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Supplemental Digital Content 1 Progressive resistance training (PRT)In support of this manuscript, this section contains a detailed description of the protocol of Linear Periodization of Physical
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01
Determine the outcome measure you want to display on the forest plot.
02
Collect the data including the treatment effect estimates and their confidence intervals for each study.
03
Calculate the weight of each study based on sample size or other relevant factors.
04
Plot the effect estimate for each study using a marker such as a square or diamond.
05
Draw horizontal lines representing the confidence intervals for each study.
06
Arrange the studies along the y-axis in descending order of publication year or effect size.
07
Add a vertical line representing the overall effect estimate using a fixed or random effects model.
08
Interpret the forest plot by assessing the spread of the data points and the overall effect estimate.

Who needs forest plot of changes?

01
Researchers conducting meta-analyses
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Healthcare professionals looking for a visual summary of treatment effects
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Students learning about evidence-based practice

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A forest plot of changes is a graphical representation used to display the results of multiple studies or analyses, showing the estimates of changes and their confidence intervals.
Typically, researchers and organizations that conduct studies requiring regulatory approval or reporting are required to file a forest plot of changes.
To fill out a forest plot of changes, you need to gather data from relevant studies, calculate the effect sizes and confidence intervals, and then plot these values on the graph.
The purpose of the forest plot of changes is to visualize and summarize the data from multiple sources, aiding in meta-analysis and decision-making processes.
The information that must be reported includes effect sizes, confidence intervals, the number of studies included, and any relevant demographic or methodological details.
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