Catherine Waithira, Dr. Njenga, Mokua Gilbert Maroko
Teenage pregnancies and parenting are still major global concerns. In developing regions, there were reportedly 21 million teenage girls aged between 15 and 19 years who conceived in 2016, with 12 million of those pregnancies ending in live births. This study investigated the influence of psychological constructs on postpartum depression among breastfeeding teenagers in Kiambu County, Kenya. The objectives were; to find out the effect of life satisfaction on postpartum depression, to find the influence of family support on postpartum and to find the effect of self-awareness on postpartum depression. The study was guided by the hormone and cognitive theories. The study design was quantitative in nature. The study employed a cross-sectional research design. The target population was 10,382 teenage mothers who are currently breastfeeding. Participants were selected using random sampling to get a sample size of 385 teenage mothers who are breastfeeding. To gather primary data for this project, questionnaires were used. The study concluded that Based on the findings, it shows that life satisfaction has a significant influence on postpartum depression among breastfeeding teenagers. Higher levels of life satisfaction, including satisfaction in marriage/relationship, family treatment, societal treatment, and overall quality of life, are associated with a lower risk of postpartum depression. The study findings indicate that a strong family support plays a crucial role in reducing the risk of postpartum depression among breastfeeding teenagers. Positive family support, including emotional, practical and paternal support, is associated with lower levels of postpartum depression. The study findings indicate that higher levels of self-awareness contribute to a reduced risk of postpartum depression among breastfeeding teenagers.
Manasi S, Tushar R Bharadwaj, Nuthan PM, Naganischay M
The field of education has been revolutionized by advancements in big data techniques, enabling educators to gain precise and timely insights into students behavioral patterns. This newfound capability is invaluable for identifying specific student groups that require targeted attention and transitioning from relying solely on qualitative empirical knowledge to incorporating scientific quantitative analysis in student affairs management.
To fully harness the potential of this revolution, a meticulously developed system was implemented to apply data mining clustering method in analyzing the campus network behavior of 3,245 students in a particular grade at B University. Over a careful four-year period, a comprehensive dataset comprising 23.843 million Internet access records was collected. Through thorough analysis, it was discovered that the students could be categorized into four distinct groups based on their unique patterns of Internet access. Notably, the study successfully identified 350 students who exhibited remarkably high levels of network usage, allowing for a comprehensive examination of how their academic performance and other achievements were influenced.
This research, driven by the power of data, provides a practical and tangible demonstration of effectively utilizing data science in student affairs management. It presents compelling evidence that supports the accurate and scientific development of student affairs management practices by providing robust data support and generating invaluable insights.
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