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Effectiveness of the "Create Sensitivity" Caring Model on Blood Glucose/ Glycosylated Hemoglobin and Quality of Life in Patients With Type 2 Diabetes.
Open Nursing Journal 2018
Objective: This study aimed to determine the effectiveness of the "Create Sensitivity" caring model on blood glucose/ glycosylated hemoglobin and quality of life in patients with type 2 Diabetes.
Methods: This study enrolled 70 patients from an educational hospital in Kurdistan, Iran. The model was implemented among the test group over a period of 3 months. Blood glucose/ glycosylated hemoglobin and patients' quality of life were measured before and after intervention. Data were analyzed using version 21 of the statistical software SPSS.
Results: After the intervention, significant differences existed between the test and control groups both in blood glucose levels (means, 146.4 ± 51.3 mg/dl and 175.6 ± 59.8 mg/dl, respectively; P =0.032) and in glycosylated hemoglobin (means, 67.89 ± 13.34 mmol/mol and 80.03 ± 17.234 mmol/mol, respectively; P = 0.002). Additionally, there was also a significant difference between the quality of life of the patients in test group (mean, 58.25 ± 5.3) and that in the control group (mean, 47.02 ± 4.5) ( P = 0.0001).
Conclusion: Use of this model was associated with reducing fasting blood glucose and glycosylated hemoglobin and increasing the total mean of quality of life in the patients in the test group. So, the application of this model is recommended.
Methods: This study enrolled 70 patients from an educational hospital in Kurdistan, Iran. The model was implemented among the test group over a period of 3 months. Blood glucose/ glycosylated hemoglobin and patients' quality of life were measured before and after intervention. Data were analyzed using version 21 of the statistical software SPSS.
Results: After the intervention, significant differences existed between the test and control groups both in blood glucose levels (means, 146.4 ± 51.3 mg/dl and 175.6 ± 59.8 mg/dl, respectively; P =0.032) and in glycosylated hemoglobin (means, 67.89 ± 13.34 mmol/mol and 80.03 ± 17.234 mmol/mol, respectively; P = 0.002). Additionally, there was also a significant difference between the quality of life of the patients in test group (mean, 58.25 ± 5.3) and that in the control group (mean, 47.02 ± 4.5) ( P = 0.0001).
Conclusion: Use of this model was associated with reducing fasting blood glucose and glycosylated hemoglobin and increasing the total mean of quality of life in the patients in the test group. So, the application of this model is recommended.
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