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"original_study": {
"claim": {
"hypothesis": "The interaction between cultural tightness and government efficiency will be negative in its association with the COVID-19 infection rate.",
"hypothesis_location": "p. 3, second paragraph",
"statement": "Nations with efficient governments and tight cultures have been most effective at limiting COVID-19’s infection rate and mortality likelihood (a significant interaction between tightness and efficiency, b = -.17, SE = .07, t(41) = -2.23, p = .031).",
"statement_location": "p. 7, first paragraph",
"study_type": "Observational"
},
"data": {
"source": "COVID-19: European Center for Disease Control; government efficiency: the World Bank’s Government Efficiency Index; cultural tightness: index from Gelfand, M. J., Raver, J. L., Nishii, L., Leslie, L. M., Lun, J., Lim, B. C., ... & Aycan, Z. (2011). Differences between tight and loose cultures: A 33-nation study. science, 332(6033), 1100-1104; economic development: GDP per capita retrieved from the International Monetary Fund; inequality: nations’ Gini coefficients retrieved from the World Bank; median ages: CIA World Factbook.",
"wave_or_subset": "World Bank: 2017(for government efficiency), and unspecified for inequality (the authors mention most recent release for each nation); Covid: 2020; International Monetary Fund: 2019; CIA World Factbook: 2018",
"sample_size": "141",
"unit_of_analysis": "nation",
"access_details": "all the data is available on the OSF (https://osf.io/pc4ef/); it is not certain if the original data collected by the authors is open access or not but no restrictions are mentioned.",
"notes": "The authors downloaded data on cases per million citizens, and indexed death rate through the number of mortalities divided by the number of total cases. According to the government efficiency metric, efficient governments score highly on 5 dimensions: they are efficient in spending public revenue, they do not place strong compliance burdens on the private sector, they are able to efficiently settle legal and judicial disputes in the private sector, they are receptive to challenges from the private sector, and they offer transparent information about changes in government policies and regulations affecting private sector 5 activities. The mortality likelihood was measured through the number of deaths from COVID-19 divided by the number of COVID-19 cases in a nation. Economic development was indexed through GDP per capita, Inequality was indexed through the nations’ Gini coefficients."
},
"method": {
"description": "The authors tested the hypothesis that nations with efficient governments and tight cultures have been most effective at limiting COVID-19’s infection rate and mortality likelihood.",
"steps": "1. Retrieve and filter the virus data to focus on the period after each nation surpassed 1 case per million people. \n2. Calculate the infection rate per million citizens for each day.\n3. Capture infection rate by fitting regression equations for each nation, log-transforming the outcome variable (cases per million people) and the predictor variable (days) to account for the exponential growth rate of the virus.\n4. Get government efficiency and cultural tightness data.\n5. Combine nation-level growth rate estimates with government efficiency and cultural tightness scores.\n6. Add and standardize control variables.\n7. Examine the distribution of the rate of cases and mortality likelihood before fitting the models like the authors did. They discovered that the growth rate of cases was normally distributed, but the mortality likelihood was highly skewed. If the distribution is similar, proceed to steps 8 and 9. If not, choose a model that better fits the data’s distributional characteristics.\n8. Conduct weighted ordinary least squares regression predicting log-transformed COVID-19 infection rate per million, including both main effects of cultural tightness and government efficiency and their interaction.\n9. Weight each nation’s observation by the number of days of data available to account for reliability.",
"models": "ordinary least squares regression",
"outcome_variable": "COVID-19 infection rate",
"independent_variables": "government efficiency, cultural tightness",
"control_variables": "economic development, inequality, median age",
"tools_software": "not stated"
},
"results": {
"summary": "The authors tested the interaction of cultural tightness and government efficiency on growth rates of COVID-19 and found a significant interaction betweentightness and efficiency, b = -.17, SE = .07, t(41) = -2.23, p = .031.",
"numerical_results": [
{
"outcome_name": "NA",
"value": "-0.17",
"unit": "NA",
"effect_size": "not stated",
"confidence_interval": {
"lower": "not stated",
"upper": "not stated",
"level": "not stated"
},
"p_value": "0.31",
"statistical_significance": "true",
"direction": "negative."
},
{
"outcome_name": "t-statistic",
"value": "-2.23",
"unit": "NA",
"effect_size": "not stated",
"confidence_interval": {
"lower": "not stated",
"upper": "not stated",
"level": "not stated"
},
"p_value": "NA",
"statistical_significance": "NA",
"direction": "NA"
}
]
},
"metadata": {
"original_paper_id": "not stated",
"original_paper_title": "Cultural and Institutional Factors Predicting the Infection Rate and Mortality Likelihood of the COVID-19 Pandemic.",
"original_paper_code": "https://osf.io/pc4ef/",
"original_paper_data": "https://osf.io/pc4ef/"
}
}
}
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