dat.landenberger2005 {metadat}R Documentation

Studies on the Effectiveness of CBT for Reducing Recidivism

Description

Results from 58 studies on the effectiveness of cognitive-behavioral therapy (CBT) for reducing recidivism in juvenile and adult offenders.

Usage

dat.landenberger2005

Format

The data frame contains the following columns:

study character (first) author and year
pubtype character publication type (book chapter, journal article, report, or thesis)
country character country where study was carried out (Canada, New Zealand, UK, or USA)
design character study design (matched groups, nonequivalent groups, or randomized trial)
program character purpose of setting up the CBT program (for demonstration, practice, or research purposes)
setting character treatment setting (community or prison)
designprob character indication of study design problems (no, favors the control group, or favors the treatment group)
n.ctrl.rec numeric number of recidivists in the control group
n.ctrl.non numeric number of non-recidivists in the control group
n.cbt.rec numeric number of recidivists in the CBT group
n.cbt.non numeric number of non-recidivists in the CBT group
interval numeric recidivism interval (in months)
group numeric study group (adults or juveniles)
age numeric mean age of the study group
male numeric percentage of males in the study group
minority numeric percentage of minorities in the study group
length numeric treatment length (in weeks)
sessions numeric number of CBT sessions per week
hrs_week numeric treatment hours per week
hrs_total numeric total hours of treatment
cbt.cogskills character CBT component: cognitive skills (yes, no)
cbt.cogrestruct character CBT component: cognitive restructuring (yes, no)
cbt.intpprbsolv character CBT component: interpersonal problem solving (yes, no)
cbt.socskills character CBT component: social skills (yes, no)
cbt.angerctrl character CBT component: anger control (yes, no)
cbt.victimimpact character CBT component: victim impact (yes, no)
cbt.subabuse character CBT component: substance abuse (yes, no)
cbt.behavmod character CBT component: behavior modification (yes, no)
cbt.relapseprev character CBT component: relapse prevention (yes, no)
cbt.moralrsng character CBT component: moral reasoning (yes, no)
cbt.roletaking character CBT component: role taking (yes, no)
cbt.other character CBT component: other (yes, no)

Details

Landenberger and Lipsey (2005) conducted a meta-analysis of 58 experimental and quasi-experimental studies of the effects of cognitive-behavioral therapy (CBT) on the recidivism rates of adult and juvenile offenders (see also Lipsey et al., 2007). The present dataset includes the results of these studies and a range of potential moderator variables to identify factors associated with variation in treatment effects.

Concepts

psychology, criminology, odds ratios, meta-regression

Author(s)

Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org

Source

Personal communication.

References

Landenberger, N. A., & Lipsey, M. W. (2005). The positive effects of cognitive-behavioral programs for offenders: A meta-analysis of factors associated with effective treatment. Journal of Experimental Criminology, 1, 451–476. ⁠https://doi.org/10.1007/s11292-005-3541-7⁠

Lipsey, M. W., Landenberger, N. A., & Wilson, S. J. (2007). Effects of cognitive-behavioral programs for criminal offenders. Campbell Systematic Reviews, 3(1), 1–27. ⁠https://doi.org/10.4073/csr.2007.6⁠

Examples

### copy data into 'dat' and examine data
dat <- dat.landenberger2005
head(dat)

## Not run: 

### load metafor package
library(metafor)

### calculate log odds ratios (for non-recidivism in CBT vs. control groups) and sampling variances
dat <- escalc(measure="OR", ai=n.cbt.non, bi=n.cbt.rec, ci=n.ctrl.non, di=n.ctrl.rec, data=dat)

### fit random-effects model
res <- rma(yi, vi, data=dat)
res

### estimated average OR and corresponding 95% CI/PI
predict(res, transf=exp, digits=2)

### examine if number of treatment sessions per week is a potential moderator
res <- rma(yi, vi, mods = ~ sessions, data=dat)
res

### predicted ORs for 1, 2, 5, or 10 sessions per week
predict(res, newmods=c(1,2,5,10), transf=exp, digits=2)


## End(Not run)

[Package metadat version 1.2-0 Index]