School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Front Public Health. 2022 Sep 30;10:927874. doi: 10.3389/fpubh.2022.927874. eCollection 2022.
Hospice and palliative care (HPC) aims to improve end-of-life quality and has received much more attention through the lens of an aging population in the midst of the coronavirus disease pandemic. However, several barriers remain in China due to a lack of professional HPC providers with positive behavioral intentions. Therefore, we conducted an original study introducing machine learning to explore individual behavioral intentions and detect factors of enablers of, and barriers to, excavating potential human resources and improving HPC accessibility.
A cross-sectional study was designed to investigate healthcare providers' behavioral intentions, knowledge, attitudes, and practices in hospice care (KAPHC) with an indigenized KAPHC scale. Binary Logistic Regression and Random Forest Classifier (RFC) were performed to model impacting and predict individual behavioral intentions.
The RFC showed high sensitivity (accuracy = 0.75; F1 score = 0.84; recall = 0.94). Attitude could directly or indirectly improve work enthusiasm and is the most efficient approach to reveal behavioral intentions. Continuous practice could also improve individual confidence and willingness to provide HPC. In addition, scientific knowledge and related skills were the foundation of implementing HPC.
Individual behavioral intention is crucial for improving HPC accessibility, particularly at the initial stage. A well-trained RFC can help estimate individual behavioral intentions to organize a productive team and promote additional policies.
缓和医疗与临终关怀（Hospice and Palliative Care，HPC）旨在提高临终质量，在冠状病毒病大流行期间，由于人口老龄化，人们越来越关注这一领域。然而，由于缺乏具有积极行为意向的专业 HPC 提供者，中国仍存在一些障碍。因此，我们进行了一项原始研究，引入机器学习来探索个人行为意向，并发现挖掘潜在人力资源和提高 HPC 可及性的促进因素和障碍因素。
本研究采用横断面设计，使用本土化的 Hospice Care 知识、态度、行为量表（KAPHC）调查医疗保健提供者在 Hospice Care 方面的行为意向、知识、态度和实践（KAPHC）。采用二项逻辑回归和随机森林分类器（RFC）对影响个人行为意向的因素进行建模和预测。
RFC 显示出较高的敏感性（准确性=0.75；F1 分数=0.84；召回率=0.94）。态度可以直接或间接地提高工作积极性，是揭示行为意向的最有效方法。持续的实践也可以提高个人的信心和提供 HPC 的意愿。此外，科学知识和相关技能是实施 HPC 的基础。
个人行为意向对于提高 HPC 的可及性至关重要，尤其是在初始阶段。经过良好训练的 RFC 可以帮助评估个人行为意向，以组织一个富有成效的团队，并推动相关政策的制定。
