7 research outputs found

    Determining the status of preconception care model in pregnant woman of Gorgan city (North of Iran) using structural equation modeling (SEM)

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    BACKGROUND: Preconception reduces unplanned pregnancies and plays an important role in reducing maternal and infant mortality. Considering the importance of these care services, this study was conducted to determine the status of preconception care (PCC) model with Structural Equation Modeling (SEM). MATERIALS AND METHODS: This cross-sectional descriptive study was conducted on 394 pregnant women referring to Gorgan's health centers. Samples were selected by multi-stage stratified sampling method. The instrument used in this research was a researcher-made questionnaire by Bayrami. Data were analyzed using R software version 4.1.4. Structural equation modeling (SEM) with weighted least square mean and variance method was used to fit the conceptual model and the significance level of the tests was considered 0.05. RESULTS: The results showed that PCC model was deemed appropriate as optimum conditions indicators of goodness of fit; knowledge with a coefficient of 0.182 leads to self-efficacy (SE), and SE affects the accessibility of facilities with a coefficient of 0.465 and the expected outcome with a coefficient of 0.500. After facility structure with a coefficient of 0.500, SE construct with a coefficient of 0.215 had the most effect on performing PCC behavior. CONCLUSIONS: Facilities and SE as a key element of empowerment have an important role in promoting PCC. Identifying the factors associated with this care appears to help health policymakers to planning for these caregivers more precise and sensitive. © 2022 Wolters Kluwer Medknow Publications. All rights reserved

    P A A FOURTH ORDER A-STABLE EXPLICIT ONE-STEP METHOD FOR SOLVING STIFF DIFFERENTIAL SYSTEMS ARISING IN CHEMICAL REACTIONS

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    Abstract: In this paper, a new A-stable explicit one-step integration method is developed for numerically solving stiff differential systems which characterize several kinds of linear reactions and diffusion from biochemistry, physiology, etc. The method is based on deriving a nonlinear relation between the dependent variable and its derivatives from the well known Taylor expansion. The method can be classified as a rational method. The accuracy and stability properties of the method are investigated and shown to yield at least fourth-order and A-stable. Some differential systems arising in chemical reactions will be solved to illustrate the performance and accuracy of the method
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