Introduction
The initial concept of precision medicine is the customization of preventive or treatment plans for specific disease-susceptible populations or groups with similar reactions to particular drugs [1]. Emerging in the backdrop of the new era, precision medicine is rapidly progressing from theoretical research to technological development and ultimately to clinical applications. As precision medicine transitions from conceptualization to clinical practice, this advanced paradigm has also been introduced into the field of nursing [2]. Precision nursing is gradually evolving into a novel nursing model.
Neurosurgery stands apart from other departments, both in theoretical knowledge and clinical practice. Diseases encountered in neurosurgery are characterized by anatomical complexity, abstract theoretical knowledge, a high proportion of critically ill patients, and significant nursing challenges. Consequently, there is a pressing need for specialized nursing in neurosurgery, making the training of nursing personnel particularly crucial. Currently, there is no unified training model for nursing personnel, and hospitals typically devise training programs based on their specific circumstances. Guided by the principles of precision medicine, the rapid development in neurosurgical nursing demands continuous education for nurses, with innovative training methods being continually explored. Exploring an effective neurosurgical nursing training system becomes an innovative and highly significant endeavor.
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Nursing personnel’s mastery of the anatomical features of the nervous system is a necessary foundation for understanding the development of diseases. Knowledge of the anatomical characteristics of diseases can enhance the quality and efficiency of various medical procedures, such as preoperative education and postoperative care. Additionally, it can boost the confidence of healthcare professionals [3‐5]. Therefore, strengthening nurses’ understanding of the anatomical features of diseases is a prerequisite for precision nursing. In the nervous system, the numerous structures are concentrated in complex three-dimensional (3D) configurations, making traditional two-dimensional diagrams insufficient for providing the accurate information needed for teaching. This is why it is considered one of the more challenging areas in medical courses [6]. Courses in neuroanatomy are even cited as a cause of “neurophobia,” negatively influencing healthcare professionals’ future choices regarding neurology [7]. Therefore, neurosurgical nursing education aims to overcome challenges in understanding anatomical structures by using engaging tools like virtual and augmented reality simulations [8], as well as 3D visualization technology [6].
3D printing technology can accurately create three-dimensional models of skull base diseases, cerebrovascular diseases, and brain tumors based on patient imaging information, with various clinical applications and scenarios [9]. In neurosurgery, 3D printing models have been reported to be applicable in preoperative education, surgical planning, and surgical simulation for diseases such as brain aneurysms and brain tumors, offering a novel management approach for patients [10‐12]. Previous studies have demonstrated that the use of 3D printing models in ophthalmology and orthopedics can guide doctors in quickly mastering complex anatomical knowledge, facilitating effective medical theory and technical education [13, 14]. Incorporating 3D printing models into the neurosurgical nursing training platform is clinically significant for improving the quality of care for relevant diseases.
In this study, to determine whether 3D printing models can enhance the quality and efficiency of neurosurgical nursing training as an innovative teaching tool, we established a neurosurgical nursing training system based on 3D printing models. The effectiveness of the training was assessed through evaluations of the professional theory and practice of trained nurses, surveys of their values, satisfaction surveys of patients, and the corresponding patient outcomes. The training system effectively elevated the professional level and nursing quality of the nurses. Future exploration and optimization of 3D printing models in neurosurgical nursing training can accelerate the development of innovative training systems.
Method
Establishment of 3D model and database
The reference images for creating disease models are Three-Dimensional Digital Subtraction Angiography (3D-DSA) or fused images of computed tomography scan (CT) and Magnetic Resonance Imaging (MRI) from the patient. 3D-DSA is commonly used as a template for printing cerebral vascular disease models, ensuring high printing accuracy. For brain tumors, fused images of CT and MRI are typically used to obtain more information about skull structures, tumors, surrounding normal brain tissue, and cerebral vessels. These models are all made of SLA-9200 high-toughness epoxy photosensitive resin (China, Union Tech) and processed by Lite600 3D printer (China, Union Tech). Corresponding educational videos on anatomical structures, disease mechanisms, and diagnosis and treatment were created for these models. These materials are primarily utilized before bedside training to deepen nursing personnel’s understanding of disease mechanisms and key nursing points.
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Research subjects
This study is a randomized controlled trial aimed at exploring whether a neurosurgical training system based on 3D printing models has better training effects compared to traditional training systems. The study included 80 nurses who participated in the neurosurgical rotation training at Shaoxing People’s Hospital from 2022 to 2023. All subjects were female, held bachelor’s degrees, had 1–2 years of nursing experience, and were qualified as N0 level (Junior title) nurses. The 80 subjects were randomly divided into an experimental group and a control group, with 40 participants in each group.
In the experimental group, there were 15 nurses with a registered nurse title and 25 with a nurse practitioner title. The age of the subjects was 23–24 years (average 23.60 ± 0.50), and their nursing experience ranged from 1 to 2 years (average 1.63 ± 0.49). In the control group, there were 18 nurses with a registered nurse title and 22 with a nurse practitioner title. The age of the subjects was 23–24 years (average 23.55 ± 0.50), and their nursing experience ranged from 1 to 2 years (average 1.55 ± 0.50). There were no statistically significant differences in the general characteristics of the two groups (P > 0.05).
This study received approval from the Shaoxing People’s Hospital Academic Ethics Committee, and all research subjects were informed and provided consent.
Training method
The experimental and control groups followed the same syllabus for theoretical teaching and bedside training. The theoretical course included 8 chapters: Scalp and skull diseases and care, Craniocerebral injuries and care, Intracranial tumors and care, Spinal and spinal cord diseases and care, Cerebrovascular diseases and care, Intracranial infectious diseases and care, Functional diseases and care, Cerebrospinal fluid circulation disorders and care. Five teaching methods were used to complete the theoretical instruction: lectures, case analysis, practical operations, role-playing, and group discussions. After completing the theoretical course, each participant conducted bedside training by caring for 20 patients under the instructor of an instructor. The experimental and control groups differed in the use of teaching resources and tools.
Experimental group
In the theoretical course training, both groups used traditional tools such as the textbook “Neurosurgical Nursing and Operational Techniques“ [15], multimedia courseware, and imaging data to teach the anatomy and care of common neurosurgical conditions. Additionally, the experimental group accessed a 3D printing model database. Initially, they will learn the anatomical structure of normal cranial tissues by utilizing 3D printing models depicting the normal structure of the skull and brain. Subsequently, using 3D printing models of relevant diseases (anterior communicating artery aneurysm, posterior communicating artery aneurysm, cerebral arteriovenous malformation, brain tumor, Moyamoya disease), they will study the imaging data, diagnosis, and treatment processes associated with each disease. This approach aims to provide nursing personnel with a comprehensive understanding of the anatomical characteristics and pathogenesis of the diseases.
In the final stage, nursing personnel will undergo bedside training. The instructors are all supervisory nurses or above, and each instructor teaches one nursing student. The instructors for the experimental group are proficient in the application of 3D printing models in nursing. Under the guidance of the instructors, each nursing personnel is required to complete full-care for 20 patients as part of bedside training. The patients assigned to the nursing students are those under the supervision of the instructor. During bedside training, nursing personnel in the experimental group will use the patients’ imaging information to create corresponding 3D printing models. These models will be utilized for preoperative education, postoperative rapid recovery, and the formulation of ongoing care plans. Assessment will be conducted after the completion of all training content.
Control group
Nursing students in the control group learned the anatomy and care of common neurosurgical conditions solely through textbooks, multimedia courseware, and imaging data. Nursing students then receive conventional bedside training without the application of 3D printing models. The allocation principle of instructor and supervisory patients is consistent with that of the experimental group. In this process, nursing work will be conducted solely under the guidance of the instructors, without the use of 3D printing models. Assessment will take place after everyone completes bedside training for 20 patients.
Evaluation indicators
After the training, nurses were assessed using internally developed tests to evaluate their understanding of the clinical features, nursing assessments, diagnoses, interventions, and health education for neurosurgical diseases. The theoretical assessment focused on the etiology, pathophysiological changes, clinical manifestations, and treatment methods of common neurosurgical diseases, with a total score of 100. The practical assessment focused on nursing skills, case analysis, and the formulation and implementation of care plans, also with a total score of 100. The comprehensive ability score was calculated as follows: daily performance * 30% + practical assessment * 30% + theoretical assessment * 40%.
Additionally, to evaluate patients’ experiences with bedside training nurses, an internally developed Patient Satisfaction Survey was used, Patient evaluation factors include health education, technical skills, and rehabilitation guidance. Results were categorized as satisfied, relatively satisfied, or dissatisfied. Subsequently, the overall satisfaction rate was calculated. Each nurse received a total of 20 satisfaction evaluations, where each “satisfied” rating earned 2 points, each “relatively satisfied” rating earned 1 point, and “dissatisfied” ratings earned no points. The total score was then divided by the maximum possible score of 80 to obtain the overall satisfaction rate. At last, both groups of nursing personnel will be assessed using the Super’s Work Values Inventory to investigate the values scores of trained nursing personnel.
Among the diseases suitable for diagnosis and treatment using 3D-printed models, intracranial aneurysms are a very common neurosurgical disease. Therefore, clinical data for patients with intracranial aneurysms participating in bedside training will be compiled. This includes complications during the perioperative period, a 6-month postoperative quality of life survey (SF-36), and the Modified Rankin Scale (mRS). This investigation aimed to assess whether the nursing approach during training might have a positive impact on patient outcomes.
All patients involved in this study have been communicated with in advance, and informed consent has been obtained from patients or their family members.
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Statistical methods
Data was analyzed using the SPSS statistical software. Normally distributed measurement data are expressed as mean ± standard deviation ( x ± s) and analyzed using the t-test. Non-normally distributed measurement data are presented as the median (interquartile range) 【M (QL, QU)】 and analyzed using the Mann-Whitney U test. Count data are expressed as counts (percentages) and analyzed using the independent sample chi-square (χ²) test. The significance level was set at P < 0.05.
Result
Database of 3D printed models for neurosurgical nursing training
To meet the demands of precision nursing training in neurosurgery, this study established a dedicated 3D printing model database. The database comprises 27 3D printing models, including six normal structural models of common sites for brain diseases, such as the circle of Willis, cerebral vascular models, pontocerebellar angle, and saddle area structure. Disease-related models consist of four anterior communicating artery aneurysms, two posterior communicating artery aneurysms, four aneurysms post-embolization or clipping, one cerebral arteriovenous malformation, one Moyamoya disease, and nine intracranial tumors in various locations (Fig. 1).
Fig. 1
3D printing models for neurosurgical nursing training. Note: A - Brainstem tumor model; B - Anterior communicating artery aneurysm model; C - Intramedullary tumor in the cervical spine; D - Pontocerebellar angle tumor. Red arrows indicate the lesion locations
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Comparison of exam scores between the two nursing groups after training
In the examinations conducted after the completion of training, both the theoretical test scores and clinical practice test scores of the experimental group were significantly higher than those of the control group (Table 1). The comprehensive ability assessment results for the personnel in the experimental group were also significantly superior to those in the control group (Table 1). This indicates that the training system based on 3D printing models can enhance the professional nursing proficiency of nursing personnel.
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Table 1
Comparison of exam scores between the two nursing groups after training
group | Theoretical test scores | clinical practice test scores | comprehensive ability assessment results |
|---|---|---|---|
experimental group | 93.5 (90.00, 95.75) | 92.5 (90.00, 95.75) | 93.5 (90.00, 95.75) |
control group | 88.0 (84.00, 88.00) | 86.0 (84.00, 90.00) | 88.0 (86.00, 90.00) |
P | <0.001 | <0.001 | <0.001 |
Comparison of professional values scores between two groups
Due to the fact that occupational values are the fundamental motivation behind people’s work attitudes, work standards, and behaviors [16], we conducted an analysis of Super’s Work Values Inventory for trained personnel in both the experimental and control groups after the training. Overall, nursing staff prioritize values such as co-workers, lifestyle, altruism, prestige, achievement, and security. The analysis between the experimental and control groups indicates that nursing staff in the experimental group scored significantly higher in co-workers, management, and security compared to the control group, while there were no significant differences in other values (Table 2). These findings suggest that training based on 3D printing models may have a positive impact on enhancing specific occupational values.
Table 2
Comparison of Super’s work values scores between the two groups of nursing staff
Super’s work values | experimental group | control group | P |
|---|---|---|---|
Co-workers | 16.00 (15.00, 16.75) | 15.00 (14.00, 16.00) | 0.021 |
Lifestyle | 15.00 (14.25, 16.00) | 15.00 (14.00, 16.00) | 0.393 |
Altruism | 15.00 (14.25, 16.00) | 15.00 (14.00, 16.00) | 0.795 |
Achievement | 15.00 (14.00, 15.75) | 15.00 (14.00, 15.75) | 0.51 |
Prestige | 15.00 (14.00, 16.00) | 15.00 (14.00, 16.00) | 0.499 |
Independence | 15.00 (14.00, 16.00) | 15.00 (13.25, 16.00) | 0.984 |
Esthetics | 15.00 (14.00, 15.75) | 15.00 (14.00, 15.75) | 0.51 |
Income | 15.00 (14.00, 15.75) | 15.00 (14.00, 15.75) | 1 |
Supervision | 15.00 (14.00, 16.00) | 15.00 (12.50, 16.00) | 0.468 |
Creativity | 14.50 (12.25, 16.00) | 15.00 (12.50, 16.00) | 0.815 |
Mental Challenge | 15.00 (14.00, 16.00) | 15.00 (14.00, 15.75) | 0.193 |
Work environment | 14.00 (13.25, 15.00) | 15.00 (13.25, 15.00) | 0.592 |
Variety | 15.00 (14.00, 15.00) | 14.00 (12.25, 15.75) | 0.16 |
Management | 15.00 (14.25, 16.00) | 14.00 (12.25, 15.75) | 0.001 |
Security | 15.00 (14.25, 16.00) | 14.50 (13.25, 15.00) | 0.002 |
Total score | 221.00 (217.25, 226.75) | 218.00 (213.25, 225.50) | 0.009 |
Comparison of patient satisfaction with two groups of nursing staff during training
Each nursing staff member provided continuous care for 20 patients during the training period. This study collected patient satisfaction evaluations of nursing staff to analyze their performance during the training. The results indicate that nursing staff in the experimental group received more satisfactory evaluations, and overall satisfaction was higher compared to the control group (Table 3).
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Table 3
Comparison of satisfaction evaluations between two groups of nursing staff
satisfied | relatively satisfied | dissatisfied | overall satisfaction rate | |
|---|---|---|---|---|
experimental group | 18 (17, 19) | 2 (1, 3) | 0 (0, 0) | 95.06% (92.5%, 97.5%) |
control group | 15 (14, 16) | 4 (3, 5) | 0 (0, 0.75) | 87.5%% (85%, 90%) |
P | <0.001 | <0.001 | 0.033 | <0.001 |
The impact of the nursing methods of the two groups of nurses on the prognosis of patients with intracranial aneurysm during the training period
During bedside training, the experimental group cared for 286 patients with intracranial aneurysms, while the control group cared for 295 patients with intracranial aneurysms. There were no significant differences in the general characteristics of the patients between the two groups (Supplementary Table 1). Statistical analysis of perioperative complications revealed no significant differences in occurrences of cerebral vasospasm, intracranial rebleeding, cerebral edema, and postoperative seizures between patients cared for by the two groups of nursing staff (Supplementary Table 2). However, the postoperative outcomes at six months differed between patients cared for by the two groups of nursing staff. From the results of the life quality survey, patients who received precise care from the experimental group showed better outcomes in Social Functioning, Mental Health, Physical Functioning, and other aspects compared to patients cared for by the control group. Additionally, the mRS scores of patients corresponding to the experimental group were lower than those of the control group (Supplementary Table 3). These results suggest that the precision care implemented by the experimental group in bedside training may have a positive impact on the prognosis of patients. However, this result needs to be further explored in more rigorous prospective clinical trials.
Discussion
In the realm of precision medicine, healthcare professionals continuously refine and enrich their perspectives from a specialized standpoint, integrating personalized information into nursing practices, thereby giving rise to the concept of precision nursing [17]. Prior research underscores that precision nursing, with a focus on health, involves the core elements of providing individualized care services such as early prevention, diagnosis, and treatment for populations through precision medical technologies [18]. 3D printing technology plays a crucial role in the medical field, surpassing textual and two-dimensional images in anatomy education. It presents abstract anatomical structures in the form of three-dimensional models, deepening healthcare professionals’ understanding of disease anatomy, etiology, and key nursing points [19]. Therefore, a neurosurgical nursing training system based on 3D-printed models aligns with the principles of precision nursing and represents an innovative training system.
In recent years, the application of 3D printing technology in medical education has garnered increasing attention. For example, in dentistry, 3D-printed models of carious lesions allow students to simulate treatment, reducing their anxiety during initial clinical practice and helping them gain confidence [20]. A 3D model of the gastrocolic trunk, created from 3D-CT angiography, has been used for training medical interns, aiding their understanding of the gastrocolic trunk’s anatomical structure and enhancing their satisfaction with the depth, novelty, and inspiration of the teaching [21]. Furthermore, as the creativity of 3D printing technology has increased, the use of movable rib models has received higher evaluations in orthopedic medical education compared to traditional static rib models [22]. The application of 3D printing technology in neurosurgical residency training has also rapidly developed, with multiple studies consistently demonstrating positive training outcomes [23]. Training medical students using 3D-printed models depicting the bony and vascular structures of craniovertebral junction malformations can help them understand anatomical structures, leading to more accurate disease diagnosis and surgical planning [24].
Although 3D printing technology has become more flexible and affordable in technological development, its application in nursing education remains quite limited. A study in 2017 investigated the potential value of using 3D models of congenital heart disease as educational tools for cardiac nurses, indicating that 3D models are particularly helpful for nurses in understanding the anatomical features of congenital heart disease [25]. Training for doctors, nurses, and auxiliary caregivers using specific preoperative 3D models of congenital heart disease patients for postoperative care simulations effectively enhanced participants’ clinical nursing abilities. Moreover, nurses who participated in the training scored significantly higher than other healthcare professionals in terms of familiarity with the surgery, clinical management skills, and perceived improvement in capabilities. Nurses were also more likely to believe that the training with 3D models was more beneficial for postoperative care than standard handover procedures [26]. This highlights the significant importance of 3D printing models in nursing training, while also indicating a substantial gap in their application within nursing education. The 3D printing model nursing training system established for neurosurgical nursing staff in this study could accelerate the development of 3D printing model applications in nursing education.
The primary objective of this study is to determine the effectiveness of a neurosurgical nursing training system based on 3D-printed models and elucidate its potential applications. The research findings indicate that, compared to traditional training methods, 3D-printed models demonstrate superior training outcomes in neurosurgical nursing training. Firstly, the training system based on 3D-printed models leads to substantial improvements in nursing personnel’s performance, patient satisfaction, and overall nursing capabilities. Studies have shown that 3D models or visualization techniques based on 3D enhance the spatial visualization abilities of healthcare professional students [27, 28]. We speculate that training based on 3D-printed models may enhance nurses’ spatial visualization abilities, thereby improving their understanding of disease anatomy. Spatial visualization ability involves the manipulation of objects in the mind and is crucial in fields such as medicine, mathematics, and engineering [29, 30]. Therefore, enhancing nurses’ spatial visualization abilities contributes to a deeper understanding of disease anatomy, facilitating preoperative education and postoperative care. Furthermore, research suggests a significant positive correlation between participation in training programs beyond higher education and nurses’ competence [31]. This underscores the importance of a nursing training system based on 3D-printed models in enhancing nurses’ learning abilities and competence. The competence of nursing personnel directly affects factors such as nursing quality, patient satisfaction, and patient safety [32]. This is very important for the patient’s later recovery.
Professional values are the foundation of nursing practitioners’ clinical practice and can even influence the development of personal values [33]. This study found that the nursing system based on 3D-printed models has increased nursing professionals’ emphasis on co-workers, management, and security within their professional values (Table 1). These aspects fall within the categories of professional values that nursing professionals tend to prioritize. The improvement in professional values may be associated with substantial enhancements in nursing professionals’ competence, nursing quality, and job satisfaction. For example, nurses’ educational levels, years of professional experience, and higher professional values scores are correlated [34]. Additionally, job satisfaction is a crucial factor influencing nursing professionals’ career development [35]. As a form of positive feedback, nursing professionals’ professional values directly impact their clinical nursing capabilities [36]. Research has reported that professional values play a significant role in nurses’ career development, as strong professional values can regulate health issues caused by stress and improve the likelihood of employees staying in the industry [37]. Some professional values are closely related to employees’ thoughts of job burnout and dedication [16]. Nursing work involves regularly facing issues such as stress, tension, and fatigue [38]. Improving nursing professionals’ professional values through a novel training system is an important method for stimulating their professional learning capabilities and enthusiasm for work.
While the neurosurgical training system based on 3D-printed models demonstrates certain advantages, it still has some limitations. For instance, the training system is in its early stages and requires gradual refinement. Throughout the training process, a substantial amount of teaching materials and clinical cases have been accumulated, necessitating the integration of these resources. It is essential to incorporate excellent nursing cases of classical cases into the database of 3D-printed models for neurosurgical nursing training, promoting resource sharing within the training system. Additionally, the intervention methods of 3D-printed models in nursing practice have their own specificities, and the teaching mode needs continuous updates through iteration.
This study also has some limitations. All participants were recruited from a single center and consisted of female junior nurses with 1 to 2 years of experience, which resulted in a relatively small sample size of participants and a lack of diversity. These factors may limit the widespread application of the 3D printing nursing training system. Additionally, we evaluated the training outcomes using subjective measures such as patient satisfaction surveys and Super’s Work Values Inventory. Although these yielded generally positive responses, it is undeniable that such surveys are susceptible to biases in how respondents choose and answer. Furthermore, the nurses in the experimental and control groups were not assigned using a double-blind method, which may have led to expectation bias among the participants, thereby affecting their learning and practice. Despite the patients cared for by the nurses of experimental group demonstrated better quality of life and neurological outcomes compared to those in the control group, the prognosis of neurosurgery patients is affected not only by various factors such as postoperative care, age, gender, the degree of neurological impairment, and the severity and location of the lesion but also by the timeliness of surgical treatment, genetic factors, complications, treatment options, and so on. These factors were not taken into account in this study, representing a limitation. Therefore, future studies with larger sample sizes are needed to support the value of the 3D printing model-based training system in neurosurgical nursing education.
A high-quality training system is a crucial factor in enhancing the professional competence of nurses. The application of 3D-printed models in nursing training proves to be an effective method for elevating the precision nursing proficiency of nurses. In the future, we will continue to refine the content and modes of training within this system. A comprehensive plan will be developed in areas such as curriculum design, training methods, skill development, and evaluation systems. This overarching strategy aims to inspire nurses’ interest in learning, improve training efficiency, and provide a scientific foundation for the advancement of both the theory and practice of precision nursing.
Conclusion
The neurosurgery nursing training system based on 3D printing models can improve the learning efficiency and nursing work satisfaction of nursing staff, thereby providing patients with higher-quality precision nursing services. This new type of training system may have a positive impact on the professional values of nursing staff, so it is necessary to continue to improve and promote the application of neurosurgical nursing training systems based on 3D printing models.
Acknowledgements
Not applicable.
Declarations
Ethics approval and consent to participate
This study received approval from the Shaoxing People’s Hospital Academic Ethics Committee (2021-K-Y-351-01), and all research subjects were informed and provided consent.
Consent for publication
All patients included in this study had signed informed consent.
Competing interests
The authors declare no competing interests.
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