How do the public interpret COVID-19 swab test results? Comparing the impact of official information about results and reliability used in the UK, US and New Zealand: a randomised, controlled trial

Objectives: To assess the effects of different official information on public interpretation of a personal COVID-19 PCR (9swab9) test result. Design: A 5x2 factorial, randomised, between-subjects experiment, comparing four wordings of information about the test result and a control arm of no additional information; for both positive and negative test results. Setting: Online experiment using recruitment platform Respondi. Participants: UK participants (n=1,744, after a pilot of n=1,657) collected by quota sampling to be proportional to the UK national population on age and sex. Interventions: Participants were given a hypothetical COVID-19 swab test result for 9John9 who was presented as having a 50% chance of having COVID-19 based on symptoms alone. Participants were randomised to receive either a positive or negative result for 9John9, then randomised again to receive either no more information, or text information on the interpretation of COVID-19 test results copied from the public websites of the UK9s National Health Service, the US9s Centers for Disease Control, New Zealand9s Ministry of Health, or a modified version of the UK9s wording incorporating uncertainty. Information identifying the source of the wording was removed. Main outcome measures: Participants were asked "What is your best guess as to the percent chance that John actually had COVID-19 at the time of his test, given his result?"; questions about their feelings of trustworthiness in the result, their perceptions of the quality of the underlying evidence, and what action they felt 9John9 should take in the light of his result. Results: Of those presented with a positive COVID-19 test result for 9John9, the mean estimate of the probability that he had the virus was 73%; for those presented with a negative result, 38%. There was no main effect of information (wording) on these means. However, those participants given the official information on the UK website, which did not mention any uncertainty around the test result, were significantly more likely to give a categorical (100% or 0%) answer (for positive result, p < .001; negative, p = .006). When asked how much they agreed that 9John9 should self-isolate, those who were told his test was positive agreed to a greater extent (mean 86 on a 0-100 scale), but many of those who were told he had a negative result still agreed (mean 51). There was also an interaction between wording and test result (p < 0.001), with those seeing the New Zealand wording about the uncertainties of the test result significantly more likely to agree that he should continue to self-isolate after a negative test than those who saw the UK wording (p = .01), the experimental wording (p = .02) or no wording at all (p = .003). Participants rated positive test results more trustworthy and higher quality of evidence than negative results. Conclusions: The UK public perceive positive test results for COVID-19 as more reliable and trustworthy than negative results without being given any information about the reliability of the tests. When additionally given the UK9s current official wording about the interpretation of the test results, people became more likely to interpret the results as definitive. The public9s assessment of the face value of both the positive and negative test results was generally conservative. The proportion of participants who felt that a symptomatic individual who tests negative definitely should not self-isolate was highest among those reading the UK wording (17.4%) and lowest among those reading the New Zealand wording (3.8%) and US wording (5.1%). Pre-registration and data repository: pre-registration of pilot at osf.io/8n62f, pre-registration of main experiment at osf.io/7rcj4, data and code in https://osf.io/pvhba/.