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BtheB

Beat the Blues Data


Description

Data from a clinical trial of an interactive multimedia program called ‘Beat the Blues’.

Usage

data("BtheB")

Format

A data frame with 100 observations of 100 patients on the following 8 variables.

drug

did the patient take anti-depressant drugs (No or Yes).

length

the length of the current episode of depression, a factor with levels <6m (less than six months) and >6m (more than six months).

treatment

treatment group, a factor with levels TAU (treatment as usual) and BtheB (Beat the Blues)

bdi.pre

Beck Depression Inventory II before treatment.

bdi.2m

Beck Depression Inventory II after two months.

bdi.4m

Beck Depression Inventory II after four months.

bdi.6m

Beck Depression Inventory II after six months.

bdi.8m

Beck Depression Inventory II after eight months.

Details

Longitudinal data from a clinical trial of an interactive, multimedia program known as "Beat the Blues" designed to deliver cognitive behavioural therapy to depressed patients via a computer terminal. Patients with depression recruited in primary care were randomised to either the Beating the Blues program, or to "Treatment as Usual (TAU)".

Note that the data are stored in the wide form, i.e., repeated measurments are represented by additional columns in the data frame.

Source

J. Proudfoot, D. Goldberg and A. Mann (2003). Computerised, interactive, multimedia CBT reduced anxiety and depression in general practice: A RCT. Psychological Medicine, 33, 217–227.

Examples

data("BtheB", package = "HSAUR")
  layout(matrix(1:2, nrow = 1))   
  ylim <- range(BtheB[,grep("bdi", names(BtheB))], na.rm = TRUE)
  boxplot(subset(BtheB, treatment == "TAU")[,grep("bdi", names(BtheB))],
          main = "Treated as usual", ylab = "BDI", 
          xlab = "Time (in months)", names = c(0, 2, 4, 6, 8), ylim = ylim)
  boxplot(subset(BtheB, treatment == "BtheB")[,grep("bdi", names(BtheB))], 
          main = "Beat the Blues", ylab = "BDI", xlab = "Time (in months)",
          names = c(0, 2, 4, 6, 8), ylim = ylim)

HSAUR

A Handbook of Statistical Analyses Using R (1st Edition)

v1.3-10
GPL
Authors
Brian S. Everitt and Torsten Hothorn
Initial release
2022-04-25

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