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相关概念视频

Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

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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:  
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Bias01:22

Bias

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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...
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Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

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The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
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Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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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,...
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Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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Blind Procedures02:07

Blind Procedures

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Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...
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相关实验视频

Updated: Jan 9, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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在临床决策工具开发中算法偏差的潜力

Jed Keenan Obra1,2, Chandan Singh3, Kenshata Watkins4

  • 1University of California, Berkeley, Berkeley, CA, USA. jedkeenan.obra@ucsf.edu.

NPJ digital medicine
|December 10, 2025
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概括

临床决策工具 (CDI) 尽管旨在减少医疗保健差异,但可以引入偏见. 这项系统性审查发现,CDI发展中的人口统计,地理代表性和可变选择存在偏差,这可能会使不平等持续存在.

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科学领域:

  • 医疗信息学 医疗信息学
  • 医学伦理 医学伦理
  • 健康 公平 卫生 公平

背景情况:

  • 临床决策工具 (CDI) 旨在规范护理并减少差异.
  • 然而,标准化可能会在医疗保健中无意中延续偏见和不平等.
  • 在CDI开发中潜在的偏见来源需要进行系统的调查.

研究的目的:

  • 在临床决策工具 (CDI) 的开发中定量描述潜在的偏差来源.
  • 系统地审查690个CDI,寻找其开发过程中存在偏见的证据.

主要方法:

  • 对690种临床决策工具 (CDI) 的定量系统审查.
  • 分析侧重于四个潜在的偏见来源:参与者人口统计,调查人员团队地理,预测变量选择和结果定义.

主要成果:

  • 在CDI开发中发现了潜在算法偏差的证据.
  • 参与者的人口统计学是倾斜的 (例如,73%的白人,55%的男性).
  • 调查小组显示地理偏差 (52%北美,31%欧洲).
  • CDI使用了潜在偏见的预测变量 (例如,1.9%使用了种族和种族).
  • 结果定义,特别是那些涉及后续 (26%),可能会引入社会经济偏见.

结论:

  • 虽然CDI旨在改善护理,但可能包含固有的偏见.
  • 诸如偏的人口统计,地理代表和变量选择等因素有助于潜在的偏见.
  • 建议包括在CDI开发过程中考虑这些因素,并透明地将它们传达给临床医生.