纳入研究特征数据集

数据集获取（Figshare）

• 源站标题：Characteristics included study.
• DOI：10.1371/journal.pone.0312001.t001
• 发布日期：2024-12-02
• 文件数：1 个
• 文件总体积：38.40 KB
• 源站页面：https://plos.figshare.com/articles/dataset/Characteristics_included_study_/27943349

命令行下载

curl -L -o "Table 1.xls" "https://ndownloader.figshare.com/files/50922380"

文件清单

• Table 1.xls（38.40 KB）

文件总体积 38.40 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

Various technology-based interventions have been designed to improve medication adherence and treatment success. However, research on the most effective mode to address this issue is still limited. Our study evaluated the effectiveness of technology-based interventions in improving treatment adherence, completion, and treatment success among tuberculosis (TBC) patients. We conducted a meta-analysis of randomized controlled trials by searching articles from six databases including PubMed, Science Direct, Cochrane, Jstor, Embase, and Scopus from 2018 to April 2023. Two independent reviewers assessed the study quality using the Cochrane Risk of Bias 2.0 tool. We analysed the data using a random-effects model. We also conducted publication bias and sensitivity analysis. In total, 13 studies were identified and 4,794 participants were included in the meta-analysis. The results indicated that technology-based interventions were effective in improving treatment adherence, completion, and success (Odds Ratio (OR): 2.57, 95% Confident Interval (CI): 1.01–6.50, I2 = 86.6%; OR: 1.77, 95% CI: 0.95–3.28, I2: 82.3%; OR: 1.61, 95% CI: 0.85–3.06, I2: 84%, respectively). We examined the possibility of publication bias in the published studies included in this systematic review. However, no evidence of publication bias was found. From the sensitivity analysis by removing one study randomly, we found that our results are robust. Based on the results, we can conclude that technology-based interventions like MERM, text-based messages, video conferencing, and VOT are effective in increasing treatment adherence and completion in tuberculosis management. Therefore, technology shows immense potential in enhancing patient outcomes.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0312001.t001（source: https://plos.figshare.com/articles/dataset/Characteristics_included_study_/27943349）。