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Using Collaborative Model Building to Better Understand the Mechanisms of Alcohol-Involved Sexual Violence on College
Michelle Dougherty1, Jessica G Burke1, Joseph Alejandro1
1Department of Behavioral and Community Health Sciences, School of Public Health, University of Pittsburgh, 130 DeSoto St, Pittsburgh, PA, 15261, United States, 1 412-624-3613.
Background:
The Collaborative Model Building Project to Understand Sexual Violence (CAMPUS) study seeks to address alcohol-involved sexual violence (AISV) by collaboratively developing an agent-based model (ABM) that can support the decisions of college campuses seeking to address this issue among students. As a first step toward ABM development, we used collaborative model building (CMB), an adaptation of group model building, to co-develop a causal loop diagram (CLD) depicting key causes and effects of AISV and opportunities for intervention. Our goal of cocreating a CLD that can be translated into an ABM to support intervention decision-making differentiates our approach from other participatory systems science studies.
Objective:
This paper provides a detailed, transferable post hoc protocol for using CMB to cocreate a CLD of AISV on college campuses that can be translated into an ABM to support intervention decision-making.
Methods:
Our approach consisted of 4 iterative phases that involved ongoing weekly discussion by the project's core modeling team (CMT), consisting of researchers with systems science and subject matter expertise. In the first phase, we conducted 4 CMB sessions with 3 groups of college campus collaborators to develop 1 preliminary CLD each. Second, our CMT reviewed each variable and causal connection across the CLDs in consultation with peer-reviewed literature to help ensure eventual ABM translation. Third, the CMT combined 3 CLDs into one, identifying specific loops for review by collaborators. Fourth, we conducted a feedback session with collaborators and created a finalized CLD linked with intervention opportunities.
Results:
Between January 2023 and March 2025, we engaged with 39 collaborators in Allegheny County, Pennsylvania, across three groups: (1) college campus practitioners (eg, student life staff; n=8), (2) undergraduate students (n=12), and (3) a mix of practitioners and students (n=19). The final output of our process was a complete CLD with 26 loops containing 28 variables showing key AISV mechanisms and intervention opportunities. Analysis of results from the CAMPUS study, funded from September 2022 to June 2027, is ongoing, and results from aim 1 of the study are expected to be published in late 2026.
Conclusions:
Given our goal of using the finalized CLD for ABM development, our approach emphasized the selection of potentially measurable and modifiable variables and causal connections. Compared with other participatory systems science approaches, our approach also emphasized intervention identification and prioritization.
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