10 research outputs found

    Characteristics of study cohort, stratified by whether they were absent from work due to illness at any point during the intervention.

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    <p>Characteristics of study cohort, stratified by whether they were absent from work due to illness at any point during the intervention.</p

    Association between the rate of unplanned absenteeism due to illness and demographic, clinical factors and physical activity.

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    <p>Association between the rate of unplanned absenteeism due to illness and demographic, clinical factors and physical activity.</p

    Sensitivity Analyses: Funnel plots of weight by natural log of the incidence rate ratio for ACL injury.

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    <p>Panel A includes all 14 studies of ACL injury, while Panel B includes only 12 ACL studies (excluding Caraffa et al and Myklebust et al).</p

    Meta-Regression: Year of Publication.

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    <p>This figure shows the association between the year of publication and intervention efficacy for A) knee injury and B) ACL injury. Publication year is along the X-axis, and each dot represents the summary IRR for that year. The size of the bubble corresponds to the average sample size for studies published in that year.</p

    Forest plots of the natural log of IRR and 95% confidence interval for knee and ACL injuries excluding studies that contribute to heterogeneity.

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    <p>Summary estimates from the meta-analysis are presented at the bottom of the plot in red. A) Forest plot of the natural log of IRR and 95% confidence interval for knee injury excluding Heidt et al. B) Forest plot of the ln IRR and 95% confidence interval for ACL injury excluding Caraffa et al and Myklebust et al.</p

    Sensitivity Analyses. Forest plots of the ln IRR and 95% confidence interval, including studies that contribute to heterogeneity.

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    <p>Panel A shows the forest plot for knee injury, including Heidt. Panel B shows the forest plot for ACL injury, including Caraffa and Myklebust. Summary estimates from the meta-analysis are presented at the bottom of the plot in red.</p
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