基于社区的研究的谬论
Simar S Bajaj1, Jaeah Kim2, Fatima Cody Stanford3
1Stanford University School of Medicine, Palo Alto, CA, USA.
Journal of general internal medicine
|July 8, 2025
概括
基于社区的研究可以促进公平的伙伴关系,但在参与和资金方面面临挑战. 为了实现更好的公共卫生成果,需要进行改革,以实现持续的合作和问责制.
科学领域:
- 公共卫生 公共卫生
- 社区参与的研究
- 健康 公平 卫生 公平
背景情况:
- 基于社区的研究 (CBR) 旨在与边缘化社区建立公平的伙伴关系.
- 当前的CBR实践往往受到肤浅的参与和系统不平等的影响.
- 这种脱节阻碍了CBR具有影响力公共卫生结果的潜力.
更多相关视频
08:53Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
5.3K
11:21Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
8.3K
相关概念视频
Bias
5.0K
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...
5.0K
Community Based Intervention
97
Community-based interventions in mental health represent a paradigm shift from institution-centered care to treatments embedded within the fabric of local communities. By prioritizing inclusion and leveraging existing societal structures, this approach fosters a supportive environment conducive to addressing mental health challenges while promoting individual dignity and agency.
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
97
Systematic Error: Methodological and Sampling Errors
2.4K
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...
2.4K
Ethics in Research
24.0K
Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound.
24.0K
Naturalistic Observations
16.0K
If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
16.0K
Bias in Epidemiological Studies
697
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:
697
