Modeling the Scaling Up of Early Crime Prevention: implementation challenges and opportunities for translational criminology
Although the amount of research evidence on the effectiveness of developmental crime prevention has grown considerably in recent decades, the translation of this scientific knowledge into policy and practice has lagged behind. In this article, we consider the challenges as well as the opportunities...
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| Contributors: | ; |
| Format: | Electronic Article |
| Language: | English |
| Published: |
2017
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| In: |
Criminology & public policy
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| Online Access: |
Volltext (Verlag) |
| Journals Online & Print: | Drawer...
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| Check availability: | HBZ Gateway |
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| Summary: | Although the amount of research evidence on the effectiveness of developmental crime prevention has grown considerably in recent decades, the translation of this scientific knowledge into policy and practice has lagged behind. In this article, we consider the challenges as well as the opportunities associated with scaling up evidence‐based programs and we offer an approach for considering the potential effects of deviations in implementation protocols during replications. We use results from the series of studies on the Nurse‐Family Partnership (NFP) to develop a computer simulation model. Based on a large number of simulations, we systematically adjusted key inputs (e.g., target population and fidelity) to mimic a range of possible implementation conditions and to observe the impacts on the estimated intervention effects. As the process progresses from the baseline condition, which reflects the initial implementation conditions specified in the NFP model, to alternative experimental scenarios reflecting problematic deviations in implementation, the number of arrests accumulated by treatment participants begins to increase. This indicates that these implementation challenges have a negative impact on program effects and that we can go some way toward predicting what might occur in implementation as they emerge and interact. |
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| ISSN: | 1745-9133 |
| DOI: | 10.1111/1745-9133.12286 |