Mahmoud Abdelwahab Khedr

Dr. Mahmoud Abdelwahab Khedr

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 January 2025 in International Nursing Review
Verified
Journal Article
Open access
Abdulqadir J. NashwanAbdulqadir J. Nashwan
Abdulqadir J. Nashwan
JCJc A. Cabrega
Jc A. Cabrega
MOMutaz I. Othman
Mutaz I. Othman
Mahmoud Abdelwahab KhedrMahmoud Abdelwahab Khedr
Mahmoud Abdelwahab Khedr
YOYasmine M. Osman
Yasmine M. Osman
AMAhmad A. Mousa
Ahmad A. Mousa
Aim: This narrative review explores the integration of artificial intelligence (AI) into nursing informatics and examines its impact on nursing practice, healthcare delivery, education, and policy.Background: Nursing informatics, which merges nursing science with information management and communication technologies, is crucial in modern healthcare. The emergence of AI presents opportunities to improve diagnostics, treatment, and healthcare resource management. However, integrating AI into nursing practice also brings challenges, including ethical concerns and the need for specialized training.Sources of evidence: A comprehensive literature search was conducted from January 2013 to December 2023 using databases like PubMed, Google Scholar, and Scopus. Articles were selected based on their relevance to AI's role in nursing informatics, particularly in enhancing patient care and healthcare efficiency.Discussion: AI significantly enhances nursing practice by improving diagnostic accuracy, optimizing care plans, and supporting resource allocation. However, its adoption raises ethical issues, such as data privacy concerns and biases within AI algorithms. Ensuring that nurses are adequately trained in AI technologies is essential for safe and effective integration.Implications for nursing practice and policy: Policymakers should promote AI literacy programs for healthcare professionals and develop ethical guidelines to govern the use of AI in healthcare. This will ensure that AI tools are implemented responsibly, protecting patient rights and enhancing healthcare outcomes.Conclusion: AI offers promising advancements in nursing informatics, leading to more efficient patient care and improved decision‐making. Nonetheless, overcoming ethical challenges and ensuring AI literacy among nurses are critical steps for successful implementation.

3 October 2023 in Issues in Mental Health Nursing
Verified
Journal Article
Closed access
Abdulqadir J. NashwanAbdulqadir J. Nashwan
Abdulqadir J. Nashwan
SGSuzan Gharib
Suzan Gharib
MAMajdi Alhadidi
Majdi Alhadidi
Ayman Mohamed El-AshryAyman Mohamed El-Ashry
Ayman Mohamed El-Ashry
AAAsma Alamgir
Asma Alamgir
BABassema Abufarsakh
Bassema Abufarsakh
This narrative review explores the transformative impact of Artificial Intelligence (AI) on mental health nursing, particularly in enhancing psychiatric patient care. AI technologies present new strategies for early detection, risk assessment, and improving treatment adherence in mental health. They also facilitate remote patient monitoring, bridge geographical gaps, and support clinical decision-making. The evolution of virtual mental health assistants and AI-enhanced therapeutic interventions are also discussed. These technological advancements reshape the nurse-patient interactions while ensuring personalized, efficient, and high-quality care. The review also addresses AI's ethical and responsible use in mental health nursing, emphasizing patient privacy, data security, and the balance between human interaction and AI tools. As AI applications in mental health care continue to evolve, this review encourages continued innovation while advocating for responsible implementation, thereby optimally leveraging the potential of AI in mental health nursing.


27 November 2024 in BMC Nursing
Verified
Journal Article
Open access
PDF file
Ayman Mohamed El-AshryAyman Mohamed El-Ashry
Ayman Mohamed El-Ashry
STSamah Mohamed Taha
Samah Mohamed Taha
EEEman Sameh Abd Elhay
Eman Sameh Abd Elhay
HHHeba Abdel-Hamid Hammad
Heba Abdel-Hamid Hammad
Mahmoud Abdelwahab KhedrMahmoud Abdelwahab Khedr
Mahmoud Abdelwahab Khedr
MEMona Metwally El-Sayed
Mona Metwally El-Sayed
Objective: To examine the prevalence of imposter syndrome among nursing students and its association with depression, stress, and anxiety. Methods: A multi-center cross-sectional survey was conducted with 1572 nursing students randomly selected from three universities across Egypt. The study was conducted over 3 months, from the beginning of January to the end of March, during the academic year 2023/2024. Clance Imposter Phenomenon Scale and Depression Anxiety Stress Scale-21 were used for data collection. Results: A significant proportion of nursing students experience moderate to highly severe levels of depression, anxiety, and stress. Around a quarter of students had moderate depression, 22.6% had moderate anxiety, and 14.9% had severe anxiety. Additionally, 13.3% of participants experienced severe stress, with only 3.8% experiencing highly severe stress. The study also found that 46.3% of students experienced moderate imposter syndrome, with 33% having frequent imposter levels and 6.2% scoring intense imposter on the scale. Furthermore, imposter syndrome was positively correlated with depression, anxiety, and stress, and the total score of the Depression Anxiety Stress Scale (r = 0.639, p < 0.001). The stepwise linear regression analysis explained that 45.0% of the variance in students' depression, anxiety, and stress was due to imposter syndrome and other sociodemographic covariates. Conclusion: This study highlighted the relationship between imposter syndrome, depression, anxiety, and stress among nursing students. Specifically, female students in higher academic years, with lower grade point averages, living in urban areas, with lower family incomes, and not participating in hobbies are more prone to depression, anxiety, and stress. Nursing implications: These findings underscore the need for a holistic approach to managing the complex nature of mental health among nursing students. Incorporating education and resources on self-care and stress management techniques into nursing training programs is imperative for addressing the implications of imposter syndrome in nursing practice. Equipping nursing students with these essential skills can enhance their resilience, foster a healthier work environment, and ultimately improve patient care outcomes.

22 March 2024 in BMC Nursing
Verified
Journal Article
Open access
PDF file
MZMennat-Allah G. Abou Zeid
Mennat-Allah G. Abou Zeid
Mahmoud Abdelwahab KhedrMahmoud Abdelwahab Khedr
Mahmoud Abdelwahab Khedr
HRHeba Nasser Rayan
Heba Nasser Rayan
BMBoshra Mostafa
Boshra Mostafa
Ayman Mohamed El-AshryAyman Mohamed El-Ashry
Ayman Mohamed El-Ashry
Background: Organizational dehumanization has detrimental consequences for nurses’ wellbeing and leads to a stressful work environment. Moreover, it is very destructive to work engagement. Aim: To examine the mediating role of nurses’ work stress between organizational dehumanization and work engagement. Method: A cross-sectional research design was conducted with 245 staff nurses over a one-month period. The researchers used structured equation modeling. Results: Work engagement and organizational dehumanization levels were both moderate. In addition, the degree of job stress among the nurses was moderate, too. The results of the structural equation modeling showed that the association between organizational dehumanization and job engagement is partially mediated by work stress. Conclusions: For staff nurses to exhibit high levels of caring behaviors, this study emphasized the need to establish a work environment that employs tactics to improve workplace engagement and happiness. In addition to changing the organizational culture of nurses to eradicate organizational dehumanization and pressures related to the job.

3 November 2023 in Nurse Education in Practice
Verified
Journal Article
Closed access
Mahmoud Abdelwahab KhedrMahmoud Abdelwahab Khedr
Mahmoud Abdelwahab Khedr
TATalal Ali F Alharbi
Talal Ali F Alharbi
AAAminah Abdullah Alkaram
Aminah Abdullah Alkaram
RHRasha Mohamed Hussein
Rasha Mohamed Hussein