Artificial Intelligence: Innovation and Midwifery Education, Practice, And Research in Arab Region; Systematic Review Based Findings
Main Article Content
Keywords
Artificial Intelligence, Innovation, Midwifery Education, Midwifery Practice, Midwifery, Research, Arab Region
Abstract
Background: Artificial intelligence innovation is defined as highly specialized productive and generalizable practices in every field of life. In the healthcare setting artificial intelligence has certain revolutions associated with the linkage of healthcare practices to provide humankind with effective healthcare interventions. Midwifery operationalizing the artificial intelligence innovation to enhance them is knowledge competencies and skills regarding the process of restoration and after a birth period.
Aim: To evaluate the literature based on artificial intelligence innovation to midwifery education, practice, and research in the Arab region.
Method: A systematic review of rationalize the fundamental strategies of Kitchenham systematic review procedure. The data collected from the Arab region published period articles from 2019 to 2023. The process involves the identification, screening, eligibility identification, and inclusion of the studies with respect to the desired concern.
Results: As 15 articles were selected out of 1000,850. Selection of the study based on identified criteria of the selection confidence interval of 95% with a margin of error of 5%.
Conclusion: Artificial intelligence has more significant work to do with the education practice and research in the paradigm of midwifery it focuses largely on identifying potential health concerns associated with the new advanced technology. Operationalization of machine learning at deep learning is one of the basic consequences through which the higher extent of health prognosis is developed to understand the health promotional parameter.
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2. Al Ali, Y. T., Al Qahtani, A. A., Assiri, H. Y., Alyahya, A. M., Al Alkharsh, F. S., Assiri, A. Y., ... & Alasiri, Y. H. (2022). Effectiveness Of Technology On Organizational Development And Services In The Saudi Health Sector. Journal of Pharmaceutical Negative Results, 2144-2155.
3. Al-Kubaisi, H., Shahbal, S., Batool, R., & Khan, A. (2023). Artificial intelligence as Revolutionary Era in Handling Financial Burden in Education Field-A Meta-Analysis Based Study. Journal of Population Therapeutics and Clinical Pharmacology, 30(8), 172-182.
4. Almarwani, A. M., & Elshatarat, R. (2022). Understanding Learning Styles in Undergraduate Nursing Programs of the Kingdom of Saudi Arabia: An Integrative Literature Review. The Open Nursing Journal, 16(1).
5. Al-Marzooqi, A. M. S. M., Al Dulaimi, A. M. Z., Lubis, A., Siren, N. B. H., & Kassim, S. B. (2022). Human Development Index and Innovation Capabilities in the Health Sector of UAE: Human Development Index in Health Care. Journal of Population Therapeutics and Clinical Pharmacology, 29(03).
6. Al-Marzooqi, S. M., Al Dulaimi, A. M. Z., Lubis, A., Siren, N. B. H., & Kassim, S. B. Journal of Population Therapeutics & Clinical Pharmacology.
7. Almutairi, S. M., Noshili, A. I., Almani, H. A., Aldousari, N. Y., Aljedani, G. H., Bakhsh, A. A., ... & Shahbal, S. (2022). The Magnet Hospital
Concept is an Ideological Approach to Job Satisfaction and Quality of Care: A Systematic Review. Journal of Positive Psychology and Wellbeing, 137-145.
8. AlOmari, F. (2022). Does a doctor's skill influence patient satisfaction, loyalty, and compliance in low-medium income countries. International Journal of Information and Decision Sciences, 14(2), 149-163.
9. Alruwaili, S. O. M., Shahbal, S., Alharbi, F. A., Makrami, W. A., Alshehri, M. S., Alanazi, R. O., ... & Alharbi, B. M. (2022). The Effect Of Workload On The Commitment To Work For The Nurses, A Systematic Review. Journal of Positive School Psychology, 6(11), 2880-2896.
10. Alvarez, E. M., Force, L. M., Xu, R., Compton, K., Lu, D., Henrikson, H. J., ... & Burkart, K. (2022). The global burden of adolescent and young adult cancer in 2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet Oncology, 23(1), 27-52.
11. Anadol, Y., & Behery, M. (2020). Humanistic leadership in the UAE context. Cross Cultural & Strategic Management, 27(4), 645-664.
12. Bala, A. (2021). Design Science Research throughout the years: an in-depth analysis of papers published in the Journal of Purchasing and Supply Management and Journal of Supply Chain Management supported by Artificial Intelligence (Master's thesis, University of Twente).
13. Bani Issa, W., Al Akour, I., Ibrahim, A., Almarzouqi, A., Abbas, S., Hisham, F., & Griffiths, J. (2020). Privacy, confidentiality, security and patient safety concerns about electronic health records. International nursing review, 67(2), 218-230.
14. Blease, C., Locher, C., Leon-Carlyle, M., & Doraiswamy, M. (2020). Artificial intelligence and the future of psychiatry: qualitative findings from a global physician survey. Digital Health, 6, 2055207620968355.
15. Cirillo, D., Catuara-Solarz, S., Morey, C., Guney, E., Subirats, L., Mellino, S., ... & Mavridis, N. (2020). Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare. NPJ digital medicine, 3(1), 81.
16. Çitil, E. T., & Çitil Canbay, F. (2022). Artificial intelligence and the future of midwifery: What do midwives think about artificial intelligence? A qualitative study. Health Care for Women International, 43(12), 1510-1527.
17. Conde, F. E. (2022). Achieving the Promise of a First-Rate Education: The UAE’s Attempt at Transforming Education Through the Lens of theLeadership for Learning Theoretical Framework. In Handbook of Research on Teacher Education: Pedagogical Innovations and Practices in the Middle East (pp. 375-393). Singapore: Springer Nature Singapore.
18. Damar, M. U. H. A. M. M. E. T. (2022). What the literature on medicine, nursing, public health, midwifery, and dentistry reveals: An overview of the rapidly approaching metaverse. Journal of Metaverse, 2(2), 62-70.
19. Demirezen, E. (2022). Nursing And Midwifery In The World Of Artificial Intelligence. Artificial Intelligence Applications and Their Economic Effects On The Field Of Health Care, 81.
20. El-Saharty, S., & Liu, A. C. (2021). COVID-19 in the Gulf Cooperation Council Countries: Health Impact and Response. In Handbook of Healthcare in the Arab World (pp. 1325-1357). Cham: Springer International Publishing.
21. Flanagin, A., Frey, T., Christiansen, S. L., & AMA Manual of Style Committee. (2021). Updated guidance on the reporting of race and ethnicity in medical and science journals. Jama, 326(7), 621-627.
22. Frenk, J., Chen, L. C., Chandran, L., Groff, E. O., King, R., Meleis, A., & Fineberg, H. V. (2022). Challenges and opportunities for educating health professionals after the COVID-19 pandemic. The Lancet, 400(10362), 1539-1556.
23. Golden, B., Asiodu, I. V., Franck, L. S., Ofori-Parku, C. Y., Suárez-Baquero, D. F. M., Youngston, T., & McLemore, M. R. (2022). Emerging approaches to redressing multi-level racism and reproductive health disparities. NPJ Digital Medicine, 5(1), 169.
24. Handayani, F., Nurhayati, N., & Kamila, A. (2022). Artificial intelligence as an educational media to improve adolescent reproductive health: Research and development studies. Jurnal Keperawatan Padjadjaran, 10(3), 170-176.
25. Hernon, O., McSharry, E., MacLaren, I., & Carr, P. J. (2023). The use of educational technology in teaching and assessing clinical psychomotor skills in nursing and midwifery education: A state-of-the-art literature review. Journal of Professional Nursing, 45, 35-50.
26. Hernon, O., McSharry, E., MacLaren, I., Dunne, R., & Carr, P. J. (2023). The Use of Educational Technology in Undergraduate and Postgraduate Nursing and Midwifery Education: A Scoping Review. CIN: Computers, Informatics, Nursing, 41(3), 162-171.
27. Higgins, O., Short, B. L., Chalup, S. K., & Wilson, R. L. (2023). Artificial intelligence (AI) and machine learning (ML) based decision
support systems in mental health: An integrative review. International Journal of Mental Health Nursing.
28. Hunt, X., Tomlinson, M., Sikander, S., Skeen, S., Marlow, M., du Toit, S., & Eisner, M. (2020). Artificial intelligence, big data, and mHealth: The frontiers of the prevention of violence against children. Frontiers in artificial intelligence, 3, 543305.
29. Jaspher, M. J., & Kavichelvi, K. (2021). Innovation: Nurse Practitioner In Midwifery (Npm) The Future Of Indian Nursing. Young, 1(02), 26-29.
30. Kais, E. C. F., Ghafouri, A., & Al Shamsi, M. (2021). A Review of the Impact of Artificial Intelligence on the Healthcare Industry: A United Arab Emirates Perspective.
31. Kemp, J., Maclean, G. D., Moyo, N., Kemp, J., Maclean, G. D., & Moyo, N. (2021). Professionalising Midwifery. Global Midwifery: Principles, Policy, and Practice, 149-162.
32. Kiguba, R., Olsson, S., & Waitt, C. (2023). Pharmacovigilance in low‐and middle‐income countries: A review with particular focus on Africa. British journal of clinical pharmacology, 89(2), 491-509.
33. Kocarnik, J. M., Compton, K., Dean, F. E., Fu, W., Gaw, B. L., Harvey, J. D., ... & Dhimal, M. (2022). Cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life years for 29 cancer groups from 2010 to 2019: a systematic analysis for the global burden of disease study 2019. JAMA oncology, 8(3), 420-444.
34. Kumar, M., Patil, J., Shastry, K. A., Darshan, S., Sastry, N. K. B., Moonesar, I. A., ... & Rao, A. (2022). ICT Enabled Disease Diagnosis, Treatment and Management—A Holistic Cost-Effective Approach Through Data Management and Analysis in UAE and India. Frontiers in Artificial Intelligence, 5.
35. Lazarus, M. D., Truong, M., Douglas, P., & Selwyn, N. (2022). Artificial intelligence and clinical anatomical education: Promises and perils. Anatomical Sciences Education.
36. Malik, A., Kumar, S., Basu, S., & Bebenroth, R. (2023). Managing disruptive technologies for innovative healthcare solutions: The role of high-involvement work systems and technologically-mediated relational coordination. Journal of Business Research, 161, 113828.
37. Meen, A. (2021). From theory to practice. British Journal of Midwifery, 29(4), 186-188.
38. Mollura, D. J., Culp, M. P., Pollack, E., Battino, G., Scheel, J. R., Mango, V. L., ... & Dako, F.(2020). Artificial intelligence in low-and middle-income countries: innovating global health radiology. Radiology, 297(3), 513-520.
39. Mounsef, J., Hasib, M., & Raza, A. (2022). Building an Arabic Dialectal Diagnostic Dataset for Healthcare. International Journal of Advanced Computer Science and Applications, 13(7).
40. Msweli, N. T., Twinomurinzi, H., & Ismail, M. (2022). The International Case for Micro-Credentials for Life-Wide And Life-Long Learning: A Systematic Literature Review. Interdisciplinary journal of information, knowledge, and management, 17, 151-190.
41. Noshili, A. I., Shahbal, S., Khan, A., Hamdi, A., Amri, Y., Kariri, M. Q., ... & Althawwabi, R. B. Global health during the past and present pandemic and community health nursing.
42. Nugroho, B. S., Maruf, I. R., Bangkara, B. A., Jayanto, I., & Ernawati, K. (2022). Understanding Best Practices in Public Health Services and Leadership in Indonesia. Science Midwifery, 10(2), 1141-1148.
43. NYONI, S. P., CHIHOHO, T. A., & NYONI, T. (2021). Projecting Total Fertility Rates for Jordan Using Artificial Neural Networks. International Research Journal of Innovations in Engineering and Technology, 5(8), 211.
44. Obaideen, K., Shihab, K. H. A., Madkour, M. I., & Faris, M. E. (2022). Seven decades of Ramadan intermittent fasting research: Bibliometrics analysis, global trends, and future directions. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 16(8), 102566.
45. O'Connor, S., Peltonen, L. M., Ronquillo, C., Chu, C., Topaz, M., Chen, L. Y. A., & Lee, J. J. (2023). A Framework for Embedding Artificial Intelligence in Nursing: Education, Innovation, Collaboration, and Implementation–the ALIGN Model.
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47. Oshida, Y. (2021). Artificial Intelligence for Medicine. In Artificial Intelligence for Medicine. De Gruyter.
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Published
May 5, 2023
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How to Cite
Sahar M. Yakout, & Ibtesam Jahlan. (2023). Artificial Intelligence: Innovation and Midwifery Education, Practice, And Research in Arab Region; Systematic Review Based Findings. Journal of Population Therapeutics and Clinical Pharmacology, 30(9), 198–214. https://doi.org/10.47750/jptcp.2023.30.09.021
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