The forward-conditional binary logistic regression method can be used to determine what interventions work and in what circumstances alongside the RCTs. Having established through the RCT that an intervention is effective, i.e. the intervention group indicates more positive results than the control group, the same data can be used to investigate the circumstances in which the intervention is more or less likely to be effective. First, the sample is divided into two groups---those that improved against a desired outcome, and those that did not. Second, the variables that may be influencing the outcome are identified through bivariate analysis, other research findings, and/or practice wisdom. Third, these selected variables are entered in a forward-conditional model. The variables that are actually influencing the outcome are retained in the equation, and those that are significant provide an exponential beta which is interpreted as an odds ratio, indicating the odds of the intervention achieving the outcome where the significant factor(s) may be present.

Pedagogical techniques. First, the methodology will be introduced, and then actual databases from evaluations of social work programmes will be used to demonstrate the utility of the methodology in investigating the circumstances where particular interventions are more likely to be effective. The audience will be invited to take part in an interactive process of data analysis and discourse using real databases from two recently completed evaluations where both RCTs and binary logistic regression models were used. It will be demonstrated that, provided reliable outcome measures are used as part of practice, these methods can be used by practitioners in a prospective evaluation of their interventions as part of empirical practice approaches. The combination of RCT and BLRs is an innovative way of testing interventions in a prospective evaluation of what works and in what circumstances, and therefore contributes to the development of effective interventions in practice.