引用率的预测因素和引用偏差的问题:一个范围审查
Birgitte Nørgaard1, Karen E Lie2, Hans Lund3
1Department of Public Health, University of Southern Denmark, Odense, Denmark.
Journal of clinical epidemiology
|November 20, 2025
概括
科学文献面临引用偏见,许多研究建议修改文章以获得更高的引用率,而不是专注于科学价值. 这种做法可能会破坏研究完整性,并突出潜在的出版偏见.
科学领域:
- 图书统计学 图书统计学
- 超级研究的研究.
- 科学出版业的科学出版.
背景情况:
- 引用对于科学完整性至关重要,提供信誉和背景.
- 引用偏差发生在研究因其科学价值之外的其他原因被引用时.
- 了解影响引用率的因素对于评估研究影响至关重要.
研究的目的:
- 系统地确定影响健康研究引用率的因素.
- 为了分类检查这些引用预测器的研究.
- 评估科学文献中引用偏差的流行程度和性质.
主要方法:
- 根据PRISMA指南进行了全面的范围审查.
- 搜索了四个电子数据库,并通过参考列表选进行了补充.
- 包括关于引用率预测因素和医疗保健偏见的经验性元研究研究.
主要成果:
- 确定了165项研究,评估了786项引用预测因子的定量分析.
- 48%的研究专注于引用偏差,而48%的研究旨在优化文章特征以增加引用量.
- 一小部分研究 (4%) 调查了文章可访问性的基础设施因素.
结论:
- 近一半的研究建议修改文章特征 (例如,标题,作者数量) 以增加引文,这可能与科学完整性相冲突.
- 这些做法可能会优先考虑引用指标,而不是科学贡献和严谨性.
- 显示引用率增加的大量研究表明出版偏差的风险.
相关概念视频
Bias
7.2K
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...
7.2K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
387
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,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
387
Bias in Epidemiological Studies
1.2K
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:
1.2K
Study Design in Statistics
9.9K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
9.9K
Hindsight Biases
4.2K
Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now?
4.2K
Systematic Error: Methodological and Sampling Errors
8.5K
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
8.5K


