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Use of Artificial Intelligence for Personalized Postnatal Education on Episiotomy Care and the Effect on Knowledge, Perception, and Self-Care Practices
Subject area: Science,Engineering and Technology · Area of research: Nursing
DOI: https://doi.org/10.64388/IREV9I12-1719054
Abstract
Episiotomy care is an important aspect of postnatal recoveries. However, several women have low knowledge and as well lack confidence in managing the self-care practices after childbirth. Therefore, the study evaluated the application of artificial intelligence for personalized postnatal education on episiotomy care and its impact on the mother’s experience, perceptions and the self care practice. The outcome of the structured artificial intelligence-based education solutions was developed using the machine learning algorithms to deliver individualized and timely postnatal guidelines to the request of postnatal mothers that have gone through episiotomy. From the consulted literatures, data were collated using standard tools for analyses, assessment of knowledge, perceptions as well as self care practices before and after the interventions. The results revealed by such studies showed that there was significant improvement in the knowledge of participants, with more perceptions on episiotomy care as well as improvement in the care practices based on the artificial intelligence guidelines. The findings show that personalized artificial intelligence postnatal education is quite good in improving mothers’ knowledge, thus leading to the reduction in misconception, fetal loss and promoting adequate self-care behaviour.
Keywords
Artificial Intelligence. Personalized Care, Postnatal Education, Episiotomy, Practices
How to cite this paper
@article{1719054,
author = {Peace Ibukunoluwa OMOYENI, Olaitan Theresa BAMIGBOYE, Olubukola Esther Abiodun-Ojo},
title = {Use of Artificial Intelligence for Personalized Postnatal Education on Episiotomy Care and the Effect on Knowledge, Perception, and Self-Care Practices},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {12},
pages = {2096-2104},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1719054.pdf},
abstract = {Episiotomy care is an important aspect of postnatal recoveries. However, several women have low knowledge and as well lack confidence in managing the self-care practices after childbirth. Therefore, the study evaluated the application of artificial intelligence for personalized postnatal education on episiotomy care and its impact on the mother’s experience, perceptions and the self care practice. The outcome of the structured artificial intelligence-based education solutions was developed using the machine learning algorithms to deliver individualized and timely postnatal guidelines to the request of postnatal mothers that have gone through episiotomy. From the consulted literatures, data were collated using standard tools for analyses, assessment of knowledge, perceptions as well as self care practices before and after the interventions. The results revealed by such studies showed that there was significant improvement in the knowledge of participants, with more perceptions on episiotomy care as well as improvement in the care practices based on the artificial intelligence guidelines. The findings show that personalized artificial intelligence postnatal education is quite good in improving mothers’ knowledge, thus leading to the reduction in misconception, fetal loss and promoting adequate self-care behaviour.},
keywords = {Artificial Intelligence. Personalized Care, Postnatal Education, Episiotomy, Practices},
month = {June},
doi = {https://doi.org/10.64388/IREV9I12-1719054}
}