F Rajati, K Kamali, S Parvizy,
Volume 7, Issue 2 (19 2011)
Abstract
Background & Objectives: Custom-orienting is a critical issue for public health service. Peoples with a variety of developmental health care needs and perspectives are health care clients. Health accessibility through “Primary health care” has been approved and emphasized in Alma Ata in 1978. It is important to have a clear and transparent understanding of clients’ health needs and problems that would enable us to address such needs and prevent the negative consequences that might otherwise ensue. The aim of this study was to understand and gain deeper insight into health service customers’ lived experience of public health accessibility.
Methods: This study has been conducted with a phenomenological approach. Max van Manen six steps method of hermeneutic-phenomenology has been used. Nine health care clients were selected purposefully and interviewed semi-structured.
Results: The results of this experiment revealed the following six themes: to encounter with holistic learning chance, custom-oriented communications, qualified health care service, appropriate time-place health services, equality- orienting, and individual participation.
Conclusion: The participants believed that health accessibility is something more than just to have health services. Therefore, health education and social equality will bring about optimum health services. To develop multi-dimensional learning and to promote individual participation will be useful for more community empowerment.
M Rezaei, N Fakhri, S Shahsavari, F Rajati,
Volume 15, Issue 4 (Vol.15, No.4 2020)
Abstract
Background and Objectives: Gestational Diabetes Mellitus (GDM) is the most common metabolic disorder in pregnancy. In case of early detection, some of its complications can be prevented. The aim of this study was to investigate early prediction of GDM by logistic regression (LR), discriminant analysis (DA), decision tree (DT) and perceptron artificial neural network (ANN) and to compare these models.
Methods: The medical files of 420 pregnant women (2010-12) in Kermanshah health centers were evaluated using convenience sampling. Demographic data, pregnancy-related variables, lab tests results, and a diagnosis of GDM according to a fasting blood sugar level of 92 or more were collected from their files. After fitting the four models, the performance of the models was compared and according to the criteria of accuracy, sensitivity and specificity (based on the ROC curve), the superior model was introduced.
Results: Following the fitting of LR, DA, DT and perceptron ANN models, the following results were obtained. The accuracy of the above models was 0.81, 0.83, 0.78 and 0.83, respectively, the sensitivity of the models was 0.50, 0.63, 0.58 and 0.58, the specificity of the models was 0.96, 0.93, 0.87 and 0.94, and the area under the ROC curve was 0.86, 0.78, 0.73 and 0.87, respectively.
Conclusion: In predicting and categorizing the presence of GDM, the ANN model had a lower error rate and a higher area under the ROC curve compared to other models. It can be concluded that this model offers better predictions and is closer to reality than other models.
