EBM Tools for Practice: Is There an App for That? Evidence-Based Practices in Mobile Health Applications

A healthy lifestyle — consisting of no smoking, healthy eating, and physical activity — and adherence to prescribed risk-reducing medication are paramount to primary prevention of atherosclerotic cardiovascular disease (ASCVD). Lifestyle interventions are included as first-line therapy in all major cholesterol management guidelines.^1,2,3 Unfortunately, less than half of all adults meet public health guidelines for physical activity,⁴ nearly 90 percent do not meet federal dietary recommendations,⁵ 67 percent are considered to be overweight or obese,⁶ and approximately 50 percent do not take their medications as prescribed.⁷

Adherence to lifestyle interventions and medications from healthcare providers decreases over time because of current barriers of primary care. The development of smartphones now offers a new and promising approach to overcoming these barriers and enhancing the delivery of behavioral interventions. A 2012 survey of 3,000 adults living in the U.S. indicated that 85 percent owned a mobile phone, with 53 percent of those being smartphones.⁸ As of 2014, 95 percent of Americans had smartphone wireless plans.⁹ Thus, smartphones now give healthcare providers the ability to reach a large number of patients to deliver multifaceted behavioral interventions, and they give patients the ability to engage in ongoing self-monitoring, regardless of the setting or location.

Indeed, the use of mobile health technologies involving smartphones is a rapidly growing focus for chronic disease management and prevention, much of which is directly applicable to primary prevention of ASCVD, including  physical activity, weight loss, smoking cessation, and medication adherence. Technology-enhanced features included in smartphone applications (apps) have the potential to reduce user burden and facilitate behavior change through integrated measurement of health parameters, social networking, patient reminders, calendar integration, and adherence prompts.

Mobile health (mHealth) apps have proliferated in recent years and now are estimated to account for more than 40,000 of the apps available in the mobile app stores for both Apple (iTunes) and Android (Google Play). It is estimated that one in five smartphone users now utilizes at least one app to support their health-related goals, and 38 percent have downloaded an app for physical activity.⁸  However, mHealth app development has far outpaced research in this area, and there has been a paucity of randomized controlled trials. A recent review by Knight, et al., found that, of 379 physical activity apps reviewed, none included the targets for aerobic exercise and only seven included targets for resistance training.¹⁰ How then are busy clinicians to recommend an app for their patients? Fortunately, some recent studies help to provide some guidance on which apps contain evidence-based lifestyle interventions and behavioral change techniques. Pagoto, et al., conducted an analysis of the 100 top-ranked paid and free apps as of January 2012 on both the iPhone and Android platforms for inclusion of the 20 behavioral strategies used in the landmark Diabetes Prevention Program (DPP) and Look AHEAD lifestyle  intervention trials. Two mobile apps that had the highest percentage of criteria met — at 65 percent — were MyNetDiary (free) and MyNetDiary Pro (paid). Apps with the next highest proportion of strategies were:

• All-in Fitness (25 percent)

• Noom Weight Loss (25 percent)

• Calorie Counter and Diet Tracker (20 percent)

• Daily Burn (20 percent)

• Spark People (20 percent)

The popular app MyFitness Pal only included 15 percent of strategies. Paid apps were no more likely than free apps to include behavioral strategies, thus price doesn’t appear to reflect the quality of evidence-based content.¹¹

Olander, et al., performed a systematic review of behavioral change techniques (BCTs) to identify those with increases in self-efficacy and physical activity behavior in obese adults. Only two BCTs had a positive association with increases in both measures: prompt self-monitoring of behavior and plan social support/change. The BCTs with the largest effect on changing physical activity were: “teaching to use prompts/cues,” “prompt practice,” and “prompt rewards contingent on effort or progress toward behavior.”¹² Middelweerd, et al., reviewed 64 apps in both iTunes and Google Play based on which of these BCTs were used in their features. Those apps with the most included BCTs included: RunKeeper (eight), followed by Big Welsh Walking Challenge, GymPush, Hubbub Health, My Pocket Coach, Sixpack, and Teemo (all seven, respectively). No differences were observed between paid and free apps. Of note, one of the two BCTs identified by Olander, et al., as having a positive effect on both self-efficacy and physical activity behavior was included in 62 of the reviewed apps, while the second of the two was included in a total of 37.¹³

Abroms, et al., reviewed 47 smoking- cessation iPhone apps to measure adherence to the U.S Public Health Service’s Clinical Practice Guidelines. Each app was evaluated by an adherence index of 20 items, each assigned a score of zero to three, with a total possible score of 60. Overall, adherence index scores were low; however, the apps with the highest scores included:

• Quit Smoking — Cold Turkey (30)

• iGuides — Stop Smoking, Now! (29.5)

• My Stop Smoking Coach with Allen Carr (23)

• iDontSmoke (20)

The most downloaded apps had among the lowest indexes.¹⁴

Dayer, et al., reviewed 160 apps available at the time on all major smartphone operating systems. Features for adherence were ranked by importance and then user tested. The top three apps were MyMedSchedule, MyMeds, and MedSimple.¹⁵

Future research on the clinical efficacy of mHealth apps is crucially needed to realize their full measure of benefits. Randomized controlled trials likely are inadequate, given their time lag in comparison to the rapid development and continuous quality improvements of the apps. In 2011, the National Institutes of Health (NIH) convened the mHealth Evidence Workshop, which described future evaluation standards, possibilities, and goals for mHealth research.

Disclosure statement: Dr. Stewart has no disclosures to report.

References are listed on page 37 of the PDF.