” was applied with a Cronbach‟s alpha of 0.81 for diagnosis. Results revealed that school students have unhealthy eating habits; 96% drink bottled juices, 65.2% eat fruits once to three times a month, and 40.2% eat pizzas or burgers three to six times a week. Regarding physical activity, 46% never or less than once a month do it with their family, 55.8% practice some kind of activity once to three times a month, and 46.9% spend time on computer or playing videogames rather than doing any physical activity. Based on the diagnosis, three virtual objects related to eating and physical activity were designed according to the stages of the Addie model. The technology and instruction-related design was validated by experts and users (school students). Most content and technical-related criteria and subcriteria obtained scores between 90% and 100% (strongly agree and agree). The study concluded that school students have inappropriate habits related to eating and physical activity.
Childhood obesity is one of the most serious public health challenges of the 21st century, with consequences lasting into adulthood. Internet of Things (IoT)-enabled devices have been studied and deployed for monitoring and tracking diet and physical activity of children and adolescents as well as a means of providing remote, ongoing support to children and their families. This review aimed to identify and understand current advances in the feasibility, system designs, and effectiveness of IoT-enabled devices to support weight management in children. We searched Medline, PubMed, Web of Science, Scopus, ProQuest Central and the IEEE Xplore Digital Library for studies published after 2010 using a combination of keywords and subject headings related to health activity tracking, weight management, youth and Internet of Things. The screening process and risk of bias assessment were conducted in accordance with a previously published protocol. Quantitative analysis was conducted for IoT-architecture related findings and qualitative analysis was conducted for effectiveness-related measures. Twenty-three full studies are included in this systematic review. The most used devices were smartphone/mobile apps (78.3%) and physical activity data (65.2%) from accelerometers (56.5%) were the most commonly tracked data. Only one study embarked on machine learning and deep learning methods in the service layer. Adherence to IoT-based approaches was low but game-based IoT solutions have shown better effectiveness and could play a pivotal role in childhood obesity interventions. Researcher-reported effectiveness measures vary greatly amongst studies, highlighting the importance for improved development and use of standardised digital health evaluation frameworks.
Introduction This systematic review and meta-analysis aims to examine the impacts of standalone gamified smartphone application-delivered interventions on physical activity. Methods Web of Science, Scopus, PubMed, PsycINFO, and ACM Digital Library were searched for publications that were published between January 1, 2008 and August 31, 2021. Eligibility criteria were RCTs or single-arm pre-to-post interventions delivered by standalone gamified applications and targeting physical activity. Study-specific results were analyzed using random-effects meta-analysis, with a standardized mean difference. Meta-regressions, subgroup analyses, and sensitivity analyses were performed. PRISMA guidelines were followed, and the Grading of Recommendations Assessment, Development and Evaluation system was used to determine the strength of the evidence. Results A total of 19 studies with 24 gamified applications were eligible, and 16 studies were included in the meta-analysis. Standalone gamified applications had a small-to-moderate effect on physical activity in both the between-group RCTs (n=12 applications, standardized mean difference=0.34, 95% CI=0.06, 0.62, I²=72%, p<0.01; Grading of Recommendations Assessment, Development and Evaluation: moderate) and the within-group pre-to-post interventions (n=18 applications, standardized mean difference=0.38, 95% CI=0.17, 0.59, I²=74%, p<0.01; Grading of Recommendations Assessment, Development and Evaluation: very low). Leave-one-out sensitivity analyses sustained the main effects with lower heterogeneity (I² of 31.0% and 47.8%, respectively). Discussion Using gamified smartphone applications as standalone interventions may increase physical activity. Future research could investigate the impacts of gamified applications on physical activity by isolating the role of specific single or clustered groups of application features.
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Background: Several reviews of mobile health (mHealth) physical activity (PA) interventions suggest their beneficial effects on behavior change in adolescents and adults. Owing to the ubiquitous presence of smartphones, their use in mHealth PA interventions seems obvious; nevertheless, there are gaps in the literature on the evaluation reporting processes and best practices of such interventions. Objective: The primary objective of this review is to analyze the development and evaluation trajectory of smartphone-based mHealth PA interventions and to review systematic theory- and evidence-based practices and methods that are implemented along this trajectory. The secondary objective is to identify the range of evidence (both quantitative and qualitative) available on smartphone-based mHealth PA interventions to provide a comprehensive tabular and narrative review of the available literature in terms of its nature, features, and volume. Methods: We conducted a scoping review of qualitative and quantitative studies examining smartphone-based PA interventions published between 2008 and 2018. In line with scoping review guidelines, studies were not rejected based on their research design or quality. This review, therefore, includes experimental and descriptive studies, as well as reviews addressing smartphone-based mHealth interventions aimed at promoting PA in all age groups (with a subanalysis conducted for adolescents). Two groups of studies were additionally included: reviews or content analyses of PA trackers and meta-analyses exploring behavior change techniques and their efficacy. Results: Included articles (N=148) were categorized into 10 groups: commercial smartphone app content analyses, smartphone-based intervention review studies, activity tracker content analyses, activity tracker review studies, meta-analyses of PA intervention studies, smartphone-based intervention studies, qualitative formative studies, app development descriptive studies, qualitative follow-up studies, and other related articles. Only 24 articles targeted children or adolescents (age range: 5-19 years). There is no agreed evaluation framework or taxonomy to code or report smartphone-based PA interventions. Researchers did not state the coding method, used various evaluation frameworks, or used different versions of behavior change technique taxonomies. In addition, there is no consensus on the best behavior change theory or model that should be used in smartphone-based interventions for PA promotion. Commonly reported systematic practices and methods have been successfully identified. They include PA recommendations, trial designs (randomized controlled trials, experimental trials, and rapid design trials), mixed methods data collection (surveys, questionnaires, interviews, and focus group discussions), scales to assess app quality, and industry-recognized reporting guidelines. Conclusions: Smartphone-based mHealth interventions aimed at promoting PA showed promising results for behavior change. Although there is a plethora of published studies on the adult target group, the number of studies and consequently the evidence base for adolescents is limited. Overall, the efficacy of smartphone-based mHealth PA interventions can be considerably improved through a more systematic approach of developing, reporting, and coding of the interventions.
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Background: Accelerometers have a distinct advantage over pedometers in the capacity to assess accurately and comprehensively physical activity and sedentary behaviours. However, the widespread use of accelerometers has been limited owing to the marked cost difference between sensors. Recent technological advancements have allowed for the development of accelerometers that are more affordable, increasing the potential usage of accelerometers on a population level. The Tractivity motion sensor has recently been developed to monitor distance, steps, and time spent during physical activities. Purpose: To examine the validity of the Tractivity sensor to measure step counts in comparison to direct observation across a range of walking speeds. Methods: Ten participants (5 M; 5 F) were evaluated during four incremental stages of treadmill walking at 2.4, 3.1, 3.5, and 4.1 mph (in randomized order). Each exercise stage lasted 6 min in duration. Step counts were evaluated (in a blinded fashion) via direct observation (video analysis) and the Tractivity sensor. Results: The Tractivity device explained 99.2% of the variance in the actual counts with no evidence of systematic bias across exercise intensity. The average difference between Tractivity device and the criterion method was -3.05 steps (0.44%) across the range of walking speeds, with the majority of step counts being within 10 steps. There was no significant difference between step counts derived by the Tractivity sensor and direct observation. Conclusion: The Tractivity sensor is a valid measure of step counts in comparison to direct observation with less than 0.5% error across a range of walking speeds.
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Effective, evidence-based, and interesting methods are needed for children's health promotion. Digital games can be such a method, but there is need for a summary of the evidence on the effectiveness of digital games in promoting children's health. The aim of this review of reviews was to evaluate the quality of systematic reviews, to summarize the evidence in systematic reviews and reviews related to the effectiveness of digital games in children's health promotion, and to identify gaps in knowledge. A systematic literature search was conducted in May–August 2013 from relevant databases, and 1178 references were found. In total, 15 systematic reviews and reviews met the inclusion criteria. Most of the systematic reviews were found to be medium quality on the AMSTAR checklist. Most commonly, systematic reviews and reviews evaluated active videogames. According to the results, evidence of the highest level and quality seems to support an increase in physical activity to light to moderate levels and energy expenditure, especially when playing active videogames that require both upper and lower body movements. In addition, sedentary games were shown to have potential in children's health education, especially in supporting changes in asthma-and diabetes-related behavior and in dietary habits. However, there are still several gaps in the knowledge. There is a need for further high-quality systematic reviews and research in the field of health games.
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Childhood obesity is a global epidemic. Health videogames are an emerging intervention strategy to combat childhood obesity. This systematic review examined published research on the effect of health videogames on childhood obesity. Fourteen articles examining 28 health videogames published between 2005 and 2013 in English were selected from 2433 articles identified through five major search engines. Results indicated that academic interest in using health videogames for childhood obesity prevention has increased during this time. Most games were commercially available. Most studies were of short duration. Diverse player and game play patterns have been identified. Most studies involved players of both genders with slightly more boys. The majority of players were non-white. Most studies had the players play the games at home, whereas some extended the play setting to school and sports/recreational facilities. Most of the games were commercially available. Positive outcomes related to obesity were observed in about 40 percent of the studies, all of which targeted overweight or obese participants.
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There is increasing interest in `moving upstream' in youth health promotion efforts to focus on building youth self-esteem, self-efficacy and civic engagement. Participatory Action Research (PAR) can be a powerful mechanism for galvanizing youth to become active agents of this change. Engaging youth in PAR and health promotion, however, is not always an easy task. This article describes a model (e-PAR) for using technology and Participatory Action Research to engage youth in community health promotion. The e-PAR Model was developed iteratively in collaboration with 57 youth and five community partners through seven projects. The Model is designed to be used with a group of youth working with a facilitator within a youth-serving organization. In addition to outlining the theoretical basis of the e-PAR Model, this article provides an overview of how the Model was developed along with implications for practice and research.
New-generation active videogames (AVGs) use motion-capture video cameras to connect a player's arm, leg, and body movements through three-dimensional space to on-screen activity. We sought to determine if the whole-body movements required to play the AVG elicited moderate-intensity physical activity (PA) in children. A secondary aim was to examine the utility of using accelerometry to measure the activity intensity of AVG play in this age group. The PA levels of boys (n=26) and girls (n=15) 5-12 years of age were measured by triaxial accelerometry (n=25) or accelerometry and indirect calorimetry (IC) (n=16) while playing the "Kinect Adventures!" videogame for the Xbox Kinect (Microsoft(®), Redmond, WA) gaming system. The experiment simulated a typical 20-minute in-home free-play gaming session. Using 10-second recording epochs, the average (mean±standard deviation) PA intensity over 20 minutes was 4.4±0.9, 3.2±0.7, and 3.3±0.6 metabolic equivalents (METs) when estimated by IC or vertical axis (Crouter et al. intermittent lifestyle equation for vertical axis counts/10 seconds [Cva2RM]) and vector magnitude (Crouter et al. intermittent lifestyle equation for vector magnitude counts/10 seconds [Cvm2RM]) accelerometry. In total, 16.9±3.2 (IC), 10.6±4.5 (Cva2RM), and 11.1±3.9 (Cvm2RM) minutes of game playing time were at a 3 MET intensity or higher. In this study, children played the Xbox Kinect AVG at moderate-intensity PA levels. The study also showed that current accelerometry-based methods underestimated the PA of AVG play compared with IC. With proper guidance and recommendations for use, video motion-capture AVG systems could reduce sedentary screen time and increase total daily moderate PA levels for children. Further study of these AVG systems is warranted.
Severe obesity afflicts between 4% and 6% of all youth in the United States, and the prevalence is increasing. Despite the serious immediate and long-term cardiovascular, metabolic, and other health consequences of severe pediatric obesity, current treatments are limited in effectiveness and lack widespread availability. Lifestyle modification/behavior-based treatment interventions in youth with severe obesity have demonstrated modest improvement in body mass index status, but participants have generally remained severely obese and often regained weight after the conclusion of the treatment programs. The role of medical management is minimal, because only 1 medication is currently approved for the treatment of obesity in adolescents. Bariatric surgery has generally been effective in reducing body mass index and improving cardiovascular and metabolic risk factors; however, reports of long-term outcomes are few, many youth with severe obesity do not qualify for surgery, and access is limited by lack of insurance coverage. To begin to address these challenges, the purposes of this scientific statement are to (1) provide justification for and recommend a standardized definition of severe obesity in children and adolescents; (2) raise awareness of this serious and growing problem by summarizing the current literature in this area in terms of the epidemiology and trends, associated health risks (immediate and long-term), and challenges and shortcomings of currently available treatment options; and (3) highlight areas in need of future research. Innovative behavior-based treatment, minimally invasive procedures, and medications currently under development all need to be evaluated for their efficacy and safety in this group of patients with high medical and psychosocial risks.