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"original_study": {
"claim": {
"hypothesis": "At the level of U.S.counties,support for Donald Trump in the 2016 presidential election will be negatively associated with social distancing behavior.",
"hypothesis_location": "The hypothesis is not stated explicitly in the text but the relationship is mentioned in the abstract, introduction and results sections.",
"statement": "An interquartile increase in support for Trump (I.Q.R. = 20.3%) resulted in a 4.1 percentage point decrease in social distancing (95% C.I. = 3.0–5.2) [ p < 0.001].",
"statement_location": "Page 4, Results section; page 7, Table 1.",
"study_type": "Observational"
},
"data": {
"source": "Unacast (for social distancing. Unacast measures county-level averages of distance traveled per person); American Community Survey (for socioeconomic status, operationalized by income per capita); MIT Election Data and Science Lab (political preferences, operationalized by the 2016 county-level vote share for President Trump); Census (for rurality).",
"wave_or_subset": "Unacast: March 19–28, 2020. American Community Survey: 5-year averages from 2014–2018. MIT Election Data and Science Lab: 2016 county-level vote share. Census: 2010.",
"sample_size": "3037",
"unit_of_analysis": "US counties.",
"access_details": "not stated; the authors thank Unacast for providing their social distancing dataset for research use, but no access details are provided.",
"notes": "There is a potential for omitted-variable and ecological biases due to aggregate, cross-sectional data. The data do not sample all cell-phone users and do not reflect non-users."
},
"method": {
"description": "The authors used multivariable OLS regression to assess how socioeconomic conditions and political orientation were associated with COVID social distancing.",
"steps": "1. Presumably the first step was to obtain the data from Unacast, American Community Survey, MIT Election Data and Science Lab, and Census. \n2. After cleaning and merging datasets, the authors had to calculate percentage point changes in average mobility.\n3. Then, they conducted bivariate analyses of per capita income and the share of voters supporting President Trump with social distancing (p. 4, Results section).\n4. Finally, they estimated associations between the degree of social distancing and socioeconomic\nand political factors using cross-sectional OLS regressions.",
"models": "cross-sectional ordinary least squares regressions",
"outcome_variable": "social distancing (measured as change in average mobility from March 19–28, relative to matched days of pre-COVID-19 reference week).",
"independent_variables": "income (county level per capita); vote share for Donald Trump (2016 elections, county level)",
"control_variables": "percentage male; percentage Black; percentage Hispanic; percentage with college degree; employment in retail; employment in transportation; employment in health, education, social services; percentage rural; age distribution (p. 3, Methods section).",
"tools_software": "not stated"
},
"results": {
"summary": "An interquartile increase in support for Trump (20.3%) was associated with a 4.1-percentage-point decrease in social distancing (95% CI = 3.0–5.2, p < 0.001).",
"numerical_results": [
{
"outcome_name": "social distancing",
"value": "4.12",
"unit": "percentage point",
"effect_size": "not stated",
"confidence_interval": {
"lower": "3.05",
"upper": "5.19",
"level": "0.95"
},
"p_value": "<0.001",
"statistical_significance": "true",
"direction": "positive"
}
]
},
"metadata": {
"original_paper_id": "https://doi.org/10.1101/2020.04.06.20055632",
"original_paper_title": "Association of County-Level Socioeconomic and Political Characteristics with Engagement in Social Distancing for COVID-19.",
"original_paper_code": "not stated",
"original_paper_data": "not stated"
}
}
}
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