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Several thousand mobile phone apps are available to download to mobile phones for health and fitness. Mobile phones may provide a unique means of administering health interventions to populations.
The purpose of this systematic review was to systematically search and describe the literature on mobile apps used in health behavior interventions, describe the behavioral features and focus of health apps, and to evaluate the potential of apps to disseminate health behavior interventions.
We conducted a review of the literature in September 2014 using key search terms in several relevant scientific journal databases. Only English articles pertaining to health interventions using mobile phone apps were included in the final sample.
The 24 studies identified for this review were primarily feasibility and pilot studies of mobile apps with small sample sizes. All studies were informed by behavioral theories or strategies, with self-monitoring as the most common construct. Acceptability of mobile phone apps was high among mobile phone users.
The lack of large sample studies using mobile phone apps may signal a need for additional studies on the potential use of mobile apps to assist individuals in changing their health behaviors. Of these studies, there is early evidence that apps are well received by users. Based on available research, mobile apps may be considered a feasible and acceptable means of administering health interventions, but a greater number of studies and more rigorous research and evaluations are needed to determine efficacy and establish evidence for best practices.
Since 2007, mobile phones like Apple’s iPhone and Google’s Android have taken over the mobile market; 56% of Americans now own a smartphone [
Health-related apps now number more than 31,000 [
A search of published, peer-reviewed literature was conducted in September 2014 for articles that studied health behavior interventions that utilized mobile apps. The researchers used key search terms to identify potential articles (see
Search terms for systematic review.
Search lines | Search terms | Filtered by |
Line 1 | Smartphone OR mobile phone OR Mobile device* OR tablet OR iphone OR “mobile technolog*” OR “Smart Phone” OR ipad OR mhealth OR android OR windows | Title/ Abstract |
2. AND | App OR apps OR “mobile app” OR application* | Title/Abstract |
3. AND | health OR BMI OR “heart disease” OR “physical activity” OR diabetes OR smoking OR exercise OR cancer OR obesity OR nutrition OR “public health” | Title/ Abstract |
4. AND | behavior OR behaviour OR intervention OR “controlled trial” OR RCT | Title/ Abstract |
5. NOT | developing OR telemedicine OR “text messaging” OR SMS | Title |
Our query returned 2254 articles. The authors reviewed the titles of articles and abstracts and eliminated duplicates and studies of non-human subjects, which reduced the sample to 334 articles. Further inclusion and exclusion criteria were applied to the sample of articles. Inclusion criteria included using a mobile app (iPhone, Android, or Windows); an intervention study of some type; use of behavioral theory, constructs, or strategies; studying a public health topic with health indicators reported; and published after 2007 to the time of the search (September 19, 2014). Studies were excluded if they were non-English studies, if they assessed an app through qualitative data only, if they had ambiguous language pertaining to whether or not they used a mobile phone app, or if they used a Web-based app and not specifically a mobile phone app. This resulted in a final sample of 24 articles selected for inclusion in the current systematic review (see
Systematic review of the literature flowchart.
Seventeen of the studies had a sample of less than 100 participants. Gajecki et al [
Of the studies reviewed, 14 involved interventions for physical activity and diet, four studies involved diabetes management, four for improving mental health, and only two studies involved interventions for addiction.
All of the studies incorporated at least one prominent health behavior theory construct or strategy. Self-monitoring was the most common, included in 18 of the studies. The next most commonly used constructs were cues to action and feedback (both included in nine studies each), followed by social support (six studies). Major theories used as frameworks included social cognitive theory (four studies) and self-determination theory (two studies).
Every app used for mental health and addiction was either designed with a specific behavioral strategy or selected with a behavioral construct in mind (eg, the theory of planned behavior, self-determination theory, behavioral activation approach) (100%, 6/6), and all but one of the physical activity and diet interventions were constructed after a specific construct or theory (93%, 13/14). The diabetes apps were the least likely to be designed or chosen with specific behavioral constructs in mind (25%, 1/4), or rather, the apps selected happened to include behavioral constructs.
The mean retention rate for smartphone use throughout the intervention period was 79.6%, with a low of 29% and a high of 100%. Retention rate for these studies was defined as the number of initial study participants who remained in the study through the intervention period and follow-up. Of the studies that reported on user acceptability (13 studies), most reported high user acceptability and feasibility of using smartphone apps for behavior change interventions, except Gajecki et al [
Of the diet and physical activity apps, Allen et al [
Matilla et al [
Only one of the diabetes studies reported acceptability; Cafazzo et al [
Ten studies targeted physical activity as a primary measure, and eight of them reported increases. Allen et al [
Ten studies targeted Body Mass Index (BMI) or weight loss, and all but one reported either decreases in BMI, weight loss, or decreases in body fat except one. Allen et al [
The three mental health interventions that addressed depression reported significantly decreased depression levels at follow-up, while the last one, a stress management intervention (Ahtinen et al [
It is also worth noting that many studies (Hebden et al [
Despite the thousands of health and fitness apps now available for download and the emerging interest in using them for improving health behaviors, very few have been tested in intervention settings. This lack of evaluation may be concerning because smartphone owners have an average of 41 apps installed [
Constructs from Bandura’s Social Cognitive Theory (SCT) were the most used in the reviewed studies as is evidenced by the presence of self-monitoring and social support, both prominent in SCT [
The findings of this review may demonstrate the potential of using apps to increase retention in health behavior interventions. These findings also mirror larger societal trends wherein consumer acceptance and demand for health and fitness apps to change behavior is growing [
Several of the articles reported improvements in physical activity. For example, King et al [
Ten interventions reviewed in this study reported a change in weight loss or reduction in BMI or body fat, but only three (Mattila et al [
The diabetes studies showed conflicting results. Cafazzo et al [
Watts et al [
For developers and future researchers, several of the findings of this study on acceptability of certain components of apps may be found useful. For instance, many of the studies found that users want apps that are fast and easy to use and that allow for discrete interactions in public, with many users reporting being socially conscientious of writing down or reporting personal data in public. Additionally, users reported high acceptability of apps that raised awareness of certain behaviors and provided potential cues to action. Finally, developers and researchers may find promise in integrating rewards into the interventions with smartphone apps to drive better behavioral outcomes.
The inclusion and exclusion criteria were developed in order to capture the most relevant studies involving mobile apps in behavioral interventions to impact health. However, there was no distinction made between studies that used a mobile app in one arm of a multi-group study, or if they were used as the principle focus of the study. Our aim was to not attempt to interpret the original study author’s intentions and to be more inclusive of studies involving mobile apps. Additionally, due to the dearth of apps that met the aims of this systematic review, it was beneficial to be more inclusive to better reflect the current literature. It should be noted that it may be difficult to compare these types of studies. Future systematic reviews may be able to be more restrictive once more studies begin to appear in the academic literature that are more robust and concrete in purpose.
Key future directions are recommended based on the findings of this study. The majority of these studies were pilot or feasibility studies with small samples. Considering the capacity of mobile technology to offer interventions to populations at minimal cost, this finding was surprising. Additionally, with the app industry extending into the billions of dollars, it is concerning that more money is not being put into researching the efficacy of these apps on a large scale. Several apps available for download in the Apple App and Google Play stores have several thousands of customer reviews. Some app companies boast hundreds of thousands of consistent users as well. In the future, health researchers should partner with successful app companies and producers in studying the efficacy of apps to impact health behavior on a much larger scale.
The purpose of this systematic review was to provide a description of app-based intervention studies, describe common behavioral features, and explore the acceptability and potential for apps to change behavior as currently dictated by the literature. In the small sample of reviewed studies, the majority of apps were viewed as acceptable, inclusive of theory, and efficacious at changing behavior. Moreover, the potential for scalable behavioral interventions through these technologies is promising, but largely untapped. Moving forward, researchers should focus on conducting rigorous RCT studies with adequately powered sample sizes to determine the utility of app-based health interventions. Future researchers may also focus on the potential benefits to behavior change when multiple apps are combined together in one single intervention.
Characteristics of eligible studies.
Body Mass Index
randomized controlled trial
Social Cognitive Theory
HP and CL conducted the initial systematic review of the literature, and CL and JW created the search terms for the review. HP, CL, JW, and JB all conceptualized the formatting and direction of the paper, conclusions of the findings, and contributed substantially to the writing and editing of the submitted manuscript.
None declared.