Method RiskStreet

Over-indebtedness, damaged luggage or accidents at work - how likely are these things going to happen to you during the next year?

Challenges in risk communication

Communicating uncertain and interdependent events to consumers

Why is it relevant to improve consumers' risk assessments?

The aim is for the consumer to be able to make (better) decisions. They need to know precise facts and figures - the so-called evidence - in order to weigh options against each other and better assess risks. This enables them to make informed decisions. In addition, the presentation of the known probabilities of occurrence helps the user not to underestimate or overestimate certain risks.

Why is it problematic to communicate uncertain events to consumers?

If you want to communicate risks, you face a number of challenges:

  • How can probabilities of occurrence be conveyed in general?
  • How can very rare events be communicated in such a way that they are also recognised as rare?
  • How can risks with extremely different probabilities of occurrence be made comparable?
  • And how can the risks be presented in an appealing way so that consumers also enjoy engaging with them?
What is a suitable scientific approach?

The risk street method can be used for risk problems, i.e. when reliable numbers are available about how often certain events occur. The method is supposed to give consumers an understanding of the probability of occurrence of such events. It is based in on prior research on the risk ladder and the Paling Perspective Scale (Paling, 2003; Singh & Paling, 1997).

In the risk street, probabilities of occurrence are communicated in absolute frequencies with the reference group of 100,000. Probabilities of occurrence of rare events can be communicated in an understandable way by visual comparisons of different events.

The problem with the common representation of very rare and rather frequent events is a correct representation in proportion. While a logarithmic scale (also called a risk ladder) is mathematically accurate, it is often too poorly understood. It can also lead to a higher risk perception (Siegrist et al., 2008). This can, for example, affect consumers with limited numerical abilities (Hess et al., 2011; Keller & Siegrist, 2009). The conventional linear scale, on the other hand, such as the number line from school, would then need a lot of space to give visible space to the very rare events. This conflict is resolved in the risk street by using a creative perspective within space and an interactive design. Rare events are distant, difficult to reach and visualised in a smaller way; more frequent events are experienced as much more present and closer. The logarithmic scale in the perspective design of a street running to the horizon thus assists interpretation despite of different probabilities of occurrence. In this way, it also ties in with findings on logarithmic scales that address the natural understanding of children and indigenous groups (Dehaene et al., 2008).

At the beginning of the street there are those risks that are most likely to occur, while at the end of the street there are those events that are rather unlikely. User can click their way through the road and events. This interactivity and dynamic visualisation is intended to inform consumers, and at the same time motivate them to engage with the visualisation. In order to assist the comparison of risks, a controlled comparison has been supplemented by a controlled list since a mere aggregation can also be disruptive (Jansen et al., 2017). Comparisons of familiar risks also help people with limited numerical abilities (Keller et al., 2009; Keller, 2011).

Proof of effectiveness

The bundling of uncertain events in a comparison using a two-dimensional number line (e.g. risk ladder) can improve the understanding of rare events. This is supported by the numerous possibilities of comparison to different events. Our studies show that this is also achieved by the newly developed perspective principle with regard to personal risk perception.

Recommended literature on methodological basics
  • Dehaene, S., Izard, V., Spelke, E., & Pica, P. (2008). Log or linear? Distinct intuitions of the number scale in Western and Amazonian indigene cultures. Science, 320(5880), 1217–1220.
  • Garcia-Retamero, R., & Galesic, M. (2010). Who proficts from visual aids: Overcoming challenges in people’s understanding of risks. Social Science & Medicine, 70(7), 1019–1025.
  • Hess, R., Visschers, V. H., Siegrist, M., & Keller, C. (2011). How do people perceive graphical risk communication? The role of subjective numeracy. Journal of Risk Research, 14(1), 47–61.
  • Janssen, E., Ruiter, R. A., & Waters, E. A. (2017). Combining risk communication strategies to simultaneously convey the risks of four diseases associated with physical inactivity to socio-demographically diverse populations. Journal of Behavioral Medicine, 1–15.
  • Keller, C., Siegrist, M., & Visschers, V. (2009). Effect of risk ladder format on risk perception in high‐and-low‐numerate individuals. Risk Analysis: An International Journal, 29(9), 1255–1264.
  • Keller, C. (2011). Using a familiar risk comparison within a risk ladder to improve risk understanding by low numerates: A study of visual attention. Risk Analysis: An International Journal, 31(7), 1043–1054.
How can you implement the method?

Option 1: You can embed the given visualisation
It is possible to embed the visualisation from our website including the frame text via iframe. To do this, use the following html-code for your website: <iframe frameborder="0" height="585px" src="https://static.risikoatlas.de/visualisations/risk-ladder/risk-ladder.html" width="1024px"></iframe>

It is also optimized for mobile devices, so you can integrate it into a mobile website.

Option 2: You can adapt the given visualisation
If you use your own data as a multiplier, your web developers can enter it into your own consumer fact box with experience-based learning.

We will provide the person responsible for your website with the documented code for download via github. You can then edit the material. The link to the repository is available on request. Contact details can be found here.

Option 3: You can apply the scientific principle independently
If you require assistance, please consult the final report on the RiskAtlas project from July 2020 or contact us. Contact details can be found here.

When using the instruments, please mention the funding agency, which is the German Federal Ministry of Justice and Consumer Protection, and the Harding Centre for Risk Literacy as the responsible developers.

Logos can be downladed here.

 

Links to other methods
Visualisation with frame text

Over-indebtedness, damaged luggage or accidents at work - how likely are these things going to happen to you during the next year?

The newsstand around the corner advertises that 12 million euros are in the lottery jackpot. Even if you have heard somewhere that a lottery win is less likely than a plane crash, you make your check marks and wait expectantly for the next draw. And of course: you do not win anything. You are not the only one, by the way: on average, 9 out of 10 people who invest in gambling have the same experience as you. And even if you win something, the amount is usually negligibly small.
At the same time, we tend to underestimate and overestimate events that actually occur - e.g. because the media attention they receive or the serious effects that they have make us forget how rarely they occur. To avoid this and to obtain a realistic overview of consumer risks, it is worth taking a look at our risk road. How likely are delays in long-distance traffic to occur? How likely is it that my legal expenses insurance will be used at some point? Our risk street can provide information on the statistical probabilities of these and other risks.

When do I need this visualisation?

The risk street is supposed to provide you with an overview and some orientation. It is not intended to support concrete decisions.
 

What does the visualisation show?

The risk street classifies various consumer risks according to their probability of occurrence within one year. The spectrum ranges from almost certain events to extremely rare occurrences. Starting with highly probable events - such as the risk of not winning any money at gambling (90,000 out of 100,000 people do not win within a year) - you can navigate through the events using the control bar on the right, the mouse wheel or the arrow keys on your keyboard. With the "Pos1" key you can jump to the beginning of the risk street, and with the "End" key you can reach the least likely event on the street.
To compare events that are not similarly likely, you can bookmark consumer risks. In this way you can create a sorted list that can be exported as a PDF file. Details on the individual risks - such as the data source and the quality of the data - are displayed by clicking on the risk bar in the window. The frequency format with 100,000 each as reference group and the indication of the absolute numbers is supposed to avoid the use of smaller percentages. It is a known fact that a large proportion of people misjudge percentages of the probability of occurrence of rare events (<1%). Additional sorting by age and gender is possible if the data permits to do so.

Sources and quality of the data

Where are the numbers coming from?

  • Bach et al., 2014. DIW.
  • BKA Bundeslagebild 2017.
  • http://appsso.eurostat.ec.europa.eu/
  • http://comms.sita.aero/rs/089-zse-857/images/baggage-report-2017.pdf
  • http://now.symassets.com/content/dam/norton/global/pdfs/norton_cybersecurity_insights/DE_NCSIR_2017.pdf
  • https://de.reuters.com/article/deutschland-hacker-umfrage-idDEKCN1P3123
  • https://de.statista.com/statistik/daten/studie/150565/umfrage/privatinsolvenzen-in-deutschland-seit-2000/
  • https://lssh.de/wp-content/uploads/2018/07/Zusammenfassung-der-BZgA-Studie-Gl%C3%BCcksspielverhalten-und-Gl%C3%BCcksspielsucht-in-Deutschland.-Ergebnisse-des-Surveys-2017-und-Trends.pdf
  • https://reklamation.com/statistik/
  • https://rp-online.de/politik/deutschland/7-6-millionen-menschen-erhalten-mindestsicherung_aid-33912859
  • https://wiwi.hs-duesseldorf.de/personen/nikola.ziehe/Documents/Kraemer%20Kalka%20Ziehe%20-%20Personalisiertes%20und%20dynamisches%20Pricing%20aus%20Einzelhandels-%20und%20Verbrauchersicht%20261110F.pdf
  • https://www.ages.at/fileadmin/AGES2015/Themen/Lebensmittel_Dateien/Lebensmittelsicherheit_und_Hygiene_im_Privathaushalt_13_12_2013.pdf
  • https://www.berlin-suchtpraevention.de/wp-content/uploads/2016/10/2015_BZgA_Ergebnisbericht_Glcksspielsucht.pdf
  • https://www.bfach.de/media/file/24871.Marktstudie_2018_Konsum-Kfz-Finanzierung_BFACH.pdf
  • https://www.bfr.bund.de/cm/350/verbrauchertipps_schutz_vor_lebensmittelinfektionen_im_privathaushalt.pdf
  • https://www.bitkom.org/Presse/Presseinformation/Jeder-zweite-Internetnutzer-von-Cyberkriminalitaet-betroffen
  • https://www.bundesnetzagentur.de/SharedDocs/Pressemitteilungen/DE/2017/28122017_Telekommunikation.html
  • https://www.creditreform.de/fileadmin/user_upload/crefo/download_de/news_termine/wirtschaftsforschung/schuldneratlas/Analyse_SchuldnerAtlas_2018.pdf
  • https://www.destatis.de/DE/PresseService/Presse/Pressemitteilungen/2016/07/PD16_243_122.html
  • https://www.destatis.de/DE/Publikationen/Thematisch/EinkommenKonsumLebensbedingungen/Ueberschuldung/EVS_GeldImmobilienvermoegenSchulden2152602139004.pdf?__blob=publicationFile
  • https://www.destatis.de/DE/ZahlenFakten/GesellschaftStaat/EinkommenKonsumLebensbedingungen/LebensbedingungenArmutsgefaehrdung/Tabellen/Eurostat_MaterielleEntbehrung_SILC.html
  • https://www.focus.de/finanzen/news/2-2-millionen-euro-schaden-wieder-mehr-betrug-mit-bankkarten-branche-ohne-sorge_id_8294582.html
  • https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&ved=2ahUKEwj59o6a3pffAhUQp4sKHTghB0AQFjABegQICBAC&url=https%3A%2F%2Fwww.presseportal.de%2Fdownload%2Fdocument%2F312756-umfrageergebnisse-dispo-nutzung-2015.pdf&usg=AOvVaw29t51ca1TN77Eh8-BRGgkP
  • https://www.marktwaechter.de/sites/default/files/downloads/schadensfaelle-auf-dem-grauen-kapitalmarkt.pdf
  • https://www.pwc.de/de/handel-und-konsumguter/assets/cyber-security-identitaetsdiebstahl-2016.pdf
  • https://www.reisereporter.de/artikel/1947-flugausfaelle-flugverspaetung-taeglich-69-faelle-probleme-mit-fluegen
  • https://www.schlichtungsstelle-energie.de/presse/presseartikel/taetigkeitsbericht-der-schlichtungsstelle-energie-39.html;  Bericht der Bundesnetzagentur 2017
  • https://www.uni-trier.de/fileadmin/fb4/prof/VWL/OAR/Hornuf_Schmitt_-_Success_and_Failure_in_Equity_Crowdfunding.pdf
  • https://www.zugreiseblog.de/bahn-puenktlichkeit-statistik/
  • Schufa-Report 2018.
  • Schufa-Report 2018.
  • Statistisches Jahrbuch der Versicherungswirtschaft.
  • VATM_TK-Marktstudie-2018_091018_f
  • Zusammenfassung-der-BZgA-Studie-Glücksspielverhalten-und-Glücksspielsucht-in-Deutschland.-Ergebnisse-des-Surveys-2017-und-Trends

 

What is the quality of the data?

The numbers and data included in the risk comparison come from various sources, e.g. frequency observations of public registers, surveys, population studies or models. Most of these risk estimates are characterised by a relatively low quality of evidence. This means that future assessments are likely to lead to different results.

There are several reasons for this:
1) There is a lack of randomised controlled trials that compare consumer actions and inactions, and thus demonstrate that certain events are caused by these actions.
2) The registration of the occurrence of consumer events in Germany is based too little on qualitative systematic population studies, but rather primarily on the number of people affected.
3) The registration of consumer risks is also always subject to conflicts of interest or self-interests, which can weaken the informative value of data.

 

Last update: 14 Oktober 2019

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