Project GRIP: An Illustration of Participatory Action Research with Communities of People Who Own and Use Firearms.

Firearm-related injury and mortality prevention strategies are often incompatible with and potentially ineffective for the very populations at risk. Such incompatibility is reflective of a cultural disconnect between investigators and prevention specialists and those who own and use firearms. The current paper describes Project GRIP, a research study that was guided by the principles of Participatory Action Research (PAR). We present the project as a case-example and demonstration of how PAR principles can inform an approach to partner with firearm owners in injury prevention research. Though PAR is a general approach and not a set of techniques, we describe the strategies we used in the hopes that they may be useful for investigators using PAR with firearm owners. We discuss the project and our approach across different stages of the process, including entering into PAR with firearm owners, building partnerships, developing a shared vision, mutual understanding, and co-learning, building and maintaining positive relationships, and executing the project tasks. The PAR approach and the intentional emphasis on partnership is, in our opinion, vital to ensuring that the perspectives of firearm owners are incorporated into the research literature so that more ecologically valid and potentially effective injury and mortality prevention strategies can be developed and disseminated.

Mixed methods evaluation of a jail diversion program: Impact on arrests and functioning.

This mixed methods study had two aims: (1) to examine the effectiveness of a jail diversion program in reducing recidivism and promoting educational and employment outcomes; and (2) to qualitatively explore mechanisms through which the program was effective. Participants were 17 individuals arrested for drug offenses who participated in an intensive, law enforcement-based jail diversion program, and 17 individuals in a comparison group. Arrests were extracted from police records, and education and employment were extracted from program data. Four intervention participants completed qualitative interviews. Arrest rates in the intervention group decreased significantly postintervention, and arrest rates in the intervention group were numerically lower than those in the comparison group. Participants experienced significant increases in employment and driver's license status. Participants also identified mechanisms through which the program was effective. This jail diversion program shows promise in reducing recidivism and promoting adaptive functioning. Jail diversion programs that include mentorship, peer support, and removal of barriers to success may be particularly effective.

Experimental evidence that rill-bed morphology is governed by emergent nonlinear spatial dynamics.

Past experimental work found that rill erosion occurs mainly during rill formation in response to feedback between rill-flow hydraulics and rill-bed roughness, and that this feedback mechanism shapes rill beds into a succession of step-pool units that self-regulates sediment transport capacity of established rills. The search for clear regularities in the spatial distribution of step-pool units has been stymied by experimental rill-bed profiles exhibiting irregular fluctuating patterns of qualitative behavior. We hypothesized that the succession of step-pool units is governed by nonlinear-deterministic dynamics, which would explain observed irregular fluctuations. We tested this hypothesis with nonlinear time series analysis to reverse-engineer (reconstruct) state-space dynamics from fifteen experimental rill-bed profiles analyzed in previous work. Our results support this hypothesis for rill-bed profiles generated both in a controlled lab (flume) setting and in an in-situ hillside setting. The results provide experimental evidence that rill morphology is shaped endogenously by internal nonlinear hydrologic and soil processes rather than stochastically forced; and set a benchmark guiding specification and testing of new theoretical framings of rill-bed roughness in soil-erosion modeling. Finally, we applied echo state neural network machine learning to simulate reconstructed rill-bed dynamics so that morphological development could be forecasted out-of-sample.