Cited by 248Risk Perception and ManagementPatient-Provider Communication in HealthcareClimate Change Communication and Perception

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Risk and Uncertainty Communication

Spiegelhalter, David·2017·Annual Review of Statistics and Its Application

DOI 10.1146/annurev-statistics-010814-020148

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Abstract

This review briefly examines the vast range of techniques used to communicate risk assessments arising from statistical analysis. After discussing essential psychological and sociological issues, I focus on individual health risks and relevant research on communicating numbers, verbal expressions, graphics, and conveying deeper uncertainty. I then consider practice in a selection of diverse case studies, including gambling, the benefits and risks of pharmaceuticals, weather forecasting, natural hazards, climate change, environmental exposures, security and intelligence, industrial reliability, and catastrophic national and global risks. There are some tentative final conclusions, but the primary message is to acknowledge expert guidance, be clear about objectives, and work closely with intended audiences.

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“In addition to the single probability distribution PGoG handles, the taxonomies cover more complex data structures and semantics, such as the epistemic v.s. aleatory distinction [48] and errors [52].”
Background
Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates
Ley, D., Bhatt, U., & Weller, A. (2021) · AAAI Conference on Artificial Intelligence · doi:10.48550/arxiv.2112.02646 · Cited by 27
“As these systems are deployed in high stakes settings, well-calibrated uncertainty estimates are in high demand (Spiegelhalter 2017).”
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Communicating tailored risk information of cancer treatment side effects: Only words or also numbers?
Vromans, R., Pauws, S. C., Bol, N., van de Poll-Franse, L. V., & Krahmer, E. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01296-7 · Cited by 25
Economics for an uncertain world
Demartino, G. F., Grabel, I., & Scoones, I. (2024) · World Development · doi:10.1016/j.worlddev.2023.106426 · Cited by 24
Reflections on 50 years of MCDM: Issues and future research needs
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Development of a checklist for people communicating evidence-based information about the effects of healthcare interventions: a mixed methods study
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“Risk and uncertainty communication 53 Explores the major issues in communicating risk assessments arising from statistical analysis and concludes with a set of recommendations.”
Vitruvian plot: a visualisation tool for multiple outcomes in network meta-analysis
Ostinelli, E., Efthimiou, O., Naci, H., Furukawa, T., Leucht, S., Salanti, G., Wainwright, L., Zangani, C., Crescenzo, F. D., Smith, K. A., et al. (2022) · Evidence-Based Mental Health · doi:10.1136/ebmental-2022-300457 · Cited by 23
Winners and losers: communicating the potential impacts of policies
Brick, C., Freeman, A. L. J., Wooding, S., Skylark, W. J., Marteau, T. M., & Spiegelhalter, D. J. (2018) · Humanities and Social Sciences Communications · doi:10.1057/s41599-018-0121-9 · Cited by 30
“For individual decisions about personal health or finances, much is known about how to present potential harms and benefits to effectively inform rather than persuade (e.g., Fischhoff et al., 2011; Spiegelhalter, 2017).”
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Effective sample size: A measure of individual uncertainty in predictions
Thomassen, D., le Cessie, S., van Houwelingen, H. V., & Steyerberg, E. (2023) · Statistics in Medicine · doi:10.1002/sim.10018 · Cited by 22
“It has also been suggested to communicate numbers only when they are estimated with sufficient certainty [8].”
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Black Swan Events and Intelligent Automation for Routine Safety Surveillance
Kjoersvik, O., & Bate, A. (2022) · Drug Safety · doi:10.1007/s40264-022-01169-0 · Cited by 24
“Humans are often irrational when considering risk and probabilities [18].”
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Fish harvesting advice under climate change: A risk-equivalent empirical approach
Duplisea, D., Roux, M., Hunter, K., & Rice, J. (2020) · bioRxiv · doi:10.1371/journal.pone.0239503 · Cited by 22
Impfbereitschaft mit einem COVID-19-Vakzin und Einflussfaktoren. Ergebnisse einer telefonischen Bevölkerungsbefragung
Haug, S., Schnell, R., & Weber, K. (2021) · Das Gesundheitswesen · doi:10.1055/a-1538-6069 · Cited by 21
“Um Wahrschein-lichkeiten unter 1 % zu veranschaulichen bieten sich sogenannte „Icon Arrays“ als einfache, verständliche, grafische Darstellungen an [25, 26].”
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Evaluating hazard awareness brochures: Assessing the textual, graphical, and numerical features of tsunami evacuation products
Lindell, M., Bostrom, A., Goltz, J., & Prater, C. S. (2021) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2021.102361 · Cited by 21
Review of potential areas for global harmonisation of risk assessment protocols for Food Contact Materials (FCMs)
Cristina, N., Alan, R., Kanungo, D., Sarah, D., Thomas, G., Christian, K., Bastian, K., Konrad, J., Charlene, L., Olivier, V., et al. (2025) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2025.104987 · Cited by 20
How do women who are informed that they are at increased risk of breast cancer appraise their risk? A systematic review of qualitative research
Woof, V. G., Howell, A., McWilliams, L., Evans, D., & French, D. (2022) · British Journal of Cancer · doi:10.1038/s41416-022-01944-x · Cited by 20
“Numerical risk information and the use of risk communication strategies produce little effect in comparison to the impact that personal experiences and affective responses can have on subjective risk appraisals [8].”
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Communicating Probability Information in Weather Forecasts: Findings and Recommendations from a Living Systematic Review of the Research Literature
Ripberger, J., Bell, A., Fox, A., Forney, A., Livingston, W., Gaddie, C., Silva, C. L., & JENKINS-SMITHa, H. (2022) · Weather, Climate, and Society · doi:10.1175/wcas-d-21-0034.1 · Cited by 20
Anticipatory Ethics and the Role of UncertaintyPreprint
Nanayakkara, P., Diakopoulos, N., & Hullman, J. (2020) · arXiv.org · doi:10.48550/arxiv.2011.13170 · Cited by 20
“Ontological uncertainty is the most philosophical in nature, describing “uncertainty about the entire modeling process as a description of reality” [25].”
Confronting verbalized uncertainty: Understanding how LLM's verbalized uncertainty influences users in AI-assisted decision-making
Xu, Z., Song, T., & Lee, Y.-C. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103455 · Cited by 18
Where does scientific uncertainty come from, and from whom? Mapping perspectives of natural hazards science advice
Doyle, E., Thompson, J., Hill, S., Williams, M., Paton, D., Harrison, S., Bostrom, A., & Becker, J. (2023) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2023.103948 · Cited by 18
Learning Personalized Decision Support Policies
Bhatt, U., Chen, V., Collins, K. M., Kamalaruban, P., Kallina, E., Weller, A., & Talwalkar, A. (2023) · AAAI Conference on Artificial Intelligence · doi:10.48550/arxiv.2304.06701 · Cited by 18
Agent-based modelling for Urban Analytics: State of the art and challenges
Malleson, N., Birkin, M., Birks, D., Ge, J.-Q., Heppenstall, A., Manley, E., McCulloch, J., & Ternes, P. (2022) · AI Communications · doi:10.3233/aic-220114 · Cited by 18
“Predictions are often highly uncertain and it is crucial that these uncertainties are communicated properly [75,84], but this uncertainty in outcomes can be challenging for practitioners.”
Estimating everyday risk: Subjective judgments are related to objective risk, mapping of numerical magnitudes and previous experience
Keage, H., & Loetscher, T. (2018) · PLoS ONE · doi:10.1371/journal.pone.0207356 · Cited by 18
What is the quality of drug safety information for patients: An analysis of REMS educational materials
Chan, H. W., Russell, A. M., & Smith, M. Y. (2018) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.4614 · Cited by 18
Interplay between physical activity volume and intensity with modeled life expectancy in women and men: A prospective cohort analysis
Zaccardi, F., Rowlands, A. V., Dempsey, P. C., Razieh, C., Henson, J. J., Goldney, J., Maylor, B. D., Bhattacharjee, A., Chudasama, Y., Edwardson, C. L., et al. (2024) · Journal of sport and health science/Journal of Sport and Health Science · doi:10.1016/j.jshs.2024.100970 · Cited by 24
“16,17 A previous analysis investigated the association of self-reported MVPA and objectively measured total PA with life expectancy, showing high vs. low categories of PA were associated with a 3 (cid:1) 5 year difference in life expectancy at 45 years of age.”
Socioeconomic position at the age of 30 and the later risk of a mental disorder: a nationwide population-based register study
Hakulinen, C. A., Komulainen, K., Suokas, K., Pirkola, S. P., Pulkki-Råbäck, L., Lumme, S., Elovainio, M. J., & Böckerman, P. (2023) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2022-219674 · Cited by 45
A comparative analysis of experienced uncertainties in relation to risk communication during COVID19: a four-country study
Cristea, F., Weishaar, H., Geurts, B., Delamou, A., Tan, M., Legido-Quigley, H., Aminu, K., Marí-Saéz, A., Rocha, C., Camara, B., et al. (2022) · Globalization and Health · doi:10.1186/s12992-022-00857-x · Cited by 17
“Previous examples include epistemic uncertainty (about facts, numbers, and science) [20] or aleatory uncertainty (inevitable unpredictability of the future due to unforeseeable factors, commonly used in statistical modeling of risk) [21].”
Background
Antenatal counselling for prospective parents whose fetus has a neurological anomaly: part 1, experiences and recommendations for service design
Hart, A., Vollmer, B., Howe, D., Boxall, S., Foulds, N., de Lacy, P., Vasudevan, C., Griffiths, P., & Piercy, H. (2021) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.15022 · Cited by 17
“001 1/100 000 Spiegelhalter et al.(33) Probability intervals and terminology used by the inter-governmental panel for climate change Virtually certain 99–100 Extremely likely 95–100 Very likely 90–100 Likely 66–100 More likely than not 50–100 About as likely as not 33–66 Unlikely 0–33 Very unlikely 0–10 Exceptionally…”
BackgroundInfluential
Multiple Hazard Uncertainty Visualization Challenges and Paths Forward
Padilla, L. M. K., Dryhurst, S., Hosseinpour, H., & Kruczkiewicz, A. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.579207 · Cited by 17
Effects of communicating uncertainty descriptions in hazard identification, risk characterization, and risk protection
Wiedemann, P., Boerner, F., & Freudenstein, F. (2021) · PLoS ONE · doi:10.1371/journal.pone.0253762 · Cited by 17
Probability Size Matters: The Effect of Foreground‐Only versus Foreground+Background Graphs on Risk Aversion Diminishes with Larger Probabilities
Okan, Y., Stone, E. R., Parillo, J., de Bruin, W. B., & Parker, A. M. (2020) · Risk Analysis · doi:10.1111/risa.13431 · Cited by 17
“The question of how best to communicate risk has received a lot of attention (Spiegelhalter, 2017; Trevena et al., 2013; Zipkin et al., 2014).”
Background
Enhancing central bank communications with behavioural insightsPreprint
Bholat, D., Broughton, N., Parker, A., Termeer, J., & Walczak, E. J. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3233695 · Cited by 17
“…have found that making information relevant to individual circumstances can increase engagement (Garner 2005; Behavioural Insights Team 2012), and that expressing financial costs in pound values instead of percentages can improve comprehension (Gigerenzer and Edwards 2003; Spiegelhalter 2017).”
A review of uncertainty visualization errors: Working memory as an explanatory theory
Padilla, L. M. K., Castro, S., & Hosseinpour, H. (2021) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/bs.plm.2021.03.001 · Cited by 17
Risk Assessment of Chemical Mixtures in Foods: A Comprehensive Methodological and Regulatory Review
Combarros, R. G., García, M. G., Blanco-Díaz, G. D., Bravo, K. S., Moya, J. L. R., & López-Sánchez, J. I. (2026) · Foods · doi:10.3390/foods15020244 · Cited by 15
“…clear narratives, contribution plots and intuitive analogies to explain mixture metrics and uncertainty while maintaining scientific accuracy, thereby supporting informed, transparent decision-making on the management of chemical “cocktails” in food and other exposure contexts [87,89,90,109].”
Influential
Psychological and behavioural considerations for integrating polygenic risk scores for disease into clinical practice
Sanderson, S. C., & Inouye, M. (2025) · Nature Human Behaviour · doi:10.1038/s41562-025-02200-x · Cited by 15
Redevelopment of the Predict: Breast Cancer website and recommendations for developing interfaces to support decision‐making
Farmer, G. D., Pearson, M., Skylark, W., Freeman, A., & Spiegelhalter, D. (2021) · Cancer Medicine · doi:10.1002/cam4.4072 · Cited by 15
“We also did not foresee that, although recommended in the risk communication literature, 13,28,29 icon arrays would be deemed to be distressingly morbid when human-shaped.”
BackgroundSelf-citation
Americans’ Views of Fusion Energy: Implications for Sustainable Public Support
Gupta, K., Jenkins-Smith, H., Ripberger, J., Silva, C. L., Fox, A., & Livingston, W. (2024) · Fusion science and technology · doi:10.1080/15361055.2024.2328457 · Cited by 14
“15] While nuclear fission continues to provide the largest share of clean energy for the U.S. grid, the enduring legacy of nuclear accidents and elevated risk perceptions have made it difficult to site nuclear facilities.”
Multiple models for outbreak decision support in the face of uncertainty
Shea, K., Borchering, R., Probert, W., Howerton, E., Bogich, T., Li, S.-L., van Panhuis, W. V., Viboud, C., Aguás, R., Belov, A., et al. (2023) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.2207537120 · Cited by 14
“The ensemble provided valuable risk quantification for decision making (20) since all models provided projections as probability distributions.”
Communication of Statistics and Evidence in Times of Crisis
Schneider, C., Kerr, J. R., Dryhurst, S., & Aston, J. (2023) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-040722-052011 · Cited by 14
“One clear way to avoid the effects of such framing is to provide the statistic from both sides (Gigerenzer, 2014; Spiegelhalter, 2017).”
BackgroundMethodInfluential
Communicating personalised risks from COVID-19: guidelines from an empirical studyPreprint
Freeman, A., Kerr, J. R., Recchia, G., Schneider, C., Lawrence, A. C. E., Finikarides, L., Luoni, G., Dryhurst, S., & Spiegelhalter, D. (2020) · medRxiv · doi:10.1101/2020.10.05.20206961 · Cited by 14
“Numbers on their own do not convey a perception of quantity – they need to be given context, particularly when the numbers are small [29].”
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Interpretable Machine Learning for Privacy-Preserving Pervasive Systems
Baron, B., & Musolesi, M. (2017) · IEEE pervasive computing · doi:10.1109/mprv.2019.2918540 · Cited by 14
“Indeed, risk itself is difficult to communicate (see for instance [18]).”
Background
Data-driven recommendations for enhancing real-time natural hazard warnings
Saunders, K., Forbes, O., Hopf, J. K., Patterson, C. R., Vollert, S. A., Brown, K., Browning, R., Canizares, M., Cottrell, R. S., Li, L., et al. (2025) · One Earth · doi:10.1016/j.oneear.2025.101274 · Cited by 16
Scenario design for infectious disease projections: Integrating concepts from decision analysis and experimental design
Runge, M. C., Shea, K., Howerton, E., Yan, K.-T., Hochheiser, H., Rosenstrom, E. T., Probert, W., Borchering, R., Marathe, M., Lewis, B., et al. (2024) · Epidemics · doi:10.1016/j.epidem.2024.100775 · Cited by 13
“Key challenges include communication of the nuances of scenario projections to lay audiences (as different from forecasts), and visualization of uncertainty (Kamal et al., 2021; Hullman et al., 2019; Hägele et al., 2022; Spiegelhalter, 2017).”
Verbal Descriptions of The Probability of Treatment Complications Lead to High Variability in Risk Perceptions: A Survey Study
Rosen, J., Agrawal, N., Flum, D., & Liao, J. M. (2021) · Annals of Surgery · doi:10.1097/sla.0000000000005255 · Cited by 13
Communicating personalized risks from COVID-19: guidelines from an empirical study
Freeman, A. L. J., Kerr, J. R., Recchia, G. L., Schneider, C. R., Lawrence, A. C. E., Finikarides, L., Luoni, G., Dryhurst, S., & Spiegelhalter, D. J. (2021) · Royal Society Open Science · doi:10.1098/rsos.201721 · Cited by 37
“Numbers on their own do not convey a perception of quantity—they need to be given context, particularly when the numbers are small [29].”
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Self-reported walking pace, polygenic risk scores and risk of coronary artery disease in UK biobank.
Zaccardi, F., Timmins, I., Goldney, J., Dudbridge, F., Dempsey, P., Davies, M., Khunti, K., & Yates, T. (2022) · NMCD. Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2022.08.021 · Cited by 12
Simple methods for improving the communication of uncertainty in species’ temporal trends
Pescott, O., Stroh, P. A., Humphrey, T., & Walker, K. (2022) · Ecological Indicators · doi:10.1016/j.ecolind.2022.109117 · Cited by 12
Reducing Kidney Discard With Artificial Intelligence Decision Support: the Need for a Transdisciplinary Systems Approach
Threlkeld, R., Ashiku, L., Canfield, C., Shank, D. B., Schnitzler, M., Lentine, K., Axelrod, D., Battineni, A. C. R., Randall, H., & Dagli, C. (2021) · Current Transplantation Reports · doi:10.1007/s40472-021-00351-0 · Cited by 12
Communicating Uncertainties About the Effects of Medical Interventions Using Different Display Formats
McDowell, M., & Kause, A. (2021) · Risk Analysis · doi:10.1111/risa.13739 · Cited by 12
“communicating uncertainty is that many of the techniques that have been developed have not been empirically tested or compared for communicating different types of uncertainty (Spiegelhalter, 2017; van der Bles et al., 2019).”
BackgroundMethodInfluential
'The AI is uncertain, so am I. What now?': Navigating Shortcomings of Uncertainty Representations in Human-AI Collaboration with Capability-focused Guidance
Schäfer, U., Sipos, L., & Müller-Birn, C. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757451 · Cited by 10
“") with a fixed denominator of 100 [28, 148, 164].”
Navigating scientific modelling and uncertainty: Insights from Hazard, Risk, and Impact Scientists in Disaster Risk Management (DRM)
Dhungana, A., Doyle, E. H., McDonald, G. W., & Prasanna, R. (2025) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2025.105260 · Cited by 11
Self-reported walking pace and 10-year cause-specific mortality: A UK biobank investigation
Goldney, J., Dempsey, P. C., Henson, J. J., Rowlands, A. V., Bhattacharjee, A., Chudasama, Y., Razieh, C., Laukkanen, J. A., Davies, M. J., Khunti, K., et al. (2023) · Progress in Cardiovascular Diseases · doi:10.1016/j.pcad.2023.09.003 · Cited by 13
Information and rational decision-making: explanations to patients and citizens about personal risk of COVID-19
McCartney, M., Sullivan, F., & Heneghan, C. (2020) · BMJ evidence-based medicine · doi:10.1136/bmjebm-2020-111541 · Cited by 11
Cognitive and Affective Processing of Risk Information: A Survey Experiment on Risk-Based Decision-Making Related to Crime and Public Safety
Berryessa, C. M., & Caplan, J. M. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.02222 · Cited by 13
“As individuals have their own perspectives on risk communication, risk information in relation to crime and public safety can often take on different forms (Spiegelhalter, 2017; Lundgren and McMakin, 2018).”
Background
Knowledge of potential harms and benefits of tamoxifen among women considering breast cancer preventive therapy
Thorneloe, R., Hall, L., Walter, F., Side, L., Lloyd, K., & Smith, S. (2019) · Cancer Prevention Research · doi:10.1158/1940-6207.capr-19-0424 · Cited by 11
“Although these aids frame numerical information using evidence-based approaches (31), they are lengthy documents that contain complex terminology.”
Trial of infographics in Northern Ireland (TINI): Preliminary evaluation and results of a randomized controlled trial comparing infographics with text
McCrorie, A., Chen, J.-W., Weller, R. R., McGlade, K., Donnelly, C., & Shiri, R. (2018) · Cogent Medicine · doi:10.1080/2331205x.2018.1483591 · Cited by 11
“Icon array was chosen as the infographic to test due to its ability to unambiguously represent part-to-whole relationships while also negating the effects of denominator neglect (Spiegelhalter, 2017; Spiegelhalter, Pearson, & Short, 2011).”
Dynamic calibration with approximate Bayesian computation for a microsimulation of disease spread
Asher, M., Lomax, N., Morrissey, K., Spooner, F., & Malleson, N. (2023) · Scientific Reports · doi:10.1038/s41598-023-35580-z · Cited by 10
Effects of flood hazard visualization format on house purchasing decisions
Dobson, B., Miles-Wilson, J., Gilchrist, I., Leslie, D. S., & Wagener, T. (2018) · Urban Water Journal · doi:10.1080/1573062x.2018.1537370 · Cited by 10
“Gestalt principles) that facilitate the perception and interpretation of visual scenes (e.g. Pinker 1990; Carpenter and Shah, 1998; Kelleher and Wagener 2011; Spiegelhalter 2017), but which have been largely overlooked or underused by risk communicators.”
Background
More Forecasts, More (Decision) Problems: How Uncertainty Representations for Multiple Forecasts Impact Decision Making
Sarma, A., Hedayati, M., & Kay, M. (2025) · International Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713725 · Cited by 9
“…is the quantifiable uncertainty arising due to statistical variability, 2 which we will refer to as probabilistic uncertainty ; the other is the “un-certainty about the modeling process as a description of reality” [57] which, following Ferson and Siegrist [12], we will refer to as incertitude .”
Modelling and mapping maize yields and making fertilizer recommendations with uncertain soil information
Takoutsing, B., Heuvelink, G., Aynekulu, E., & Shepherd, K. (2024) · Precision Agriculture · doi:10.1007/s11119-024-10200-6 · Cited by 9
“…in critical situations such as the COVID-19 pandemic (McCabe et al., 2021 ), it becomes evident that scientists often do not convey uncertainty through appropriate communication channels or present in a format easily digestible by farmers for integration into decision-making (Spiegelhalter, 2017 ).”

Authors: Spiegelhalter, D.
Affiliations: University of Cambridge (GB)
Corresponding author: Spiegelhalter, David
ORCID: Spiegelhalter, David
Venue: Annual Review of Statistics and Its Application
Publisher: Annual Reviews
Published: 2017-03-07
Volume: 4
Issue: 1
Pages: 31-60
ISSN: 2326-8298 (ISSN-L)
2326-831X
DOI: 10.1146/annurev-statistics-010814-020148
OpenAlex: W2529483981
Cited by: 248
References: 0
Citations by year: 2026: 33 · 2025: 35 · 2024: 32 · 2023: 31 · 2022: 31 · 2021: 29 · 2020: 26 · 2019: 15 · 2018: 16
FWCI: 4.77
Type: journal article
Language: en
Open access: closed
Locations: Annual Review of Statistics and Its Application (publishedVersion)
Topics: Social Sciences › Sociology and Political Science › Risk Perception and Management
Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
Social Sciences › Sociology and Political Science › Climate Change Communication and Perception
Keywords: risk communication, uncertainty communication, risk assessment, health risks, gambling, weather forecasting, natural hazards, climate change, environmental exposure, production reliability, catastrophic risk, expert guidance, audience understanding

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