PCC框架
非洲地区曲马多非医疗使用的范围综述研究方案,包含背景、方法和预期结果,旨在了解滥用行为与健康后果。

基本信息
资源简介
PCC框架
【数据集背景】
本数据集源站标题为《PCC framework.》。源站首次发布:2023-05-19。
【数据内容】
源站原始描述:Background Tramadol is one of the most prescribed painkillers in the world. It is a synthetic opioid that is an excellent alternative to morphine and its derivatives in African countries. It is an essential drug due to its low cost and constant availability. However, the health consequences of tramadol use due to illicit trafficking, like those caused by fentanyl and methadone in North America, are poorly documented. This scoping review aims to understand the nature and extent of the use and hea…
【数据结构与技术规格】
文件数 1 个,合计 5.63 KB。Table 1.xls:application/vnd.ms-excel,5.63 KB。数据集 DOI:10.1371/journal.pone.0285809.t001。
【主题与分类】
源站学科分类:Medicine、Microbiology、Pharmacology、Biotechnology、Cancer、Science Policy。主题标签:scoping review aims、identify risk factors、essential drug due、drug abuse ,"、illicit drugs ,"、xlink "> due、scoping review study、open science framework、independently select studies、xlink "> tramadol。
【适用方向】
文本类数据可用于医学自然语言处理,如命名实体识别、信息抽取与文本分类。
【获取与许可】
源站页面:https://plos.figshare.com/articles/dataset/PCC_framework_/22965769
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Boun, Saidou Sabi; Omonaiye, Olumuyiwa; Yaya, Sanni (2023). PCC framework.. PLOS ONE. Dataset
【使用注意】
· 源站最后修改于 2023-06-02,引用时请注意版本时效。
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:PCC framework.
- DOI:10.1371/journal.pone.0285809.t001
- 发布日期:2023-05-19
- 文件数:1 个
- 文件总体积:5.63 KB
- 源站页面:https://plos.figshare.com/articles/dataset/PCC_framework_/22965769
命令行下载
curl -L -o "Table 1.xls" "https://ndownloader.figshare.com/files/40708012"
文件清单
Table 1.xls(5.63 KB)
文件总体积 5.63 KB(源站 API 实测)。
数据说明
Background
Tramadol is one of the most prescribed painkillers in the world. It is a synthetic opioid that is an excellent alternative to morphine and its derivatives in African countries. It is an essential drug due to its low cost and constant availability. However, the health consequences of tramadol use due to illicit trafficking, like those caused by fentanyl and methadone in North America, are poorly documented. This scoping review aims to understand the nature and extent of the use and health consequences of the Non-Medical Use (NMU) of tramadol in Africa to guide future research.
Methods
Due to the perceived lack of African literature on the subject, our search strategy is based on the simultaneous use of the keywords “tramadol” and Medical Subject Heading (MeSH), such as “Drug abuse,” “illicit drugs,” or “Prescription Drug Misuse,” combined with the term “Africa” and Boolean operators (and, or not) to form our search equations. Two researchers will independently select studies from literature searched in several databases such as Medline, Embase, the Scopus database, Web of Science, the African Journals online database, and for grey literature Google Scholar without any time restriction. All research, in various formats, conducted in Africa, will be included in our study on the prevalence of use in different African population groups or on evidence of addiction, intoxication, seizures and mortality related to NMU of tramadol.
Results
Through this study, we aim to map consumers and identify risk factors, health consequences, and prevalence of the NMU of tramadol in African countries.
Discussion
We are conducting the first scoping review study to investigate the prevalence and consequences of NMU of tramadol in Africa. Upon completion, our findings will be published in a peer-reviewed journal and presented at relevant conferences and workshops. However, since health is not limited to the lack of disease, our study is likely incomplete without incorporating the studies of the social impact of NMU of tramadol.
Systematic review registration
Open Science Framework: https://osf.io/ykt25/.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0285809.t001(source: https://plos.figshare.com/articles/dataset/PCC_framework_/22965769)。
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。
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