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Nursing Dissertation Topics I phdassistance.com
Introduction
Nursing education and practice are progressing at a fast pace; however, the key challenges persist and prevent the nursing workforce from being effectively prepared. The recent studies have shown that there are still gaps that need to be filled, as pointed out by Wei et al. (2025), Wang and Raman (2025), and Daneshfar and Moonaghi (2025). Among these, the most prominent are the impossibility of giving and accepting AI transparently and ethically, the unavailability of training in digital skills, the inadequate research designs in blended learning, and the lack of evaluation in simulation-based education.
All these problems lead to the conclusion that there is a need for more convincing proofs, clearer educational models, and more rigorous research methods that deal with the areas of clinical competence, psychological well-being, and technological readiness. The dissertation topics outlined below have been specifically designed to address these gaps and promote the development of nursing education through ethical, culturally responsive, and scientifically grounded practices.
Proposed PhD Topic 1
Developing Transparent and Explainable Artificial Intelligence Systems for Nursing Practice: A Framework for Enhancing Trust, Safety, and Clinical Decision Support
Background Context
The use of AI in nursing practice has grown significantly in a short span of time, yet its rollout is still facing substantial challenges regarding transparency and trust. According to Wei et al. (2025) in Frontiers in Medicine, a considerable number of sophisticated AI technologies are functioning as opaque “black boxes” that do not allow nurses to understand the process by which clinical suggestions are made. The non-interpretability of such systems curtails the clinicians’ trust, increases the safety concerns, and also makes it less probable to use them in critical areas like emergency departments, decision-making in surgery, and clinical decision support systems. Furthermore, nursing staff often cite ethical issues, lack of communication with patients, and unreliability as their concerns while using AI tools that are non-transparent. Overcoming these drawbacks will need intensive research work to come up with explainable, user-centred AI systems that would go along with the cognitive processes and always demands of the nursing workflow.
PhD-Level Verification
A PhD study is needed for the formation, validation, and assessment of a multi-dimensional framework that promotes the implementation of AI with ethical principles, clinical training, and cultural adaptability in nursing.
Research Questions
• Which ethical standards have to be set to ensure AI in nursing protects the patient’s right to make decisions, their privacy, and the communication of trust between the patient and the nurse?
• In what ways can nursing courses be restructured to provide students with both AI knowledge and hands-on skills development?
• What changes can be made to AI frameworks so that they can be used in culturally diverse and low-resource healthcare settings?
PhD-Level Contributions
- • A credible, ethical AI framework for nursing that is applicable worldwide.
- • An AI-enhanced nursing education model where curriculum guidelines are provided.
- • Migrant-friendly and fair healthcare AI use through practical tools.
Reference
Wei, Q., Pan, S., Liu, X., Hong, M., Nong, C., & Zhang, W. (2025). The integration of AI in nursing: addressing current applications, challenges, and future directions. Frontiers in medicine, 12, 1545420. https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1545420/full
Proposed PhD Topic 2
Establishing an Ethical and Educational Framework for AI Integration in Nursing: Addressing Workforce Preparedness, Autonomy, and Culturally Responsive Implementation
Background Context
The application of AI technology in the healthcare sector is quite fast and unstoppable, but still, the nursing sector is unable to keep up with it due to many systemic issues. The study conducted by Wei et al. (2025) brings out the matter of the absence of ethical frameworks concerning nursing, the shortage of AI-related training in nursing and the lack of culturally adaptable implementation strategies as the main reasons for the uncertainty of AI’s impact on patient autonomy, data privacy, and the confidentiality of the nurse-patient relationship. In many parts of the world, nursing programs provide very little training on AI skills, and therefore, the graduates are not well prepared for the digital healthcare environment that is developing. Thus, it is very important to make a comprehensive ethical and educational framework that will help in responsible AI integration and also prepare the nursing workforce globally for future practice.
PhD-Level Verification
It is going to take a PhD to create the multidimensional framework that is going to be composed of various factors like ethical principles, clinical training, and cultural adaptability, which will then be merged with AI for nursing.
Research Questions
• Which ethical principles should be used as the basis for the application of AI in the nursing field so that the following aspects can be protected?
• In what ways can the nursing education system be changed to include not only the theoretical understanding of AI but also that of its practical use as a competency-building activity?
• How can AI systems be modified to be suitable for clinics with diverse cultures and limited resources?
PhD-Level Contributions
• An integration of nursing education and AI with curriculum guidelines is being developed.
• Increased availability of practical tools for the adoption of AI in a manner that is culturally sensitive and equitable in healthcare settings.
Suggested Readings
Wei, Q., Pan, S., Liu, X., Hong, M., Nong, C., & Zhang, W. (2025). The integration of AI in nursing: addressing current applications, challenges, and future directions. Frontiers in medicine, 12, 1545420. https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1545420/full
Proposed Dissertation topic 3
Evaluating the Causal Impact of Blended Learning on Clinical Reasoning and Clinical Judgment in Undergraduate Nursing Education
Background Context
Although blended learning (BL) has been very effective in the field of nursing education, current research still has a large gap concerning the methodology that almost entirely accounts for the success of BL. As pointed out by Wang and Raman (2025), this situation is primarily due to the heavy reliance on quasi-experimental studies, while RCTs have hardly contributed anything to the amount of evidence. Thus, the area of nursing still lacks strong proof of causation for the effectiveness of BL in the case of advanced cognitive skills, which are highly required for nursing practice. Besides, the current study mainly focuses on general critical thinking, while clinical thinking, which consists of clinical reasoning development and clinical judgment, is still very much underexplored. Such competencies are deemed essential to enable safe and effective nursing decisions, and therefore, the question of whether BL significantly develops these skills needs to be backed by powerful research evidence.
PhD Level Verification
As of now, there is no empirical framework based on Randomised Controlled Trials (RCTs) that investigates the causal effects of BL on all clinical thinking abilities of nursing students. By conducting an RCT that assesses the direct influence of BL on clinical reasoning and clinical judgment, this research will fill the gap that has existed in the literature for some time.
Research Questions
PhD-Level Contributions
Suggested Readings
Wang, R., & Raman, A. (2025). Systematic literature review on the effects of blended learning in nursing education. Nurse Education in Practice, 82, 104238. https://doi.org/10.1016/j.nepr.2024.104238
Proposed Dissertation Topic 4
Blended Learning and Psychological Well-Being in Nursing Students: A Comprehensive Theoretical Framework and Empirical Evaluation
Background Context
According to Wang and Raman (2025), there is a substantial lack of research in the area of the psychological and emotional impact of blended learning (BL) on nursing students. The available literature deals with limited psychological indicators (like stress, anxiety, depression, and resilience) only, and often yields different results. Besides, most of the studies suffer from theoretical and methodological issues, e.g., they have small sample sizes, do convenience sampling and poor designs, which makes it hard to come up with significant conclusions. Since nursing students have been reported to experience a high psychological burden, the issue of how BL influences their mental well-being calls for thorough and theory-driven research.
PhD-Level Verification
Presently, there is no all-encompassing theoretical or empirical framework that elucidates the impact of BL on various dimensions of nursing students’ psychological health. This dissertation proposes a solution by creating a unified model consisting of educational psychology, cognitive load theory, and digital learning frameworks.
Research Questions
Contributions at the PhD-Level
Suggested Readings
Wang, R., & Raman, A. (2025). Systematic literature review on the effects of blended learning in nursing education. Nurse Education in Practice, 82, 104238. https://doi.org/10.1016/j.nepr.2024.104238
Dissertation Topic 5:
A Longitudinal and Multi-Modal Evaluation of Clinical Simulation in Nursing Education
Background Context
Clinical simulation in nursing is asserted as an extensively accepted practice to bridge the theory-practice gap in nursing education. However, the present literature does not provide a solid base since inappropriate methodological strategies have been applied, e.g., the use of self-report measures, short intervention periods, and a lack of rigorous designs. Daneshfar and Moonaghi (2025) stress the need for longitudinal studies, standardised measurements for experiential learning and wider generalisations through stronger research designs. In addition, topical gaps such as no comparative research on new simulation modalities (e.g., VR, hybrid simulation-based education), and not studying behavioural competencies (like empathy, interprofessional collaboration, and ethical reasoning) still exist. All these gaps point out that simulation in nursing education needs more thorough and systematic evaluation.
PhD-Level Verification
The current state of research does not cover a comprehensive, longitudinal framework that views at the same time, different simulation modalities, specific physicians’ performance, and emotional learning outcomes. There is not a single study that has combined a multi-site, methodologically superior approach, which includes objective performance measures along with experiential learning frameworks. Therefore, this dissertation will tackle these gaps straight away.
Research Questions
PhD-Level Contributions
Suggested Readings
Daneshfar, M., & Moonaghi, H. K. (2025). The impact of clinical simulation on bridging the theory–practice gap in nursing education: A systematic review. BMC Medical Education, 25(1216). https://pubmed.ncbi.nlm.nih.gov/40877870/
Conclusion
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PhDAssistance. (n.d.). Nursing Dissertation Topics
. Retrieved December 15th, from https://www.phdassistance.com/topic/history-dissertation-topics/
Jalolova, M., and Musawwir, M. “History Dissertation Topics
for PhD Scholars.” PhDAssistance, https://www.phdassistance.com/topic/history-dissertation-topics/ Accessed 03rd December 2025.
Jalolova, M., and Musawwir, M. “History Dissertation Topics
for PhD Scholars.” PhDAssistance, PhDAssistance, Web. 03rd December 2025.
Jalolova, M., and Musawwir, M., n.d. History Dissertation Topics for PhD scholars. [online] Available at: https://www.phdassistance.com/topic/history-dissertation-topics/ [Accessed 03rd December 2025].
Jalolova M., Musawwir M. History Dissertation Topics
for PhD scholars [Internet]. PhDAssistance; [cited 2025 03rd December]. Available from: https://www.phdassistance.com/topic/history-dissertation-topics/
Jalolova, M., and Musawwir, M. (n.d.). History Dissertation Topics for PhD scholars. Retrieved 03rd December 2025, from https://www.phdassistance.com/topic/history-dissertation-topics/
Jalolova, M., and Musawwir, M., History Dissertation Topics
n.d.) https://www.phdassistance.com/topic/history-dissertation-topics/ accessed 03rd December 2025.
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