在拉丁美洲护理期刊上发表的随机对照试验中的质量和偏差:一项超流行病学研究
Diana Buitrago-García1,2, Melixa Medina-Aedo3,4,5, Camila Montesinos-Guevara6
1Hospital Universitario Mayor - Méderi, Universidad del Rosario, Bogotá, Colombia.
概括
拉丁美洲护理期刊中的随机对照试验 (RCT) 在报告方法质量和偏差风险方面存在重大差距. 改善对CONSORT等标准的遵守对于可靠的基于证据的护理服务至关重要.
科学领域:
- 护理研究 护理研究
- 临床试验方法论 临床试验方法论
- 基于证据的实践.
背景情况:
- 随机对照试验 (RCT) 是基于证据的护理的基础.
- 拉丁美洲护理期刊中RCT的报告质量和方法的遵守程度尚不清楚.
- 本研究通过评估已发表的RCT来弥补这一差距.
研究的目的:
- 评估拉丁美洲护理期刊上发表的RCT报告的合规性.
- 评估这些RCT中的偏差风险.
- 确定需要改进的研究方法和报告的领域.
主要方法:
- 一项超级研究研究,涉及29个拉丁美洲护理期刊 (2000-2024) 的手动搜索.
- 评估34个已识别的RCT,以遵守CONSORT报告准则.
- 使用COMET分类法对偏差风险的评估和结果的分类.
主要成果:
- 中位数CONSORT合规是19个项目;抽象报告,目标和参与者选择的高合规性.
- 在随机化,盲目化和协议注册方面发现了较低的坚持率 (<40%).
- 大多数RCT对偏见风险有"一些担忧",主要是因为报告不够好. "提供护理"和"身体功能"是常见的结果领域.
结论:
- 从拉丁美洲护理期刊的RCT报告质量和偏差风险评估中存在重大差距.
- 这些缺陷影响了研究的透明度,可复制性和证据合成.
- 建议加强编辑政策和执行报告标准,以提高研究质量.
相关概念视频
Current Trends in Nursing II
Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
Bias
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Study Designs in Epidemiology
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Confounding in Epidemiological Studies
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This phenomenon...
Bias in Epidemiological Studies
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
