ArticleBMC nursing2024
A neurosurgical nursing training system based on 3D printing models: practice and exploration of precision medicine.
Article in BMC nursing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Article
- Current 3D Printing Technologies and their Potential Applications in Drug Delivery, Personalized Medicine & Pharmaceutical Sciences.Current drug discovery technologies · 2026Review
- 3D-Printing in Neurosurgical Training: Hands-On Practice, Patient-Specific Planning and Simulation.Advances and technical standards in neurosurgery · 2026Review
- Enhancing nursing practice through patient outcome measures: a framework for optimizing care in intracranial surgery.BMC nursing · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundIn recent years, the concept of precision medicine has gradually permeated the field of nursing, presenting new challenges for neurosurgical nursing staff. Traditional teaching methods often struggle to adequately convey complex anatomical knowledge and nursing skills, thereby affecting the learning outcomes and clinical decision-making abilities of nurses. As an innovative educational tool, three-dimensional (3D) printing technology has demonstrated significant potential in medical education in recent years. Therefore, this project aims to explore the advantages and feasibility of using 3D printed models as a novel teaching tool in neurosurgical nursing.
methodsThe study involved 80 nursing personnel who participated in the neurosurgical rotation training at Shaoxing People's Hospital from 2022 to 2023. The control group (40 individuals) used only traditional teaching tools such as textbooks, multimedia courseware, and laboratory equipment for theoretical and practical training based on the curriculum. The experimental group (40 individuals) incorporated a 3D printing model database as an innovative teaching tool on the basis of traditional teaching methods, and used patient-specific 3D printed models for precise nursing training. After the training, both groups were assessed for theoretical and practical abilities, professional values, job satisfaction, and the prognosis of intracranial aneurysm patients they cared for.
resultsThe experimental group demonstrated superior scores in theoretical and practical abilities, professional values, and job satisfaction compared to the control group. During the training period, patients with intracranial aneurysms receiving precision nursing care from the experimental group showed better quality of life and neurological functional outcomes compared to the control group.
conclusionsThe nursing training system based on 3D printing models can enhance the learning efficiency and nursing work satisfaction of nursing personnel. It may have a positive impact on the professional values of nursing personnel, thereby laying a solid foundation for providing high-quality, precise nursing services in the field of neurosurgery in the future.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.