Advertisement

Judging risk magnitude: walking to the left and base jumping to the right

  • Anne MacnamaraEmail author
  • Tobias Loetscher
  • Hannah A. D. Keage
Research Article

Abstract

When thinking about quantifiable domains such as numbers, pitch, and size, they are implicitly mapped on to representational space with small/low/less and large/high/more of the respective domain represented on the left and right sides of representational space, respectively. Recent research has also demonstrated that more abstract domains (colours, language, political party names) are also mapped in the same way. This study investigated a new abstract domain, risk, to examine if this same pattern of effects is apparent (left = low risk/right = high risk) to get a better understanding of how risk magnitudes are processed. Experiment 1 (n = 26) presented objective, statistically calculated risk stimuli (micromorts) to participants, who indicated if the stimuli had lower or higher risks than a referent, with their left and right hands. Experiment 2 (n = 25) utilised the same task, but the risk stimuli were generated by the participants themselves. Both experiments found the expected association of risk with space—indicated by faster left-hand responses to low-risk stimuli and faster right-hand responses to high-risk stimuli. Risks appear to fit onto a standard left–right spatial association; however, the effect sizes for all analyses were small. The results of this study are not only in line with the idea of a generalised magnitude processing system, but might also inform best practices in effective communications of risks.

Keywords

Spatial associations SNARC Distance effect Risk communication 

Supplementary material

221_2018_5449_MOESM1_ESM.docx (31 kb)
Supplementary material 1 (DOCX 30 KB)

References

  1. Ahmad N, Peterson N, Torella F (2015) The Micromort: a unit for comparing and communicating risk to patients. Int J Clin Pract 69:515–517.  https://doi.org/10.1111/ijcp.12643 CrossRefPubMedGoogle Scholar
  2. Blastland M, Spiegelhalter D (2013) Norm Chronicles: stories about number and danger. Profile Books, Great BritainGoogle Scholar
  3. Bueti D, Walsh V (2009) The parietal cortex and the representation of time, space, number and other magnitudes. Philos Trans R Soc B 364:1831–1940.  https://doi.org/10.1098/rstb.2009.0028 CrossRefGoogle Scholar
  4. Cantlon JF, Platt ML, Brannon EM (2009) Beyond the number domain. Trends Cogn Sci 13:83–91.  https://doi.org/10.1016/j.tics.2008.11.007 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Cipora K, Hohol M, Nuerk HC, Willmes K, Brożek B, Kucharzyk B, Nęcka E (2016) Professional mathematicians differ from controls in their spatial-numerical associations. Psychol Res 80:710–726.  https://doi.org/10.1007/s00426-015-0677-6 CrossRefPubMedGoogle Scholar
  6. Cohen Kadosh R, Lammertyn J, Izard V (2008) Are numbers special? An overview of chronometric, neuroimaging, developmental and comparative studies of magnitude representation. Prog Neurobiol 84:132–147.  https://doi.org/10.1016/j.pneurobio.2007.11.001 CrossRefPubMedGoogle Scholar
  7. Cokely ET, Galesic M, Schulz E, Ghazal S, Garcia-Retamero R (2012) Measuring risk literacy: the Berlin numeracy test. Judgm Decis Mak 7:25–47. http://journal.sjdm.org/. Accessed 20 Mar 2017
  8. Conson M, Cinque F, Barbarulo AM, Trojano L (2008) A common processing system for duration, order and spatial information: evidence from a time estimation task. Exp Brain Res 187:267–274.  https://doi.org/10.1007/s00221-008-1300-5 CrossRefPubMedGoogle Scholar
  9. Cutini S, Scarpa F, Scatturin P, Dell’Acqua R, Zorzi M (2014) Number-space interactions in the human parietal cortex: enlightening the SNARC effect with functional near-infrared spectroscopy. ‎Cereb Cortex 24:444–451.  https://doi.org/10.1093/cercor/bhs321 CrossRefPubMedGoogle Scholar
  10. Dehaene S (1997) The number sense: how the mind creates mathematics. Oxford University Press, New YorkGoogle Scholar
  11. Dehaene S, Bossini S, Giraux P (1993) The mental representation of parity and number magnitude. J Exp Psychol 122:371–396.  https://doi.org/10.1037//0096-3445.122.3.371 CrossRefGoogle Scholar
  12. Ding X, Feng N, Cheng X, Liu H, Fan Z (2015) Are past and future symmetric in mental time line? Front Psychol 6:1–8.  https://doi.org/10.3389/fpsyg.2015.00208 CrossRefGoogle Scholar
  13. Fabbri M, Cellini N, Martoni M, Tonetti L, Natale V (2013) The mechanisms of space-time association: comparing motor and perceptual contributions in time reproduction. Cogn Sci 37:1228–1250.  https://doi.org/10.1111/cogs.12038 CrossRefPubMedGoogle Scholar
  14. Fias W, Lammertyn J, Reynvoet B, Dupont P, Orban GA (2003) Parietal representation of symbolic and non-symbolic magnitude. J Cogn Neurosci 15:47–56.  https://doi.org/10.1162/089892903321107819 CrossRefPubMedGoogle Scholar
  15. Fias W, van Dijck JP, Gevers W (2011) How is number associated with space? The role of working memory. In: Dehaene S, Brannon E (eds) Space, time and number in the brain. Elsevier, Amsterdam, pp 133–148.  https://doi.org/10.1016/B978-0-12-385948-8.00010-4 CrossRefGoogle Scholar
  16. Finucane ML, Alhakami A, Slovic P, Johnson SM (2000) The affect heuristic in judgments of risks and benefits. J Behav Decis Mak 13:1–17.  https://doi.org/10.1002/(SICI)1099-0771(200001/03)13:1%3C1::AID-BDM333%3E3.0.CO;2-S CrossRefGoogle Scholar
  17. Fischhoff B, Slovic P, Lichtenstein S, Read S, Combs B (1978) How safe is safe enough? A psychometric study of attitudes towards technological risks and benefits. Policy Schemes 9:127–152.  https://doi.org/10.1007/BF00143739 CrossRefGoogle Scholar
  18. Fox-Glassman KT, Weber EU (2016) What makes risk acceptable? Revisiting the 1978 psychological dimensions of perceptions of technological risks. J Math Psychol 75:157–169.  https://doi.org/10.1016/j.jmp.2016.05.003 CrossRefGoogle Scholar
  19. Fry AM, Harrison A, Daigneault M (2016) Micromorts—what is the risk? Br J Oral Maxillofac Surg 54:230–231.  https://doi.org/10.1016/j.bjoms.2015.11.023 CrossRefPubMedGoogle Scholar
  20. Fuhrman O, Boroditsky L (2010) Cross-cultural differences in mental representations of time: evidence from an implicit nonlinguistic task. Cogn Sci 34:1430–1451.  https://doi.org/10.1111/j.1551-6709.2010.01105.x CrossRefPubMedGoogle Scholar
  21. Galesic M, Garcia-Retamero R, Gigerenzer G (2009) Using icon arrays to communicate medical risks: overcoming low numeracy. Health Psychol 28:210–216.  https://doi.org/10.1037/a0014474 CrossRefPubMedGoogle Scholar
  22. Garcia-Retamero R, Cokely ET (2013) Communicating health risks with visual aids. ‎Curr Direct Psychol Sci 22:392–399.  https://doi.org/10.1177/0963721413491570 CrossRefGoogle Scholar
  23. Garcia-Retamero R, Galesic M (2010) Who profits from visual aids: overcoming challenges in people’s understanding of risks. Soc Sci Med 70:1019–1025.  https://doi.org/10.1016/j.socscimed.2009.11.031 CrossRefPubMedGoogle Scholar
  24. Gevers W, Reynvoet B, Fias W (2003) The mental representation of ordinal sequences is spatially organized. Cognition 87:B87–B95.  https://doi.org/10.1016/S0010-0277(02)00234-2 CrossRefPubMedGoogle Scholar
  25. Gompertz B (1825) On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philos Trans R Soc Lond 115:513–583.  https://doi.org/10.1098/rstl.1825.0026 CrossRefGoogle Scholar
  26. Hoffmann D, Mussolin C, Martin R, Schiltz C (2014) The impact of mathematical proficiency on the number-space association. PLoS One 9:e85048.  https://doi.org/10.1371/journal.pone.0085048 CrossRefPubMedPubMedCentralGoogle Scholar
  27. Irwin MG, Kong VKF (2014) Quantifying and communicating peri-operative risk. Anaesthesia 69:1299–1303.  https://doi.org/10.1111/anae.12881 CrossRefPubMedGoogle Scholar
  28. Keage HAD, Loetscher T (2018) Estimating everyday risk: subjective judgments are related to objective risk, mapping of numerical magnitudes and previous experience. PLoS One 13:e0207356.  https://doi.org/10.1371/journal.pone.0207356 CrossRefPubMedGoogle Scholar
  29. Lidji P, Kolinsky R, Lochy A, Morais J (2007) Spatial associations for musical stimuli: a piano in the head? J Exp Psychol Hum Percept Perform 33:1189–1207.  https://doi.org/10.1037/0096-1523.33.5.1189 CrossRefPubMedGoogle Scholar
  30. Macnamara A, Keage HAD, Loetscher T (2017) Mapping of non-numerical domains on space: a systematic review and meta-analysis. Exp Brain Res 236:335–346.  https://doi.org/10.1007/s00221-017-5154-6 CrossRefPubMedGoogle Scholar
  31. Moyer RS, Landauer TK (1967) Time required for judgements of numerical inequality. Nature 215:1519–1520.  https://doi.org/10.1038/2151519a0 CrossRefPubMedGoogle Scholar
  32. Nicholls MER, Thomas NA, Loetscher T, Grimshaw GM (2013) The Flinders Handedness survey (FLANDERS): a brief measure of skilled hand preference. Cortex 49:2914–2926.  https://doi.org/10.1016/j.cortex.2013.02.002 CrossRefPubMedGoogle Scholar
  33. Pinel P, Piazza M, Le Bihan D, Dehaene S (2004) Distributed and overlapping cerebral representations of number, size, and luminance during comparative judgments. Neuron 41:983–993.  https://doi.org/10.1016/S0896-6273(04)00107-2 CrossRefPubMedGoogle Scholar
  34. Prado J, Van der Henst J-B, Noveck IA (2008) Spatial associations in relational reasoning: evidence for a SNARC-like effect. Q J Exp Psychol 61:1143–1150.  https://doi.org/10.1080/17470210801954777 CrossRefGoogle Scholar
  35. Psychology Software Tools, Inc. [E-Prime 2.0] (2012) http://www.pstnet.com. Accessed 5 Apr 2016
  36. Santiago J, Lupianez J, Perez E, Funes MJ (2007) Time (also) flies from left to right. Psychon Bull Rev 14:512–516.  https://doi.org/10.3758/BF03194099 CrossRefPubMedGoogle Scholar
  37. Sellaro R, Treccani B, Job R, Cubelli R (2015) Spatial coding of object typical size: evidence for a SNARC-like effect. Psychol Res 79:950–962.  https://doi.org/10.1007/s00426-014-0636-7 CrossRefPubMedGoogle Scholar
  38. Selya AS, Rose JS, Dierker LC, Hedeker D, Mermelstein RJ (2012) A practical guide to calculating Cohen’s f 2, a measure of local effect size, from PROC MIXED. Front Psychol 3:1–6.  https://doi.org/10.3389/fpsyg.2012.00111 CrossRefGoogle Scholar
  39. Shaki S, Gevers W (2011) Cultural characteristics dissociate magnitude and ordinal information processing. J Cross Cult Psychol 42:639–650.  https://doi.org/10.1177/0022022111406100 CrossRefGoogle Scholar
  40. Shaki S, Fischer MH, Petrusic WM (2009) Reading habits for both words and numbers contribute to the SNARC effect. Psychon Bull Rev 16:328–331.  https://doi.org/10.3758/PBR.16.2.328 CrossRefPubMedGoogle Scholar
  41. Slovic P (1987) Perception of risk. Science 236:280–285. http://www.sciencemag.org/. Accessed 15 May 2018
  42. Slovic P (2016) Understanding perceived risk: 1978–2015. Environ Sci Policy Sustain Dev 58:25–29.  https://doi.org/10.1080/00139157.2016.1112169 CrossRefGoogle Scholar
  43. Slovic P, Peters E (2006) Risk perception and affect. ‎Curr Direct Psychol Sci 15:322–325.  https://doi.org/10.1111/j.1467-8721.2006.00461.x CrossRefGoogle Scholar
  44. Slovic P, Fischhoff B, Lichtenstein S (1979) Rating the risks. Environ Sci Policy Sustain Dev 21:14–39.  https://doi.org/10.1080/00139157.1979.9933091 CrossRefGoogle Scholar
  45. Sokolowski HM, Fias W, Bosah Ononye C, Ansari D (2017) Are numbers grounded in a general magnitude processing system? A functional neuroimaging meta-analysis. Neuropsychologia 105:50–69.  https://doi.org/10.1016/j.neuropsychologia.2017.01.019 CrossRefPubMedGoogle Scholar
  46. Soreide K, Ellingsen CL, Knutson V (2007) How dangerous is BASE jumping? An analysis of adverse events in 20,850 jumps from the Kjerag Massif, Norway. Trauma Inj Infect Crit Care 62:1113–1117.  https://doi.org/10.1097/01.ta.0000239815.73858.88 CrossRefGoogle Scholar
  47. Spiegelhalter DJ (2014) The power of the MicroMort. BJOG: Int J Obstet Gynaecol 121:662–663.  https://doi.org/10.1111/1471-0528.12663 CrossRefGoogle Scholar
  48. Spiegelhalter D (2017) Risk and uncertainty communication. Annu Rev Stat Appl 4:31–60.  https://doi.org/10.1146/annurev-statistics-010814-020148 CrossRefGoogle Scholar
  49. van Dijck JP, Fias W (2011) A working memory account for spatial-numerical associations. Cognition 119:114–119.  https://doi.org/10.1016/j.cognition.2010.12.013 CrossRefPubMedGoogle Scholar
  50. van Opstal F, Verguts T (2011) The origins of the numerical distance effect: the same-different task. ‎J Cogn Psychol 23:112–120.  https://doi.org/10.1080/20445911.2011.466796 CrossRefGoogle Scholar
  51. van Elk M, van Schie HT, Bekkering H (2010) From left to right: processing acronyms referring to names of political parties activates spatial associations. Q J Exp Psychol 63:2202–2219.  https://doi.org/10.1080/17470218.2010.495160 CrossRefGoogle Scholar
  52. van Dijck JP, Abrahamse EL, Majerus S, Fias W (2013) Spatial attention interacts with serial-order retrieval from verbal working memory. Psychol Sci 24:1854–1859.  https://doi.org/10.1177/0956797613479610 CrossRefPubMedGoogle Scholar
  53. van der Linden S (2014) On the relationship between personal experience, affect and risk perception: the case of climate change. ‎Eur J Soc Psychol 44:430–440.  https://doi.org/10.1002/ejsp.2008 CrossRefPubMedPubMedCentralGoogle Scholar
  54. Viarouge A, Hubbard EM, McCandliss BD (2014) The cognitive mechanisms of the SNARC effect: an individual differences approach. PLoS One 9:e95756.  https://doi.org/10.1371/journal.pone.0095756 CrossRefPubMedPubMedCentralGoogle Scholar
  55. Walsh V (2003) A theory of magnitude: common cortical metrics of time, space and quantity. Trends Cogn Sci 7:483–488.  https://doi.org/10.1016/j.tics.2003.09.002 CrossRefPubMedGoogle Scholar
  56. Wood G, Willmes K, Nuerk HC, Fischer MH (2008) On the cognitive link between space and number: a meta-analysis of the SNARC effect. Psychol Sci Q 50:489–525.  https://doi.org/10.1027/1618-3169.52.3.187 CrossRefGoogle Scholar
  57. Zhang M, Gao X, Li B, Yu S, Gong T, Jiang T, Hu Q, Chen Y (2016) Spatial representation of ordinal information. Front Psychol 7:1–6.  https://doi.org/10.3389/fpsyg.2016.00505 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Psychology, Social Work and Social PolicyUniversity of South AustraliaAdelaideAustralia

Personalised recommendations