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      Factors associated with decision-making autonomy in healthcare utilization among married women from the Indonesia demographic health survey 2017

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          Abstract

          Women’s autonomy in healthcare decision-making is crucial not only for improving maternal health but also enhancing their overall health and well-being. However, most studies focused solely on fertility, child health, or maternal healthcare use, often overlooking the broader aspects of women’s health. Due to this reason, the magnitudes and factors associated with women’s autonomy in other types of healthcare remain unclear. Therefore, this study aimed to estimate the magnitude and identify factors associated with healthcare decision-making autonomy among married women in Indonesia. A national cross-sectional study was conducted among married women using the Indonesia Demographic and Health Surveys 2017. Women’s healthcare decision-making autonomy was measured based on responses regarding the individual typically responsible for making healthcare decisions on behalf of the respondent. Potential factors, such as intrapersonal, interpersonal, community, and policy-related were obtained. Multinomial logistic regression was used to determine the associations between potential factors and outcomes. The odds ratio (OR) and 95% confidence intervals (CI) of the analysis were reported. The respondents in this study comprised 16,050 married women across 34 provinces in Indonesia. Most respondents (46.4%) reported making healthcare decisions independently. The result showed that several factors were associated with either women’s full autonomy or jointly with the husbands in the healthcare decision-making. These factors included ownership of mobile telephones, urban living, residency in Java, Bali, Sulawesi, Maluku and Papua islands, participation of women in decision-making on how to spend their earnings, on large household purchases, no financial barrier in accessing treatment, and independence in visiting a medical center. Public health interventions should focus on vulnerable women, such as those who live in rural areas, participate less in the decision-making of earnings spending and household purchase, and are incapable of visiting a medical center alone to increase the healthcare decision-making autonomy. Collaborative efforts with health facilities in each region can support the implementation of this intervention.

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          Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.

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            An Ecological Perspective on Health Promotion Programs

            During the past 20 years there has been a dramatic increase in societal interest in preventing disability and death in the United States by changing individual behaviors linked to the risk of contracting chronic diseases. This renewed interest in health promotion and disease prevention has not been without its critics. Some critics have accused proponents of life-style interventions of promoting a victim-blaming ideology by neglecting the importance of social influences on health and disease. This article proposes an ecological model for health promotion which focuses attention on both individual and social environmental factors as targets for health promotion interventions. It addresses the importance of interventions directed at changing interpersonal, organizational, community, and public policy, factors which support and maintain unhealthy behaviors. The model assumes that appropriate changes in the social environment will produce changes in individuals, and that the support of individuals in the population is essential for implementing environmental changes.
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              Purposeful selection of variables in logistic regression

              Background The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process. Methods In this paper we introduce an algorithm which automates that process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE. Results We show that the advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction. In addition to significant covariates, this variable selection procedure has the capability of retaining important confounding variables, resulting potentially in a slightly richer model. Application of the macro is further illustrated with the Hosmer and Lemeshow Worchester Heart Attack Study (WHAS) data. Conclusion If an analyst is in need of an algorithm that will help guide the retention of significant covariates as well as confounding ones they should consider this macro as an alternative tool.
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                Author and article information

                Contributors
                sofa.alfian@unpad.ac.id
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                21 March 2025
                21 March 2025
                2025
                : 15
                : 9770
                Affiliations
                [1 ]Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, ( https://ror.org/00xqf8t64) Jatinangor, Indonesia
                [2 ]Center of Excellence for Pharmaceutical Care Innovation, Universitas Padjadjaran, ( https://ror.org/00xqf8t64) Jatinangor, Indonesia
                [3 ]Center for Health Technology Assessment, Universitas Padjadjaran, ( https://ror.org/00xqf8t64) Jatinangor, Indonesia
                [4 ]Department of Pharmaceutics and Industrial Pharmacy, College of Pharmacy, Taif University, ( https://ror.org/014g1a453) Taif, Saudi Arabia
                Article
                94057
                10.1038/s41598-025-94057-3
                11928671
                40119094
                5f36d017-a5c6-4290-becf-6b0406bf6e0a
                © The Author(s) 2025

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 July 2024
                : 11 March 2025
                Funding
                Funded by: University of Padjadjaran
                Categories
                Article
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                © Springer Nature Limited 2025

                Uncategorized
                women,autonomy,healthcare,decision-making,demographic health survey,indonesia,diseases,health care,risk factors

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