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\name{dat.baskerville2012}
\docType{data}
\alias{dat.baskerville2012}
\title{Studies on the Effectiveness of Practice Facilitation Interventions}
\description{Results from 23 studies on the effectiveness of practice facilitation interventions within the primary care practice setting.}
\usage{
dat.baskerville2012
}
\format{The data frame contains the following columns:
\tabular{lll}{
\bold{author} \tab \code{character} \tab study author(s) \cr
\bold{year} \tab \code{numeric} \tab publication year \cr
\bold{score} \tab \code{numeric} \tab quality score (0 to 12 scale) \cr
\bold{design} \tab \code{character} \tab study design (cct = controlled clinical trial, rct = randomized clinical trial, crct = cluster randomized clinical trial) \cr
\bold{alloconc} \tab \code{numeric} \tab allocation concealed (0 = no, 1 = yes) \cr
\bold{blind} \tab \code{numeric} \tab single- or double-blind study (0 = no, 1 = yes) \cr
\bold{itt} \tab \code{numeric} \tab intention to treat analysis (0 = no, 1 = yes) \cr
\bold{fumonths} \tab \code{numeric} \tab follow-up months \cr
\bold{retention} \tab \code{numeric} \tab retention (in percent) \cr
\bold{country} \tab \code{character} \tab country where study was conducted \cr
\bold{outcomes} \tab \code{numeric} \tab number of outcomes assessed \cr
\bold{duration} \tab \code{numeric} \tab duration of intervention \cr
\bold{pperf} \tab \code{numeric} \tab practices per facilitator \cr
\bold{meetings} \tab \code{numeric} \tab (average) number of meetings \cr
\bold{hours} \tab \code{numeric} \tab (average) hours per meeting \cr
\bold{tailor} \tab \code{numeric} \tab intervention tailored to the context and needs of the practice (0 = no, 1 = yes) \cr
\bold{smd} \tab \code{numeric} \tab standardized mean difference \cr
\bold{se} \tab \code{numeric} \tab corresponding standard error
}
}
\details{
Baskerville et al. (2012) describe outreach or practice facilitation as a "multifaceted approach that involves skilled individuals who enable others, through a range of intervention components and approaches, to address the challenges in implementing evidence-based care guidelines within the primary care setting". The studies included in this dataset examined the effectiveness of practice facilitation interventions for improving some relevant evidence-based practice behavior. The effect was quantified in terms of a standardized mean difference, comparing the change (from pre- to post-intervention) in the intervention versus the comparison group (or the difference from baseline in prospective cohort studies).
}
\source{
Baskerville, N. B., Liddy, C., & Hogg, W. (2012). Systematic review and meta-analysis of practice facilitation within primary care settings. \emph{Annals of Family Medicine}, \bold{10}(1), 63--74. \verb{https://doi.org/10.1370/afm.1312}
}
\author{
Wolfgang Viechtbauer, \email{wvb@metafor-project.org}, \url{https://www.metafor-project.org}
}
\examples{
### copy data into 'dat' and examine data
dat <- dat.baskerville2012
dat
\dontrun{
### load metafor package
library(metafor)
### random-effects model
res <- rma(smd, sei=se, data=dat, method="DL")
print(res, digits=2)
### funnel plot
funnel(res, xlab="Standardized Mean Difference", ylim=c(0,0.6))
### rank and regression tests for funnel plot asymmetry
ranktest(res)
regtest(res)
### meta-regression analyses examining various potential moderators
rma(smd, sei=se, mods = ~ score, data=dat, method="DL")
rma(smd, sei=se, mods = ~ alloconc, data=dat, method="DL")
rma(smd, sei=se, mods = ~ blind, data=dat, method="DL")
rma(smd, sei=se, mods = ~ itt, data=dat, method="DL")
rma(smd, sei=se, mods = ~ duration, data=dat, method="DL")
rma(smd, sei=se, mods = ~ tailor, data=dat, method="DL")
rma(smd, sei=se, mods = ~ pperf, data=dat, method="DL")
rma(smd, sei=se, mods = ~ I(meetings * hours), data=dat, method="DL")
}
}
\keyword{datasets}
\concept{medicine}
\concept{primary care}
\concept{standardized mean differences}
\concept{publication bias}
\concept{meta-regression}
\section{Concepts}{
medicine, primary care, standardized mean differences, publication bias, meta-regression
}
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