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dat.gibson2002

Studies on the Effectiveness of Self-Management Education and Regular Medical Review for Adults with Asthma


Description

Results from 15 trials examining the effectiveness of self-management education and regular medical review for adults with asthma.

Usage

dat.gibson2002

Format

The data frame contains the following columns:

author character first author of study
year numeric publication year
n1i numeric number of participants in the intervention group
m1i numeric mean number of days off work/school in the intervention group
sd1i numeric standard deviation of the number of days off work/school in the intervention group
n2i numeric number of participants in the control/comparison group
m2i numeric mean number of days off work/school in the control/comparison group
sd2i numeric standard deviation of the number of days off work/school in the control/comparison group
ai numeric number of participants who had one or more days off work/school in the intervention group
bi numeric number of participants who no days off work/school in the intervention group
ci numeric number of participants who had one or more days off work/school in the control/comparison group
di numeric number of participants who no days off work/school in the control/comparison group
type numeric numeric code for the intervention type (see below)

Details

Asthma management guidelines typically recommend for patients to receive education and regular medical review. While self-management programs have been shown to increase patient knowledge, it is less clear to what extent they actually impact health outcomes. The systematic review by Gibson et al. (2002) examined the effectiveness of self-management education and regular medical review for adults with asthma. In each study, participants receiving a certain management intervention were compared against those in a control/comparison group with respect to a variety of health outcomes. One of the outcomes examined in a number of studies was the number of days off work/school.

The majority of studies reporting this outcome provided means and standard deviations allowing a meta-analysis of standardized mean differences. Seven studies also reported the number of participants who had one or more days off work/school in each group. These studies could be meta-analyzed using, for example, (log) risk ratios. Finally, one could also consider a combined analysis based on standardized mean differences computed from the means and standard deviations where available and using probit transformed risk differences (which also provide estimates of the standardized mean difference) for the remaining studies.

Some degree of patient education was provided in all studies. In addition, the type variable indicates what additional intervention components were included in each study:

  1. optimal self-management (writing action plan, self-monitoring, regular medical review),

  2. self-monitoring and regular medical review,

  3. self-monitoring only,

  4. regular medical review only,

  5. written action plan only.

Source

Gibson, P. G., Powell, H., Wilson, A., Abramson, M. J., Haywood, P., Bauman, A., et al. (2002). Self-management education and regular practitioner review for adults with asthma. Cochrane Database of Systematic Reviews, 3.

Examples

### copy data into 'dat' and examine data
dat <- dat.gibson2002
dat

### fixed-effects model analysis of the standardized mean differences
dat <- escalc(measure="SMD", m1i=m1i, sd1i=sd1i, n1i=n1i, m2i=m2i, sd2i=sd2i, n2i=n2i, data=dat)
res <- rma(yi, vi, data=dat, method="FE")
print(res, digits=2)

### fixed-effects model analysis of the (log) risk ratios
dat <- escalc(measure="RR", ai=ai, bi=bi, ci=ci, di=di, data=dat)
res <- rma(yi, vi, data=dat, method="FE")
print(res, digits=2)
predict(res, transf=exp, digits=2)

### fixed-effects model analysis of the standardized mean differences and the probit transformed
### risk differences (which also provide estimates of the standardized mean difference)
dat <- escalc(measure="SMD", m1i=m1i, sd1i=sd1i, n1i=n1i, m2i=m2i, sd2i=sd2i, n2i=n2i, data=dat)
dat <- escalc(measure="PBIT", ai=ai, bi=bi, ci=ci, di=di, data=dat, replace=FALSE)
dat
res <- rma(yi, vi, data=dat, method="FE")
print(res, digits=2)

metafor

Meta-Analysis Package for R

v2.4-0
GPL (>= 2)
Authors
Wolfgang Viechtbauer [aut, cre] (<https://orcid.org/0000-0003-3463-4063>)
Initial release
2020-03-19

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