Abstract
Objetive: To identify and understand the characteristics of mobile applications for self-management of type 1 mellitus diabetes in users of continuous insulin infusion systems.
Method: integrative review with searches carried out in the month of June 2020, based on the articles published in PUBMED, CINAHL, Cochrane Library, Web of Science and Scopus. The eligibility criteria were based to consider those studies that addressed mobile applications for self-management of DM1 in users of Continuous Infusion System of Insulin without time restriction. Only unavailable studies were excluded.
Results: After the analysis of two independent reviewers, 14 studies were included in the final analysis, and 11 mobile applications for smartphones that can assist in self-management of DM1 were identified; these were named as iDECIDE, Sugar Sleuth, VoiceDiab, Blip, GoCARB, Nightscout, Intelligent Diabetes Management, Calculator Food exchange mobile, Insulin Pump, DiaMob and Interactive Diary on Diabetes.
Conclusion: Mobile applications were developed to promote behavioral changes and treatment adjustments in a positive way, both in clinical results and in the quality of life and self-management of diabetes in people with DM1. Mobile apps for smartphones can assist in self-management of DM1 by enabling assistance in the decision to apply insulin, glycemic control, analysis of the need for insulin in meals, food management, calculation of food components in meals, continuous glucose monitoring and automatic calculation of bolus of carbohydrates and insulin.
References
Akil AA, Yassin E, Al-Maraghi A, Aliyev E, Al-Malki K, Fakhro KA. Diagnosis and treatment of type 1 diabetes at the dawn of the personalized medicine era. J Transl Med. 2021;19(1):1-19. http://dx.doi.org/10.1186/s12967-021-02778-6
Sora ND, Shashpal F, Bond EA, Jenkins AJ. Insulin Pumps: Review of Technological Advancement in Diabetes Management. Am J Med Sci. 2019; 358(5):326-331. http://dx.doi.org/10.1016/j.amjms.2019.08.008
Galderisi A, Sherr JL. A Technological Revolution: The Integration of New Treatments to Manage Type 1 Diabetes. Pediatr Ann. 2019;48(8):311-318. http://dx.doi.org/10.3928/19382359-20190725-03
Doupis J, Festas G, Tsilivigos C, Efthymiou V, Kokkinos A. Smartphone-Based Technology in Diabetes Management. Diabetes Ther. 2020; 11(3): 607-619. http://dx.doi.org/10.1007/s13300-020-00768-3
McGill DE, Laffel LM, Volkening LK, Butler DA, Levy WL, Wasserman RM, et al. Text Message Intervention for Teens with Type 1 Diabetes Preserves HbA1c: Results of a Randomized Controlled Trial. Diabetes Technol Ther. 2020; 22(5):374-382. http://dx.doi.org/10.1089/dia.2019.0350
Kirwan M, Vandelanotte C, Fenning A, Duncan MJ. Diabetes self-management smartphone application for adults with type 1 diabetes: randomized controlled trial. J Med Internet Res. 2013;15(11):e235. http://dx.doi.org/10.2196/jmir.2588.
Hou C, Carter B, Hewitt J, Francisa T, Mayor S. Do Mobile Phone Applications Improve Glycemic Control (HbA1c) in the Self-management of Diabetes? A Systematic Review, Meta-analysis, and GRADE of 14 Randomized Trials. Diabetes Care. 2016;39(11):2089-2095. http://dx.doi.org/10.2337/dc16-0346.
Bonoto BC, de Araújo VE, Godói IP, de Lemos LL, Godman B, Bennie M, et al. Efficacy of Mobile Apps to Support the Care of Patients With Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. JMIR Mhealth Uhealth. 2017;5(3):1-16. http://dx.doi.org/10.2196/mhealth.6309
Pankowska E, Ladyzynski P, Foltynski P, Mazurczak K. A Randomized Controlled Study of an Insulin Dosing Application That Uses Recognition and Meal Bolus Estimations. J Diabetes Sci Technol. 2017;11(1):43-49. http://dx.doi.org/10.1177/1932296816683409
Foltynski P, Ladyzynski P, Pankowska E, Mazurczak K. Efficacy of automatic bolus calculator with automatic speech recognition in patients with type 1 diabetes: A randomized cross-over trial. J Diabetes. 2018;10(7):600-608. http://dx.doi.org/10.1111/1753-0407.12641
Paul J, Criado AR. The art of writing literature review: what do we know and what do we need to know?. Inter Business Review, 2020; 29 (4): 101717. http://dx.doi.org/10.1016/j.ibusrev.2020.101717.
Mendes KDS, Silveira RCCP, Galvão CM. Revisão integrativa: método de pesquisa para a incorporação de evidências na saúde e na enfermagem. Texto Contexto Enferm, Florianópolis, 2008; 17(4): 758-64. https://doi.org/10.1590/S0104-07072008000400018
Melnyk BM, Fineout-Overholt E. Making the case for evidence-based practice. In: Melnyk BM, Fineout-Overholt E. Evidence-based practice in nursing & healthcare. A guide to best practice. Philadelphia: Lippincot Williams & Wilkins; p.3-24, 2005.
Karway G, Grando MA, Grimm K, Groat D, Cook C, Thompson B. Self-Management Behaviors of Patients with Type 1 Diabetes: Comparing Two Sources of Patient-Generated Data. Appl Clin Inform. 2020; 11(1):70-78. http://dx.doi.org/10.1055/s-0039-1701002
Toschi E, Fisher L, Wolpert H, Love M, Dunn T, Hayter G. Evaluating a Glucose-Sensor-Based Tool to Help Clinicians and Adults With Type 1 Diabetes Improve Self-Management Skills. J Diabetes Sci Technol. 2018; 12(6):1143-1151. http://dx.doi.org/10.1177/1932296818791534
Ladyzynski P, Krzymien J, Foltynski P, Rachuta M, Bonalska B. Accuracy of Automatic Carbohydrate, Protein, Fat and Calorie Counting Based on Voice Descriptions of Meals in People with Type 1 Diabetes. Nutrients. 2018;10(4):518. http://dx.doi.org/10.3390/nu10040518
Wong JC, Neinstein AB, Look H, Arbiter B, Chokr N, Ross C, Adi S. Pilot Study of a Novel Application for Data Visualization in Type 1 Diabetes. J Diabetes Sci Technol. 2017;11(4):800-807. http://dx.doi.org/10.1177/1932296817691305
Bally L, Dehais J, Nakas CT, Anthimopoulos M, Laimer M, Rhyner D, et al. Carbohydrate Estimation Supported by the GoCARB System in Individuals With Type 1 Diabetes: A Randomized Prospective Pilot Study. Diabetes Care. 2017; 40(2):6-7. http://dx.doi.org/10.2337/dc16-2173
Lee JM, Newman MW, Gebremariam A, Choi P, Lewis D, Nordgren W, et al. Real-World Use and Self-Reported Health Outcomes of a Patient-Designed Do-it-Yourself Mobile Technology System for Diabetes: Lessons for Mobile Health. Diabetes Technol Ther. 2017;19(4):209-219.http://dx.doi.org/10.1089/dia.2016.0312
Ryan EA, Holland J, Stroulia E, Bazelli B, Babwik SA, Li H, et al. Improved A1C Levels in Type 1 Diabetes with Smartphone App Use. Can J Diabetes. 2017 Feb; 41(1):33-40. http://dx.doi.org/10.1016/j.jcjd.2016.06.001
Szypowski W, Kunecka K, Zduńczyk B, Piechowiak K, Dyczek M, Dąbrowa K, et al. Food exchange estimation by children with type 1 diabetes at summer camp. J Pediatr Endocrinol Metab. 2017; 30(1):71-76. http://dx.doi.org/10.1515/jpem-2016-0282.
Neinstein A, Wong J, Look H, Arbiter B, Quirk K, McCanne S, et al. A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes management. J Am Med Inform Assoc. 2016; 23(2):324-32. http://dx.doi.org/10.1093/jamia/ocv104
Esvant A, Lefebvre MA, Campillo-Gimenez B, Lannes M, Delamarre D, Guilhem I, et al. A Mobile Application Guiding Patients With Type 1 Diabetes Using Sensor-Augmented Insulin Pump Therapy. J Diabetes Sci Technol. 2016; 10(4):985-6. http://dx.doi.org/10.1177/1932296816633486
Froisland DH, Arsand E. Integrating visual dietary documentation in mobile-phone-based self-management application for adolescents with type 1 diabetes. J Diabetes Sci Technol. 2015; 9(3):541-8. http://dx.doi.org/10.1177/1932296815576956
Rossi MC, Nicolucci A, Pellegrini F, Bruttomesso D, Bartolo PD, Marelli G, et al. Interactive diary for diabetes: A useful and easy-to-use new telemedicine system to support the decision-making process in type 1 diabetes. Diabetes Technol Ther. 2009;11(1):19-24. http://dx.doi.org/10.1089/dia.2008.0020
Lloyd B, Groat D, Cook CB, Kaufman D, Grando A. iDECIDE: A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences. Stud Health Technol Inform. 2015; 216:93-7. https://pubmed.ncbi.nlm.nih.gov/26262017/
Veazie S, Winchell K, Gilbert J, Paynter R, Ivlev I, Eden KB, et al. Rapid Evidence Review of Mobile Applications for Self-management of Diabetes. J Gen Intern Med. 2018; 33(7): 1167-1176. http://dx.doi.org/10.1007/s11606-018-4410-1.
Castensoe-Seidenfaden P, Husted G, Tellmann G, Hommel E, Olsen B, Kensing F. Designing a self-management app for young people with diabetes type 1 - methodological challenges, experiences and recommendations. JMIR Mhealth Uhealth 2017;5(10):e124. http://dx.doi.org/10.2196/mhealth.8137
Kordonouri O, Riddell MC. Use of apps for physical activity in type 1 diabetes: current status and requirements for future development. Ther Adv Endocrinol Metab. 2019;10 (1): 1-7. http://dx.doi.org/10.1177/2042018819839298
Cui M, Wu X, Mao J, Wang X, Nie M. T2DM Self-Management via Smartphone Applications: A Systematic Review and Meta-Analysis. PLoS One. 2016; 11(11):e0166718. http://dx.doi.org/10.1371/journal.pone.0166718
AbdulAziz YH, Al-Sallami HS, Wiltshire E, Rayns J, Jinny Willis J , McClintock J, et al. Insulin pump initiation and education for children and adolescents – a qualitative study of current practice in New Zealand. J Diabetes Metab Disord. 2019; 18 (1): 59–64. https://doi.org/10.1007/s40200-019-00390-6
Alghadeer S, Aljuaydi K, Balkhi B, Alhossan A and Yazed Alruthia1. The attitude and basic knowledge of insulin pump therapy among healthcare providers. Biomed Res J. 2019; 30 (3): 446-451. https://doi.org/10.35841/biomedicalresearch.30-19-181
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