The Correlation of Early Detection Results using Self Detection Application for Diabetes (SEDAB) with Haemoglobin A1C (HBA1C) Levels

• Published in: Jurnal ners dan kebidanan (Online) Vol. 9; no. 2; pp. 205 - 210
• Main Authors: Priyanto, Agus, Suprayitno, Eko Dian Hadi, Suhirman, Andika Santo
• Format: Journal Article
• Language: English
• Published: STIKes Patria Husada Blitar in collaboration with PPNI Kabupaten blitar 24.08.2022
• Subjects: application, early detection, diabetes miletus, hba1c levels
• ISSN: 2355-052X; 2548-3811
• DOI: 10.26699/jnk.v9i2.ART.p205-210

The increasing cases of diabetes mellitus significantly from year to year increase the burden on society and the government, because it requires time, cost and technology in handling. This disease can be controlled if the symptoms are detected early. The purpose of this research was to determine the correlation between the results of early detection using self-detection application for diabetes (SEDAB) with hemoglobin A1C (HbA1C) levels. The research was carried out on June 2022. The research was a correlative research with a cross sectional approach. The population was the people of the Mojoroto Kediri village. The samples were taken with consideration of a minimum sample of 30 respondents with simple random sampling technique. The instrument used to assess the level of symptoms of diabetes mellitus was the SEDAB application. Diabetes Mellitus category was assessed through the observation sheet of laboratory examination results Hemoglobin A1C (HbA1C. The data analysis used the Spearman Rank test. The test results with the Spearman rank test showed a p-value of = 0.000. This meant that there was a correlation between the level of diabetes mellitus symptoms results detection with Self Detection Application for Diabetic (SEDAB) with diabetes mellitus level based on HBA1c examination results. It is important for health workers to expand the scope of early detection of diabetes mellitus by promoting independent early detection using an effective and efficient diabetes mellitus early detection instrument, namely the SEDAB application which easy to access and use.