Author: 0000-0002-7772-8492 - Octopus

Organisation	Role	Department	Start date	End date
University College London	Lecturer	Not specified	2023-07-01
University of Cambridge	Research Associate	Not specified	2018-10-01	2023-01-01

Title	DOI	Published date
The effects of communicating uncertainty around statistics, on public trust	10.1098/rsos.230604	2023-11
How People Understand Risk Matrices, and How Matrix Design Can Improve their Use: Findings from Randomized Controlled Studies	10.1111/risa.13822	2022-05
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
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
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

Method

Method to test the effects of different formats of communication of uncertainty around projected numbers of COVID-19 deaths, on a public audience

On 31st October 2020, the UK government announced a second national lockdown to mitigate the spread of COVID-19. See Figure 1 [1].Figure 1: A timeline of UK government responses to the Covid-19 pandemic between March 2020 and December 2021 (Courtesy of the Institute for Government).The briefing papers supplied by various expert groups to inform that policy decision...

Published April 6, 2024, by S. Dryhurst, A. Freeman

Rationale / Hypothesis

Theoretical rationale for investigating the effects of communicating uncertainty around future projections of the effects of COVID-19

Research in fields such as weather forecasting has shown that people tend to be accepting of aleatory uncertainty when projecting into the future [1–3], but there is no consensus on which formats best help communicate the uncertainties appropriately. Good communication of uncertainty gives the audience a sense of what experts think the chances are of a range of dif...

Published March 10, 2024, by S. Dryhurst, A. Freeman

Research Problem

How does communicating uncertainty affect people’s reaction to future projections of the effects of COVID-19 and their accuracy?

Communicating uncertainties around future projections

Published March 9, 2024, by A. Freeman, S. Dryhurst

Interpretation

Interpretation of an experiment to test the effects of different formats of communication of indirect uncertainty around the COVID-19 R number on a public audience

This experiment set out to investigate the effects of the communication of indirect uncertainty (the level of consensus between different estimates) in combination with direct uncertainty (the statistical range around a point estimate) in a pair of experiments within a single online survey. The first experiment presented people with a text form of the information (...

Published November 21, 2023, by A. Freeman, J. Kerr, S. Dryhurst

Results / Sources

Results of an experiment to test the effects of different formats of communication of indirect uncertainty around the COVID-19 R number on a public audience

This experiment was given ethical approval by the University of Cambridge’s Psychology Research Ethics Committee (PRE.2023.087)UK-based Participants were recruited via the platform Prolific.com using their ‘representative sample’ option to give a participant pool representative of the UK’s population on the basis of age (5 brackets), sex (2 groups) and ethnicity (5...

Published November 15, 2023, by A. Freeman, J. Kerr, S. Dryhurst

Method

Method to test the effects of different formats of communication of indirect uncertainty around the COVID-19 R number on a public audience

A method to test the effects of different verbal/numeric and graphical communications of uncertainty around the Covid-19 R number (pre-registration)

Published September 7, 2023, by S. Dryhurst, J. Kerr, A. Freeman

Rationale / Hypothesis

How might the format used to communicate uncertainty around the R value of COVID-19 affect audiences?

A review of what is known about the effects of communicating uncertainty around the R value of an epidemic, or similar numbers.

Published September 6, 2023, by S. Dryhurst, A. Freeman

Research Problem

How to communicate uncertainty around the R number of COVID-19?

‘R’ is a key figure communicated throughout the pandemic for decision-making, but is always uncertain. How is that uncertainty perceived when communicated?

Published September 4, 2023, by S. Dryhurst, A. Freeman, E. So

Research Problem

How to communicate uncertainty?

One of the greatest challenges in risk and evidence communication is how to communicate the inherent uncertainties in information and numbers. These uncertainties can be of many types, and there may be several different ways to communicate each. For example, inherent and unpredictable randomness or chance causes what is known as aleatory uncertainty. This kind of u...

Published September 4, 2023, by A. Freeman, S. Dryhurst, D. Spiegelhalter

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 / Sources

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, J. Kerr, S. Dryhurst, G. Recchia, C. Schneider

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 / Sources

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

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

Sarah Dryhurst

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