Abstract
BackgroundResearch on the impact of various types of stressors on refugee wellbeing may not readily inform those designing interventions about the supports that will be most helpful in particular settings. Composite variables used in psychosocial research that represent overarching types of stressors provide only vague information about intervention targets. Dynamic networks model individual phenomena separately (i.e., specific stressors and symptoms of distress) to inform how phenomena interact with each other in ways that may be useful for individuals planning interventions in humanitarian aid settings.MethodsUsing archival data from Darfur refugees, we used a dynamic networks approach to model relationships between locally-validated measures of traumatic events, displacement stressors, impairment, and distress.ResultsFindings aligned with previous research on the centrality of basic needs in refugee populations. Further, specific stressors were highlighted as particularly impactful for this population, and sleep and physical difficulties emerged as key aspects of distress and impairment, suggesting areas for targeted intervention. Conclusions: Dynamic network approaches may be fruitful for identifying setting-specific intervention targets and maximizing the impact of limited resources in humanitarian aid settings.
Highlights
Research on the impact of various types of stressors on refugee wellbeing may not readily inform those designing interventions about the supports that will be most helpful in particular settings
We propose that avoiding composite variables and treating stressors and symptoms as individual phenomena within dynamic networks may provide practitioners with a more practicable approach
Given the convergence of data and theory, it seems reasonable that addressing sleep problems might be an opportune target for intervention. All of these symptoms were part of the CCD hozun identified by Rasmussen et al [28], such network findings provide targets for intervention in ways that defining the set of symptoms cannot
Summary
Research on the impact of various types of stressors on refugee wellbeing may not readily inform those designing interventions about the supports that will be most helpful in particular settings. Dynamic networks model individual phenomena separately (i.e., specific stressors and symptoms of distress) to inform how phenomena interact with each other in ways that may be useful for individuals planning interventions in humanitarian aid settings. We propose that avoiding composite variables and treating stressors and symptoms as individual phenomena within dynamic networks may provide practitioners with a more practicable approach. This is consistent with criticisms that emphasize the futility of using composite variables to elucidate how individual phenomena interact with and have causal impacts on each other [32]
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