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28 Cards in this Set
- Front
- Back
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narrative native and systematic reviews
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objectives
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narrative reviews
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easier, general overvies,
published in pharmacy and medical journals... a chapter in one of our books. |
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narrative reviews
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we don't know how the information was obtained, its just a general review,,, tertiary literature.
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narrative reviews
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remember to look at reference list. is it current, and where was the source from?
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narrative reviews
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we dont want authors to continuously author their own work it will probably mean that they have a very limited point of views
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systematic reviews
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answering a specific topic,
they tell you how the research was conducted. |
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systematic reviews
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very critical about their reviews
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systematic reviews
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objective, study design, results, conclusion,
what data bases were used? |
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quantitative systematic reviews
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the data is pooled
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qualitative systematic reviews
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where the data is not pooled, too many factors and variables to pool the data,
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quantitative systematic reviews
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meta-analysis
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meta-analysis
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study analyses, study of study
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meta-analysis
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takes data from pervasively published research and combine it.
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meta-analysis
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has data from many clinical trials which may provided more accurate information.
it may reach a new conclusion... it may be reviewing primary literature, but because it may give off new unknown answers it is commonly believed to be primary literature. |
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meta-analysis
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by pooling data from other studies it increases sample size, and statical power.
this may help to find new differences. best used to clarify uncertainty |
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meta-analysis
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improve estimates of effect size
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yes, size does matter
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meta-analysis
thats what she said |
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meta-analysis
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in introduction you described how "we dont know" like a clinical trail, these meta analyses must be justified
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meta-analysis
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will have search strategies
and we have standards of what studies we will and wont include. |
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meta-analysis
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studies should be included based on quality of study, not based on results...
this will help to avoid selection bias... which can become a big problem when combining studies |
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meta-analysis
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should have multiple people extract data to avoid more selection bias
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meta-analysis
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data extraction should also be done independently to help avoid a bias
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homogeneity and heterogeneity,
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can we pool the data? or cant we pool
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homogeneity
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pooling can be problematic
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cochran Q test
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we want the P value to be less than 0.05
which means that the difference between the study is due to a difference that actually exist |
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I squared index
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percentage of variability,
the smaller the number the less liketly the studies are heterogeneous. the higher the I squared the more likely heterogeneousness |
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when the confidence intervals include 1
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there is no increased risk... however, if we pool multiple confidence intervals the CI may be above 1.06... resulting an a significant and suggested.
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sensitivity analysis
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helps to determine how strong the study is.
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