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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

  

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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

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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

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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

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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

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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

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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.

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