Author: 0000-0002-6612-5186 - Octopus

Organisation	Role	Department	Start date	End date
University of Cambridge	Not specified	Not specified	2019

Organisation	Degree/title	Department	Start date	End date
Columbia University	PhD	Not specified		2018

Title	DOI	Published date
Social norms as a powerful lever for motivating pro-climate actions	10.1016/j.oneear.2023.03.014	2023-04
Transparent communication of evidence does not undermine public trust in evidence	10.1093/pnasnexus/pgac280	2022-11-01
COVID-19 risk perception and hoax beliefs in the US immediately before and after the announcement of President Trump's diagnosis	10.1098/rsos.212013	2022-08
The effects of communicating scientific uncertainty on trust and decision making in a public health context	10.1017/S1930297500008962	2022-07
Motivating prosocial behavior by leveraging positive self‐regard through values affirmation	10.1111/jasp.12841	2022-02
The effects of President Trump’s COVID-19 diagnosis on hoax beliefs and risk perceptions of the virus in the U.S.	10.31234/osf.io/frxt8	2021-12-01
The effects of quality of evidence communication on perception of public health information about COVID-19: Two randomised controlled trials	10.1371/journal.pone.0259048	2021-11-17
The effects of communicating uncertainty around statistics on public trust: an international study	10.1101/2021.09.27.21264202	2021-09-29
Correlates of intended COVID-19 vaccine acceptance across time and countries: results from a series of cross-sectional surveys	10.1136/bmjopen-2020-048025	2021-08
The Misinformation Susceptibility Test (MIST): A psychometrically validated measure of news veracity discernment	10.31234/osf.io/gk68h	2021-07-06
How do the UK public interpret COVID-19 test results? Comparing the impact of official information about results and reliability used in the UK, USA and New Zealand: a randomised controlled trial	10.1136/bmjopen-2020-047731	2021-05
The effects of quality of evidence communication on perception of public health information about COVID-19: two randomised controlled trials	10.1101/2021.04.07.21255010	2021-04-13
COVID-19 risk perception: a longitudinal analysis of its predictors and associations with health protective behaviours in the United Kingdom	10.1080/13669877.2021.1890637	2021-04-03
Communicating personalized risks from COVID-19: guidelines from an empirical study	10.1098/rsos.201721	2021-04
Predictors of COVID-19 vaccine acceptance across time and countries	10.1101/2020.12.09.20246439	2020-12-11
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	10.1101/2020.12.04.20243840	2020-12-04
Communicating personalised risks from COVID-19: guidelines from an empirical study	10.1101/2020.10.05.20206961	2020-10-06
Susceptibility to misinformation about COVID-19 around the world	10.1098/rsos.201199	2020-10
Risk perceptions of COVID-19 around the world	10.1080/13669877.2020.1758193	2020-08-02
The influence of anticipated pride and guilt on pro-environmental decision making	10.1371/journal.pone.0188781	2017-11-30

Interpretation

Interpretation: what the public already know, want to know and need to know, about their personal risks from COVID-19

This Interpretation is based on work published in: https://doi.org/10.1098/rsos.201721 The interviews and the survey responses combined help give us an overall view of the public’s information needs regarding their personal COVID-19 risk, as of July 2020.The majority of participants clearly showed a desire for quantitative information about COVID-19 (much of which...

Published May 31, 2023, by A. Freeman, J. Kerr, A. Lawrence, G. Recchia, C. Schneider, S. Dryhurst, L. Finikarides, G. Luoni

Results

Results of surveys: finding out what the public already know, want to know and need to know, about their personal risks from COVID-19

These Results are based on work published in: https://doi.org/10.1098/rsos.201721 This study was approved by the Psychological Research Ethics Committee at the University of Cambridge (PRE.2020.070).All stages of the study were carried out between the 3 June 2020 and 23 July 2020.The questions were split over four different surveys carried out with members of the p...

Published July 22, 2022, by A. Freeman, J. Kerr, G. Recchia, C. Schneider, S. Dryhurst

Interpretation

Interpretation of an analysis of the effects of different numerical formats on people’s perception of their risk of dying from COVID-19

This Interpretation is based on work published in: https://doi.org/10.1098/rsos.201721 The analysis of the data - from 2,500 members of the UK general public who were asked to rate how risky they felt five different numerical risk levels were (0.1%, 1%, 5%, 12%, 20%) when presented to them in a random order - confirms the collected findings of previous studies. The...

Published July 22, 2022, by A. Freeman, G. Recchia, S. Dryhurst, C. Schneider, J. Kerr

Method

Method for online surveys to find out what the public already know, want to know and need to know, about their personal risks from COVID-19

This Method is based on work published in: https://doi.org/10.1098/rsos.201721 A combination of in depth qualitative interviews and large-scale quantitative surveys are ideal for gaining insights into people’s understanding of a topic such as their risk from COVID-19, and their information needs.Quantitative surveys can give broad insights into opinions across a po...

Published July 21, 2022, by A. Freeman, C. Schneider, J. Kerr, G. Recchia, S. Dryhurst

Rationale / Hypothesis

Finding out what the public already know, and want to know, about their personal risks from COVID-19

This Hypothesis/Theoretical rationale is based on work published in: https://doi.org/10.1098/rsos.201721One method of approaching risk communication is the ‘mental models’ approach, whereby researchers use both qualitative and quantitative methods to build up an understanding of the audience’s intuitive model of causality in a situation, as well as the probabilitie...

Published July 21, 2022, by A. Freeman, J. Kerr, G. Recchia, S. Dryhurst, C. Schneider, A. Lawrence

Results

Results of testing the effects of different numerical formats on people’s perception of their risk of dying from COVID-19

These Results are based on work published in: https://doi.org/10.1098/rsos.201721The data from this experiment is available in the Open Science Framework repository: https://doi.org/10.17605/OSF.IO/AUF8H Survey 4.This study was approved by the Psychology Research Ethics Committee at the University of Cambridge (PRE.2020.070).The survey was carried out online, with...

Published July 21, 2022, by A. Freeman, J. Kerr, C. Schneider, G. Recchia, S. Dryhurst

Method

Testing the effects of different numerical formats on people’s perception of their risk of dying from COVID-19

This Method is based on work published in: https://doi.org/10.1098/rsos.201721This method was pre-registered before data was collected, at: https://doi.org/10.17605/OSF.IO/RDTC4 Participants will be asked to imagine they have received a personalised estimate of their risk of dying if infected with COVID-19. They will be asked ‘How would you classify that risk in yo...

Published July 21, 2022, by A. Freeman, C. Schneider, G. Recchia, J. Kerr

Research Problem

What information do the public need and want to know about their personal risk from COVID-19?

This Problem is based on work published in: https://doi.org/10.1098/rsos.201721Different communicators might have different aims when approaching the communication of personalized risk from COVID-19. Some may feel it important to encourage people to take mitigating actions, and hence to ensure that risks are perceived as relatively high to increase motivation [1,2]...

Published July 19, 2022, by A. Freeman, J. Kerr, G. Recchia, S. Dryhurst, A. Lawrence, C. Schneider

Research Problem

When presenting people with their personal risk from COVID-19, what format should they be shown the numbers in?

This Problem is based on work published in: https://doi.org/10.1098/rsos.201721Probabilistic information can be represented numerically in different ways, and research has shown that these different formats can affect the perception of likelihoods as well as affecting the ease with which people can make mental comparisons and manipulations of the information [1-5....

Published July 19, 2022, by A. Freeman, G. Recchia, S. Dryhurst, J. Kerr, C. Schneider

Claudia R Schneider

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