Efficacy of video educational program on interception of urinary tract infection and neurological stress among teenage girls: An uncontrolled experimental study
Usha Rani Kandula , Daisy Philip , Sunitha Mathew , Anusha Subin , Godphy AA , Nidhi Alex , Renju B
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引用次数: 3
Abstract
Background: Nowadays, there is a lot more emphasis on promoting health, wellbeing, and self-care including stress management strategies. Health is regarded as a natural extension of a wellness-oriented lifestyle. The objectives are to measure knowledge, evaluate the efficacy of a video education program, and examine the relationship between before and after-existing knowledge measurement and specified socio factors on Urinary tract infections (UTI) and neurological stress in teenage girls.
Materials and methods: This study employed an uncontrolled experimental study design. Initially, the mean and standard deviation of before and after-existing knowledge were determined. The ‘t’ test was applied to compare the variance between the before-existing and after-existing knowledge measurements of teenage girls on UTI and neurological stress, to find the efficacy of a video education program on eliminating urinary tract infection and neurological stress in teenage girls. Finally, the Chi-square model is used to measure the relationship between before-existing knowledge measurements and social characteristics.
Results and interpretation: The analyzed data found that the teenage girls' mean after-existing knowledge measurement was 33.46% times greater than their mean before-existing knowledge measurement of 24.6%. According to the findings, there is no strong relationship between teenage girls before-existing knowledge measurement and selected socio-demographic factors.
Conclusion: According to the study's findings, there is a critical need for healthcare providers to educate teenage girls about the interception of UTI prevalence and neurological stress management strategies inorder to avoid UTI among teenage girls.
Neuroscience informaticsSurgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology