Adapted and novel interventions are more effective than adopted interventions: a meta-analytic replication of controlled social intervention research across prevention level and setting

AbstractBackground.Several approaches to the implementation of evidence-based interventions (EBIs) are currently in use. EBIs may be adapted or adopted from previous settings or novel interventions may be developed to achieve public health goals. Within the intervention and implementation literature, a major unsolved dilemma relates to the management of adaptation versus fidelity when EBIs are transferred between settings. An initial attempt to empirically understand this dilemma was made in 2015 which explored meta-analytically the origins of interventions and compared their effect sizes. It was found that adapted interventions produced the highest effect sizes followed by novel and adopted interventions. The current study attempts to replicate these findings using a larger data set.Methods.We used meta-analytic techniques to compare effect sizes across a population of Swedish efficacy and effectiveness studies. Interventions investigated were categorized into adapted, adopted, and novel interventions. Nine subcategories were explored. In addition, we explored differences in effect sizes between settings as well as the impact of study characteristics on effect size.Results.Of the 523 studies included, 22% described adapted interventions, 33% adopted interventions, and 45% novel interventions. The largest effect size was found for adapted interventions followed by novel and adopted interventions. Standard mean effects were significantly different from zero across categories. Study characteristics did not have a large impact on effect size, but interventions provided in the mental health setting showed the highest standard mean difference, followed by somatic healthcare and social services.Conclusions.The results reported here are in line with a growing body of evidence suggesting that there is a need to take the fit between the EBI and the context into account when implementing interventions.