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  • 标题:Important Considerations in Conducting Statistical Mediation Analyses
  • 本地全文:下载
  • 作者:Osvaldo F. Morera ; Felipe González Castro
  • 期刊名称:American journal of public health
  • 印刷版ISSN:0090-0036
  • 出版年度:2013
  • 卷号:103
  • 期号:3
  • 页码:394-396
  • DOI:10.2105/AJPH.2012.301047
  • 语种:English
  • 出版社:American Public Health Association
  • 摘要:An investigator wishes to examine mediation in a randomized control trial of the effectiveness of an intervention, which consists of a computerized decision aid for promoting colorectal cancer screening. Mediation is a naturally occurring process, and in any given instance, research investigators seek to ascertain whether it has occurred. In the case of a prevention intervention for a specific chain of events, mediation occurs (1) when the prevention intervention effects a change on a targeted intermediate condition: a mediator, for example, a person’s intentions to get a colorectal screening examination; and (2) when, at a later point in time, this condition effects a change on a targeted outcome, for example, the actual behavior of getting a colorectal screening exam. Full mediation is said to occur when the effectiveness of the intervention on the targeted outcome only takes place through the intermediate condition and does not directly affect the targeted outcome. Partial mediation is said to occur when the intervention causes changes in both the intermediate condition and the targeted outcome. The assessment of mediation is important because conclusions about the efficacy of a public health intervention may depend on how these indirect influences are assessed. Open in a separate window Open in a separate window The proposed study regarding the effectiveness of this aforementioned decision aid would include 200 individuals who will be randomized to a decision aid (intervention) condition or to a usual care (control) condition. Thus, the group variable that contains these 2 conditions serves as the independent variable. The researcher hypothesizes that the independent variable will cause changes in a mediator variable (e.g., increased intentions to get screened for colorectal cancer). The mediator variable is then hypothesized to cause changes in the outcome (the dependent variable), which is the actual screening behavior that would occur at a later time point.
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