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Enhancing Understanding and Recall of Quantitative Information about Medical Risks: A Cross-Cultural Comparison between Germany and Spain

Published online by Cambridge University Press:  10 January 2013

Rocio Garcia-Retamero ,
Mirta Galesic  and
Gerd Gigerenzer
Rocio Garcia-Retamero*
Affiliation:
Universidad de Granada (Spain)
Mirta Galesic
Affiliation:
Max Planck Institute for Human Development (Germany)
Gerd Gigerenzer
Affiliation:
Max Planck Institute for Human Development (Germany)
*
Correspondence concerning this article should be addressed to Rocio Garcia-Retamero. Departamento de Psicologia Experimental, Facultad de Psicologia. Universidad de Granada. Campus Universitario de Cartuja s/n. 18071 Granada. (Spain). Phone: +34-958246240, Fax: +34-958246239. E-mail: rretamer@ugr.es
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Abstract

In two experiments, we analyzed cross-cultural differences in understanding and recalling information about medical risks in two countries—Germany and Spain—whose students differ substantially in their quantitative literacy according to the 2003 Programme for International Student Assessment (PISA; OECD, 2003, 2010). We further investigated whether risk understanding can be enhanced by using visual aids (Experiment 1), and whether different ways of describing risks affect recall (Experiment 2). Results showed that Spanish students are more vulnerable to misunderstanding and forgetting the risk information than their German counterparts. Spanish students, however, benefit more than German students from representing the risk information using ecologically rational formats—which exploit the way information is represented in the human mind. We concluded that our results can have important implications for clinical practice.

En dos experimentos, hemos analizado si existen diferencias culturales en la comprensión y recuerdo de información sobre riesgos médicos. Nos hemos centrado en dos países—Alemania y España—ya que, según los resultados encontrados en el Programme for International Student Assessment (PISA; OECD, 2003, 2010). los estudiantes procedentes de los mismos difieren substancialmente en sus habilidades para procesar información cuantitativa. Así mismo hemos investigado si es posible mejorar la comprensión de los riesgos médicos mediante el uso de material visual de apoyo (Experimento 1), o del uso de diferentes formatos verbales para describir dichos riesgos (Experimento 2). Los resultados de nuestros experimentos han puesto de manifiesto que los estudiantes españoles son más vulnerables a interpretar incorrectamente y a olvidar la información sobre los riesgos que los estudiantes alemanes. Sin embargo, los primeros se benefician en mayor medida que los segundos de la representación de la información sobre riesgos médicos a través del uso de formatos ecológicos—los cuales representan la información de un modo similar a como lo hace la mente humana. Concluimos que nuestros resultados pueden tener implicaciones importantes para la práctica clínica.

Keywords

medical risksProgramme for International Student Assessment (PISA)risk perceptionrisk communicationriesgos médicosProgramme for International Student Assessment (PISA)percepción de riesgoscomunicación de riesgos
Type
Research Article
Information
The Spanish Journal of Psychology , Volume 14 , Issue 1 , May 2011 , pp. 218 - 226
Copyright
Copyright © Cambridge University Press 2011

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References

Ancker, J. S., Senathirajah, Y., Kukafka, R., & Starren, J. B. (2006) Design features of graphs in health risk communication: A systematic review. Journal of American Medical Informatics Association, 13, 608–618. doi:10.1197/jamia.M2115Google Scholar
Cleary, P. D., & Angel, R. (1984). The analysis of relationships involving dichotomous dependent-variables. Journal of Health and Social Behavior, 25, 334–348. doi:10.2307/2136429CrossRefGoogle ScholarPubMed
Covey, J. (2007). A meta-analysis of the effects of presenting treatment benefits in different formats. Medical Decision Making, 27, 638–654. doi:10.1177/0272989X07306783CrossRefGoogle ScholarPubMed
Elmore, J. G., & Gigerenzer, G. (2005). Benign breast disease-the risks of communicating risk. New England Journal of Medicine, 353, 297–299. doi:10.1056/NEJMe058111CrossRefGoogle ScholarPubMed
Eurostat. (2007). Europe in figures: Education. Retrieved from: http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-CD-06-001-02/EN/KS-CD-06-001-02-EN.PDF.Google Scholar
Eurostat. (2009). Europe in figures: Eurostat year book 2009. Retrieved from: http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-CD-09-001/EN/KS-CD-09-001-EN.PDF.Google Scholar
Fagerlin, A., Wang, C., & Ubel, P. A. (2005). Reducing the influence of anecdotal reasoning on people's health care decisions: Is a picture worth a thousand statistics? Medical Decision Making, 25, 398–405. doi:10.1177/0272989X05278931Google Scholar
Feixas, G., & Saul, L. A. (2004). The multi-center dilemma project: An investigation of the role of cognitive conflicts in health. The Spanish Journal of Psychology, 7, 69–78.CrossRefGoogle ScholarPubMed
Fontaine, K. R., Redden, D. T., Wang, C., Westfall, A. O., & Allison, D. B. (2003). Years of life lost due to obesity. The Journal of the American Medical Association, 289, 187–193. doi:10.1001/jama.289.2.187Google Scholar
Franco, O. H., Laet, C. D., Peeters, A., Jonker, J., Mackenbach, J., & Nusselder, W. (2005). Effects of physical activity on life expectancy with cardiovascular disease. Archives of Internal Medicine, 165, 2355–2360. doi:10.1001/archinte.165.20.2355Google Scholar
Galesic, M., & Garcia-Retamero, R. (2010). Statistical numeracy for health: A cross-cultural comparison with probabilistic national samples. Archives of Internal Medicine, 170, 462–468. doi:10.1001/archinternmed.2009.481CrossRefGoogle Scholar
Galesic, M., & Garcia-Retamero, R. (2011). Communicating consequences of risky behaviors: Life expectancy versus risk of disease. Patient Education and Counseling, 82, 30–35. doi:10.1016/j.pec.2010.02.008Google Scholar
Galesic, M., & Garcia-Retamero, R. (in press). Graph literacy: A cross-cultural comparison. Medical Decision Making.Google Scholar
Galesic, M., Garcia-Retamero, R., & Gigerenzer, G. (2009). Using icon arrays to communicate medical risks: Overcoming low numeracy. Health Psychology, 28, 210–216.Google Scholar
Garcia-Retamero, R., & Dhami, M. K. (2011). Pictures speak louder than numbers: On communicating medical risks to immigrants with limited non-native language proficiency. Health Expectations, 14, 46–57.Google Scholar
Garcia-Retamero, R., & Galesic, M. (2009a). Communicating treatment risk reduction to people with low numeracy skills: A cross-cultural comparison. American Journal of Public Health, 99, 2196–2202. doi:10.2105/AJPH.2009.160234Google Scholar
Garcia-Retamero, R., & Galesic, M. (2009b). Heuristics. In Kattan, M. W. (Ed.), The encyclopedia of medical decision making (pp. 596–599). Thousand Oaks, CA: SAGE Publications.Google Scholar
Garcia-Retamero, R., & Galesic, M. (2009c). Trust in health care. In Kattan, M. W. (Ed.), The encyclopedia of medical decision making (pp. 1153–1155). Thousand Oaks, CA: SAGE Publications.Google Scholar
Garcia-Retamero, R., & Galesic, M. (2010a). How to reduce the effect of framing on messages about health. Journal of General Internal Medicine, 25, 1323–1329. doi:10.1007/s11606-010-1484-9Google Scholar
Garcia-Retamero, R., & Galesic, M. (2010b). Who profits from visual aids? Overcoming challenges in people's understanding of risks. Social Science & Medicine, 70, 1019–1025. doi:10.1016/j.socscimed.2010.03.019CrossRefGoogle ScholarPubMed
Garcia-Retamero, R., & Galesic, M. (in press). Risk communication and medical decision making: A cross-cultural perspective. New York, NY: Springer.Google Scholar
Garcia-Retamero, R., Galesic, M., & Gigerenzer, G. (2010). Do icon arrays help reduce denominator neglect? Medical Decision Making, 30, 672–684. doi:10.1177/0272989X10369000CrossRefGoogle ScholarPubMed
Garcia-Retamero, R., Takezawa, M., & Gigerenzer, G. (2009). Does imitation benefit cue order learning? Experimental Psychology, 56, 307–320. doi:10.1027/1618-3169.56.5.307Google Scholar
Gigerenzer, G., & Edwards, A. (2003). Simple tools for understanding risks: From innumeracy to insight. British Medical Journal, 327, 741–744. doi:10.1136/bmj.327.7417.741Google Scholar
Gigerenzer, G., Gaissmaier, W., Kurz-Milcke, E., Schwartz, L. M., & Woloshin, S. (2008). Helping doctors and patients make sense of health statistics. Psychological Science in the Public Interest, 8, 53–96.CrossRefGoogle Scholar
Gigerenzer, G., & Hoffrage, U. (1995). How to improve Bayesian reasoning without instruction: Frequency formats. Psychological Review, 102, 684–704. doi:10.1037//0033-295X.102.4.684CrossRefGoogle Scholar
Gigerenzer, G., Todd, P. M., & the ABC Research Group. (1999). Simple heuristics that make us smart. New York, NY: Oxford University Press.Google Scholar
Hunt, E., & Wittmann, W. (2008). National intelligence and national prosperity. Intelligence, 36, 1–9. doi:10.1016/j.intell.2006.11.002Google Scholar
Instituto Nacional de Estadística [National Institute of Statistics]. (2009). Cifras de población y censo demográfico [population figures and demographic census]. Retrieved from: http://www.ine.es/inebmenu/mnu_cifraspob.htm.Google Scholar
Kenchaiah, S., Evans, J. C., Levy, D., Wilson, P. W. F., Benjamin, E. J., Larson, M. G., … Vasan, R. S. (2002). Obesity and the risk of heart failure. New England Journal of Medicine, 347, 305–313. doi:10.1056/NEJMoa020245Google Scholar
Lipkus, I. M. (2007). Numeric, verbal, and visual formats of conveying health risk: Suggested best practices and future recommendations. Medical Decision Making, 27, 696–713. doi:10.1177/0272989X07307271Google Scholar
Lipkus, I. M., & Hollands, J. G. (1999). The visual communication of risk. Journal of the National Cancer Institute Monographs, 25, 149–163.CrossRefGoogle Scholar
Lunney, G. H. (1970). Using analysis of variance with a dichotomous dependent variable-An empirical study. Journal of Educational Measurement, 7, 263–269. doi:10.1111/j.1745-3984.1970.tb00727.xGoogle Scholar
Marks, G. N., Cresswell, J., & Ainley, J. (2006). Explaining socioeconomic inequalities in student achievement: The role of home and school factors. Educational Research and Evaluation, 12, 105–128. doi:10.1080/13803610600587040Google Scholar
Miller, T. D., Balady, G. J., & Fletcher, G. F. (1997). Exercise and its role in the prevention and rehabilitation of cardiovascular disease. Annals of Behavioral Medicine, 3, 220–229. doi:10.1007/BF02892287Google Scholar
Montori, V. M., & Rothman, R. L. (2005). Weakness in numbers-The challenge of numeracy in healthcare. Journal of General Internal Medicine, 11, 1071–1072. doi:10.1111/j.1525-1497.2005.051498.xGoogle Scholar
OEDC (2003). The PISA 2003 Assessment framework–Mathematics, reading, science, and problem solving knowledge and skills. Paris: OEDC.Google Scholar
OECD (2010). PISA 2009 Results: What students know and can do – Student performance in reading, mathematics and science (Volume I). Paris: OEDC. doi.org/10.1787/9789264091450-enGoogle Scholar
Paling, J. (2003). Strategies to help patients understand risks. British Medical Journal, 327, 745–748. doi:10.1136/bmj.327.7417.745Google Scholar
Rindermann, H. (2007). The g-factor of international cognitive ability comparisons: The homogeneity of results in PISA, TIMSS, PIRLS and IQ-tests across nations. European Journal of Personality, 21, 667–706. doi:10.1002/per.634Google Scholar
Schwartz, L. M., Woloshin, S., Black, W. C., & Welch, H. G. (1997). The role of numeracy in understanding the benefit of screening mammography. Annals of Internal Medicine, 127, 966–972.Google Scholar
Skolbekken, J. A. (1998). Communicating the risk reduction achieved by cholesterol reducing drugs. British Medical Journal, 316, 1956–1958.CrossRefGoogle ScholarPubMed
Statistisches Bundesamt Deutschland. (2009). Microcensus. Retrieved from: https://www-genesis.destatis.de/genesis/online.Google Scholar
Stone, E. R., Yates, J. F., & Parker, A. M. (1997). Effects of numerical and graphical displays on professed risk-taking behavior. Journal of Experimental Psychology: Applied, 3, 243–256. doi:10.1037//1076-898X.3.4.243Google Scholar
Waters, E. A., Weinstein, N. D., Colditz, G. A., & Emmons, K. M. (2007). Reducing aversion to side effects in preventive medical treatment decisions. Journal of Experimental Psychology: Applied, 13, 11–21. doi:10.1037/1076-898X.13.1.11Google Scholar
World Health Organization. (2009). Core health indicators. Retrieved from: http://www.who.int/whosis/database/core/core_select_process.cfm?countries=all&indicators=nha.Google Scholar