结构方程模型分析
包含北京医护人员对HIV/TB共感染管理知识、态度和实践的问卷调查数据,共565份,采用结构方程模型分析。

基本信息
资源简介
结构方程模型分析
【数据集背景】
本数据集源站标题为《Structural equation model analysis.》。源站首次发布:2026-02-23。
【数据内容】
源站原始描述:Background Human Immunodeficiency Virus (HIV) and tuberculosis (TB) co-infection poses a significant challenge to public health systems due to its complex clinical management and high mortality. This study aimed to reveal the specific mechanisms through which knowledge influences practice in HIV/TB co-infection management among healthcare providers (HCPs) using structural equation modeling (SEM). Methods An exploratory cross-sectional study using convenience sampling was conducted from May to Ju…
【数据结构与技术规格】
文件数 1 个,合计 5.63 KB。Table 3.xls:application/vnd.ms-excel,5.63 KB。数据集 DOI:10.1371/journal.pone.0341132.t003。
【主题与分类】
源站学科分类:Medicine、Biotechnology、Cancer、Science Policy、Infectious Diseases、Virology。主题标签:sem analysis indicated、preliminary findings suggest、complex clinical management、8 &# 8211、565 valid questionnaires、42 %) completed、10 &# 8211、affiliated tertiary hospitals、40 ), respectively、generally positive attitudes。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://plos.figshare.com/articles/dataset/_p_Structural_equation_model_analysis_p_/31391539
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Liu, Yuwei; Liu, Jinghe; Chang, Yufei; Chen, Xiaoyou (2026). Structural equation model analysis.. PLOS ONE. Dataset
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:<p>Structural equation model analysis.</p>
- DOI:10.1371/journal.pone.0341132.t003
- 发布日期:2026-02-23
- 文件数:1 个
- 文件总体积:5.63 KB
- 源站页面:https://plos.figshare.com/articles/dataset/_p_Structural_equation_model_analysis_p_/31391539
命令行下载
curl -L -o "Table 3.xls" "https://ndownloader.figshare.com/files/62097181"
文件清单
Table 3.xls(5.63 KB)
文件总体积 5.63 KB(源站 API 实测)。
数据加载示例(图像类)
from PIL import Image
import glob, os
files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)
# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path) # 要求 子目录=类别
目录组织与标注格式以源站说明和下载后实际文件为准。
数据说明
Background
Human Immunodeficiency Virus (HIV) and tuberculosis (TB) co-infection poses a significant challenge to public health systems due to its complex clinical management and high mortality. This study aimed to reveal the specific mechanisms through which knowledge influences practice in HIV/TB co-infection management among healthcare providers (HCPs) using structural equation modeling (SEM).
Methods
An exploratory cross-sectional study using convenience sampling was conducted from May to June 2025 involving healthcare providers (HCPs) across various medical institutions in Beijing, which included university-affiliated tertiary hospitals, specialized hospitals, and community health centers.
Results
A total of 565 valid questionnaires were collected, with 364 (64.42%) completed by medical doctors. The knowledge, attitude, and practice scores were 18.51 ± 7.75 (possible range: 0–30), 43.64 ± 5.51 (possible range: 10–50), and 30.75 ± 7.44 (possible range: 8–40), respectively. Spearman correlation analysis revealed significant positive correlations between knowledge and attitude (r = 0.500, P Conclusion
In our sample, respondents demonstrated limited knowledge, generally positive attitudes, and moderately adequate practices regarding HIV and TB co-infection. These preliminary findings suggest that targeted educational interventions designed to enhance knowledge may effectively improve both attitudes and practical behaviors, though more rigorous research is needed to confirm these relationships.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0341132.t003(source: https://plos.figshare.com/articles/dataset/_p_Structural_equation_model_analysis_p_/31391539)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。




