Insights From Google Play Store User Reviews for the Development of Weight Loss Apps: Mixed-Method Analysis

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Abstract

Background

Significant weight loss takes several months to achieve, and behavioral support can enhance weight loss success. Weight loss apps could provide ongoing support and deliver innovative interventions, but to do so, developers must ensure user satisfaction.

Objective

The aim of this study was to conduct a review of Google Play Store apps to explore what users like and dislike about weight loss and weight-tracking apps and to examine qualitative feedback through analysis of user reviews.

Methods

The Google Play Store was searched and screened for weight loss apps using the search terms weight loss and weight track*, resulting in 179 mobile apps. A content analysis was conducted based on the Oxford Food and Activity Behaviors taxonomy. Correlational analyses were used to assess the association between complexity of mobile health (mHealth) apps and popularity indicators. The sample was then screened for popular apps that primarily focus on weight-tracking. For the resulting subset of 15 weight-tracking apps, 569 user reviews were sampled from the Google Play Store. Framework and thematic analysis of user reviews was conducted to assess which features users valued and how design influenced users’ responses.

Results

The complexity (number of components) of weight loss apps was significantly positively correlated with the rating ( r=.25; P=.001), number of reviews ( r=.28; P<.001), and number of downloads ( r=.48; P<.001) of the app. In contrast, in the qualitative analysis of weight-tracking apps, users expressed preference for simplicity and ease of use. In addition, we found that positive reinforcement through detailed feedback fostered users’ motivation for further weight loss. Smooth functioning and reliable data storage emerged as critical prerequisites for long-term app usage.

Conclusions

Users of weight-tracking apps valued simplicity, whereas users of comprehensive weight loss apps appreciated availability of more features, indicating that complexity demands are specific to different target populations. The provision of feedback on progress can motivate users to continue their weight loss attempts. Users value seamless functioning and reliable data storage.

Related collections

Most cited references 22

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Apps to promote physical activity among adults: a review and content analysis

Anouk Middelweerd, Julia Mollee, C Natalie van der Wal … (2014)

Background In May 2013, the iTunes and Google Play stores contained 23,490 and 17,756 smartphone applications (apps) categorized as Health and Fitness, respectively. The quality of these apps, in terms of applying established health behavior change techniques, remains unclear. Methods The study sample was identified through systematic searches in iTunes and Google Play. Search terms were based on Boolean logic and included AND combinations for physical activity, healthy lifestyle, exercise, fitness, coach, assistant, motivation, and support. Sixty-four apps were downloaded, reviewed, and rated based on the taxonomy of behavior change techniques used in the interventions. Mean and ranges were calculated for the number of observed behavior change techniques. Using nonparametric tests, we compared the number of techniques observed in free and paid apps and in iTunes and Google Play. Results On average, the reviewed apps included 5 behavior change techniques (range 2–8). Techniques such as self-monitoring, providing feedback on performance, and goal-setting were used most frequently, whereas some techniques such as motivational interviewing, stress management, relapse prevention, self-talk, role models, and prompted barrier identification were not. No differences in the number of behavior change techniques between free and paid apps, or between the app stores were found. Conclusions The present study demonstrated that apps promoting physical activity applied an average of 5 out of 23 possible behavior change techniques. This number was not different for paid and free apps or between app stores. The most frequently used behavior change techniques in apps were similar to those most frequently used in other types of physical activity promotion interventions.

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Mobile applications for weight management: theory-based content analysis.

Kristen M. J. Azar, Lenard I Lesser, Brian Laing … (2013)

The use of smartphone applications (apps) to assist with weight management is increasingly prevalent, but the quality of these apps is not well characterized. The goal of the study was to evaluate diet/nutrition and anthropometric tracking apps based on incorporation of features consistent with theories of behavior change. A comparative, descriptive assessment was conducted of the top-rated free apps in the Health and Fitness category available in the iTunes App Store. Health and Fitness apps (N=200) were evaluated using predetermined inclusion/exclusion criteria and categorized based on commonality in functionality, features, and developer description. Four researchers then evaluated the two most popular apps in each category using two instruments: one based on traditional behavioral theory (score range: 0-100) and the other on the Fogg Behavioral Model (score range: 0-6). Data collection and analysis occurred in November 2012. Eligible apps (n=23) were divided into five categories: (1) diet tracking; (2) healthy cooking; (3) weight/anthropometric tracking; (4) grocery decision making; and (5) restaurant decision making. The mean behavioral theory score was 8.1 (SD=4.2); the mean persuasive technology score was 1.9 (SD=1.7). The top-rated app on both scales was Lose It! by Fitnow Inc. All apps received low overall scores for inclusion of behavioral theory-based strategies. © 2013 American Journal of Preventive Medicine.

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Randomized trial of lifestyle modification and pharmacotherapy for obesity.

Thomas A. Wadden, Robert Berkowitz, Leslie G Womble … (2005)

Weight-loss medications are recommended as an adjunct to a comprehensive program of diet, exercise, and behavior therapy but are typically prescribed with minimal or no lifestyle modification. This practice is likely to limit therapeutic benefits. In this one-year trial, we randomly assigned 224 obese adults to receive 15 mg of sibutramine per day alone, delivered by a primary care provider in eight visits of 10 to 15 minutes each; lifestyle-modification counseling alone, delivered in 30 group sessions; sibutramine plus 30 group sessions of lifestyle-modification counseling (i.e., combined therapy); or sibutramine plus brief lifestyle-modification counseling delivered by a primary care provider in eight visits of 10 to 15 minutes each. All subjects were prescribed a diet of 1200 to 1500 kcal per day and the same exercise regimen. At one year, subjects who received combined therapy lost a mean (+/-SD) of 12.1+/-9.8 kg, whereas those receiving sibutramine alone lost 5.0+/-7.4 kg, those treated by lifestyle modification alone lost 6.7+/-7.9 kg, and those receiving sibutramine plus brief therapy lost 7.5+/-8.0 kg (P<0.001). Those in the combined-therapy group who frequently recorded their food intake lost more weight than those who did so infrequently (18.1+/-9.8 kg vs. 7.7+/-7.5 kg, P=0.04). The combination of medication and group lifestyle modification resulted in more weight loss than either medication or lifestyle modification alone. The results underscore the importance of prescribing weight-loss medications in combination with, rather than in lieu of, lifestyle modification. Copyright 2005 Massachusetts Medical Society.

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Author and article information

Contributors

Kerstin Frie:

Nuffield Department of Primary Care Health SciencesMedical Sciences DivisionUniversity of OxfordRadcliffe Primary Care Building, Radcliffe Observatory QuarterWoodstock RoadOxford, OX2 6GGUnited Kingdom44 1865289317kerstin.frie@phc.ox.ac.uk

ORCID: http://orcid.org/0000-0002-4717-5874

Journal

Journal ID (nlm-ta): JMIR Mhealth Uhealth

Journal ID (iso-abbrev): JMIR Mhealth Uhealth

Journal ID (publisher-id): JMU

Title: JMIR mHealth and uHealth

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Electronic): 2291-5222

Publication date Collection: December 2017

Publication date (Electronic): 22 December 2017

Volume: 5

Issue: 12

Electronic Location Identifier: e203

Affiliations

[1] ¹ Nuffield Department of Primary Care Health Sciences Medical Sciences Division University of Oxford Oxford United Kingdom

Author notes

Corresponding Author: Kerstin Frie kerstin.frie@ 123456phc.ox.ac.uk

Author information

Kerstin Frie http://orcid.org/0000-0002-4717-5874

Jamie Hartmann-Boyce http://orcid.org/0000-0001-9898-3049

Susan Jebb http://orcid.org/0000-0001-9190-2920

Charlotte Albury http://orcid.org/0000-0002-1036-6626

Rebecca Nourse http://orcid.org/0000-0002-1298-7346

Paul Aveyard http://orcid.org/0000-0002-1802-4217

Article

Publisher ID: v5i12e203

DOI: 10.2196/mhealth.8791

PMC ID: 5756316

PubMed ID: 29273575

SO-VID: e4728daa-708f-4bbd-9bc1-a6f078eaefe9

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 20 August 2017

Date revision requested : 21 September 2017

Date revision received : 16 October 2017

Date accepted : 29 October 2017

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