School of Pharmaceutical Sciences and Yunnan Provincial Key Laboratory of Pharmacology for Natural Products, Kunming Medical University, Kunming, Yunnan, China.
Yunnan Provincial Center for Drug Policy Research, Kunming, Yunnan, China.
Front Public Health. 2024 Mar 19;12:1358117. doi: 10.3389/fpubh.2024.1358117. eCollection 2024.
This study focuses on understanding pharmacovigilance knowledge, attitudes, and practices (KAP) in Yunnan Province, employing Structural Equation Modeling (SEM) and network analysis. It aims to evaluate the interplay of these factors among healthcare personnel and the public, assessing the impact of demographic characteristics to inform policy and educational initiatives.
A cross-sectional survey was conducted in Yunnan, targeting healthcare personnel and the public. Data collection was through questionnaires, with subsequent analysis involving correlation matrices, network visualization, and SEM. The data analysis utilized SPSS 27.0, AMOS 26.0, and Gephi software for network analysis.
This study evaluated pharmacovigilance KAP among 209 public participants and 823 healthcare personnel, uncovering significant differences. Public respondents scored averages of 4.62 ± 2.70 in knowledge, 31.99 ± 4.72 in attitudes, and 12.07 ± 4.96 in practices, while healthcare personnel scored 4.38 ± 3.06, 27.95 ± 3.34, and 7.75 ± 2.77, respectively. Statistically significant correlations across KAP elements were observed in both groups, highlighting the interconnectedness of these factors. Demographic influences were more pronounced among healthcare personnel, emphasizing the role of professional background in pharmacovigilance competency. Network analysis identified knowledge as a key influencer within the pharmacovigilance KAP network, suggesting targeted education as a vital strategy for enhancing pharmacovigilance engagement.
The research reveals a less-than-ideal state of pharmacovigilance KAP among both healthcare personnel and the public in Yunnan, with significant differences between the two groups. SEM and network analysis confirmed a strong positive link among KAP components, moderated by demographics like age, occupation, and education level. These insights emphasize the need to enhance pharmacovigilance education and awareness, thereby promoting safer drug use.
本研究采用结构方程模型（SEM）和网络分析，聚焦于云南省的药物警戒知识、态度和实践（KAP），旨在评估医护人员和公众中这些因素之间的相互作用，评估人口统计学特征对政策和教育计划的影响。
本研究在云南省进行了一项横断面调查，针对医护人员和公众。通过问卷调查收集数据，随后进行相关矩阵分析、网络可视化和 SEM 分析。数据分析采用 SPSS 27.0、AMOS 26.0 和 Gephi 软件进行网络分析。
本研究评估了 209 名公众参与者和 823 名医护人员的药物警戒 KAP，发现了显著差异。公众受访者在知识方面的平均得分为 4.62±2.70，态度为 31.99±4.72，实践为 12.07±4.96，而医护人员的得分分别为 4.38±3.06、27.95±3.34 和 7.75±2.77。两组人群中 KAP 元素之间均存在统计学显著相关性，突出了这些因素的相互关联性。人口统计学因素对医护人员的影响更为显著，强调了专业背景在药物警戒能力中的作用。网络分析确定知识是药物警戒 KAP 网络中的关键影响因素，表明针对教育是增强药物警戒参与度的重要策略。
本研究揭示了云南省医护人员和公众的药物警戒 KAP 状况不理想，两组人群之间存在显著差异。SEM 和网络分析证实了 KAP 各组成部分之间存在强烈的正相关关系，年龄、职业和教育水平等人口统计学因素起到了调节作用。这些发现强调了需要加强药物警戒教育和意识，从而促进更安全的药物使用。
