Derleme
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Prediyabet ve Mobil Uygulamalar

Yıl 2026, Cilt: 35 Sayı: 1 , 178 - 189 , 16.04.2026
https://doi.org/10.34108/eujhs.1800245
https://izlik.org/JA79DF35UB

Öz

Prediyabet, diyabet gelişimi öncesindeki geçiş evresini temsil eden, glukoz metabolizmasında bozulma ile karakterize bir durumdur. Obezite, fiziksel inaktivite ve sağlıksız beslenme gibi değiştirilebilir risk faktörleriyle yakından ilişkilidir. Son yıllarda dijital sağlık teknolojilerindeki gelişmelerle birlikte mobil sağlık uygulamaları, prediyabetli bireylerin öz-yönetim becerilerini geliştirmede ve hastalık ilerleyişini önlemede önemli bir araç haline gelmiştir. Bu derleme çalışmada, prediyabete yönelik geliştirilen mobil uygulamaların odak noktaları ve etkileri incelenmiştir. Literatürdeki kanıtlar; mobil uygulamaların fiziksel aktivite artışı, kilo kontrolü, glisemik parametrelerin (glikolize hemoglobin, açlık plazma glukozu) iyileştirilmesi ve sağlıklı yaşam biçimi davranışlarının geliştirilmesinde etkili olduğunu göstermektedir. Uygulamalarda sıklıkla yaşam koçu, hemşire veya sağlık profesyonelleri danışmanlığı, adım sayacı entegrasyonu ve kişiye özel bildirimlerle davranış değişikliği desteklenmektedir. Bununla birlikte, veri güvenliği, klinik geçerlilik ve uygulama kalitesi konularında eksiklikler olduğu, bu nedenle uygulamaların geliştirilmesinde sağlık profesyonellerinin aktif rol almasının önem taşıdığı vurgulanmaktadır. Sonuç olarak, prediyabet mobil uygulamaları birincil korunmada etkili ve maliyet açısından avantajlı araçlar olmakla birlikte, standartlara uygunluk ve klinik doğrulama süreçlerinin güçlendirilmesi gerekmektedir.

Etik Beyan

Çalışma metodolojisinden dolayı gerek görülmemiştir.

Destekleyen Kurum

Bu çalışma için, kamu, ticari veya kar amacı gütmeyen sektörlerdeki finansman kuruluşlarından belirli bir destek alınmadı.

Proje Numarası

-

Teşekkür

-

Kaynakça

  • Yüzügülen Ö, Erdoğdu Hİ. Prediyabet hastalarında D vitamini ve parathormona göre insülin direncinin değerlendirilmesi. Sakarya Tıp Dergisi. 2020;10(3):437-444. doi:10.31832/smj.683489.
  • Türk Diyabet Vakfı. Prediyabet Tanı ve Tedavi Rehberi. Türk Diyabet Vakfı Yayınları, İstanbul: AdrH Pozitif Reklam ve İletișim Hizmetleri; c2023:10-11.
  • Çakır E. Prediyabet. Selçuk Med J. 2018;30(1):1-4.
  • Centers for Diseases Control and Prevention (CDC). Prediabetes; your chance to prevent type 2 diabetes. https://www.cdc.gov/diabetes/prevention-type-2/prediabetes-prevent-type-2.html?CDC_AAref_Val=https://www.cdc.gov/diabetes/basics/prediabetes.html. Published December 26, 2024. Accessed September 05, 2025.
  • T.C. Sağlık Bakanlığı. Türkiye Halk Sağlığı Kurumu. Türkiye Diyabet Programı. Sağlık Bakanlığı Yayınları, Ankara: Kuban; c2023:52-54.
  • Satman I, Omer B, Tutuncu Y, et al. Twelve-year trends in the prevalence and risk factors of diabetes and prediabetes in Turkish adults. Eur J Epidemiol. 2013;28(2):169-180. doi:10.1007/s10654-013-9771-5.
  • Li Y, Chen W, Liang Y, Yang L, Hou L. Evaluation of mobile health technology ınterventions for the postdischarge management of patients with head and neck cancer: Scoping review. JMIR Mhealth Uhealth. 2023;11:e49051. doi:10.2196/49051.
  • Tezcan C. Sağlığa yenilikçi bir bakış açısı: Mobil sağlık. İstanbul: Sis Matbaacılık; c2016:33.
  • Tsirintani M. Use of mobile health by health care professionals in Greece: A validation study. Stud Health Technol Inform. 2025;328:403-406. doi:10.3233/SHTI250747.
  • Demir H, Arslan ET. Mobil sağlık uygulamalarının hastanelerde kullanılabilirliği, hastane yöneticileri üzerine bir araştırma. KMÜ Sosyal ve Ekonomik Araştırmalar Dergisi. 2017;19(33):71-83. doi:10.18493/kmusekad.400161.
  • Wu Y, Yao X, Vespasiani G, et al. Mobile app-based interventions to support diabetes self-management: A systematic review of randomized controlled trials to identify functions associated with glycemic efficacy. JMIR mHealth uHealth. 2017;5(3):e35. doi:10.2196/mhealth.6522.
  • Yamaguchi S, Waki K, Nannya Y, Nangaku M, Kadowaki T, Ohe K. Usage patterns of GlucoNote, a self-management smartphone app, based on ResearchKit for patients with type 2 diabetes and prediabetes. JMIR mHealth uHealth. 2019;7(4):e13204. doi:10.2196/13204.
  • Behnoush AH, Maleki S, Arzhangzadeh A, et al. Prediabetes and major adverse cardiac events after acute coronary syndrome: An overestimated concept. Clin Cardiol. 2024;47(4):e24262. doi:10.1002/clc.24262.
  • Echouffo-Tcheugui JB, Perreault L, Ji L, Dagogo-Jack S. Diagnosis and management of prediabetes: A review. JAMA. 2023;329(14):1206-1216. doi:10.1001/jama.2023.4063.
  • Leung AY, Xu XY, Chau PH, et al. A mobile app for identifying individuals with undiagnosed diabetes and prediabetes and for promoting behavior change: 2-year prospective study. JMIR mHealth uHealth. 2018;6(5):e10662. doi:10.2196/10662.
  • Cassidy S, Okwose N, Scragg J, et al. Assessing the feasibility and acceptability of Changing Health for the management of prediabetes: Protocol for a pilot study of a digital behavioural intervention. Pilot Feasibility Stud. 2019;5(1):139. doi:10.1186/s40814-019-0519-1.
  • Powell-Wiley TM, Poirier P, Burke LE, et al. Obesity and cardiovascular disease: A scientific statement from the American Heart Association. Circulation. 2021;143(21):e984-e1010. doi:10.1161/CIR.0000000000000973.
  • Haapala I, Barengo NC, Biggs S, Surakka L, Manninen P. Weight loss by mobile phone: A 1-year effectiveness study. Public Health Nutr. 2009;12(12):2382-2391. doi:10.1017/S1368980009005230.
  • Griauzde D, Kullgren JT, Liestenfeltz B, et al. A mobile phone-based program to promote healthy behaviors among adults with prediabetes who declined participation in free diabetes prevention programs: Mixed-methods pilot randomized controlled trial. JMIR mHealth uHealth. 2019;7(1):e11267. doi:10.2196/11267.
  • Wu X, Guo X, Zhang Z. The efficacy of mobile phone apps for lifestyle modification in diabetes: Systematic review and meta-analysis. JMIR mHealth uHealth. 2019;7(1):e12297. doi:10.2196/12297.
  • American Diabetes Association. 3. prevention or delay of type 2 diabetes. Diabetes Care. 2019;42(1):29-33. doi:10.2337/dc19-S003.
  • Yip WC, Sequeira IR, Plank LD, Poppitt SD. Prevalence of pre-diabetes across ethnicities: A review of impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) for classification of dysglycaemia. Nutrients. 2017;9(11):1273. doi:10.3390/nu9111273.
  • Altuve M, Severeyn E. Joint analysis of fasting and postprandial plasma glucose and insulin concentrations in Venezuelan women. Diabetes Metab Syndr. 2019;13(3):2242-2248. doi:10.1016/j.dsx.2019.05.029.
  • Toro-Ramos T, Michaelides A, Anton M, et al. Mobile delivery of the diabetes prevention program in people with prediabetes: Randomized controlled trial. JMIR mHealth uHealth. 2020;8(7):e17842. doi:10.2196/17842.
  • Signal V, McLeod M, Stanley J, et al. A mobile-and web-based health intervention program for diabetes and prediabetes self-management (BetaMe/Melon): Process evaluation following a randomized controlled trial. J Med Internet Res. 2020;22(12):e19150. doi:10.2196/19150.
  • Schippers M, Adam PCG, Smolenski DJ, Wong HTH, De Wit JBF. A meta‐analysis of overall effects of weight loss interventions delivered via mobile phones and effect size differences according to delivery mode, personal contact, and intervention intensity and duration. Obes Rev. 2017;18(4):450-459. doi:10.1111/obr.12492.
  • Centers for Diseases Control and Prevention (CDC). Diabetes prevention recognition program. https://www.cdc.gov/diabetes-prevention/media/pdfs/legacy/dprp-standards.pdf?CDC_AAref_Val= https://www.cdc.gov/diabetes/prevention/pdf/dprp-standards.pdf. Published June 1, 2024. Accessed September 01, 2025.
  • US Preventive Services Task Force, Mangione CM, Barry MJ, et al. Behavioral counseling interventions to promote a healthy diet and physical activity for cardiovascular disease prevention in adults without cardiovascular disease risk factors: US Preventive Services Task Force Recommendation Statement. JAMA. 2022;328(4):367-374. doi:10.1001/jama.2022.10951.
  • Smith KJ, Kuo S, Zgibor JC, et al. Cost effectiveness of an internet-delivered lifestyle intervention in primary care patients with high cardiovascular risk. Prev Med. 2016;87:103-109. doi:10.1016/j.ypmed.2016.02.036.
  • Srivastava P, Verma A, Geronimo C, Button TM. Behavior stages of a physician-and coach-supported cloud-based diabetes prevention program for people with prediabetes. SAGE Open Med. 2019;7:2050312119841986. doi:10.1177/2050312119841986.
  • Lee EY, Cha SA, Yun JS, et al. Efficacy of personalized diabetes self-care using an electronic medical record-integrated mobile app in patients with type 2 diabetes: 6-month randomized controlled trial. J Med Internet Res. 2022;24(7):e37430. doi:10.2196/37430.
  • Baniasadi T, Niakan Kalhori SR, Ayyoubzadeh SM, Zakerabasali S, Pourmohamadkhan M. Study of challenges to utilise mobile-based health care monitoring systems: A descriptive literature review. J Telemed Telecare. 2018;24(10):661-668. doi:10.1177/1357633X18804747.
  • Han CY, Lim SL, Ong KW, Johal J, Gulyani A. Behavioral lifestyle ıntervention program using mobile application improves Diet Quality in Adults With Prediabetes (D'LITE Study): A randomized controlled trial. J Acad Nutr Diet. 2024;124(3):358-371. doi:10.1016/j.jand.2023.10.005.
  • Lim D, Meier L, Cadwell KM, Jacob C. From diabetes care to prevention: Review of prediabetes apps in the DACH region. Mhealth. 2025;11:8. doi:10.21037/mhealth-24-57.
  • Ayre J, Bonner C, Bramwell S, et al. Factors for supporting primary care physician engagement with patient apps for type 2 diabetes self-management that link to primary care: Interview study. JMIR mHealth uHealth. 2019;7(1):e11885. doi:10.2196/11885.
  • Granja C, Janssen W, Johansen MA. Factors determining the success and failure of eHealth interventions: systematic review of the literature. J Med Internet Res. 2018;20(5):e10235. doi:10.2196/10235.
  • Özen F, Kaynar AH, Korkut AK, Teker Açıkel ME, Kaynar ZD, Kaynar AM. The role of telemedicine towards improved sustainability in healthcare and societal productivity in Turkey. PLoS One. 2024;19(12):e0314986. doi:10.1371/journal.pone.0314986 .
  • Kaufman N, Khurana I. Using digital health technology to prevent and treat diabetes. Diabetes Technol Ther. 2016;18(S1):56-68. doi:10.1089/dia.2016.2506.
  • Drincic A, Prahalad P, Greenwood D, Klonoff DC. Evidence-based mobile medical applications in diabetes. Endocrinol Metab Clin. 2016;45(4):943-965. doi:10.1016/j.ecl.2016.06.001.
  • Fleming GA, Petrie JR, Bergenstal RM, Holl RW, Peters AL, Heinemann L. Diabetes digital app technology: benefits, challenges, and recommendations. A consensus report by the European Association for the Study of Diabetes (EASD) and the American Diabetes Association (ADA) Diabetes Technology Working Group. Diabetes Care. 2020;43(1):250-260. doi:10.2337/dci19-0062.
  • Durmuş A. The influence of digital literacy on mHealth app usability: The mediating role of patient expertise. Digit Health. 2024;10:20552076241299061. doi:10.1177/20552076241299061.
  • Ali M, Khan SUR, Hussain S. Self-adaptation in smartphone applications: Current state-of-the-art techniques, challenges, and future directions. Data & Knowledge Engineering. 2021;136:101929. doi:10.1016/j.datak.2021.101929.
  • Konukbay D, Efe M, Yıldız D. Teknolojinin hemşirelik mesleğine yansıması: Sistematik derleme. Sağlık Bilimleri Üniversitesi Hemşirelik Dergisi. 2020;2(3):175–182. doi:10.48071/sbuhemsirelik.700870.
  • Kaplan T, Van Giersbergen MY. Hemşirelikte teknoloji kullanımı: Yenilikler ve gelecek perspektifleri. Doğu Karadeniz Sağlık Bilimleri Dergisi. 2025;4(4):350-358. doi:10.59312/ebshealth.1663790.
  • Omez-Barrera MG, Luisa M, Hoyo LD, et al. Nurse-led telephone program for nonadherent type 2 diabetics with comorbid depression: A costconsequence and budget impact analysis. J Nurs Manag. 2024;32(4):9989080. doi:10.1155/2024/9989080.

Prediabetes and Mobile Applications

Yıl 2026, Cilt: 35 Sayı: 1 , 178 - 189 , 16.04.2026
https://doi.org/10.34108/eujhs.1800245
https://izlik.org/JA79DF35UB

Öz

Prediabetes represents an intermediate stage preceding diabetes, characterized by impaired glucose metabolism. It is closely associated with modifiable risk factors such as obesity, physical inactivity, and unhealthy dietary habits. With advances in digital health technologies, mobile health applications have become valuable tools for improving self-management and preventing the progression of prediabetes. This review examines the focus areas and effectiveness of mobile applications developed for individuals with prediabetes. Evidence from the literature indicates that mobile applications can enhance physical activity, support weight management, improve glycemic parameters (glycolyzed hemoglobin, fasting plasma glucose), and promote healthy lifestyle behaviors. Many applications incorporate features such as step counters, personalized notifications, and counseling from health professionals or certified coaches to facilitate behavioral change. However, concerns remain regarding data security, clinical validity, and the quality of application design. Therefore, the active involvement of healthcare professionals in app development and evaluation is crucial. In conclusion, mobile applications for prediabetes are effective and cost-efficient tools that contribute to primary prevention. Strengthening clinical validation and ensuring compliance with medical and technological standards will further enhance their reliability and long-term sustainability in healthcare practice.

Etik Beyan

Not required due to the study methodology.

Destekleyen Kurum

The authors disclosed that they received no financial support for this study.

Proje Numarası

-

Teşekkür

-

Kaynakça

  • Yüzügülen Ö, Erdoğdu Hİ. Prediyabet hastalarında D vitamini ve parathormona göre insülin direncinin değerlendirilmesi. Sakarya Tıp Dergisi. 2020;10(3):437-444. doi:10.31832/smj.683489.
  • Türk Diyabet Vakfı. Prediyabet Tanı ve Tedavi Rehberi. Türk Diyabet Vakfı Yayınları, İstanbul: AdrH Pozitif Reklam ve İletișim Hizmetleri; c2023:10-11.
  • Çakır E. Prediyabet. Selçuk Med J. 2018;30(1):1-4.
  • Centers for Diseases Control and Prevention (CDC). Prediabetes; your chance to prevent type 2 diabetes. https://www.cdc.gov/diabetes/prevention-type-2/prediabetes-prevent-type-2.html?CDC_AAref_Val=https://www.cdc.gov/diabetes/basics/prediabetes.html. Published December 26, 2024. Accessed September 05, 2025.
  • T.C. Sağlık Bakanlığı. Türkiye Halk Sağlığı Kurumu. Türkiye Diyabet Programı. Sağlık Bakanlığı Yayınları, Ankara: Kuban; c2023:52-54.
  • Satman I, Omer B, Tutuncu Y, et al. Twelve-year trends in the prevalence and risk factors of diabetes and prediabetes in Turkish adults. Eur J Epidemiol. 2013;28(2):169-180. doi:10.1007/s10654-013-9771-5.
  • Li Y, Chen W, Liang Y, Yang L, Hou L. Evaluation of mobile health technology ınterventions for the postdischarge management of patients with head and neck cancer: Scoping review. JMIR Mhealth Uhealth. 2023;11:e49051. doi:10.2196/49051.
  • Tezcan C. Sağlığa yenilikçi bir bakış açısı: Mobil sağlık. İstanbul: Sis Matbaacılık; c2016:33.
  • Tsirintani M. Use of mobile health by health care professionals in Greece: A validation study. Stud Health Technol Inform. 2025;328:403-406. doi:10.3233/SHTI250747.
  • Demir H, Arslan ET. Mobil sağlık uygulamalarının hastanelerde kullanılabilirliği, hastane yöneticileri üzerine bir araştırma. KMÜ Sosyal ve Ekonomik Araştırmalar Dergisi. 2017;19(33):71-83. doi:10.18493/kmusekad.400161.
  • Wu Y, Yao X, Vespasiani G, et al. Mobile app-based interventions to support diabetes self-management: A systematic review of randomized controlled trials to identify functions associated with glycemic efficacy. JMIR mHealth uHealth. 2017;5(3):e35. doi:10.2196/mhealth.6522.
  • Yamaguchi S, Waki K, Nannya Y, Nangaku M, Kadowaki T, Ohe K. Usage patterns of GlucoNote, a self-management smartphone app, based on ResearchKit for patients with type 2 diabetes and prediabetes. JMIR mHealth uHealth. 2019;7(4):e13204. doi:10.2196/13204.
  • Behnoush AH, Maleki S, Arzhangzadeh A, et al. Prediabetes and major adverse cardiac events after acute coronary syndrome: An overestimated concept. Clin Cardiol. 2024;47(4):e24262. doi:10.1002/clc.24262.
  • Echouffo-Tcheugui JB, Perreault L, Ji L, Dagogo-Jack S. Diagnosis and management of prediabetes: A review. JAMA. 2023;329(14):1206-1216. doi:10.1001/jama.2023.4063.
  • Leung AY, Xu XY, Chau PH, et al. A mobile app for identifying individuals with undiagnosed diabetes and prediabetes and for promoting behavior change: 2-year prospective study. JMIR mHealth uHealth. 2018;6(5):e10662. doi:10.2196/10662.
  • Cassidy S, Okwose N, Scragg J, et al. Assessing the feasibility and acceptability of Changing Health for the management of prediabetes: Protocol for a pilot study of a digital behavioural intervention. Pilot Feasibility Stud. 2019;5(1):139. doi:10.1186/s40814-019-0519-1.
  • Powell-Wiley TM, Poirier P, Burke LE, et al. Obesity and cardiovascular disease: A scientific statement from the American Heart Association. Circulation. 2021;143(21):e984-e1010. doi:10.1161/CIR.0000000000000973.
  • Haapala I, Barengo NC, Biggs S, Surakka L, Manninen P. Weight loss by mobile phone: A 1-year effectiveness study. Public Health Nutr. 2009;12(12):2382-2391. doi:10.1017/S1368980009005230.
  • Griauzde D, Kullgren JT, Liestenfeltz B, et al. A mobile phone-based program to promote healthy behaviors among adults with prediabetes who declined participation in free diabetes prevention programs: Mixed-methods pilot randomized controlled trial. JMIR mHealth uHealth. 2019;7(1):e11267. doi:10.2196/11267.
  • Wu X, Guo X, Zhang Z. The efficacy of mobile phone apps for lifestyle modification in diabetes: Systematic review and meta-analysis. JMIR mHealth uHealth. 2019;7(1):e12297. doi:10.2196/12297.
  • American Diabetes Association. 3. prevention or delay of type 2 diabetes. Diabetes Care. 2019;42(1):29-33. doi:10.2337/dc19-S003.
  • Yip WC, Sequeira IR, Plank LD, Poppitt SD. Prevalence of pre-diabetes across ethnicities: A review of impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) for classification of dysglycaemia. Nutrients. 2017;9(11):1273. doi:10.3390/nu9111273.
  • Altuve M, Severeyn E. Joint analysis of fasting and postprandial plasma glucose and insulin concentrations in Venezuelan women. Diabetes Metab Syndr. 2019;13(3):2242-2248. doi:10.1016/j.dsx.2019.05.029.
  • Toro-Ramos T, Michaelides A, Anton M, et al. Mobile delivery of the diabetes prevention program in people with prediabetes: Randomized controlled trial. JMIR mHealth uHealth. 2020;8(7):e17842. doi:10.2196/17842.
  • Signal V, McLeod M, Stanley J, et al. A mobile-and web-based health intervention program for diabetes and prediabetes self-management (BetaMe/Melon): Process evaluation following a randomized controlled trial. J Med Internet Res. 2020;22(12):e19150. doi:10.2196/19150.
  • Schippers M, Adam PCG, Smolenski DJ, Wong HTH, De Wit JBF. A meta‐analysis of overall effects of weight loss interventions delivered via mobile phones and effect size differences according to delivery mode, personal contact, and intervention intensity and duration. Obes Rev. 2017;18(4):450-459. doi:10.1111/obr.12492.
  • Centers for Diseases Control and Prevention (CDC). Diabetes prevention recognition program. https://www.cdc.gov/diabetes-prevention/media/pdfs/legacy/dprp-standards.pdf?CDC_AAref_Val= https://www.cdc.gov/diabetes/prevention/pdf/dprp-standards.pdf. Published June 1, 2024. Accessed September 01, 2025.
  • US Preventive Services Task Force, Mangione CM, Barry MJ, et al. Behavioral counseling interventions to promote a healthy diet and physical activity for cardiovascular disease prevention in adults without cardiovascular disease risk factors: US Preventive Services Task Force Recommendation Statement. JAMA. 2022;328(4):367-374. doi:10.1001/jama.2022.10951.
  • Smith KJ, Kuo S, Zgibor JC, et al. Cost effectiveness of an internet-delivered lifestyle intervention in primary care patients with high cardiovascular risk. Prev Med. 2016;87:103-109. doi:10.1016/j.ypmed.2016.02.036.
  • Srivastava P, Verma A, Geronimo C, Button TM. Behavior stages of a physician-and coach-supported cloud-based diabetes prevention program for people with prediabetes. SAGE Open Med. 2019;7:2050312119841986. doi:10.1177/2050312119841986.
  • Lee EY, Cha SA, Yun JS, et al. Efficacy of personalized diabetes self-care using an electronic medical record-integrated mobile app in patients with type 2 diabetes: 6-month randomized controlled trial. J Med Internet Res. 2022;24(7):e37430. doi:10.2196/37430.
  • Baniasadi T, Niakan Kalhori SR, Ayyoubzadeh SM, Zakerabasali S, Pourmohamadkhan M. Study of challenges to utilise mobile-based health care monitoring systems: A descriptive literature review. J Telemed Telecare. 2018;24(10):661-668. doi:10.1177/1357633X18804747.
  • Han CY, Lim SL, Ong KW, Johal J, Gulyani A. Behavioral lifestyle ıntervention program using mobile application improves Diet Quality in Adults With Prediabetes (D'LITE Study): A randomized controlled trial. J Acad Nutr Diet. 2024;124(3):358-371. doi:10.1016/j.jand.2023.10.005.
  • Lim D, Meier L, Cadwell KM, Jacob C. From diabetes care to prevention: Review of prediabetes apps in the DACH region. Mhealth. 2025;11:8. doi:10.21037/mhealth-24-57.
  • Ayre J, Bonner C, Bramwell S, et al. Factors for supporting primary care physician engagement with patient apps for type 2 diabetes self-management that link to primary care: Interview study. JMIR mHealth uHealth. 2019;7(1):e11885. doi:10.2196/11885.
  • Granja C, Janssen W, Johansen MA. Factors determining the success and failure of eHealth interventions: systematic review of the literature. J Med Internet Res. 2018;20(5):e10235. doi:10.2196/10235.
  • Özen F, Kaynar AH, Korkut AK, Teker Açıkel ME, Kaynar ZD, Kaynar AM. The role of telemedicine towards improved sustainability in healthcare and societal productivity in Turkey. PLoS One. 2024;19(12):e0314986. doi:10.1371/journal.pone.0314986 .
  • Kaufman N, Khurana I. Using digital health technology to prevent and treat diabetes. Diabetes Technol Ther. 2016;18(S1):56-68. doi:10.1089/dia.2016.2506.
  • Drincic A, Prahalad P, Greenwood D, Klonoff DC. Evidence-based mobile medical applications in diabetes. Endocrinol Metab Clin. 2016;45(4):943-965. doi:10.1016/j.ecl.2016.06.001.
  • Fleming GA, Petrie JR, Bergenstal RM, Holl RW, Peters AL, Heinemann L. Diabetes digital app technology: benefits, challenges, and recommendations. A consensus report by the European Association for the Study of Diabetes (EASD) and the American Diabetes Association (ADA) Diabetes Technology Working Group. Diabetes Care. 2020;43(1):250-260. doi:10.2337/dci19-0062.
  • Durmuş A. The influence of digital literacy on mHealth app usability: The mediating role of patient expertise. Digit Health. 2024;10:20552076241299061. doi:10.1177/20552076241299061.
  • Ali M, Khan SUR, Hussain S. Self-adaptation in smartphone applications: Current state-of-the-art techniques, challenges, and future directions. Data & Knowledge Engineering. 2021;136:101929. doi:10.1016/j.datak.2021.101929.
  • Konukbay D, Efe M, Yıldız D. Teknolojinin hemşirelik mesleğine yansıması: Sistematik derleme. Sağlık Bilimleri Üniversitesi Hemşirelik Dergisi. 2020;2(3):175–182. doi:10.48071/sbuhemsirelik.700870.
  • Kaplan T, Van Giersbergen MY. Hemşirelikte teknoloji kullanımı: Yenilikler ve gelecek perspektifleri. Doğu Karadeniz Sağlık Bilimleri Dergisi. 2025;4(4):350-358. doi:10.59312/ebshealth.1663790.
  • Omez-Barrera MG, Luisa M, Hoyo LD, et al. Nurse-led telephone program for nonadherent type 2 diabetics with comorbid depression: A costconsequence and budget impact analysis. J Nurs Manag. 2024;32(4):9989080. doi:10.1155/2024/9989080.
Toplam 45 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Halk Sağlığı (Diğer), Halk Sağlığı Hemşireliği
Bölüm Derleme
Yazarlar

İbrahim Topuz 0000-0003-0540-2095

Ayşegül Topuz 0000-0001-6049-8611

Proje Numarası -
Gönderilme Tarihi 9 Ekim 2025
Kabul Tarihi 10 Mart 2026
Yayımlanma Tarihi 16 Nisan 2026
DOI https://doi.org/10.34108/eujhs.1800245
IZ https://izlik.org/JA79DF35UB
Yayımlandığı Sayı Yıl 2026 Cilt: 35 Sayı: 1

Kaynak Göster

APA Topuz, İ., & Topuz, A. (2026). Prediyabet ve Mobil Uygulamalar. Sağlık Bilimleri Dergisi, 35(1), 178-189. https://doi.org/10.34108/eujhs.1800245
AMA 1.Topuz İ, Topuz A. Prediyabet ve Mobil Uygulamalar. Sağlık Bilimleri Dergisi. 2026;35(1):178-189. doi:10.34108/eujhs.1800245
Chicago Topuz, İbrahim, ve Ayşegül Topuz. 2026. “Prediyabet ve Mobil Uygulamalar”. Sağlık Bilimleri Dergisi 35 (1): 178-89. https://doi.org/10.34108/eujhs.1800245.
EndNote Topuz İ, Topuz A (01 Nisan 2026) Prediyabet ve Mobil Uygulamalar. Sağlık Bilimleri Dergisi 35 1 178–189.
IEEE [1]İ. Topuz ve A. Topuz, “Prediyabet ve Mobil Uygulamalar”, Sağlık Bilimleri Dergisi, c. 35, sy 1, ss. 178–189, Nis. 2026, doi: 10.34108/eujhs.1800245.
ISNAD Topuz, İbrahim - Topuz, Ayşegül. “Prediyabet ve Mobil Uygulamalar”. Sağlık Bilimleri Dergisi 35/1 (01 Nisan 2026): 178-189. https://doi.org/10.34108/eujhs.1800245.
JAMA 1.Topuz İ, Topuz A. Prediyabet ve Mobil Uygulamalar. Sağlık Bilimleri Dergisi. 2026;35:178–189.
MLA Topuz, İbrahim, ve Ayşegül Topuz. “Prediyabet ve Mobil Uygulamalar”. Sağlık Bilimleri Dergisi, c. 35, sy 1, Nisan 2026, ss. 178-89, doi:10.34108/eujhs.1800245.
Vancouver 1.İbrahim Topuz, Ayşegül Topuz. Prediyabet ve Mobil Uygulamalar. Sağlık Bilimleri Dergisi. 01 Nisan 2026;35(1):178-89. doi:10.34108/eujhs.1800245