Fatigue Detection (DTIK) : Monitoring a Fatigue
Abstract
This study aims to develop an application to detect fatigue and educate people about diabetes. The research method used is Research and Development (R&D). The analysis results obtained the conformity of the validation results of media experts 1 and 2 (kappa 0.654; p = 0.001). 95.5% of people with diabetes stated that the application was feasible without revision. The application contains a menu of measurement and education. In conclusion, DTIK is an application that can detect fatigue more efficiently during the COVID-19 pandemic. This application is free and can be used by people with diabetes anywhere and anytime.
Keywords: Application, Fatigue Detection, Diabetes Education
References
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Widyanthari, D. M., Jawi, I. M., Antari, G. A. A., & Widyanthini, D. N. (2020). Fatigue among diabetic patients: A descriptive study. EnfermerÃa ClÃnica, 30, 131–134. https://doi.org/https://doi.org/10.1016/j.enfcli.2020.07.027
Abbas, Q., & Alsheddy, A. (2021). Driver Fatigue Detection Systems Using Multi-Sensors, Smartphone, and Cloud-Based Computing Platforms: A Comparative Analysis. In Sensors (Vol. 21, Issue 1). https://doi.org/10.3390/s21010056
Abdelhafiz, A. H., Emmerton, D., & Sinclair, A. J. (2021). Diabetes in COVID-19 pandemic-prevalence, patient characteristics, and adverse outcomes. International Journal of Clinical Practice, July 2020, 1–11. https://doi.org/10.1111/ijcp.14112
Azar, A., Deighton, A. J., & Wang, B. X. (2021). Barts X as a Model for Teaching Digital Health. Medical Science Educator, 31(4), 1537–1538. https://doi.org/10.1007/s40670-021-01299-7
Banerjee, M., Chakraborty, S., & Pal, R. (2020). Diabetes self-management amid COVID-19 pandemic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(4), 351–354. https://doi.org/https://doi.org/10.1016/j.dsx.2020.04.013
Dahodwala, M., Geransar, R., Babion, J., de Grood, J., & Sargious, P. (2018). The impact of the use of video-based educational interventions on patient outcomes in hospital settings: A scoping review. Patient Education and Counseling, 101(12), 2116–2124. https://doi.org/https://doi.org/10.1016/j.pec.2018.06.018
Erraguntla, M., Sasangohar, F., & Qaraqe, K. (2020). Classification of fatigue phases in healthy and diabetic adults using wearable sensor. Sensor.
Fabi, A., Bhargava, R., Fatigoni, S., Guglielmo, M., Horneber, M., Roila, F., Weis, J., Jordan, K., & Ripamonti, C. I. (2020). Cancer-related fatigue: ESMO Clinical Practice Guidelines for diagnosis and treatment† Annals of Oncology, 31(6), 713–723. https://doi.org/10.1016/j.annonc.2020.02.016
Gayatri, R. W., Katmawanti, S., Wardani, H. E., & Yun, L. W. (2022). Android Application-Based Interactive Services for Diabetes Mellitus Patients. Proceedings of the 3rd International Scientific Meeting on Public Health and Sports (ISMOPHS 2021), 44(Ismophs 2021), 156–162. https://doi.org/10.2991/ahsr.k.220108.027
Griggs, S., & Morris, N. S. (2018). Fatigue Among Adults With Type 1 Diabetes Mellitus and Implications for Self-Management: An Integrative Review. The Diabetes Educator, 44(4), 325–339. https://doi.org/10.1177/0145721718782148
Handayani, E. U., Utami, R. L., & Tamsil, I. M. (2021). How to Create Effective and Efficient Naḥwu Media with Short Videos Based on the Camtasia Application? ALSUNIYAT: Jurnal Penelitian Bahasa, Sastra, Dan Budaya Arab, 4(1), 15–28. https://doi.org/10.17509/alsuniyat.v4i1.29232
Huang, S., Li, J., Zhang, P., & Zhang, W. (2018). Detection of mental fatigue state with wearable ECG devices. International Journal of Medical Informatics, 119, 39–46. https://doi.org/https://doi.org/10.1016/j.ijmedinf.2018.08.010
Hui, Y., Li, Y., Tong, X., Wang, Z., Mao, X., Huang, L., & Zhang, D. (2020). The risk factors for mortality of diabetic patients with severe COVID-19: A retrospective study of 167 severe COVID-19 cases in Wuhan. PLoS ONE, 15(12 December), 1–14. https://doi.org/10.1371/journal.pone.0243602
Jiang, X., Wang, J., Lu, Y., Jiang, H., & Li, M. (2019). Self-efficacy-focused education in persons with diabetes: A systematic review and meta-analysis. Psychology Research and Behavior Management, 12, 67–79. https://doi.org/10.2147/PRBM.S192571
Kalra, S., & Sahay, R. (2018). Diabetes Fatigue Syndrome. Diabetes Therapy, 9(4), 1421–1429. https://doi.org/10.1007/s13300-018-0453-x
Laakkonen, M.-P., & Kivivirta, V. (2022). Elevators as media objects manipulating information in time. New Media & Society, 14614448211067460. https://doi.org/10.1177/14614448211067460
Li, Z., Liu, G., Wang, L., Liang, Y., Zhou, Q., Wu, F., Yao, J., & Chen, B. (2020). From the insight of glucose metabolism disorder: Oxygen therapy and blood glucose monitoring are crucial for quarantined COVID-19 patients. Ecotoxicology and Environmental Safety, 197, 110614. https://doi.org/10.1016/j.ecoenv.2020.110614
Moran, J., Briscoe, G., & Peglow, S. (2018). Current Technology in Advancing Medical Education: Perspectives for Learning and Providing Care. Academic Psychiatry, 42(6), 796–799. https://doi.org/10.1007/s40596-018-0946-y
Muijs, L. T., de Wit, M., Knoop, H., & Snoek, F. J. (2021). Feasibility and user experience of the unguided web-based self-help app ‘MyDiaMate’ aimed to prevent and reduce psychological distress and fatigue in adults with diabetes. Internet Interventions, 25(July 2020), 1–9. https://doi.org/10.1016/j.invent.2021.100414
Puspitarini, Y. D., & Hanif, M. (2019). Using Learning Media to Increase Learning Motivation in Elementary School. Anatolian Journal of Education, 4(2), 53–60. https://doi.org/10.29333/aje.2019.426a
Sankoda, A., Waki, K., Yamaguchi, S., Mieno, M., Nangaku, M., Yamauchi, T., & Ohe, K. (2021). Effect of Digital Health Among People With Type 2 Diabetes Mellitus During the COVID-19 Pandemic in Japan. Journal of Diabetes Science and Technology, 16(1), 256–258. https://doi.org/10.1177/19322968211050040
Sculco, C., Belletti, G., Fontanelli, M., & Galeone, C. (2022). Patient-Support Program in Diabetes Care During the Covid-19 Pandemic : An Italian Multicentric Experience. Patient Preference and Adherenceatient Preference and Adherence, 113–122.
Tuma, F. (2021). The use of educational technology for interactive teaching in lectures. Annals of Medicine and Surgery, 62, 231–235. https://doi.org/https://doi.org/10.1016/j.amsu.2021.01.051
Veazie, S., Winchell, K., Gilbert, J., Paynter, R., Ivlev, I., Eden, K. B., Nussbaum, K., Weiskopf, N., Guise, J. M., & Helfand, M. (2018). Rapid Evidence Review of Mobile Applications for Self-management of Diabetes. Journal of General Internal Medicine, 33(7), 1167–1176. https://doi.org/10.1007/s11606-018-4410-1
Widyanthari, D. M., Jawi, I. M., Antari, G. A. A., & Widyanthini, D. N. (2020). Fatigue among diabetic patients: A descriptive study. EnfermerÃa ClÃnica, 30, 131–134. https://doi.org/https://doi.org/10.1016/j.enfcli.2020.07.027
Published
2023-02-04
Section
Articles
Copyright (c) 2023 Rumentalia Sulistini, Devi Mediarti, Imelda Erman, Ririn Sri Handayani
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
