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Changes in attitudes to childbirth in modern times illustrated over three generations in Iraq
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Abstract<sec><title>Objective

To describe changes in attitudes and expectations of labor over the previous six decades, comparing the Iraqi generation who labored at home without medical assistance with their descendants.

Study Design

We used semi‐structured telephone interviews with 22 women across three generations of one extended family living and giving birth in Iraq between the 1950s and the 2010s. Qualitative data were analyzed thematically using open, axial, and selective coding.

Results

Each generation experienced a paradigm shift in childbirth, from exclusive home births to hospital‐directed maternity care, to a trend that favors planned cesarean birth, driven by generation‐specific changes in outlook. Emerging themes included social influences, changing technology, and medical professionals' recommendations; all of these affected attitudes toward childbirth and pregnancy. There were generational disconnects in perceptions concerning the reasons childbirth has changed over the past 60 years, with the youngest generation citing wider pressures regarding body image and marital relationships as two of the factors affecting preferences in childbirth options.

Conclusions

Societal changes and availability of healthcare services affect women's choices and experiences of childbirth. To be successful, efforts to improve women's experiences in labor, as well as maternal and neonatal outcomes, must consider these wider sociocultural issues.

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Fri Jul 24 2020
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Speculations of Immunotherapy in COVID-19 Patients with Practical Applications During Childhood and Pregnancy
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Mon Dec 30 2013
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Efficacy of Saccharomyces cerevesiae on promoting growth in tomato: Nahida M.Saleh |Adnan A. Issa
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Developing an Immune Negative Selection Algorithm for Intrusion Detection in NSL-KDD data Set
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Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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