How Do Infant Feeding Apps in China Measure Up? A Content Quality Assessment

Journals

1. Cheng H, Tutt A, Llewellyn C, Size D, Jones J, Taki S, Rossiter C, Denney-Wilson E. Content and Quality of Infant Feeding Smartphone Apps: Five-Year Update on a Systematic Search and Evaluation. JMIR mHealth and uHealth 2020;8(5):e17300 View
2. Tang K, Gerling K, Chen W, Geurts L. Information and Communication Systems to Tackle Barriers to Breastfeeding: Systematic Search and Review. Journal of Medical Internet Research 2019;21(9):e13947 View
3. Jiang H, Li M, Wen L, Baur L, He G, Ma X, Qian X. A Short Message Service Intervention for Improving Infant Feeding Practices in Shanghai, China: Planning, Implementation, and Process Evaluation. JMIR mHealth and uHealth 2018;6(10):e11039 View
4. Alamoodi A, Garfan S, Zaidan B, Zaidan A, Shuwandy M, Alaa M, Alsalem M, Mohammed A, Aleesa A, Albahri O, Al-Hussein W, Alobaidi O. A systematic review into the assessment of medical apps: motivations, challenges, recommendations and methodological aspect. Health and Technology 2020;10(5):1045 View
5. Zhao J, Li M, Freeman B. A Baby Formula Designed for Chinese Babies: Content Analysis of Milk Formula Advertisements on Chinese Parenting Apps. JMIR mHealth and uHealth 2019;7(11):e14219 View
6. Taki S, Russell C, Wen L, Laws R, Campbell K, Xu H, Denney-Wilson E. Consumer Engagement in Mobile Application (App) Interventions Focused on Supporting Infant Feeding Practices for Early Prevention of Childhood Obesity. Frontiers in Public Health 2019;7 View
7. Wu Y, Ma X, Fraser W, Li M, Wang W, Huang H, Landry M, Hao Y, Liu H, Semenic S, Zhang Y, Wang H, Zhang J, Yu J, La X, Zhang C, Marc I, Jiang H. Caregivers’ perceptions, challenges and service needs related to tackling childhood overweight and obesity: a qualitative study in three districts of Shanghai, China. BMC Public Health 2021;21(1) View
8. Woulfe F, Fadahunsi K, Smith S, Chirambo G, Larsson E, Henn P, Mawkin M, O’ Donoghue J. Identification and Evaluation of Methodologies to Assess the Quality of Mobile Health Apps in High-, Low-, and Middle-Income Countries: Rapid Review. JMIR mHealth and uHealth 2021;9(10):e28384 View
9. Grundy Q. A Review of the Quality and Impact of Mobile Health Apps. Annual Review of Public Health 2022;43(1):117 View
10. Jibb L, Amoako E, Heisey M, Ren L, Grundy Q. Data handling practices and commercial features of apps related to children: a scoping review of content analyses. Archives of Disease in Childhood 2022;107(7):665 View
11. Simon S, Kaar J, Talker I, Reich J. Evidence-Based Behavioral Strategies in Smartphone Apps for Children’s Sleep: Content Analysis. JMIR Pediatrics and Parenting 2022;5(1):e32129 View
12. Rollins N, Piwoz E, Baker P, Kingston G, Mabaso K, McCoy D, Ribeiro Neves P, Pérez-Escamilla R, Richter L, Russ K, Sen G, Tomori C, Victora C, Zambrano P, Hastings G. Marketing of commercial milk formula: a system to capture parents, communities, science, and policy. The Lancet 2023;401(10375):486 View
13. Acharya K. Designing Equitable and Inclusive mHealth Technology: Insights from Global South Healthcare Practitioners. IEEE Transactions on Professional Communication 2024;67(2):229 View
14. Albahri O, Alamoodi A, Pamucar D, Simic V, Chen J, Mahmoud M, Albahri A, Sharaf I. Selection of smartphone-based mobile applications for obesity management using an interval neutrosophic vague decision-making framework. Engineering Applications of Artificial Intelligence 2024;137:109191 View
15. Rajeshkumar L, Mishkind M, Coleman J, Pahwa M, LaPreze D, Solenske S, Wright J. Computer-assisted Cognitive Behavior Therapy and Mobile Apps for Depression and Anxiety: Evidence-based Digital Tools for Clinical Practice. Journal of Psychiatric Practice 2024;30(6):389 View