Conte Luana, De Nunzio Giorgio, Lupo Roberto, Cascio Donato, Cioce Marco, Vitale Elsa, Ianne Chiara, Rubbi Ivan, Martino Massimo, Lombardini Letizia, Vassanelli Aurora, Pupella Simonetta, Pollichieni Simona, Sacchi Nicoletta, Ciceri Fabio, Botti Stefano
Department of Physics and Chemistry, University of Palermo, Palermo, Italy.
Laboratory of Advanced Data Analysis for Medicine (ADAM), University of Salento, Lecce, Italy.
Int J Hematol. 2025 Apr;121(4):511-525. doi: 10.1007/s12185-024-03894-x. Epub 2024 Dec 12.
In Italy, the demand for allogeneic transplantation exceeds the number of compatible donors in the Italian Bone Marrow Donor Registry (IBMDR). This study aimed to explore the knowledge, beliefs, opinions, values, and feelings of the Italian population regarding stem cell donation.
An online survey was shared via social media. Respondents were retrospectively identified as registered on the IBMDR (donor group) or never registered (non-donor group). Statistical analyses confirmed the relationship between knowledge level and willingness to donate. Six machine learning classifiers were trained using questionnaire responses to predict the probability of IBMDR registration.
A total of 1518 respondents participated. Characteristics identified in the non-donor group were a lower level of knowledge regarding donation needs (51.7% vs 24.4%, p < 0.001) and negative feelings such as fear (Z = - 2.2642, p = 0.02), confusion (Z = 4.4821, p < 0.001), and uncertainty (Z = 3.3425, p < 0.001). Higher knowledge predicted a greater likelihood of IBMDR enrollment. Machine learning analysis showed an AUC ranging from 0.65 to 0.81, depending on the classifier.
The results underscore the need to improve strategies to raise awareness and knowledge of stem cell donation among the Italian population.
在意大利,异基因移植的需求超过了意大利骨髓捐献者登记处(IBMDR)中匹配供体的数量。本研究旨在探索意大利民众对干细胞捐献的知识、信念、观点、价值观和感受。
通过社交媒体分享在线调查问卷。回顾性地将受访者确定为在IBMDR登记的(捐献者组)或从未登记的(非捐献者组)。统计分析证实了知识水平与捐献意愿之间的关系。使用问卷回复训练了六个机器学习分类器,以预测在IBMDR登记的概率。
共有1518名受访者参与。在非捐献者组中发现的特征是对捐献需求的了解程度较低(51.7%对24.4%,p < 0.001)以及恐惧(Z = -2.2642,p = 0.02)、困惑(Z = 4.4821,p < 0.001)和不确定(Z = 3.3425,p < 0.001)等负面情绪。知识水平较高预示着在IBMDR登记的可能性更大。机器学习分析显示,根据分类器的不同,曲线下面积(AUC)在0.65至0.81之间。
结果强调需要改进策略,以提高意大利民众对干细胞捐献的认识和了解。