141st APHA Annual Meeting

In This section

277179
An evaluation of weight management apps for use in clinical practice: Room for improvement

Monday, November 4, 2013 : 4:50 PM - 5:10 PM

Kristen Azar, RN MPH , Patient Outcomes and Clinical Research, Palo Alto Medical Foundation Research Institute, Palo Alto, CA
Lenard Lesser, MD MSHS , Department of Health Policy, Palo Alto Medical Foundation Research Institute, Palo Alto, CA
Brian Laing, MD , Robert Wood Johnson Foundation Clinical Scholars Program, University of California, Los Angeles, Los Angeles, CA
Janna Stephens, RN , School of Nursing, Johns Hopkins University, Baltimore, MD
Magi Aurora, BS , Patient Outcomes and Clinical Research, Palo Alto Medical Foundation Research Institute, Palo Alto, CA
Lora Burke, PhD MPH RN , School of Nursing, University of Pittsburgh, Pittsburgh, PA
Latha Palaniappan, MD MSHS , Patient Outcomes and Clinical Research, Palo Alto Medical Foundation Research Institute, Palo Alto, CA
INTRODUCTION: The use of smartphone applications (apps) to assist with weight management is highly prevalent but data on efficacy is sparse. We conducted a study to determine whether apps focused on diet and/or anthropometric tracking contain features consistent with behavioral change theory. METHODS: We conducted a comparative assessment of the top-rated free smartphone applications in the “Health and Fitness” category of the iTunes App Store (N = 200). The pre-determined inclusion/exclusion criteria to categorize apps were based on commonality in functionality, features, and stated purpose. Four researchers evaluated the two most popular apps in each category with two evaluation tools: one based on behavioral theory, and one based on interactivity. For the behavioral theory content score (TCS), apps could receive a score from 0-100, with 100 having all the features; for the interactivity score (IS), apps could receive a score from 0-6. RESULTS: We created 6 categories: 1) diet tracking, 2) healthy cooking, 3) weight tracking, 4) grocery decision making, 5) behavior tracking, and 6) restaurant decision making. For the 11 apps, the mean TCS was 8.9 (sd 4.2); the mean IS was 2.1 (sd 1.6). The top rated app on both scales was Lose It. Other highly ranked apps were: MyFitnessPal, Venio Health, Withings Health Companion, and Fooducate. CONCLUSIONS: The categories we developed may aid individuals in selecting an app that is best suited for their individual health goals. Most of the popular weight management apps received low scores for behavioral theory strategies, but earned stronger scores for interactivity. App developers may be able to make a greater impact on health by incorporating more behavioral change strategies that have demonstrated efficacy. Head to head comparisons of popular apps in clinical trials for weight loss are necessary to make evidence-based recommendations to health care professionals and the general public.

Learning Areas:
Chronic disease management and prevention
Public health or related research
Social and behavioral sciences

Learning Objectives:
Identify features of smartphone apps that are based on the behavioral theories and engagement strategies. Compare the most popular smartphone apps for weight management and identify which apps best suited for specific behavior change goals.

Keywords: Obesity, Technology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a family physician who does research on obesity and mobile technology.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.