evaluation of a mobile phone-based diet game for weight control
Post on 11-Mar-2017
216 Views
Preview:
TRANSCRIPT
http://jtt.sagepub.com/Journal of Telemedicine and Telecare
http://jtt.sagepub.com/content/16/5/270The online version of this article can be found at:
DOI: 10.1258/jtt.2010.090913
2010 16: 270J Telemed TelecareWonbok Lee, Young Moon Chae, Sukil Kim, Seung Hee Ho and Inyoung ChoiEvaluation of a mobile phone-based diet game for weight control
Published by:
http://www.sagepublications.com
can be found at:Journal of Telemedicine and TelecareAdditional services and information for
http://jtt.sagepub.com/cgi/alertsEmail Alerts:
http://jtt.sagepub.com/subscriptionsSubscriptions:
http://www.sagepub.com/journalsReprints.navReprints:
http://www.sagepub.com/journalsPermissions.navPermissions:
What is This?
- Jul 1, 2010Version of Record >>
at CORNELL UNIV on November 5, 2014jtt.sagepub.comDownloaded from at CORNELL UNIV on November 5, 2014jtt.sagepub.comDownloaded from
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
RESEARCH Original article
Q Evaluation of a mobile phone-based dietgame for weight control
Wonbok Lee*, Young Moon Chae†, Sukil Kim‡, Seung Hee Ho§ andInyoung Choi***U-healthcare Team, LG CNS, Seoul; †Department of Health Informatics, Graduate School of Public Health, Institute of Health Service
Research, Yonsei University, Seoul; ‡Department of Preventive Medicine, College of Medicine, Catholic University of Korea, Seoul;§Research Institute of National Rehabilitation Center, Ministry for Health, Welfare and Family Affairs, Seoul; **Graduate School of
Healthcare Management and Policy, Catholic University of Korea, Seoul, Korea
Summary
We developed an interactive mobile-phone based application, SmartDiet, that analyzes daily nutrition intake and patterns
of daily exercise. It provides a personalized diet profile and promotes knowledge about nutrition using a diet game.
We evaluated the effectiveness of the SmartDiet application in terms of acquiring dietary information, weight control and
user satisfaction. A case-control study was conducted over a six-week period, with 19 people in the intervention group
and 17 people in the control group. During the study, a total of 235 successful data transmissions were performed from the
mobile phones and there was a mean of 12.4 transmissions per participant. The three body composition measures
(fat mass, weight and body mass index) decreased significantly after the intervention in the intervention group, but
there were no significant changes in the control group. In a questionnaire survey at the end of the study, the majority
of the participants responded that the system was useful for obtaining information and managing the diet process.
The SmartDiet mobile weight management application appears to contribute to weight loss in obese adults.
Introduction
Cardiovascular disease, obesity and lack of physical fitness
are increasingly common and damage people’s health. In
Korea, more than a quarter of people had a body mass index
(BMI) greater than 25 kg/m2, which is considered to
represent obesity (33% of men and 29% of women).1,2
Obesity is related to a metabolic syndrome and therefore
obese people are at a greater risk of developing
cardiovascular disease.
Several studies have shown that computer-game software
can provide nutrition knowledge, and facilitate and
reinforce dietary management for weight loss.3,4 The
board-game Kaledo increases food variety in healthy
children with problems of food refusal, and was
demonstrated to be effective in providing nutrition
knowledge and promoting a healthy dietary behaviour for
children from three middle schools in Naples, Italy.5
MetaKenkoh, a web-based activity-contingent game, also
showed potential to facilitate increased physical activity in
children.6 MOPET is a wearable system that supervises a
physical fitness activity based on alternating jogging and
fitness exercises in outdoor environments. It provides
knowledge elicited from sports physiologists and
professional trainers.7 An automatic transcript of spoken
dietary records (SDRs) facilitated the provision of real-time
dietary records.8
In addition, a web-based therapy management system
with mobile phone access has been developed for obese
patients to support weight management. After users logged
in and entered their personal information, automated
feedback with recommendations was provided.9 Educating
overweight people about healthy eating through modern
play-based educational tools appears more likely to succeed
than food prohibitions or conventional teaching.
The use of mobile phones can provide a real-time dietary
record, and therefore increase the potential advantages for
accessibility, ease of use, and options for near-instantaneous
transfer of dietary information.10 One of the main
advantages of a mobile phone is its ability to connect
wirelessly to a central computer, thus enabling the
centralization of individual nutrition and physical activity
information, in contrast to wired systems which are
constrained to the location where the connection exists. In
Korea, about 70% of the population are mobile Internet
subscribers, who use the technology as a communication
network for everyday life such as mobile shopping, banking
and advertising.11
Accepted 6 January 2010
Correspondence: Professor Young Moon Chae, Department of Health
Informatics, Graduate School of Public Health, Institute of Health Service
Research, Yonsei University, 134 Sinchon-dong, Seodaemun-gu, Seoul 120-752,
Korea (Fax: þ82 2 392 8996; Email: ymchae@yuhs.ac)
Journal of Telemedicine and Telecare 2010; 16: 270–275 DOI: 10.1258/jtt.2010.090913
at CORNELL UNIV on November 5, 2014jtt.sagepub.comDownloaded from
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
We developed the SmartDiet, a mobile phone-based
weight control system that tracks an obese patient’s daily
nutrition intake, and also has games that users can play to
learn about weight control. The SmartDiet is different from
previous dieting applications because users can download
and implement personalized dietary information onto their
personal mobile phones, rather than having to access the
mobile Internet browser every time they want to access the
diet program. The present study evaluated the effectiveness
of the mobile phone application SmartDiet with respect to
acquiring dietary information, weight control and user
satisfaction.
Methods
The SmartDiet is composed of two modules: a Diet Planner
which provides the personalized nutrition information for
food and activity, and calculates the proper calorie and
exercise level; and a Diet Game which provides a game-style
learning tool about how to control nutritional intake and
exercise. We developed it with the JBuilder software for JAVA
script programming and the SKVM communication protocol
(developed by SK Telecom) using a screen size of 240 � 320
pixels. We developed SmartDiet using a PC emulator with a
fixed 240 � 320 pixel screen size. The emulator creates a
mobile phone environment on a PC screen.
Unlike other studies on mobile phone applications for
weight control,9,12 we used the server to download the
SmartDiet program onto mobile phones and receive
information from the mobile phones, maintaining and
updating a large calorie database, storing user information,
and maintaining and updating the Diet Game. Answers in
the Diet Game (100: general dietary quiz, 101: quiz on food
intake, 102: quiz on exercise) and the calories calculated by
the SmartDiet application on the mobile phone (200: food
intake, 201: exercise) were sent to the server (see Figure 1).
Due to the limitation of the mobile phone’s memory space,
information on food intake and exercise could not be stored
in the mobile phone for a long period of time and were sent
to the server once a month.
Diet planner
User management
The user could enter demographic information via the user
management screen, except sex and blood type which were
downloaded from the server (Figure 2). Gender information
was included in the server because the recommended
calorie intake, which was calculated by the server, varies
according to the gender. We also included the blood type
because most Koreans believe that it affects individual
lifestyle and health. Lifestyle information and purpose of
use were also entered via the user management screen. In
the present study, we defined regular eating as having a
meal within one hour of the average meal time. Based on
this information, a three-dimensional image representing
the user was displayed on the screen in the form of an
Avatar. There were three types of Avatar: skinny, normal and
fat. The Avatar could be altered according to the weight
changes, enabling the user to virtually simulate their
current and future body shape.
MyPage
The MyPage application recorded the daily calorie intake
and consumption. The application automatically calculated
the essential (or suggested) calories, based on the
demographic and lifestyle information, and displayed the
calorie information for the present, previous week and
previous month (Figure 3). If the calorie intake was less than
the calorie consumption, it meant that more body fat was
used than stored. If intake was greater than consumption, a
lower calorie intake was recommended. This function can
help people to develop a diet plan and manage their own
weight.
Meal assessment
The calorie intake and consumed calories for each meal
were calculated based on the information from the food and
exercise database which contained information about 600
kinds of foods and 100 types of exercise. The database was
developed using the dietary recommendations and
Figure 1 Server data from the Smart Diet application
Figure 2 User management screen. (a) User information; (b) Purpose
of SmartDiet
W Lee et al. Mobile phone-based diet game
Journal of Telemedicine and Telecare Volume 16 Number 5 2010 271 at CORNELL UNIV on November 5, 2014jtt.sagepub.comDownloaded from
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
standards based on the book by Han.13 The suggested
calorie content for each meal, actual calorie content, and
the difference between the two were displayed on the Meal
assessment screen (Figure 4).
Exercise plan
Calorie requirements for exercise could be calculated either
manually or automatically using a stop-watch function in
the mobile phone. For example, when the user selected the
stop-watch function and began walking, the calories
consumed were calculated and displayed when he or she
finished walking.
Diet Game
The Diet Game provided a quiz-based learning tool for
recommended exercise type and intensity. It used simple
true/false quiz or multiple choice questions for exercise,
nutrition and life style. It contained three types of
questions, based on life style, calories consumed and
calories digested (Figure 5). The user could set the target
weight and could simulate a proper diet profile over a period
of six months. The target weight reduction was less than
4 kg a month to stay in a healthy condition. The contents of
the Diet Game were obtained from information in the
books by Han13 and Yoo.14 After the SmartDiet application
was developed, it was pre-tested by nutritionists and nurses
at the obesity clinic.
Study design
The effectiveness of the SmartDiet application was
evaluated based on a case-control design. A total of 19
subjects were assigned to the case or intervention group,
and 17 subjects were assigned to the control group. They
were all voluntary participants from the obese clinic at the
fitness centre in Seoul and all of them signed an informed
consent form before the intervention. All subjects were told
about the study prior to the intervention process. They were
informed about the intervention process, functions of the
SmartDiet program, how to use it and the communication
costs. However, they had to pay for the communication,
which was about $1.30 for downloading the SmartDiet
program and about $0.20 for sending the meal and exercise
information to the server. They were allowed to access the
SmartDiet game through the mobile phone Internet
connection for six weeks starting in April 2008. Body
composition for each participant was measured at the
beginning and the end of the intervention in order to assess
the changes in body composition at the clinic by using an
analyzer called the Inbody system. The demographic
characteristics and lifestyle information was surveyed on the
first day of the intervention.
Differences in demographic characteristics and lifestyle
between the intervention group and the control group were
analyzed using a chi-squared test. The changes in body
composition before and after the intervention for both
groups were compared by a paired t-test.
Results
The average ages of those in the intervention and control
groups were 28.2 and 29.5 years, respectively. The difference
Figure 3 Screenshot from the MyPage application. (a) Planning period;(b) Assessment of calorie intake for the period
Figure 5 Screenshot from the Diet Game application. (a) Title page ofthe Diet Game; (b) Diet quiz for nutrition
Figure 4 Screenshot from the meal assessment function of the SmartDiet application. (a) Calculation of calorie intake for the meal; (b)
Assessment of daily diet
W Lee et al. Mobile phone-based diet game
272 Journal of Telemedicine and Telecare Volume 16 Number 5 2010
at CORNELL UNIV on November 5, 2014jtt.sagepub.comDownloaded from
was not significant (Table 1). There were more office workers
in the intervention group (42%) than the control group
(29%). There were fewer participants without a job in the
intervention group (32%) than the control group (41%).
Most of the participants in both groups had at least a college
education. There were more participants with a monthly
income of over $4000 in the intervention group (79%) than
in the control group (59%). However, none of these
differences between the groups was significant.
Lifestyle
Percentages of participants who did not exercise were 47%
for the intervention group and 35% for the control group;
and percentages of participants who exercised more than
three times a week were 26% for the intervention group and
18% for the control group (Table 2). Participants in the
intervention group tended to eat more regularly than those
in the control group. The percentages of participants who
had never eaten irregularly were 32% for the intervention
group and 24% for the control group; the percentages of
participants who often ate irregularly were 26% for the
intervention group and 29% for the control group.
Participants in the control group ate less when they felt
stress (21%) than the participants in the control group
(24%). The percentages of participants who had never
smoked were 90% for the intervention group and 77% for
the control group. The percentages of participants who
drank more than once a week were 26% for the intervention
group and 29% for the control group. However, these
differences in lifestyle were not significantly different
between the two groups.
Data transmission
A total of 235 successful data transmissions were performed.
The mean number of transmissions was 12.4 per patient. Of
these, 62 transmissions were related to the Diet Game (47
for the general dietary quiz, 9 for the quiz on food intake
and 6 for the quiz on exercise) and 173 transmissions were
related to the Diet Planner (134 for calories on food intake
and 39 for calories on exercise).
Body composition
The three body composition measures (fat mass, weight and
BMI) were significantly decreased for the intervention
group, but none of the measures in the control group were
significantly decreased after the intervention (Table 3).
SmartDiet
The majority of the participants thought that the SmartDiet
application was useful for obtaining information (58%) and
managing the diet process (50%) (see Table 4). In particular,
83% and 67% of participants in the intervention group
responded that the system was useful for checking calories
and consumed calories. Therefore, the mobile application
was useful for obtaining dietary information.
System effectiveness
Of the participants in the intervention group, 58% agreed
that the system was easy to use and the contents were
interesting (Table 5). The cost to transmit data to the server
was about $1.5 and the participants thought it was
reasonable. All participants agreed that the system was easy
to access. Therefore, the system was judged to be very
effective in terms of content, cost and access. Fifty-eight
Table 1 Demographic characteristics. Values shown are the number of
subjects (%)
Variable
Intervention
(n 5 19)
Control
(n 5 17) P value
Age Under 25 years 6 (32) 5 (29) 0.94
26–30 years 7 (37) 5 (29)
31–35 years 4 (21) 5 (29)
Over 35 years 2 (11) 2 (12)
Occupation Office worker 8 (42) 5 (29) 0.79
Service 2 (11) 3 (18)
Professional/owner 3 (16) 2 (12)
None 6 (32) 7 (41)
Education High school 2 (11) 1 (6) 0.51
College 17 (90) 15 (88)
Graduate school 0 1 (6)
Monthly
income
Under $3000 0 4 (24) 0.11
$3000–4000 2 (12) 3 (18)
$4001–5000 8 (47) 4 (24)
Over $5000 7 (41) 6 (35)
The percentages may not add up to 100% due to rounding errors
Table 2 Lifestyle information. Values shown are the number ofsubjects (%)
Variable Response
Intervention
(n 5 19)
Control
(n 5 17)
P
value
Exercise No exercise 9 (47) 6 (35) 0.43
Less than twice a
week
5 (26) 8 (47)
More than three
times a week
5 (26) 3 (18)
Irregular
eating
Never 6 (32) 4 (24) 0.87
Sometimes 8 (42) 8 (47)
Often 5 (26) 5 (29)
Eating when
stressed
Never 9 (47) 6 (35) 0.75
Sometimes 6 (32) 7 (41)
Often 4 (21) 4 (24)
Smoking No smoking 17 (90) 13 (77) 0.49
Past smoker 1 (5) 3 (18)
Current smoker 1 (5) 1 (6)
Drinking No drinking 5 (26) 5 (29) 0.74
1–2 times a month 9 (47) 7 (41)
1–3 times a week 5 (26) 5 (29)
The percentages may not add up to 100% due to rounding errors
Table 3 Body composition before and after the intervention
Variable
Intervention (n 5 19) Control (n 5 17)
Before After t Before After t
Fat mass (kg) 17.3 16.1 2.9� 16.9 15.7 2.3
Weight (kg) 58.5 56.6 3.6� 58.3 57.8 0.8
BMI (kg/m2) 22.2 21.4 3.6� 22.3 22.1 0.9
�P , 0.05
W Lee et al. Mobile phone-based diet game
Journal of Telemedicine and Telecare Volume 16 Number 5 2010 273 at CORNELL UNIV on November 5, 2014jtt.sagepub.comDownloaded from
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
percent of the participants intended to use it in the future
and 67% of them stated that they would recommend the
system to others. In addition, most of the participants
(75%) used the system once a week and 8% used it every
day.
Discussion
Obesity is closely related to various diseases, such as
cardiovascular diseases, diabetes and hyperlipidaemia.
Previous studies have shown that dieting is effective in
reducing weight and preventing obesity. The present study
addressed whether the mobile phone application,
SmartDiet, could help people to lose weight by the
provision of immediate access to a caloric database, the
function of calorie calculation, and the Diet Game which is
a quiz-based learning tool for recommending exercise type.
The results of the present study suggest that mobile phones
have the potential to contribute to dietary management
and that people perceive the system as being useful and
effective in controlling their weight.
Mobile and wireless communication for health care
represents the evolution of telemedicine from desktop to
wearable technologies.15 There have been several attempts
to use the mobile phone to send text therapy messages to
obese patients and diabetes patients. Morak et al.9
developed a web-based management system with mobile
phone access and conducted a pilot study with obese
patients. Joo et al.12 used short text messages for sending
therapy messages to community residents and found a
reduction in their waist sizes and weights. The changes in
body weights and the BMI for obese patients from Morak’s
study were 2.4 kg and 0.78 kg/m2; and 1.6 kg and 0.6 kg/m2
for community residents from Joo’s study, respectively.
While our results (fat mass reduced by 1.2 kg, body weight
reduced by 2.0 kg and BMI reduced by 0.75 kg/m2) were not
significant, perhaps because of a short intervention period
and because many subjects were not obese, these changes
were similar to those from other studies.
In the present study, a total of 235 successful data
transmissions were performed and the mean number of
transmissions per participants was 12.4. These figures were
slightly lower than those in Morak et al.’s study (361
transmissions and 14.4 per patient). Istepanian et al.16
evaluated the effectiveness of a mobile phone monitoring
system for glycaemic control in patients with diabetes.
While these studies found that mobile phone applications
were effective in controlling obesity and diabetes, they used
simple text messages or required the subjects to use a mobile
Internet browser every time they wanted to access the
dieting program.
In our approach, we developed a dietary therapy program
with a therapy database, which can be installed on
individual mobile phones. Once the SmartDiet program was
installed onto the user’s mobile phone, it was easier to
access therapy information than by using a mobile web
browser every time the user wanted to retrieve dietary
information. This resulted in increased user satisfaction. In
addition, we used a case-control design to control for
socio-demographic factors that might have affected the
body composition measures. The findings of our study add
to those of earlier studies that reported the effectiveness of
text messaging for body composition reduction and
metabolic variables.
There were, however, some limitations to our study. Only
19 people participated in the intervention and therefore it is
difficult to generalize the results. In addition, we
encouraged the participants to enter their food intake at
every meal time and how much they exercised at every
Table 4 System usefulness (n ¼ 12)
Measurement %
Useful to get information Yes 58
Borderline 25
No 17
Useful to manage weights Yes 42
Borderline 42
No 17
Useful to manage diet process Yes 50
Borderline 42
No 8
Useful to enter dietary information Yes 50
Borderline 25
No 25
Useful to check calories Yes 83
Borderline 17
No 0
Useful to calculate consumed calories from the meal Yes 67
Borderline 25
No 8
Useful to calculate consumed calories from the exercise Yes 75
Borderline 17
No 8
Table 5 System effectiveness
%
Effectiveness of the
system
Ease of use Yes 58
Borderline 25
No 17
Information completeness Yes 33
Borderline 50
No 17
Communication cost Yes 58
Borderline 33
No 8
Contest interest Yes 58
Borderline 33
No 8
Ease of access Yes 100
Borderline 0
No 0
System use Future intention to use Yes 58
Borderline 25
No 17
Intent to recommend to
others
Yes 67
Borderline 25
No 8
Frequency of use Everyday 8
Once a week 75
1–2 times per
2 weeks
17
W Lee et al. Mobile phone-based diet game
274 Journal of Telemedicine and Telecare Volume 16 Number 5 2010
at CORNELL UNIV on November 5, 2014jtt.sagepub.comDownloaded from
exercise session, in order to examine the effects on weight.
However, only 8% of participants followed the instructions
every day and 75% of participants used the system about
once a week. Since they were all voluntary participants, we
could not force them to use the system every day. In future,
a more effective way to encourage them to use the system
will be required. Moreover, the intervention period was
limited to six weeks and therefore we were unable to
measure the long-term effects. In addition, only subjects
using SK Telecom mobile phones with a 230 � 240 pixel
screen were used in the study. Since the SmartDiet program
can be used by other mobile phones after a simple
conversion for screen size and communication protocol, it
should be tested more widely in future.
References
1 Lee Y, Lee HS, Jang YA, Lee HJ, Kim BH, Kim CI. Dietary intake pattern
of the Korean adult population by weight status: 2001 national
health and nutrition survey. Korean J Community Nutr
2006;11:317–26 [Korean]
2 Kim Y, Oh K, Jang M, Park J, Lee Y. Korea National Health and Nutrition
Examination Survey (KNHANES III) 2005. Seoul: Korea Center for Disease
Control and Prevention, 2006
3 Bartfay WJ, Bartfay E. Promoting health in schools through a board game.
West J Nurs Res 1994;16:438–46
4 Corbett RW, Lee BT. Nutriquest: a fun way to reinforce nutrition
knowledge. Nurse Educ 1992;17:33–5
5 Amaro S, Viggiano A, Di Costanzo A, et al. Kaledo, a new educational
board-game, gives nutritional rudiments and encourages healthy eating
in children: a pilot cluster randomized trial. Eur J Pediatr 2006;165:630–5
6 Southard DR, Southard BH. Promoting physical activity in children with
MetaKenkoh. Clin Invest Med 2006;29:293–7
7 Buttussi F, Chittaro L. MOPET: a context-aware and user-adaptive
wearable system for fitness training. Artif Intell Med 2008;42:153–63
8 Lacson R, Long W. Natural language processing of spoken diet records
(SDRs). AMIA Annu Symp Proc 2006:454–8
9 Morak J, Schindler K, Goerzer E, et al. A pilot study of mobile phone-based
therapy for obese patients. J Telemed Telecare 2008;14:147–9
10 Tufano JT, Karras BT. Mobile e-health interventions for obesity: a timely
opportunity to leverage convergence trends. J Med Internet Res
2005;7:58–62
11 Bang J, Choi I. South Korea: the emerging technotopia. In: Dholakia N,
Rask M, Dholakia RR, eds. M-commerce: Global Experiences and Perspectives.
Idea Group Publishing, 2006
12 Joo NS, Kim BT. Mobile phone short message service messaging for
behaviour modification in a community-based weight control
programme in Korea. J Telemed Telecare 2007;13:416–20
13 Han YS. Easy Calorie Book, vol. 1. Seoul: Hyunam Publishing, 2007
14 Yoo TW. You Can Lose 10 kg. Seoul: Samsung Publishing, 2006
15 Istepanian RSH, Laxminarayan S, Pattichis CS, eds. M-Health: Emerging
Mobile Health Systems. London: Springer, 2006
16 Istepanian RS, Zitouni K, Harry D, et al. Evaluation of a mobile phone
telemonitoring system for glycaemic control in patients with diabetes.
J Telemed Telecare 2009;15:125–8
W Lee et al. Mobile phone-based diet game
Journal of Telemedicine and Telecare Volume 16 Number 5 2010 275 at CORNELL UNIV on November 5, 2014jtt.sagepub.comDownloaded from
top related