Obesity has become a worldwide epidemic. Qatar, a rapidly developing country in the Middle East, has seen a sharp increase in the prevalence of obesity. The increase can be attributed to several reasons, including sedentary lifestyles imposed by a harsh climate and the introduction of Western fast food. Mobile technologies have been used and studied as a technology to support individuals’ weight loss. The authors have developed a mobile application that implements three strategies drawn from proven theories of behavioral change. The application is localized to the cultural context of its proposed users. The objective of this paper is to present a method through which we adapted the messaging content of a weight loss application to the context of its users while retaining an effective degree of automation. The adaptation addressed body image, eating and physical exercise habits, and regional/cultural needs. The paper discusses how surveying potential users can be used to build a profile of a target population, find common patterns, and then develop a database of text messages. The text messages are automated and sent to the users at specific times of day, as suggested by the survey results.
Tackling the weight issue is a significant undertaking. Worldwide, the number of obese people has doubled in the past 20 years [
According to the International Association for the Study of Obesity, the numbers for obesity for the Qatari population are alarming. The association ranks the country sixth on its list of the most obese countries worldwide. The numbers presented in [
The implications of an overweight citizenry for a nation’s healthcare system have been widely publicized. A major challenge in addressing the problem has been to find ways to communicate the health implications of overweight and to motivate the population to adopt a healthier lifestyle. The ubiquity of cellphones has attracted the attention of some researchers as both a communication and motivational tool. In Qatar, the mobile phones subscription rate was 142% in February 2012 [
Few localized mobile applications on weight loss are available. Brunstein et al. (2012a) [
An important feature of our application is the messaging between a nutritionist and the users of the mobile application. Using messaging for mobile applications is not new and has been proven to be effective. The messaging (SMS exchange messages) function is usually used to send reminders and motivational or educational messages. Research has proved various degrees of efficacy. For example, shoppers who received advice on food substitution via SMS continued buying healthier alternatives after the program ended [
One of the advantages of automated SMSs is the ability to reach many users instantly and deliver information and motivational messages. However, the messages must be well designed to meet the dietary and physical exercise needs of individual users. Indeed, highly personalized support could be achieved by sending differentiated messages to each user, but that would be too time consuming for a nutritionist assisting them. The objective of this paper is to present a method through which we adapted the messaging content of a weight loss application to the context of its users while retaining an effective degree of automation. The adaptation addressed body image, eating and physical exercise habits, and regional/cultural needs.
In this paper, we briefly describe our application, which can be used by any user who can read English or Arabic. Our mobile application uses three features: automated motivational messages and reminders or messaging with a nutritionist, social group support, and self-monitoring of preestablished small and attainable goals. We present the application in Section
The authors of this paper worked with physicians to understand the nutritional aspect of healthy living in Qatar. In [
We also worked with nutritionists and psychologists to understand what may motivate individuals to start a healthful lifestyle or to continue one. Traditional weight loss programs may not trigger long-term change. Multiple simultaneous interventions achieve better results than single-intervention programs; the latter programs typically achieve only modest weight loss. Our analysis led to a description of how theories of behavioral change can be mapped into a mobile application to trigger change [
In [
The application was developed in both English and Arabic, using the Android platform. The usability of the application was tested and fully described in [
Screenshot of the mobile application (English version).
In the following section, we describe the method we used to construct relevant messages.
The effectiveness of automated messages will be increased if they are tailored to the targeted population group (the individuals pursuing weight loss). By tailoring we mean not only creating meaningful content but also the best times for transmitting this content and the frequency of transmissions as well. Hence, understanding the profile of participants is essential for the optimal customization of the content of these messages. We adopted the following methods.
Our first step was to design a survey to ascertain the most common eating and exercise habits of a targeted population. In the results section, we show the example of targeting a group of female Qatari college students. The survey consisted of questions pertaining to the following Demographics. Body mass index (BMI). A contour drawing rating scale (CDRS): it asks respondents to select the outline of a body that they perceive as most closely representing their own as well as one that represents their ideal figure. The CDRS was adapted from [ Eating patterns and attitudes: this survey section was adapted from a questionnaire by [ Physical activity: this survey section asked respondents if they were physically active and about the amount of time they devoted to physical activity. The section seeks to determine whether respondents fall within the recommended activity levels of the World Health Organization (WHO). WHO defines physical activity in adults (18–64) as including “leisure time physical activity (e.g., walking, dancing, gardening, hiking, and swimming), transportation (e.g., walking or cycling), occupational (i.e., work), household chores, play, games, sports or planned exercise in the context of daily, family, and community activities” [ Typical participant’s profile: we used the survey to profile a typical participant’s eating and physical exercise behaviors and patterns. The typical profile was used to later design appropriate messages as well as determine the timing and frequency for sending messages.
Body contour images used by participants.
We used authoritative references on healthful lifestyles to build a database of messages. We then reduced the messages to short, concise text. We divided the messages into categories. The appropriate categories can be devised after analyzing the survey results and determining the typical eating and physical exercise patterns of a targeted population. We had the selected messages reviewed by a nutritionist to validate the health information. We had the messages reviewed by a psychologist to ensure they were motivational and appealing. Most of the comments from the psychologist related to rephrasing the messages to address small and achievable goals and to convey positive and supportive information. A database of messages was then created. The database arranged the messages according to the frequency and time of day a message from a given category would be sent (daily, weekly, etc.).
See Figure
Application architecture.
The survey described in Section
Survey responses were further filtered, by selecting those who were native speakers of Arabic. These 26 responses were analyzed. About 65% of the native Arabic-speaking female students were 18–20 years old. The mean BMI of this group was 24.65 (which is in the normal range, overweight starting at 25 or above), in the range of 17 (underweight)–41.5 (obese class III); median and mode were 25.4 (overweight) and 27.1 (overweight), respectively, with a standard deviation of 5.62 (see Table
BMI profiles.
BMI range | Average | Median | Mode | Standard deviation | Perceived CDRS mode | Desirable CDRS mode |
---|---|---|---|---|---|---|
17–41.5 | 24.65 | 25.4 | 27.1 | 5.62 | 4 | 3 |
The most common diet was “halal” food, comparable to a kosher diet in the West. This is a religious and cultural norm, and almost all the respondents followed this particular diet. Of the 26 respondents, only two followed a low-fat diet, and two followed a vegetarian diet. These respondents with special diets, such as low fat, restricted their eating to at least two hours before sleeping or received specially planned meals from a diet shop. These persons were slightly above the normal BMI threshold and perceived their body images as normal (4-5, on a 9-point scale).
In terms of meals consumed, respondents on average consumed about two meals a day, with lunch—out of breakfast, brunch, lunch, and dinner—being the most frequent meal consumed. A large proportion of the group snacked in the afternoon (12) or throughout the day (12). The most common snacks included chocolate, chips, crackers and biscuits, cookies, cereals, and fruits.
An indicator of cultural eating habits may be the frequency with which young adults eat out or order “takeout” meals in [
Respondents were asked how frequently they ate various types of food, such as starch, dairy, meat, poultry, and fat. Table
Eating patterns: food items.
Item | Freq. | |||||
---|---|---|---|---|---|---|
Never | 1-2 | 3–5 | 6–8 | 9–11 | Total | |
Starch (bread, rice, pasta, and potato) | 0 | 15 | 8 | 3 | 0 | 26 |
Fruits | 0 | 20 | 6 | 0 | 0 | 26 |
Vegetables | 0 | 16 | 10 | 0 | 0 | 26 |
Dairy | 2 | 19 | 3 | 2 | 0 | 26 |
Meat, fish, poultry, and eggs | 0 | 15 | 8 | 2 | 1 | 26 |
Fat | 2 | 16 | 5 | 3 | 0 | 26 |
Sweets | 1 | 18 | 5 | 2 | 0 | 26 |
Respondents were asked about their intake of beverages. We compared the consumption of water with the suggested adequate intake (AI) of water. Adequate intake is the average total water intake, including direct and indirect water consumption, by a group of healthy people [
The respondents were asked if they would like to change their eating habits, and 23 of 26 responded “Yes.” The most common changes the respondents wanted to bring about were replacing unhealthful snacks with more healthful options, cutting down on junk food, reducing sugar intake, and making breakfast a regular daily meal, along with balanced meals in general (see Table
Beverages.
Item | Freq. | |||
---|---|---|---|---|
1–5 | 6–10 | Not consuming | Total | |
Water (glasses) | 20 | 6 | 0 | 26 |
Coffee | 10 | 0 | 16 | 16 |
Tea | 13 | 0 | 13 | 26 |
Soda | 7 | 0 | 19 | 26 |
Alcohol | 0 | 0 | 26 | 26 |
Others (juice, etc.) | 6 | 0 | 26 | 26 |
The final segment of the survey included the Eating Attitudes Test (EAT) (see Section
We believe that these behaviors—attitudes toward eating and concerns about body image in healthy or overweight females—may be attributable to the local social stigma pertaining to weight and body image. In the region, having a thin figure is part of what is deemed attractive. This puts social and peer pressure on females to “fit” the image of an attractive young woman. Young females are constantly concerned about their body image, and we find that even healthy females are dissatisfied with their perceived body images and want to lose weight (see the section on BMI-image dissatisfaction). These social and peer pressures, along with the social definition of attractive, may be the factors behind body image dissatisfaction and anorexic health behaviors and attitudes toward food (see Table
EATs values.
Range | Average | Median | Mode | Standard deviation | Cut-off score | Score greater than 30 |
---|---|---|---|---|---|---|
5–61 | 21.85 | 21.5 | 14 | 12.93 | 30 | 4 |
The third section of the survey asked respondents if they were physically active (see Section
Vigorous-intensity physical activity.
Estimated engagement in vigorous-intensity physical activity (minutes per week) | |||||
---|---|---|---|---|---|
<20 | 21–40 | 41–60 | 61–75 | >75 | Physically inactive |
3 | 7 | 4 | 1 | 1 | 10 |
Moderate-intensity physical activity.
Estimated engagement in moderate-intensity physical activity | ||||||
---|---|---|---|---|---|---|
<30 | 31–60 | 61–90 | 91–120 | 121–150 | >150 | Physically |
4 | 4 | 4 | 3 | 0 | 1 | 10 |
Most of the respondents fell far short of the recommended amount of physical activity (see Table
We targeted female respondents enrolled in our university who are native speakers of Arabic. We had a total of 26 respondents from the target group after filtering out male respondents, those who were not currently enrolled, or those who were not native Arabic speakers.
The typical respondent, based on the survey, is a female native speaker of Arabic who is a student in our university and between the ages of 18 and 20. She has a normal range BMI of 24.65 (her self-perceived body image is 4.23, and her desirable body image is 2.92 on a 9-point scale).
In terms of eating patterns, she follows a halal diet. Her most regular meal of the day is lunch, with breakfast being the meal most often skipped. She also snacks throughout the day; her typical snacks are chocolate, chips, crackers, or biscuits. She eats out or orders takeout meals at least once a week, and fast food is typically her first choice. American or Italian is her usual cuisine of choice. She balances various types of food preparation, such as frying, boiling, and baking, but does not typically broil. In terms of food items, her diet is balanced between starch, vegetables, dairy, meat, fat, and sweets. She should, however, increase her daily fruit intake. In terms of fluid consumption, she does not consume alcohol, but she would benefit from reducing her intake of soda and juice and also by drinking 3 to 7 more glasses of water a day. She would like to change her eating habits, starting by replacing unhealthful snacks with healthier options, cutting down on fast food, reducing her sugar intake, and having balanced meals, a goal that includes making breakfast a regular part of her day.
This typical respondent is also moderately active physically. She does not engage in enough physical activity and would benefit from significantly increasing it. She would also like to change her exercise habits by engaging in activities with more vigorous intensity, increasing the weekly frequency of her workouts, enrolling in a gymnasium, and introducing fast walking into her physical activity. Finally, in terms of her eating attitudes, she does not exhibit symptoms of anorexia nervosa.
We used the survey results to compile a database of messages. The categories for the SMS database were discerned from the survey, based on the topics that needed to be addressed. The category of “eating habits” contained messages targeting a change in eating habits, such as having balanced meals, eating at a comfortable pace and within limits, fighting urges, and replacing sugary beverages with water. A majority of the survey respondents wanted to overcome unhealthful habits, to cut down on sugar, and to eat healthful and balanced meals. A category of junk food was introduced as well. It aimed at educating the participants on the detrimental effects of junk food and at suggesting healthier alternatives, reducing the frequency of eating junk food, and suggesting alternative food preparation techniques, such as grilling or broiling instead of frying. As we have seen in the eating patterns discerned from the survey, more than half of the respondents go to fast food restaurants and would like to switch to healthier options. Consequently, we included a category on restaurants to induce healthful eating behavior when eating out on weekends with friends or family. Typical messages suggested replacing side dishes with healthier options, such as replacing fried or mashed potatoes with a salad, replacing soda with water, sharing a dessert, and starting meals with soup and salad. Thirteen of the 23 respondents who ate out or ordered takeout meals did so at least once a week, and this is another instance of behavior that we can change for the better. We introduced a category on snacks to help participants make better choices instead of trying to stop snacking entirely. The messages promote a healthier approach to snacking, such as fighting the urge to snack all the time, avoiding snacks before bedtime, keeping healthier alternatives such as fruits in sight, and doing diet-conscious grocery shopping, such as picking up water-filled grapes because they occupy more stomach volume. Finally, a category on physical activity was included because, as mentioned earlier, almost all the respondents were far short of the recommended amount of physical activity. Moreover, most of the respondents, as is the case with a majority of the population in the region, lead sedentary lifestyles with insufficient outdoor physical activity because of the unfavorable climate. Most of the respondents, as is the case with a significant number of students here, are dropped off or picked up close to the doors of the university. Hence, our messages include such suggestions as parking farther away than usual at the university and also at shopping malls and taking stairs instead of elevators. Other messages encourage working out, visiting a gymnasium regularly (with friends, to keep up motivation), as well as general messages calculated to raise awareness of the benefits of exercise (see Table
SMS categories and frequency.
Category | Number of messages | Frequency | Typical timings | Sample message |
---|---|---|---|---|
Eating habits: driving change | 23 | Daily | Breakfast (7:15 am) |
A calorie is a calorie regardless of its source. Whether you're eating carbohydrates, fats, sugars, or proteins, all of them contain calories [ |
Junk food: alternatives and awareness | 22 | At least four times a week | Lunch (12:00 pm) on Friday |
Fast foods have no nutritional value. “They are very low in vegetables. Most of it is refined products and processed foods” [ |
Restaurants: alternatives and awareness | 6 | Weekends (Thursday, Friday) | Evening (6:00 pm) | Start your meal with a soup and salad and order vegetables as your side dish [ |
Snacks: good choices | 30 | Daily | Morning (10:30 am) |
Having snacks in a convenient place to reach is helpful. Try putting fruit in a bowl on the counter, so you can grab an apple or orange when you're hungry [ |
Physical activity: | 26 | Daily | Morning (9:00 am) |
Hunt for the farthest parking space. If you drive to run errands, purposefully park your car a little farther from your store entrance [ |
This paper presented a method for designing text messages for use in a contextual mobile application. The application is designed to support achieving sustainable weight loss. With our method, text messages are not guesses aimed at targeting potential future users but are derived after creation of a profile of typical users. This profile was constructed through the use of a survey that adapted previous research into an overall design to elicit respondents eating and exercise habits as well as gain insights into their relationships to food and their perceptions of their bodies. After the typical user profile was constructed and the database of messages was developed, the messages were reviewed by a nutritionist and a by psychologist to validate their health information and to ensure they were motivational.
To illustrate our method, we ran the survey with the targeted background of young native Arabic-speaking females at our university. We analyzed their eating patterns and typical health behavior. Some of the important findings showed that the typical representative of the target population does not eat healthfully, skips meals while still maintaining a balanced diet, does not consume enough water, and does not engage in recommended amounts of physical activity. These findings allowed us to develop a customized database of text messages that can be used in a mobile application. The mobile application can be used to transmit timely text messages aimed at the nutrition and exercise habits of a typical respondent profile.
The results presented are localized to young Arab females attending universities. The derived profiles can be of interest to universities in the region as well as nutritionists concerned about healthful habits in the Middle East. However, our method does not depend on the context of the study and may be used to assess respondents’ eating and physical activity profiles. Even if used on a nonhomogeneous group (say patients attending a weight loss clinic of mixed genders, ages, and ethnicities), it is possible, through statistical analysis of the surveys, to derive profiles and adapt sets of text messages. The survey would identify not just one but as many profiles as the studied group would suggest it encompasses.
The next step in our research will be to test the application as well as its culturally adapted content through a five-week pilot study. The study will test the effectiveness of each of the three components—the SMS exchange, goal setting and progress monitoring, and social support network—of the mobile application against traditional intervention methods. The usability questionnaires, distributed exclusively to the experiment group that uses smartphones, will help assess the adaptability of the mobile application to the local context and culture. On the other hand, the health behavior questionnaires, given to both the experiment and the control groups, will help track participants’ changes in health behavior and attitudes; they also will yield qualitative information, such as temptations encountered and how participants overcame them.
A future study lasting 15 weeks would permit firmer conclusions about the application’s effectiveness because it will enable measurement of behavioral changes and weight loss over a longer duration. This will help assess any sustainable weight loss and behavioral change. It will also enable researchers to evaluate each aspect of the mobile application and hence the underlying theories of behavioral change.
The authors declare that there is no conflict of interests regarding the publication of this paper.
The authors would like to acknowledge that the work for this paper was partly funded by the Qatar Foundation for Education, Science and Community Development. The statements made herein are solely the responsibility of the authors and do not reflect any official position by the Qatar Foundation or Carnegie Mellon University.