Published on in Vol 4, No 3 (2016): Jul-Sept

This is a member publication of Queensland University of Technology, Australia

The Quality and Accuracy of Mobile Apps to Prevent Driving After Drinking Alcohol

The Quality and Accuracy of Mobile Apps to Prevent Driving After Drinking Alcohol

The Quality and Accuracy of Mobile Apps to Prevent Driving After Drinking Alcohol

Journals

  1. Mandracchia F, Llauradó E, Tarro L, Valls R, Solà R. Mobile Phone Apps for Food Allergies or Intolerances in App Stores: Systematic Search and Quality Assessment Using the Mobile App Rating Scale (MARS). JMIR mHealth and uHealth 2020;8(9):e18339 View
  2. Sharpe J, Kamara M. A systematic evaluation of mobile apps to improve the uptake of and adherence to HIV pre-exposure prophylaxis. Sexual Health 2018;15(6):587 View
  3. Akbar S, Coiera, E, Magrabi F. Safety concerns with consumer-facing mobile health applications and their consequences: a scoping review. Journal of the American Medical Informatics Association 2020;27(2):330 View
  4. Ning P, Chen B, Cheng P, Yang Y, Schwebel D, Yu R, Deng J, Li S, Hu G. Effectiveness of an app-based intervention for unintentional injury among caregivers of preschoolers: protocol for a cluster randomized controlled trial. BMC Public Health 2018;18(1) View
  5. Bardus M, Ali A, Demachkieh F, Hamadeh G. Assessing the Quality of Mobile Phone Apps for Weight Management: User-Centered Study With Employees From a Lebanese University. JMIR mHealth and uHealth 2019;7(1):e9836 View
  6. Warren I, Meads A, Whittaker R, Dobson R, Ameratunga S. Behavior Change for Youth Drivers: Design and Development of a Smartphone-Based App (BackPocketDriver). JMIR Formative Research 2018;2(2):e25 View
  7. Ning P, Gao D, Cheng P, Schwebel D, Wei X, Tan L, Xiao W, He J, Fu Y, Chen B, Yang Y, Deng J, Wu Y, Yu R, Li S, Hu G. Needs Analysis for a Parenting App to Prevent Unintentional Injury in Newborn Babies and Toddlers: Focus Group and Survey Study Among Chinese Caregivers. JMIR mHealth and uHealth 2019;7(4):e11957 View
  8. Moon K, Park K, Sung Y. Sexual Abuse Prevention Mobile Application (SAP_MobAPP) for Primary School Children in Korea. Journal of Child Sexual Abuse 2017;26(5):573 View
  9. Talwar D, Yeh Y, Chen W, Chen L. Characteristics and quality of genetics and genomics mobile apps: a systematic review. European Journal of Human Genetics 2019;27(6):833 View
  10. Khan E, Shambour M. An analytical study of mobile applications for Hajj and Umrah services. Applied Computing and Informatics 2018;14(1):37 View
  11. Bardus M, Awada N, Ghandour L, Fares E, Gherbal T, Al-Zanati T, Stoyanov S. The Arabic Version of the Mobile App Rating Scale: Development and Validation Study. JMIR mHealth and uHealth 2020;8(3):e16956 View
  12. Bauer M, Glenn T, Geddes J, Gitlin M, Grof P, Kessing L, Monteith S, Faurholt-Jepsen M, Severus E, Whybrow P. Smartphones in mental health: a critical review of background issues, current status and future concerns. International Journal of Bipolar Disorders 2020;8(1) View
  13. Jamaladin H, van de Belt T, Luijpers L, de Graaff F, Bredie S, Roeleveld N, van Gelder M. Mobile Apps for Blood Pressure Monitoring: Systematic Search in App Stores and Content Analysis. JMIR mHealth and uHealth 2018;6(11):e187 View
  14. Sereda M, Smith S, Newton K, Stockdale D. Mobile Apps for Management of Tinnitus: Users’ Survey, Quality Assessment, and Content Analysis. JMIR mHealth and uHealth 2019;7(1):e10353 View
  15. Vogel R, Niendorf K, Lee H, Petzel S, Lee H, Geller M. A qualitative study of barriers to genetic counseling and potential for mobile technology education among women with ovarian cancer. Hereditary Cancer in Clinical Practice 2018;16(1) View
  16. Rodin A, Shachak A, Miller A, Akopyan V, Semenova N. Mobile Apps for Eye Care in Canada: An Analysis of the iTunes Store. JMIR mHealth and uHealth 2017;5(6):e84 View
  17. Chow P, Showalter S, Gerber M, Kennedy E, Brenin D, Schroen A, Mohr D, Lattie E, Cohn W. Use of Mental Health Apps by Breast Cancer Patients and Their Caregivers in the United States: Protocol for a Pilot Pre-Post Study. JMIR Research Protocols 2019;8(1):e11452 View
  18. Colonna R, Tucker P, Holmes J, Wilson J, Alvarez L. Mobile-based brief interventions targeting cannabis-impaired driving among youth: A Delphi study. Journal of Substance Abuse Treatment 2022;141:108802 View
  19. Warsinsky S, Schmidt-Kraepelin M, Rank S, Thiebes S, Sunyaev A. Conceptual Ambiguity Surrounding Gamification and Serious Games in Health Care: Literature Review and Development of Game-Based Intervention Reporting Guidelines (GAMING). Journal of Medical Internet Research 2021;23(9):e30390 View
  20. Stein D, Shoptaw S, Vigo D, Lund C, Cuijpers P, Bantjes J, Sartorius N, Maj M. Psychiatric diagnosis and treatment in the 21st century: paradigm shifts versus incremental integration. World Psychiatry 2022;21(3):393 View
  21. Martin-Payo R, Carrasco-Santos S, Cuesta M, Stoyan S, Gonzalez-Mendez X, Fernandez-Alvarez M. Spanish adaptation and validation of the User Version of the Mobile Application Rating Scale (uMARS). Journal of the American Medical Informatics Association 2021;28(12):2681 View
  22. Ramos G, Ponting C, Labao J, Sobowale K. Considerations of diversity, equity, and inclusion in mental health apps: A scoping review of evaluation frameworks. Behaviour Research and Therapy 2021;147:103990 View
  23. Mubin O, Cai B, Al Mahmud A, Kharub I, Lwin M, Khan A. A Preliminary Evaluation of Mobile Phone Apps to Curb Alcohol Consumption. International Journal of Environmental Research and Public Health 2021;19(1):135 View
  24. Mendi O, Kiymac Sari M, Stoyanov S, Mendi B. Development and validation of the Turkish version of the Mobile App Rating Scale – MARS-TR. International Journal of Medical Informatics 2022;166:104843 View
  25. Gornyi B, Bunova A, Kulikova M, Kushunina D, Kalinina A, Drapkina O. Mobile applications in the control and correction of excess body weight (expert assessment results). Profilakticheskaya meditsina 2021;24(8):66 View
  26. Torous J, Haim A. Dichotomies in the Development and Implementation of Digital Mental Health Tools. Psychiatric Services 2018;69(12):1204 View
  27. Podéus H, Simonsson C, Nasr P, Ekstedt M, Kechagias S, Lundberg P, Lövfors W, Cedersund G. A physiologically-based digital twin for alcohol consumption—predicting real-life drinking responses and long-term plasma PEth. npj Digital Medicine 2024;7(1) View
  28. Jama D, Sekuła K, Zuba D. Analysis of the most popular online BAC calculators = Analiza najpopularniejszych dostępnych w sieci „kalkulatorów trzeźwości”. Problems of Forensic Sciences 2024;(136):321 View