Browsing by Author "McKee, Kevin L."
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- County-level social distancing and policy impact in the United States: A dynamical systems modelMcKee, Kevin L.; Crandell, Ian C.; Hanlon, Alexandra L. (JMIR Publications, 2020-10-01)Background: Social distancing and public policy have been crucial for minimizing the spread of SARS-CoV-2 in the United States. Publicly available, county-level time series data on mobility are derived from individual devices with global positioning systems, providing a variety of indices of social distancing behavior per day. Such indices allow a fine-grained approach to modeling public behavior during the pandemic. Previous studies of social distancing and policy have not accounted for the occurrence of pre-policy social distancing and other dynamics reflected in the long-term trajectories of public mobility data. Objective: We propose a differential equation state-space model of county-level social distancing that accounts for distancing behavior leading up to the first official policies, equilibrium dynamics reflected in the long-term trajectories of mobility, and the specific impacts of four kinds of policy. The model is fit to each US county individually, producing a nationwide data set of novel estimated mobility indices. Methods: A differential equation model was fit to three indicators of mobility for each of 3054 counties, with T=100 occasions per county of the following: distance traveled, visitations to key sites, and the log number of interpersonal encounters. The indicators were highly correlated and assumed to share common underlying latent trajectory, dynamics, and responses to policy. Maximum likelihood estimation with the Kalman-Bucy filter was used to estimate the model parameters. Bivariate distributional plots and descriptive statistics were used to examine the resulting county-level parameter estimates. The association of chronology with policy impact was also considered. Results: Mobility dynamics show moderate correlations with two census covariates: population density (Spearman r ranging from 0.11 to 0.31) and median household income (Spearman r ranging from -0.03 to 0.39). Stay-at-home order effects were negatively correlated with both (r=-0.37 and r=-0.38, respectively), while the effects of the ban on all gatherings were positively correlated with both (r=0.51, r=0.39). Chronological ordering of policies was a moderate to strong determinant of their effect per county (Spearman r ranging from -0.12 to -0.56), with earlier policies accounting for most of the change in mobility, and later policies having little or no additional effect. Conclusions: Chronological ordering, population density, and median household income were all associated with policy impact. The stay-at-home order and the ban on gatherings had the largest impacts on mobility on average. The model is implemented in a graphical online app for exploring county-level statistics and running counterfactual simulations. Future studies can incorporate the model-derived indices of social distancing and policy impacts as important social determinants of COVID-19 health outcomes.
- Dissociation and other trauma symptomatology are linked to imbalance in the competing neurobehavioral decision systemsBasso, Julia C.; Satyal, Medha K.; McKee, Kevin L.; Lynn, Sarah; Gyamfi, Daphne; Bickel, Warren K. (Frontiers Media, 2024-01-31)Objective: Dissociation is a conscious state characterized by alterations in sensation and perception and is thought to arise from traumatic life experiences. Previous research has demonstrated that individuals with high levels of dissociation show impairments in cognitive-emotional processes. Therefore, using the Competing Neurobehavioral Decisions System (CNDS) theory, we used statistical modeling to examine whether dissociative experience and trauma symptoms are independently predicted by impulsivity, risk-seeking, affective state (i.e., anxiety, depression, stress, and negative affect), and trauma history. Method: In this cross-sectional study design, data were collected via Amazon Mechanical Turk from a total of n = 557 English-speaking participants in the United States. Using Qualtrics, participants answered a series of self-reported questionnaires and completed several neurocognitive tasks. Three independent multiple linear regression models were conducted to assess whether impulsivity, risk seeking, affective state, and trauma history predict depersonalization, trauma symptoms, and PTSD symptoms. Results: As hypothesized, we found that depersonalization and other trauma symptoms are associated with heightened impulsivity, increased risk-seeking, impaired affective states, and a history of traumatic experiences. Conclusion: We demonstrate that an imbalanced CNDS (i.e., hyperimpulsive/ hypoexecutive), as evidenced by decreased future valuation, increased risk seeking, and impaired affective states, predicts heightened depersonalization and other trauma and PTSD symptomatology. This is the first time that dissociation has been connected to delay discounting (i.e., the tendency to place more value on rewards received immediately compared to farther in the future). Interventions that positively impact areas of the CNDS, such as episodic future thinking or mindfulness meditation, may be a target to help decrease dissociative symptoms.