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1.
Proc Natl Acad Sci U S A ; 116(22): 10723-10728, 2019 05 28.
Article in English | MEDLINE | ID: mdl-31072934

ABSTRACT

Randomized experiments have enormous potential to improve human welfare in many domains, including healthcare, education, finance, and public policy. However, such "A/B tests" are often criticized on ethical grounds even as similar, untested interventions are implemented without objection. We find robust evidence across 16 studies of 5,873 participants from three diverse populations spanning nine domains-from healthcare to autonomous vehicle design to poverty reduction-that people frequently rate A/B tests designed to establish the comparative effectiveness of two policies or treatments as inappropriate even when universally implementing either A or B, untested, is seen as appropriate. This "A/B effect" is as strong among those with higher educational attainment and science literacy and among relevant professionals. It persists even when there is no reason to prefer A to B and even when recipients are treated unequally and randomly in all conditions (A, B, and A/B). Several remaining explanations for the effect-a belief that consent is required to impose a policy on half of a population but not on the entire population; an aversion to controlled but not to uncontrolled experiments; and a proxy form of the illusion of knowledge (according to which randomized evaluations are unnecessary because experts already do or should know "what works")-appear to contribute to the effect, but none dominates or fully accounts for it. We conclude that rigorously evaluating policies or treatments via pragmatic randomized trials may provoke greater objection than simply implementing those same policies or treatments untested.


Subject(s)
Ethics, Research , Pragmatic Clinical Trials as Topic , Randomized Controlled Trials as Topic , Humans , Pragmatic Clinical Trials as Topic/ethics , Pragmatic Clinical Trials as Topic/legislation & jurisprudence , Randomized Controlled Trials as Topic/ethics , Randomized Controlled Trials as Topic/legislation & jurisprudence , Treatment Outcome
4.
Sci Rep ; 14(1): 23591, 2024 10 10.
Article in English | MEDLINE | ID: mdl-39390039

ABSTRACT

Early racial disparities in COVID-19 vaccination rates have been attributed primarily to personal vaccine attitudes and behavior. Little attention has been paid to the possibility that inequitable vaccine distribution may have contributed to racial disparities in vaccine uptake when supplies were most scarce. We test the hypothesis that scarce vaccines were distributed inequitably using the shipping addresses of 385,930 COVID-19 vaccine doses distributed in the first 17 weeks of Pennsylvania's Phase 1 rollout (December 14, 2020 through April 12, 2021). All shipments we analyze were allocated via the Federal Retail Pharmacy Program, a public-private partnership coordinated by the Centers for Disease Control and Prevention.Overall, White people had an average of 81.4% more retail pharmacy program doses shipped to their neighborhoods than did Black people. Regression models reveal that weekly vaccine allocations determined by pharmacy chains-rather than initial shipment and administration site decisions requiring state and federal approval-drove these effects. All findings remained consistent after controlling for neighborhood differences in income, population density, insurance coverage, number of pharmacies, and other social determinants of health.Our findings suggest that the private distribution of scarce public resources should be assessed for racial impact, regulated as public resources, and monitored continuously.


Subject(s)
COVID-19 Vaccines , COVID-19 , Humans , Pennsylvania , COVID-19/prevention & control , COVID-19/epidemiology , COVID-19 Vaccines/supply & distribution , COVID-19 Vaccines/administration & dosage , Pharmacies/statistics & numerical data , Residence Characteristics , Healthcare Disparities , SARS-CoV-2 , White People/statistics & numerical data , Black or African American/statistics & numerical data , Vaccination/statistics & numerical data
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