Browsing by Author "Simsek-Cetinkaya S."

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Effects of a smartphone-based nursing counseling and feedback system for women with gestational diabetes on compliance, glycemic control, and satisfaction: a randomized controlled study
(2022-01-01) Simsek-Cetinkaya S.; Koc G.
Background: Gestational diabetes mellitus (GDM) is a health problem that threatens maternal and infant health with increasing prevalence in the world. Patient education is very effective in managing the disease. Aim: In this study, we aimed to investigate the effect of a smartphone-based nursing counseling and feedback system on physical activity, glycemic control, and patient satisfaction among women with GDM. Design: This was a single-center, randomized controlled study. Women with GDM were randomized to the intervention and control groups. The groups received (1) routine biweekly prenatal care (control group) or (2) counseling and feedback from the nurse via a platform installed on their smartphone (smartphone group) in addition to routine clinical care. Results: A total of 45 GDM patients were randomly assigned to either the control (n = 22) or intervention groups (n = 23). Women in the intervention group received a mobile and web-based counseling program in addition to standard care. GDM knowledge, physical activity, and adherence to diet were higher in the intervention group compared to the control group (p <.05). There was no difference between the groups in terms of glucose level (p >.05). This study concluded that the mobile and web-based nursing counseling program increased patient satisfaction. Conclusion: Nursing counseling and feedback provided via smartphone is important as a factor in the individualization of care. It increased the physical activity status of women, facilitated their adherence to diet, increased patient satisfaction, and reduced the rate of insulin therapy. No effect was found on blood glucose values.
Evaluation of the effectiveness of artificial intelligence assisted interactive screen-based simulation in breast self-examination: An innovative approach in nursing students
(2023-08-01) Simsek-Cetinkaya S.; Cakir S.K.
Background: Breast self-examination is important in the early diagnosis of breast cancer. The use of traditional education methods is insufficient for student nurses to gain breast self-examination skills in nurse education. New and different education methods are needed to gain skills in nurse education. Objective: The aim of this study was to evaluate the effectiveness of artificial intelligence-assisted screen-based simulations practice and standard patient simulation in teaching breast self-examination skills in nursing undergraduate students. Design: This study was a comparative intervention trial. Settings: This study was conducted at a university in XX, in XXX in the first semesters of the academic years 2022–2023. Methods: This study enlisted 103 students enrolled in first year in a nursing department. Students were randomized into artificial intelligence-assisted screen-based simulations practice group (n = 52) and standard patient simulation group (n = 51). Data were collected using student description form, breast self-examination checklist, student satisfaction and self-confidence in learning scale, Spielberger's state and trait anxiety inventory. Results: The highest score regarding the total score means of breast self-examination skills belonged to the standard patient simulation group, and the differences between the groups were found to be statistically significant (p < 0.05). Although the mean score of anxiety levels of the students' artificial intelligence-assisted screen-based simulations practice group was higher than the standard patient simulation (p < 0.05). The mean score of the students' satisfaction with the simulation was higher in artificial intelligence-assisted screen-based simulations practice group than the standard patient simulation group (p < 0.05). Conclusions: The results of the research showed that the use of artificial intelligence-assisted simulation learning increased students' satisfaction, but at the same time students' anxiety increased. In addition, artificial intelligence-assisted simulation learning is not as effective as standard patient simulation learning in gaining breast self-examination skills.