Computational protocol: Supported Employment for the Reintegration of Disability Pensioners with Mental Illnesses: A Randomized Controlled Trial

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Protocol publication

[…] For the general analyses, a sample size of 250 persons had been calculated using power analysis software G*Power (). A medium effect size (0.42 SD) should be detected with a power of 95% at a two-tailed significance level of 0.05. All statistical analyses were conducted with SPSS 20.0. Data of all participants were analyzed as intention-to-treat. For that, the last observation carried forward (LOCF) method was used, meaning that in case of dropout, the last observation of a participant was used to replace the missing value. As some concerns exists that the use of LOCF can lead to an overestimation (or underestimation) of the effects (), we additionally performed analyses only with the study completers (i.e., drop outs were rated as missing values and only those participants who participated until the end of the study were rated). With this analysis, we intended to control for the stability of the results.Patient characteristics were analyzed descriptively (means, standard deviations, frequencies, and percentages). To test for normal distribution of continuous variables, the Kolmogorov–Smirnov-test was applied. Mann–Whitney-U-tests were performed if the variables were not normally distributed. Categorical variables were analyzed using cross tabulations with chi-square tests.To test for the primary outcome, cross tabulations and chi-square tests were conducted. To test for group differences with respect of having competitive employment (i.e., being employed in the competitive employment market yes/no) over all measurements point, a generalized estimating equation model (GEE) was conducted. GEE is an advantageous model for the analysis of repeated measurements of categorical outcome variables. GEE was squared to allow more flexibility in handling possible fluctuations regarding the primary outcome during different measurement points. The development of the participants’ work in competitive employment across the study period is shown as a line graph. The differences between the single measurement points were analyzed by chi-square tests. The analyses of the secondary outcome variables were restricted to people who worked in competitive employment market for at least 1 month. The continuous secondary outcome variables: time of longest job tenure, hours worked per month, and number of months employed were analyzed with respect to group differences using Mann–Whitney-U-tests. […]

Pipeline specifications

Software tools G*Power, SPSS
Application Miscellaneous
Organisms Homo sapiens