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Researchers should design epidemiologic studies in such a way as to avoid or minimize known or suspected biases. They should acknowledge unavoidable biases and explain how they may affect results. Careful selection of the control group can minimize or avoid biases in case control studies. Forms of selection bias include self-selection bias, diagnostic suspicion bias, and assembly (susceptibility) bias. The process of acquiring needed data can produce information bias. Forms of information bias are recall bias caused by selective memory and surveillance bias. Confounding occurs when two exposures or processes occur simultaneously and the effect of one is obscured by or distorted by the effect of the other. The confounding variable may misconstrue the apparent relationship between the exposure under study and the outcome of interest. If the research has measured the confounding variable, its effects can be disentangled. Age is the most common and important confounding variable. Since age tends to be related to both exposures and outcomes, researchers need to match subjects by age or to control for age in the analysis. Age may be a confounding variable in some case control studies between oral contraceptives (OCs) and cervical cancer. The risk of disease is reported as the odds ratio in case control studies, while it is the relative risk for cohort studies. It is best to use well-designed studies and large sample sizes to find statistically significant strengths of association. Meta-analysis is used more and more to increase sample sizes but the individual study populations and the variables are often very different. In fact, the studies in the meta-analysis tend to be confounders. Clinicians should consider the aforementioned concerns when interpreting the results of epidemiologic studies. They must be prepared to address validity and clinical relevance. To do so, they need to be familiar with basic study designs and associated issues to provide appropriate counseling and informed clinical decision making.

作者:C L, Westhoff

来源:Dialogues in contraception 1995 年 4卷 5期

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作者:
C L, Westhoff
来源:
Dialogues in contraception 1995 年 4卷 5期
标签:
Bias Biology Case Control Studies Clinic Activities Cohort Analysis Counseling Critique Epidemiologic Methods Epidemiology Error Sources Health Measurement Obstacles Program Activities Programs Public Health Risk Factors Studies Study Design
Researchers should design epidemiologic studies in such a way as to avoid or minimize known or suspected biases. They should acknowledge unavoidable biases and explain how they may affect results. Careful selection of the control group can minimize or avoid biases in case control studies. Forms of selection bias include self-selection bias, diagnostic suspicion bias, and assembly (susceptibility) bias. The process of acquiring needed data can produce information bias. Forms of information bias are recall bias caused by selective memory and surveillance bias. Confounding occurs when two exposures or processes occur simultaneously and the effect of one is obscured by or distorted by the effect of the other. The confounding variable may misconstrue the apparent relationship between the exposure under study and the outcome of interest. If the research has measured the confounding variable, its effects can be disentangled. Age is the most common and important confounding variable. Since age tends to be related to both exposures and outcomes, researchers need to match subjects by age or to control for age in the analysis. Age may be a confounding variable in some case control studies between oral contraceptives (OCs) and cervical cancer. The risk of disease is reported as the odds ratio in case control studies, while it is the relative risk for cohort studies. It is best to use well-designed studies and large sample sizes to find statistically significant strengths of association. Meta-analysis is used more and more to increase sample sizes but the individual study populations and the variables are often very different. In fact, the studies in the meta-analysis tend to be confounders. Clinicians should consider the aforementioned concerns when interpreting the results of epidemiologic studies. They must be prepared to address validity and clinical relevance. To do so, they need to be familiar with basic study designs and associated issues to provide appropriate counseling and informed clinical decision making.