Artificial Intelligence in Perioperative Nursing: A Mixed-Methods Study on Current Perspectives and Future Directions Among Surgical Ward and Operating Room Nurses.

Student summary

Why This Research Matters

This article introduces a study that aims to understand how perioperative nurses, those who work in surgical wards and operating rooms, feel about using artificial intelligence (AI) in their jobs. The research is called 'Artificial Intelligence in Perioperative Nursing: A Mixed-Methods Study on Current Perspectives and Future Directions Among Surgical Ward and Operating Room Nurses.' It's a clinical trial that has just started recruiting participants.

The main focus of this study is to find out what perioperative nurses think about AI right now, how they feel about using it (their attitudes), and whether they are ready for more AI in their work. The researchers want to know if these nurses have already used any AI tools or systems at their jobs. They also want to understand how easy the nurses find AI to use – is it user-friendly? Do they think it helps them do their job better?

The study will look into what impact AI might have on nursing as a profession. For example, could AI change some of the tasks that nurses usually do? Could it make certain jobs easier or more efficient? And finally, the researchers want to know how prepared these nurses are for future changes where AI becomes even more common in healthcare.

This study uses both numbers (quantitative data) and stories from people (qualitative data). This means they will collect information through surveys that ask questions with specific answers, which can then be counted or measured. They will also conduct interviews or focus groups where nurses can share their personal thoughts, experiences, and feelings about AI in a more open way.

The study is being done by researchers from Alexandria University in Egypt. It's important to note that this research has not yet been completed; it is currently recruiting participants for the trial. This means we don't have any final results or conclusions from the study at this point, only its plan and purpose.

When reading about studies like this, especially those still underway, students should think about a few things: 1. **What's being asked?** The questions are clear: perspectives, attitudes, preparedness regarding AI in perioperative nursing. 2. **Who is involved?** Nurses from surgical wards and operating rooms – the people who will be directly affected by these changes. 3. **How is it done?** Mixed methods mean they'll get a fuller picture than if they only used one type of data collection. 4. **What's not known yet?** Since this study has just started recruiting, we don't know the findings or what the nurses actually think until the trial finishes and results are published elsewhere.

As future nurses, it's important to understand how new technologies like AI might change your work environment. This study aims to gather information from experienced perioperative nurses about these changes before they happen on a larger scale. It helps in understanding potential benefits (like improved efficiency or better patient care) and challenges (like learning new skills or concerns about job roles). The findings, once available, could help nursing educators prepare students for an AI-integrated future and guide healthcare organizations in implementing such technologies effectively.

The source of this information is ClinicalTrials.gov. This website lists clinical trials that are happening around the world. It's a good place to find out about new research studies but remember that it doesn't always contain all details or final results, especially for ongoing trials like this one. The record itself states 'Clinical trial - RECRUITING,' which means participants are currently being sought.

When considering how to use evidence from such sources in nursing practice: * **Appraisal:** Always check the source and status of a study (e.g., is it recruiting, completed?). For this one, since it's recruiting, its findings aren't yet available for direct application. Wait until results are published. * **Source/Right Cautions:** The information comes from ClinicalTrials.gov. This means you can find the official details of the trial there (like NCT07601373). It's a public registry, so it's generally accessible for research purposes. However, specific rights to use data or full text might be governed by the study itself or Alexandria University. * **Reasoning from Evidence:** Once results are available, nurses can reason about them by asking: Do these findings align with my own experiences? Are there any limitations mentioned in the final report that I should consider? How could this information help me improve patient care or adapt to new technologies? The study's goal is not to provide immediate answers for clinical practice but rather to lay the groundwork for understanding how perioperative nurses view AI. This foundational knowledge will be crucial as AI becomes more prevalent in healthcare settings.

Faculty notes

Educational Relevance

This article outlines a mixed-methods clinical trial (NCT07601373) investigating current perspectives, attitudes, and preparedness of perioperative nurses regarding the integration of artificial intelligence (AI) into their practice. The study is conducted by researchers from Alexandria University, Egypt.

The research aims to explore several key aspects: AI utilization (whether nurses have encountered or used AI tools in their work), perceived usability (how easy they find these systems to use and whether they believe them to be effective), professional impact (potential changes to nursing roles, responsibilities, and the profession itself due to AI adoption), and readiness for future implementation (nurses' preparedness for increased reliance on AI).

The study targets perioperative nurses specifically working in surgical wards and operating rooms. These are critical areas where precision, efficiency, and rapid decision-making are paramount, making them fertile ground for exploring AI's potential benefits and challenges.

Methodologically, the research employs a mixed-methods approach, combining quantitative data (e.g., surveys with Likert-scale questions to measure attitudes and preparedness) with qualitative data (e.g., interviews or focus groups to capture nuanced perspectives, experiences, and concerns). This dual approach allows for a more comprehensive understanding of the complex phenomenon being studied.

The study is currently in its recruiting phase ('Clinical trial - RECRUITING'). As such, no final findings are yet available. The primary purpose of this article is to describe the research design and objectives rather than report results.

For faculty teaching nursing informatics or perioperative nursing: 1. **Educational Value:** This study serves as an excellent example for students to understand how mixed-methods designs can be applied in healthcare research, particularly when exploring human perceptions of new technologies like AI. It highlights the importance of considering both quantitative metrics and qualitative narratives. 2. **Critical Appraisal Skills:** Students can learn to critically appraise a trial protocol or registry entry (like this one) by examining its stated aims, target population, methodology, and current status ('RECRUITING'). This helps them understand that not all research findings are immediately available and requires patience for results. 3. **Ethical Considerations:** While not detailed in the abstract provided, faculty can use this as a springboard to discuss ethical considerations in clinical trials involving healthcare professionals (e.g., informed consent, data privacy). 4. **Future Directions:** The study's focus on 'future directions' and 'readiness for future implementation' underscores the dynamic nature of nursing practice and the need for continuous education and adaptation. 5. **Interdisciplinary Nature:** AI in healthcare is inherently interdisciplinary. This study bridges nursing, informatics, computer science (implicitly), and ethics, providing a rich context for discussing collaborative research. The faculty summary should emphasize that this record primarily describes an ongoing clinical trial protocol rather than presenting completed research findings.