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Kin 330 Week 8 post midterm.docx

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KIN 330
Laura Middleton

Kin 330 Week 8 In case you want to watch the video in its entirety: AAAEAA SYSTEMATIC REVIEWS & META-ANALYSIS Setting the stage  Sometimes there are many studies addressing the same research topic with conflicting results o Important to choose the best evidence to apply in practice  How do you know what study to trust? o Highest quality study? o Systematic review or meta-analysis?*  Summarizes results of all studies. RECALL: Evidence-based Practice: Multi-step Process  Define the problem o Formulate an answerable question  Track down best evidence to solve the problem  Critically appraise best evidence  Apply to the individual o Based on clinical expertise and context  Evaluate practice outcomes When to do a review?  There are multiple studies with results regarding a specific research question.  Those studies are relatively uniform in design.  The findings for the studies are relatively consistent with each other  There is value to be gained by understanding the actual magnitude of a statistical effect with better precision. Three Types of Reviews Narrative Reviews  Summarize findings and opinions from a numerous studies examining a topic  Summarizes large amount of data in a narrative style (tells a story) Systematic reviews.  Similar to above, but with very specific criteria set out describing how the studies were selected  More rigorous search strategy with strict inclusion/exclusion criteria Meta analyses.  Atype of systematic review  Systematic search strategy  Addition of calculation of effect sizes by totally results across studies  Results in QUANTITATIVE summary of findings across studies SYSTEMATIC REVIEW/META-ANALYSIS PROCESS: Objective & Search Strategy  State the study objective, i.e. research question o What is the P.I.C.O. of interest?  Develop the protocol o Inclusion/exclusion criteria o P.I.C.O. characteristics o Study designs Advantages for both including only highest quality versus broad range of study types  Only RCTs: o Higher internal validity o Disadvantage: May not reflect all research o Good if area there are many studies  Broad range of research designs: o Advantage: better reflects breadth of knowledge o Disadvantage: some lower quality studies may bias the results  Develop the search strategy o Databases searched o Search terms o Review of reference lists Search  Conduct search o As planned with specified inclusion/exclusion & databases  Retrieve papers  Screen & select o Further evaluate for relevance: study objective, inclusion/exclusion criteria Evaluation  Evaluate methodological quality o Quality of designs & measures evaluated against standard criteria  Have evaluated strengths/weaknesses of study designs  Will spend substantial time in the remainder of this term to discuss further evaluation of study quality • Risk of bias • Reliability & validity of measures Analyzing & Synthesizing Results First step, collect data from all papers:  Collect information relevant to PICOT  Collect information regarding study sample  Collect information regarding study quality Next Step:  Summarize results (statistics) For example, SYSTEMATIC REVIEW VS. META-ANALYSIS  Both include similar systematic search strategies  Meta-analyses include synthesis of data by analysis (effect sizes) o Systematic reviews do not  If sufficient data, then meta-analyses are generally preferred Challenges We need a statistical method to synthesize the results of existing studies BUT, the studies use slightly different methods:  Different study features o Different control groups, different measures, different time periods, different measurement of sperm quality  Different statistics o Mean differences, odds ratios, relative risks Solution: Effect Size Can be derived from:  Means  Relative Risk  Odds Ratios (basically, any summary statistic that might be described in a quantitative study...) Denoted “d”  Calculated differently, depending on the source data Means  Results fromANOVAor t-test  Presented in mean (SD) by group and p-value for difference  Effect size, d = meaexposure mean comparison SD pooled What type of studied would have use means? Experimental If there was NO difference between groups, what would d (the effect size) be? ZERO Relative risk/odds ratio  Odds ratio (OR): o Ratio of odds between I/C o Odds: #with outcome/#without outcome  Relative Risk (RR): o Ratio of risk between I/C o Risk: #without outcome/total #  Effect sized = OR or RR (or HR) What type of studied would use OR/RR/HR? Observational IF was NO diff between groups, what would D be? 1! The Process  Once all are converted into effect sizes (d), they are comparable across studies!  Now need to combine into one summary effect size  Lots of variability among studies o Should they all contribute the equally to summary statistic? NO larger designs, should contribute more Which should contribute more or less? - Larger better designed studies ****************************************************************************** For example: Smith et al. (2001) (n=320) • High vs. low physical activity (adj. age, sex, educ) • Measured with actigraphy • Risk of dementia lower in active group Taylor et al. (1998)(n=498) • High vs. low physical activity (adj. age, sex, educ) • Measured by self-reports • Risk of dementia lower in active group Bosch et al. (2008)(n=84) • High vs. low physical activity (adj. age only) • Measured with self-reports • No significant difference in dementia between groups ****************************************************************************** Weighting  Which studies should contribute more? o Studies that are Larger in size and/or better designed  Effect size is known to be a better estimate of population risk when sample size is large than small  SO...  Compute effect size (d) for each study  Also weight effect size by sample size of study  Can you think of any other considerations that we could weight studies on? Forest Plot  In addition to a text-based description of the findings, the effect size indexes and overall effect size are normally presented in something called a forest plot.  This is a highly efficient and effective way of conveying the individual study findings and cumulative findings... Study 1 Large sample Study 2 size, What do u notice about Individual Study 3 study Study 4 confidence interval? Its effectsize Study 5 smaller Study 6 Study 7 Study 8 Box Size= sample size Study 9 Study10 Horizontal line= Study 11 Study 12 confidenceinterval (arrow head means Study 13 Study 14 offthe chart) Represents overall effect Vertical line represents NO difference size (across studies) If centre = 1 observational studies combined **** Centre =
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