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European adolescents and students tend to have low levels of physical activity and eat unhealthy foods, and the prevalence of overweight and obesity has increased, which poses a public health challenge. Mobile apps play an important role in their daily lives, suggesting their potential to be used in health-promoting strategies.
This review aimed to explore how mobile apps can contribute to the promotion of healthy nutrition, physical activity, and prevention of overweight in adolescents and students. For the apps identified, the review describes the content, the theoretical mechanisms applied, and lessons learned.
The databases Scopus, MEDLINE, Embase, and PsycINFO were searched for English-language publications from January 2009 to November 2013. Studies were included if (1) the primary component of the intervention involves an app; (2) the intervention targets healthy nutrition, or physical activity, or overweight prevention; and (3) the target group included adolescents or students (aged 12-25 years).
A total of 15 studies were included, which describe 12 unique apps. Ten of these apps functioned as monitoring tools for assessing dietary intake or physical activity levels. The other apps used a Web-based platform to challenge users to exercise and to allow users to list and photograph their problem foods. For 5 apps, the behavioral theory underpinning their development was clearly specified. Frequently applied behavior change techniques are prompting self-monitoring of behavior and providing feedback on performance. Apps can function self-contained, but most of them are used as part of therapy or to strengthen school programs. From the age of 10 years users may be capable of using apps. Only 4 apps were developed specifically for adolescents. All apps were tested on a small scale and for a short period.
Despite large potential and abundant usage by young people, limited research is available on apps and health promotion for adolescents. Apps seem to be a promising health promotion strategy as a monitoring tool. Apps can enable users to set targets, enhance self‐monitoring, and increase awareness. Three apps incorporated social features, making them “social media,” but hardly any evidence appeared available about their potential.
The lifestyle of European adolescents and students poses a serious public health challenge. Adolescents and students tend to have low levels of physical activity and eat unhealthy foods. In addition, the prevalence of overweight and obesity within this group has increased in many countries. A study that monitored the physical activity of children and adolescents at ages 9, 11, 12, and 15 years found that physical activity levels decreased as children enter adolescence [
Mobile apps seem to be promising tools to help people improve their health [
An interesting question is whether apps can be applied in health promotion for adolescents and students. Additionally, it would be beneficial to know how mobile apps can be used effectively in health promotion. So far, little research has been published about their effectiveness in health promotion [
Theory-based interventions use one or more theories during their development [
Abraham and Michie [
The purpose of this review was to provide insight into how mobile apps can contribute to the promotion of healthy lifestyles among adolescents and students. We provide an overview of apps that have been developed (also) for adolescents or students with the aim of improving health, by promoting healthy nutrition, physical activity, and preventing overweight and obesity. For the apps that have been identified, we describe which theoretical mechanisms were applied during the development of the apps, and we summarize the lessons learned.
Only publications written in English were included. Furthermore, studies were included if (1) the primary component of the intervention involves a mobile app and this mobile app is already developed; (2) the intervention targets healthy nutrition, or physical activity, or overweight prevention; and (3) the focus is on adolescents and students (aged 12-25 years). Studies that also included people outside this age range (eg, 18-30 years) were included because these studies could provide valuable information regarding the primary target group. The articles were read carefully for age-specific information. The inclusion criteria for healthy nutrition include, among others, eating more vegetables and fruits, reducing soft drink or increasing water consumption, and reducing snack consumption. The applied methodology of the studies, for example, to assess effectiveness, was not an inclusion criterion because this was not relevant for answering parts 1 and 2 of the research questions (ie, the overview of existing apps and their theoretical bases). For the third part, the lessons learned, this is of relevance, and we mention the research methodology in that section of the paper.
Studies were excluded if researchers did not develop the mobile app described, if researchers did not focus on mobile apps, or if the app was used for data collection for research purposes (monitoring). Studies were included when data collection was applied with the intention of changing behavior. For example, the app served as a tool that was meant to increase awareness, a relevant step during the process of changing behavior. Other exclusion criteria were apps developed for a specific group of people with a health-related condition (patients with congenital heart disease or diabetes) and studies that focused on other preventive health issues, such as sport injuries and alcohol abuse.
The research databases Scopus, MEDLINE, Embase, and PsycINFO were searched for publications from January 2009 to November 2013 (Scopus and MEDLINE November 14, 2013; Embase, MEDLINE, and PsycINFO November 27, 2013). It was decided to include studies since January 2009 because the Apple App Store was opened in July 2008. For Scopus, the following search string was used: (((“mobile phone*” OR “smart phone*”OR “smart-phone*”) AND (“app” OR “apps” OR “application”)) AND (TITLE (physical* OR healthy OR overweight OR nutrition* OR exercise*))) AND (TITLE-ABS-KEY-AUTH (adolesc* OR young* OR school* OR teenager*)) AND (LIMIT-TO (DOCTYPE, “ar”) OR LIMIT-TO (DOCTYPE, “re”)). The following search terms were used for Embase, MEDLINE, and PsycINFO (November 27, 2013): smartphone (smart phone*, mobile phone*, game, games, gaming, mobile (all in title), phone, phones, android), exercise, sports, physical activity, food, body weight, nutrition, adolescent, young adult, youngster, teenage*, and mHealth. The extensive search strategy is shown in
Search strategy.
On the basis of title, 203 studies were screened. A total of 125 studies were excluded because they did not match the following criteria: the study was not written in English (n=2), the study was a review (n=11; reference lists were checked for additional studies), the article did not involve a mobile app (n=110), and the study was published before January 2009 (n=2). Thereafter, abstracts and, in some cases, entire studies were read. Studies were excluded based on target group (adults n=22, patients n=7), aim of the app (not part of a health promotion strategy n=4, only monitoring for research purpose n=11), topics addressed in the app (n=2), and a combination of these exclusion criteria (n=9). Furthermore, studies were excluded if the primary component of the intervention did not involve a mobile app or the mobile app was not developed by the researchers (n=8). Eventually 15 studies were included. Information of the included studies was extracted into a structured summary table. This table was not ordered by study, but by the apps, because this is the focus of this review. Some studies described several apps and some apps were described in several studies. Information of interest was information about the target group, study design, health topic, aim of the app, working mechanism of the app, mode of delivery, and use of theories and behavior change techniques (
The taxonomy developed by Abraham and Michie [
The 15 included studies describe 12 apps in total (
Two apps strove for increased physical activity levels by making the users aware of their daily amount of physical activity and by encouraging users to exercise. Eight apps aimed for dietary improvements, and 2 apps targeted both topics. Regarding dietary improvements, the apps focused on increased fruit and vegetable intake, reduced consumption of sugar-sweetened drinks, reduced excessive intake of fast food, monitoring all foods and beverages consumed, and defining problem foods.
Ten apps function as monitoring tools for assessing dietary intake or physical activity levels (
Two apps have a different approach. The Ak-Shen app uses a Web-based platform that challenges users to execute activities and to share this information with others. Users can upload this information with Global Positioning System (GPS) and camera features that are included in the app. W8Loss2Go focuses on compulsive overeating by allowing users to list and photograph their problem foods and to set targets in order to tackle this problem.
Regarding the broader context surrounding the apps, most apps are applied as part of a prevention program. The apps ePASS, eVIP, eSIYP, and eTIYP are part of TXT2BFiT, a healthy lifestyle program, which consists of a booklet, a Web site, community blogs, text messages, emails, and the apps to monitor several health conditions. The CHAT app is also part of a broader program in which students are supported by text messages. MoSeBo/DiaTrace is integrated in a structured treatment and teaching program (STTP). The app is used to assess physical activity levels and eating habits. W8Loss2Go can be used as part of a therapeutic program for obese children. Ak-Shen is implemented at school as part of a physical education class. App-Hongu contributes to a broader intervention strategy that promotes walking via a Web site containing a social element; that is, youth register as teams that can compete with each other. Other apps function on their own (MMM) or the broader context is not clearly described (Recaller, Frapp).
Characteristics of mobile apps.
No. | Mobile app | Topic (nutrition, physical activity): aim of the app | Described in the following study/studies (first author, year, country) | Reach (participants' characteristics) | Duration of the usage |
1 | ePASS | Physical activity: increase physical activity level. | Hebden, 2012, Australia [ |
21 participants at high risk of becoming overweight or obese, 18-35 years old (10 of them evaluated the app). | Not described |
Hebden, 2013, Australia [ |
RCTahas not yet been performed, unknown. | RCT has not yet been performed, unknown | |||
2 | eVIP | Nutrition: increase fruit and vegetable intake. | Hebden, 2012, Australia [ |
21 participants at high risk of becoming overweight or obese, 18-35 years old (10 of them evaluated the app). | Not described |
Hebden, 2013, Australia [ |
RCT has not yet been performed, unknown. | RCT has not yet been performed, unknown | |||
3 | eSIYP | Nutrition: reduce consumption of sugar-sweetened drinks. | Hebden, 2012, Australia [ |
21 participants at high risk of becoming overweight or obese, 18-35 years old (10 of them evaluated the app). | Not described |
Hebden, 2013, Australia [ |
RCT has not yet been performed, unknown. | RCT has not yet been performed, unknown | |||
4 | eTIYP | Nutrition: reduce excessive intake of high-fat takeout (fast-food) meals. | Hebden, 2012, Australia [ |
21 participants at high risk of becoming overweight or obese, 18-35 years old (10 of them evaluated the app). | Not described |
Hebden, 2013, Australia [ |
RCT has not yet been performed, unknown. | RCT has not yet been performed, unknown | |||
5 | CHAT (Technology Assisted Dietary Assessment (TADA) Project) | Nutrition: increase fruit and vegetable intake, reduce junk food intake. | Kerr, 2012, Australia [ |
RCT has not yet been performed, unknown. Intention is to include users aged 18-30 years living in the suburbs of Perth, Western Australia. | RCT has not yet been performed, unknown |
Zhu, 2010, USA [ |
78 participants (26 males, 52 females), 11-18 years old. | Not described | |||
Six, 2010, USA [ |
Sample 1: 78 participants (26 males, 52 females), 11-18 years old. |
Sample 1: one lunch and meal |
|||
Six, 2011, Australia [ |
15 participants (12 boys, 3 girls), adolescents. | 1 day | |||
6 | MoSeBo/DiaTrace | Nutrition, physical activity: weight reduction or stabilization. | Schiel, 2012, Germany [ |
124 participants (44% males, 56% females), average age 13.5 years. | On average 36.5 days |
Schiel, 2010, Germany [ |
30 overweight/obese participants, average age 14 years. | On average 4 days | |||
7 | Ak-Shen app (part of i-Challenge! program) | Nutrition, physical activity: increase physical activity, fruit and vegetable consumption, nutrition knowledge, motivation. | Mosqueda, 2012, USA [ |
30 healthy participants (21 males, 9 females), 11-14 years old. | 8 weeks |
8 | MMM (My Meal Mate) | Nutrition: weight loss by self-monitoring of food and drink intake. | Carter, 2012, UK [ |
50 participants (students and staff). | 7 days |
Carter, 2013, UK [ |
43 participants, 18-65 years old (66% males, 33% females). | 6 months | |||
9 | Recallerb | Nutrition: raising awareness of dietary intake and eating pattern. | Suzuki, 2012, USA [ |
41 participants, college students (median age 22 years). | 6 days |
10 | W8Loss2Goc | Nutrition: weight loss by identifying problem foods. | Pretlow, 2012, USA [ |
12 obese participants, 8-21 years old. | 2 months |
11 | FRappc | Nutrition: monitor dietary intake. | Casperson, 2013, USA [ |
17 participants, 11-14 years old. | 3-7 days |
12 | App-Hongub | Physical activity: encouraging reporting of miles walked in a physical activity program. | Hongu, 2013, USA [ |
30 participants, 11-14 years old. | Not described |
aRCT: randomized controlled trial.
bOnly a conference abstract was found and the authors did not respond to attempts to contact them.
cOnly a conference abstract was found; studies are not yet published.
Detailed information about mobile apps.
No. | Mobile app | Context | Short description of mobile app |
1 | ePASS | ePASS is part of the TXT2BFiT program, which consists of a booklet, a Web site, weight tracker, handouts, community blog, text messages, emails, personal coaching calls. | ePASS uses the target of moderate-level exercise for 30 minutes per day. Users can specify the type of activity and intensity and self-monitor their daily level of physical activity. |
2 | eVIP | eVIP is part of the TXT2BFiT program, which consists of a booklet, a Web site, weight tracker, handouts, community blog, text messages, emails, personal coaching calls. | eVIP allows users to monitor their daily intake of fruits and vegetables. A graphical display shows the number of fruits and vegetables the user recorded. As a reference, the app uses the targets of 2 servings of fruits and 5 servings of vegetables daily. |
3 | eSIYP | eSIYP is part of TXT2BFiT program, which consists of a booklet, a Web site, weight tracker, handouts, community blog, text messages, emails, personal coaching calls. | eSIYP allows users to specify the drink category (eg, water, tea or coffee, alcohol). The app presents users with a colored display with the total amounts of energy, sugar, and alcohol intake. The colors green, orange, and red indicate “ideal”, “acceptable”, and “too much” as threshold levels of intake, respectively. |
4 | eTIYP | eTIYP is part of the TXT2BFiT program, which consists of a booklet, a Web site, weight tracker, handouts, community blog, text messages, emails, personal coaching calls. | eTIYP allows users to specify the food and beverages consumed. A colored display shows the average energy and fat content of takeout meals, in which green indicates acceptable intake and red indicates excessive intake. |
5 | CHAT | CHAT used text messages to send users tailored feedback. Users are trained in using the app in advance and the app is currently developed to be used on an iPod touch. | CHAT provides users the ability to assess dietary intake (fruits, vegetables, junk food) by taking before and after pictures. Based on nutrition characteristics and volume estimation, tailored feedback and dietary recommendations are given regarding the estimated energy and nutrition. |
6 | MoSeBo/DiaTrace | The app is integrated in a structured treatment and teaching program (STTP) for overweight children and adolescents. The STTP consists of 28 therapeutic sessions in which personal goals are defined for each patient with respect to energy intake and physical activity. | The app consists of a built-in sensor that measures physical activity (mobile motion sensor, MoSeBo). The sensor measures the type, intensity, and duration of physical activity. The amount of physical activity is displayed on the display of the phone. With the camera (DiaTrace) eating habits are documented. |
7 | Ak-Shen app | i-Challenge! is an 8-week intervention that consists of an app and Web site and is part of a physical education class at junior high school. In a newsletter, a weekly i-Challenge! is delivered. An i-Challenge! is a small, fun, and challenging activity related to nutrition and physical activity intended to keep participants engaged in the project. | Ak-Shen app allows users to share activities with others. It consists of 3 components: 2 GPS-based mobile phone apps (GeoKnect and GeoSnap) and a social network, i-Challenge!. With GeoKnect and GeoSnap, the user can directly show on i-Challenge! what activity they do. With GeoKnect, a GPS-based feature, users can mark and describe points, lines, and areas of interest on a map. GeoSnap is a camera that captures photos and their descriptions and sends them automatically to the i-Challenge! Website. |
98 | MMM (My Meal Mate) | Users are also supported by tailored weekly text messages. | The MMM app allows users to set a weight loss goal and self-monitor daily calorie intake. Users select food and drinks consumed from a database and record items in an electronic food diary. Users can take photographs of their meals that serve as a memory aid. Physical activity can also be recorded in the diary. |
9 | Recaller | Not described. | Recaller is a nutrition assessment tool that allows users to take photos of all food eaten to improve diet awareness. |
10 | W8Loss2Go | Not described. | The app allows users to list and photograph their problem foods, with sequential withdrawal from each food. Furthermore, it includes a buddy and online community support. |
11 | FRapp | Not described. | FRapp is a food record app. It allows users to monitor dietary intake by taking before and after pictures of all foods and beverages consumed. |
12 | App-Hongu | The app is added to an 8-week online walking program that uses a Web site. | The app allows youth to report their walking miles. |
Of the 12 apps, 5 described behavioral theories that served as a foundation for the apps (
CHAT (app 5) is based on the self-determination theory (SDT), combined with motivational interviewing [
A behavior change theory, it is not specified which one, is applied in the development of the Ak-Shen app (app 7) [
Subsequently, it was determined which behavior change techniques, identified by Abraham and Michie [
Another frequently applied technique is “specific goal setting” (technique 10), which is applied in 6 apps, mostly with general guidelines as being the reference for the target behavior (apps 1-4). As underpinned by several authors, it is important to provide contingent rewards (technique 14). These apps provide motivational tips (apps 1-4) or tailored messages (apps 5 and 8) based on the targeted behavior. The aim of these messages is to increase users' self-efficacy and to reinforce positive behavioral beliefs. Because the authors stress the importance of providing tailored feedback, possibly this technique is also applied in the Ak-Shen app (app 7).
Two apps primarily used other techniques than self-monitoring. The Ak-Shen app (app 7) provides adolescents with specific physical activity challenges (ie, treasure hunt, mapping, earth drawing, and tag) supported by the app, which incorporates a Global Positioning System. Furthermore, this app applies a technique involving social comparison. Users can share their activities with other members.
W8Loss2Go (app 10) allows users to list and photograph their problem foods in order to prompt barrier identification. The app aims at relapse prevention by providing coping skills, showing other ways to handle negative emotions and neutralize cravings. In line with Ak-Shen (app 7), this app uses a technique involving social support. Users are, for example, linked to a buddy. Furthermore, the MoSeBo app (app 6) virtually connects users with a buddy and provides the buddy information on performance, enhancing social comparison.
Applied behavior change techniques in mobile apps.
No. | Mobile app | Theoretical basis | Behavior change techniques by Abraham and Michie [ |
Examples of applied behavior change techniques |
1 | ePASS | Transtheoretical model | Model or demonstrate behavior (9) |
9: ePASS uses healthy role models. |
2 | eVIP | Transtheoretical model | Model or demonstrate behavior (9) |
9: eVIP uses healthy role models. |
3 | eSIYP | Transtheoretical model | Model or demonstrate behavior (9) |
9: eSIYP uses healthy role models. |
4 | eTIYP | Transtheoretical model | Model or demonstrate behavior (9) |
9: eTIYP uses healthy role models. |
5 | CHAT | Self-determination theory |
Prompt specific goal setting (10) |
10: CHAT sets goals based on dietary assessment. |
6 | MoSeBo/DiaTrace | Not described | Prompt self-monitoring of behavior (12) |
12: MoSeBo/DiaTrace measures physical activity. |
7 | Ak-Shen app | Behavior change theory; not specified by the authorsa | Set graded tasks (7) |
7: The participants received four different challenges on their phones. |
8 | MMM (My Meal Mate) | Authors stress the importance of goal setting, self-monitoring, and feedback messages | Prompt specific goal setting (10) |
10: The app allows users to set weight loss goals. |
9 | Recaller | Not described | Prompt self-monitoring of behavior (12) |
12: The app provides the ability to monitor dietary intake. |
10 | W8Loss2Go | Identification of problem foods and enhancing coping skills | Prompt barrier identification (5) |
5: The user is able to list and photograph his/her problem foods. |
11 | FRapp | Not described | Prompt self-monitoring of behavior (12) |
12: The app provides the ability to monitor dietary intake. |
12 | App-Hongu | Not described | Prompt self-monitoring of behavior (12) |
12: The participants registered the miles walked with their mobile phones. |
aThe authors indicate that the app raises awareness, increases motivation, and provides tailored feedback.
To make statements regarding the lessons learned, it is important to know which research methods were used to test the apps. Only 2 studies measured the effect of using the app on the target group: Schiel et al [
Schiel et al [
Mosqueda [
In several studies, the pretests indicated that the users were willing and able to use the app. The users of CHAT (app 5) aged 11-18 years considered the software easy to use, and no difference in proficiency with the tool was found between users aged 11-14 years and 14-18 years [
Five of the included apps (apps 1-4 and app 8; described in 2 studies) also specified users outside the age range as their target population, that is, people older than 25 years. According to apps 1-4, qualitative feedback provided by young adults related to practical features such as the speed of using the app and the necessity of a login, which was considered a barrier.
Duration of usage varies largely among the apps, which makes it difficult to make statements regarding feasibility of long-term use. Some apps were only tested for several days: CHAT (app 5) was used for 1 day, Recaller (app 9) for 6 days, and FRapp (app 11) for 3-7 days [
Limited research has been done so far on mobile apps and their use in health promotion for adolescents and students. This review found only 15 studies that describe the use of 12 apps to improve the health of adolescents and students regarding their dietary intake and physical activity levels. This may seem surprising because apps are widely used, especially among adolescents and students; 23% of the European adolescents download free apps on a daily basis [
The limited number of publications concerning apps indicates the difficulty of capturing technology in science. Because of the dynamic and rapid development of apps and the long processes of doing research and publishing, it is difficult to provide up-to-date information. The MoSeBo/DiaTrace app by Schiel et al [
For 5 of the 12 included apps, the behavioral theory underpinning their development was clearly specified. The 4 apps developed by Hebden et al [
We applied the taxonomy of behavior change techniques [
Besides the behavior change techniques of self-monitoring and providing feedback on performance, specific goal setting combined with personal feedback messages is also considered as a promising approach. Kohl et al [
Three apps (MoSeBo/DiaTrace, Ak-Shen, and W8Loss2Go) offer a social function and can be categorized as social media. An example is the Ak-Shen app that uses an online platform that challenges users to execute activities and to share this information with others. The app contributes to users' motivation by providing rewards and opportunities for social comparison. Kaplan and Haenlein [
It should be clarified that we described techniques (summarized in
According to the technique “teach about environmental cues” (15), we identified one app demonstrating this potential [
Mobile apps have the potential to tackle health issues. Several arguments are mentioned in the studies. Hebden et al [
Our review not only supports the idea that apps can be a promising tool as part of health promotion strategies but also highlights that the scientific base for adolescents is small. Hardly any evidence on their effectiveness is available from high-quality research studies. Even less evidence is available for longer-term usage, which is supposed to enhance maintenance of any changes in behavior that may be achieved when using the app. Most apps are tested on a small scale only and for a short period. It is unclear for what duration the users are willing to test the apps. The MMM app (app 8) was used for 6 months (which is the longest period), but within the context of an RCT mainly involving adults [
The strength of this review is that it approaches a new area of research in which there is still much to discover and to learn. Although the search revealed a large number of hits, as summarized in
Overall, it is useful to have used the taxonomy of techniques for this review, because it clearly demonstrates the focus of these apps. It should be noted, however, that this taxonomy is primarily proposed for health promotion in adults. Some techniques, which may be particularly important for young people, could not clearly be coded; for example, the incorporation of a game or competition element. This was not part of the Hongu-app itself [
Furthermore, inaccuracies may have occurred by applying the taxonomy of behavior change techniques [
Many different terms are used to describe mobile apps: smartphone applications/smart phone applications, mobile phone-based healthy lifestyle program, using mobile devices/mobile phones, electronic health technology, and a mobile telephone record; this makes the search for relevant studies very difficult. It is because of this that the two searches in MEDLINE were not entirely consistent. As a result of a small adjustment in the research terms, not all studies found in search 1 were also included in search 2. Therefore, we decided to use both searches and to remove duplicates. It appeared necessary to use a broad definition for mobile apps. Some studies did not seem to describe a “real” mobile app. An example is the application of Schiel et al [
The present review aimed to identify mobile apps to be used in health promotion for adolescents and students. It became clear that apps are suitable as monitoring tools for both dietary intake and physical activity. The apps enable users to set targets and self-monitor, provide tailored feedback, and subsequently raise awareness and increase motivation. These types of monitoring tools can function independently, but most of the identified apps are part of a treatment program or support educational methods, that is, methods used in schools. Three apps facilitated social interaction and support and can be characterized as social media. Subsequently, these “social” apps apply other behavior change techniques, such as providing opportunities for social comparison and social support, in comparison with monitoring apps. The limited number of studies clearly indicates the need for additional research, and one may question whether this should be performed in a “traditional” way. Further research is recommended on the effectiveness, reach, and long-term use of mobile apps and to identify other possibilities to tackle health issues with mobile apps, especially with respect to their potential social features.
Search strategy Embase, MEDLINE, and PsycINFO, November 27, 2013.
Search strategy MEDLINE, November 14, 2013.
Eligible table.
Global Positioning System
randomized controlled trial
self-determination theory
structured treatment and teaching program
The authors wish to thank Mr. Adam de Jong for his advice and support and Mr. Rob van Spronsen for his assistance during the literature search.
JB is a staff member of the WHO Regional Office for Europe. The authors alone are responsible for the views expressed in this publication and they do not necessarily represent the decisions or the stated policy of the WHO.