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

Journals

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3. Park J, Li J, Howren A, Tsao N, De Vera M. Mobile Phone Apps Targeting Medication Adherence: Quality Assessment and Content Analysis of User Reviews. JMIR mHealth and uHealth 2019;7(1):e11919 View
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5. Frie K, Hartmann-Boyce J, Jebb S, Oke J, Aveyard P. Patterns in Weight and Physical Activity Tracking Data Preceding a Stop in Weight Monitoring: Observational Analysis. Journal of Medical Internet Research 2020;22(3):e15790 View
6. Frie K, Hartmann-Boyce J, Jebb S, Aveyard P. Testing the effectiveness of a weight loss intervention to enhance self-regulation in adults who are obese: protocol for a randomised controlled trial. BMJ Open 2019;9(12):e031572 View
7. Claassen A, Vliet Vlieland T, Busch V, Schers H, van den Hoogen F, van den Ende C. An Electronic Health Tool to Prepare for the First Orthopedic Consultation: Use and Usability Study. JMIR Formative Research 2019;3(4):e13577 View
8. Honary M, Bell B, Clinch S, Wild S, McNaney R. Understanding the Role of Healthy Eating and Fitness Mobile Apps in the Formation of Maladaptive Eating and Exercise Behaviors in Young People. JMIR mHealth and uHealth 2019;7(6):e14239 View
9. Huberty J, Eckert R, Puzia M, Laird B, Larkey L, Mesa R. A Novel Educational Control Group Mobile App for Meditation Interventions: Single-Group Feasibility Trial. JMIR Formative Research 2020;4(7):e19364 View
10. Tavares B, Pires I, Marques G, Garcia N, Zdravevski E, Lameski P, Trajkovik V, Jevremovic A. Mobile Applications for Training Plan Using Android Devices: A Systematic Review and a Taxonomy Proposal. Information 2020;11(7):343 View
11. Fagernäs S, Hamilton W, Espinoza N, Miloff A, Carlbring P, Lindner P. What do users think about Virtual Reality relaxation applications? A mixed methods study of online user reviews using natural language processing. Internet Interventions 2021;24:100370 View
12. Gessa A, Jiménez A, Sancha P. Open Innovation in Digital Healthcare: Users’ Discrimination between Certified and Non-Certified mHealth Applications. Journal of Open Innovation: Technology, Market, and Complexity 2020;6(4):130 View
13. Zečević M, Mijatović D, Kos Koklič M, Žabkar V, Gidaković P. User Perspectives of Diet-Tracking Apps: Reviews Content Analysis and Topic Modeling. Journal of Medical Internet Research 2021;23(4):e25160 View
14. Al-Abbadey M, Fong M, Wilde L, Ingham R, Ghio D. Mobile health apps: An exploration of user-generated reviews in Google Play Store on a physical activity application. DIGITAL HEALTH 2021;7 View
15. Gessa A, Sancha P, Jiménez A. Quality Assessment of Health-apps using a Public Agency Quality and Safety Seal. The Appsaludable Case. Journal of Medical Systems 2021;45(7) View
16. ATAGÜN E, TİMUÇİN T, BİROĞUL S. Topluluk Öğrenme ile Google Uygulamalarının İçerik Derecelendirmelerini Analiz Etme. El-Cezeri Fen ve Mühendislik Dergisi 2022 View
17. Setyorini S, Mustakim . Application of The Nearest Neighbor Algorithm for Classification of Online Taxibike Sentiments In Indonesia In The Google Playstore Application. Journal of Physics: Conference Series 2021;2049(1):012026 View
18. Biviji R, Williams K, Vest J, Dixon B, Cullen T, Harle C. Consumer Perspectives on Maternal and Infant Health Apps: Qualitative Content Analysis. Journal of Medical Internet Research 2021;23(9):e27403 View
19. Nuo M, Zheng S, Wen Q, Fang H, Wang T, Liang J, Han H, Lei J. Mining the Influencing Factors and Their Asymmetrical Effects of mHealth Sleep App User Satisfaction From Real-world User-Generated Reviews: Content Analysis and Topic Modeling. Journal of Medical Internet Research 2023;25:e42856 View
20. Nitkowski J, Pitts M. Qualitative analysis of user reviews from Nurx and Planned Parenthood Direct: what user experiences reveal about telecontraception apps. Sexual Health 2022;19(5):417 View
21. Hartmann‐Boyce J, Harmer G, Hobson A, Bateman P, Tudor K, Aveyard P, Jebb S. Oxford Food and Activity Behaviors 20‐item questionnaire to assess personal weight management strategies: Development and testing. Obesity 2022;30(9):1752 View
22. Wang T, Zheng X, Liang J, An K, He Y, Nuo M, Wang W, Lei J. Use of Machine Learning to Mine User-Generated Content From Mobile Health Apps for Weight Loss to Assess Factors Correlated With User Satisfaction. JAMA Network Open 2022;5(5):e2215014 View
23. Wahyudi B. Prediksi Peringkat Aplikasi di Google Play Menggunakan Metode Random Forest. Jurnal Nasional Teknologi Komputer 2022;2(1):38 View
24. Ciolfi Felice M, Søndergaard M, Balaam M. Analyzing User Reviews of the First Digital Contraceptive: Mixed Methods Study. Journal of Medical Internet Research 2023;25:e47131 View
25. Chembakottu B, Li H, Khomh F. A large-scale exploratory study of android sports apps in the google play store. Information and Software Technology 2023;164:107321 View
26. Martin-Vicario L, Bustos Díaz J, Martínez-Sánchez M, Nicolas-Sans R. Mobile applications for weight-loss in the Spanish-speaking market: Usability and engagement. Obesity Medicine 2023;41:100499 View
27. Leitão M, Pérez-López F, Marôco J, Pimenta F. Cognitive and behavioral weight management strategies during the menopausal transition: Insights from the Menopause and Weight Loss (ME-WEL) project. Maturitas 2024;187:108060 View
28. Olaleye S, Ahiabenu K, Ojubanire O. The democratization of digital currency in Nigeria: A sentiment analysis of eNaira app usability. African Journal of Science, Technology, Innovation and Development 2024;16(5):603 View