Assessing Model-Based Reasoning using Evidence- Centered Design

Abstract

Context: The growing shortage of organs has reached unprecedentedlevels. Despite national attempts to increase donation and federal lawsmandating the equitable allocation of organs, their availability andwaiting times vary significantly nationwide. Organ donor designation isa collective action problem in public health, in which the regionalorgan supply and average waiting times are determined by the willingnessof individuals to be listed as organ donors. Social capital increasesthe probability of collective action by fostering norms of reciprocityand cooperation while increasing costs to defectors. We examine whethersocial capital and other community-level factors explain geographicvariation in organ donor designation rates in Massachusetts.MethodsWe obtained a sample of 3,281,532 registered drivers in 2010 fromthe Massachusetts Department of Transportation Registry of MotorVehicles (MassDOT RMV). We then geocoded the registry data, matched themto 4,466 census blocks, and linked them to the 2010 US Census, theAmerican Community Survey (ACS), and other sources to obtaincommunity-level sociodemographic, social capital (residentialsegregation, voter registration and participation, residential mobility,violent-death rate), and religious characteristics. We used spatialmodeling, including lagged variables to account for the effect ofadjacent block groups, and multivariate regression analysis to examinethe relationship of social capital and community-level characteristicswith organ donor designation rates.FindingsBlock groups with higher levels of social capital, racialhomogeneity, income, workforce participation, owner-occupied housing,native-born residents, and white residents had higher rates of organdonor designation (p < 0.001). These factors remained significant in themultivariate model, which explained more than half the geographicvariance in organ donor designation (R-2 = 0.52).ConclusionsThe findings suggest that community-level factors, includingsocial capital, predict more than half the variation in donordesignation. Future interventions should target the community as theunit of intervention and should tailor messaging for areas with lowsocial capital.