The Most Popular Smartphone Apps for Weight Loss: A Quality Assessment

Background Advancements in mobile phone technology have led to the development of smartphones with the capability to run apps. The availability of a plethora of health- and fitness-related smartphone apps has the potential, both on a clinical and public health level, to facilitate healthy behavior change and weight management. However, current top-rated apps in this area have not been extensively evaluated in terms of scientific quality and behavioral theory evidence base. Objective The purpose of this study was to evaluate the quality of the most popular dietary weight-loss smartphone apps on the commercial market using comprehensive quality assessment criteria, and to quantify the behavior change techniques (BCTs) incorporated. Methods The top 200-rated Health & Fitness category apps from the free and paid sections of Google Play and iTunes App Store in Australia (n=800) were screened in August 2014. To be included in further analysis, an app had to focus on weight management, include a facility to record diet intake (self-monitoring), and be in English. One researcher downloaded and used the eligible apps thoroughly for 5 days and assessed the apps against quality assessment criteria which included the following domains: accountability, scientific coverage and content accuracy of information relevant to weight management, technology-enhanced features, usability, and incorporation of BCTs. For inter-rater reliability purposes, a second assessor provided ratings on 30% of the apps. The accuracy of app energy intake calculations was further investigated by comparison with results from a 3-day weighed food record (WFR). Results Across the eligible apps reviewed (n=28), only 1 app (4%) received full marks for accountability. Overall, apps included an average of 5.1 (SD 2.3) out of 14 technology-enhanced features, and received a mean score of 13.5 (SD 3.7) out of 20 for usability. The majority of apps provided estimated energy requirements (24/28, 86%) and used a food database to calculate energy intake (21/28, 75%). When compared against the WFR, the mean absolute energy difference of apps which featured energy intake calculations (23/28, 82%) was 127 kJ (95% CI -45 to 299). An average of 6.3 (SD 3.7) of 26 BCTs were included. Conclusions Overall, the most popular commercial apps for weight management are suboptimal in quality, given the inadequate scientific coverage and accuracy of weight-related information, and the relative absence of BCTs across the apps reviewed. With the limited regulatory oversight around the quality of these types of apps, this evaluation provides clinicians and consumers an informed view of the highest-quality apps in the current popular app pool appropriate for recommendation and uptake. Further research is necessary to assess the effectiveness of apps for weight management.

[1]  Gunnar Hartvigsen,et al.  Mobile Phone-Based Self-Management Tools for Type 2 Diabetes: The Few Touch Application , 2010, Journal of diabetes science and technology.

[2]  Lyndal Trevena,et al.  A systematic review of quality assessment methods for smartphone health apps. , 2015, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[3]  Lorien C Abroms,et al.  A content analysis of popular smartphone apps for smoking cessation. , 2013, American journal of preventive medicine.

[4]  Elise Dusseldorp,et al.  Combinations of techniques that effectively change health behavior: evidence from Meta-CART analysis. , 2014, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[5]  Lucy Yardley,et al.  Opportunities and challenges for smartphone applications in supporting health behavior change , 2013 .

[6]  Juho Hamari,et al.  Defining gamification: a service marketing perspective , 2012, MindTrek.

[7]  Tyler Sax,et al.  Just a Fad? Gamification in Health and Fitness Apps , 2014, JMIR serious games.

[8]  Jounghwa Choi,et al.  Smoking Cessation Apps for Smartphones: Content Analysis With the Self-Determination Theory , 2014, Journal of medical Internet research.

[9]  M. Carter,et al.  Adherence to a Smartphone Application for Weight Loss Compared to Website and Paper Diary: Pilot Randomized Controlled Trial , 2013, Journal of medical Internet research.

[10]  Miguel López-Coronado,et al.  Mobile Apps in Cardiology: Review , 2013, JMIR mHealth and uHealth.

[11]  Jerilyn K Allen,et al.  Randomized Controlled Pilot Study Testing Use of Smartphone Technology for Obesity Treatment , 2013, Journal of obesity.

[12]  Reetta Heinonen,et al.  Usability and feasibility of mobile phone diaries in an experimental physical exercise study. , 2012, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[13]  Robustillo CortésMaría de las Aguas,et al.  High Quantity But Limited Quality in Healthcare Applications Intended for HIV-Infected Patients , 2014 .

[14]  Juho Hamari,et al.  Does Gamification Work? -- A Literature Review of Empirical Studies on Gamification , 2014, 2014 47th Hawaii International Conference on System Sciences.

[15]  Jessica R L Lieffers,et al.  Use of mobile device applications in Canadian dietetic practice. , 2014, Canadian journal of dietetic practice and research : a publication of Dietitians of Canada = Revue canadienne de la pratique et de la recherche en dietetique : une publication des Dietetistes du Canada.

[16]  Lennart E. Nacke,et al.  From game design elements to gamefulness: defining "gamification" , 2011, MindTrek.

[17]  S. Michie,et al.  Using the Internet to Promote Health Behavior Change: A Systematic Review and Meta-analysis of the Impact of Theoretical Basis, Use of Behavior Change Techniques, and Mode of Delivery on Efficacy , 2010, Journal of medical Internet research.

[18]  Borja Martínez-Pérez,et al.  Mobile Health Applications for the Most Prevalent Conditions by the World Health Organization: Review and Analysis , 2013, Journal of medical Internet research.

[19]  Chi-Hong Tseng,et al.  Effectiveness of a Smartphone Application for Weight Loss Compared With Usual Care in Overweight Primary Care Patients , 2014, Annals of Internal Medicine.

[20]  J. West,et al.  There ’ s an App for That : Content Analysis of Paid Health and Fitness Apps , 2018 .

[21]  D. Ney Principles of Nutritional Assessment, 2nd Edition , 2006 .

[22]  Wilhelm Kirch,et al.  Mobile Applications for Diabetics: A Systematic Review and Expert-Based Usability Evaluation Considering the Special Requirements of Diabetes Patients Age 50 Years or Older , 2014, Journal of medical Internet research.

[23]  M. Sevick,et al.  Self-monitoring in weight loss: a systematic review of the literature. , 2011, Journal of the American Dietetic Association.

[24]  Philip T. Kortum,et al.  Determining what individual SUS scores mean: adding an adjective rating scale , 2009 .

[25]  Devin Mann,et al.  Evidence-based strategies in weight-loss mobile apps. , 2013, American journal of preventive medicine.

[26]  Margaret Allman-Farinelli,et al.  Development of Smartphone Applications for Nutrition and Physical Activity Behavior Change , 2012, JMIR research protocols.

[27]  R. Hanning,et al.  Dietary assessment and self-monitoring with nutrition applications for mobile devices. , 2012, Canadian journal of dietetic practice and research : a publication of Dietitians of Canada = Revue canadienne de la pratique et de la recherche en dietetique : une publication des Dietetistes du Canada.

[28]  J. L. Bender,et al.  A Lot of Action, But Not in the Right Direction: Systematic Review and Content Analysis of Smartphone Applications for the Prevention, Detection, and Management of Cancer , 2013, Journal of medical Internet research.

[29]  María de las Aguas Robustillo Cortés,et al.  High quantity but limited quality in healthcare applications intended for HIV-infected patients. , 2014 .

[30]  Paul A Komesaroff,et al.  "They all work...when you stick to them": A qualitative investigation of dieting, weight loss, and physical exercise, in obese individuals , 2008, Nutrition Journal.

[31]  Ara Darzi,et al.  Smartphone breast applications - what's the evidence? , 2014, Breast.

[32]  Francesc Saigí-Rubió,et al.  Use of mobile phones as a tool for weight loss: a systematic review , 2014, Journal of telemedicine and telecare.

[33]  S. Michie,et al.  Behavior Change Techniques in Popular Alcohol Reduction Apps: Content Analysis , 2015, Journal of medical Internet research.

[34]  Emily R Breton,et al.  Weight loss—there is an app for that! But does it adhere to evidence-informed practices? , 2011, Translational behavioral medicine.

[35]  Ka Ooi Gan,et al.  A scientific audit of smartphone applications for the management of obesity , 2011, Australian and New Zealand journal of public health.

[36]  Amos S Hundert,et al.  Commercially Available Mobile Phone Headache Diary Apps: A Systematic Review , 2014, JMIR mHealth and uHealth.

[37]  Inmaculada Plaza,et al.  Mindfulness-Based Mobile Applications: Literature Review and Analysis of Current Features , 2013, JMIR mHealth and uHealth.

[38]  Oksana Zelenko,et al.  Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps , 2015, JMIR mHealth and uHealth.

[39]  Alan D. Lopez,et al.  The Global Burden of Disease Study , 2003 .

[40]  James T. Miller,et al.  An Empirical Evaluation of the System Usability Scale , 2008, Int. J. Hum. Comput. Interact..

[41]  G. Hartvigsen,et al.  Features of Mobile Diabetes Applications: Review of the Literature and Analysis of Current Applications Compared Against Evidence-Based Guidelines , 2011, Journal of medical Internet research.

[42]  R. Whittaker,et al.  Do physical activity and dietary smartphone applications incorporate evidence-based behaviour change techniques? , 2014, BMC Public Health.

[43]  Alan D. Lopez,et al.  Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013 , 2014, The Lancet.

[44]  C. Abraham,et al.  A taxonomy of behavior change techniques used in interventions. , 2008, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[45]  C. Abraham,et al.  Effective techniques in healthy eating and physical activity interventions: a meta-regression. , 2009, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[46]  C L Cheney,et al.  The effect of keeping food records on eating patterns. , 1998, Journal of the American Dietetic Association.

[47]  Lora E Burke,et al.  Mobile applications for weight management: theory-based content analysis. , 2013, American journal of preventive medicine.

[48]  J. Stinson,et al.  “There’s a Pain App for That”: Review of Patient-targeted Smartphone Applications for Pain Management , 2015, The Clinical journal of pain.

[49]  Lorien C Abroms,et al.  iPhone apps for smoking cessation: a content analysis. , 2011, American journal of preventive medicine.

[50]  Rebecca Jenkinson,et al.  “Let’s get Wasted!” and Other Apps: Characteristics, Acceptability, and Use of Alcohol-Related Smartphone Applications , 2013, JMIR mHealth and uHealth.

[51]  Jerilyn K Allen,et al.  Mobile phone interventions to increase physical activity and reduce weight: a systematic review. , 2013, The Journal of cardiovascular nursing.

[52]  Charmian Reynoldson,et al.  Assessing the quality and usability of smartphone apps for pain self-management. , 2014, Pain medicine.

[53]  G D Lundberg,et al.  Assessing, controlling, and assuring the quality of medical information on the Internet: Caveant lector et viewor--Let the reader and viewer beware. , 1997, JAMA.

[54]  Christopher E. Beaudoin,et al.  Apps Seeking Theories: Results of a Study on the Use of Health Behavior Change Theories in Cancer Survivorship Mobile Apps , 2015, JMIR mHealth and uHealth.

[55]  J. L. Bender,et al.  Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace , 2015, JMIR mHealth and uHealth.

[56]  J. B. Brooke,et al.  SUS: A 'Quick and Dirty' Usability Scale , 1996 .

[57]  Ara Darzi,et al.  ‘Gamification’: Influencing health behaviours with games , 2013, Journal of the Royal Society of Medicine.

[58]  M. Allman-Farinelli,et al.  Feasibility and validity of mobile phones to assess dietary intake. , 2014, Nutrition.