Background. Visual aids tend to help diverse and vulnerable individuals understand risk communications, as long as these individuals have a basic understanding of graphs (i.e., graph literacy). Tests of objective graph literacy (OGL) can effectively identify individuals with limited skills, highlighting vulnerabilities and facilitating custom-tailored risk communication. However, the administration of these tests can be time-consuming and may evoke negative emotional reactions (e.g., anxiety). Objectives. To evaluate a brief and easy-to-use assessment of subjective graph literacy (SGL) (i.e., self-reported ability to process and use graphically presented information) and to estimate the robustness and validity of the SGL scale and compare it with the leading OGL scale in diverse samples from different cultures. Participants. Demographically diverse residents (n = 470) of the United States, young adults (n = 172) and patients (n = 175) from Spain, and surgeons (n = 175) from 48 countries. Design. A focus group and 4 studies for instrument development and initial validation (study 1), reliability and convergent and discriminant validity evaluation (study 2), and predictive validity estimation (studies 3 and 4). Measures. Psychometric properties of the scale. Results. In about 1 minute, the SGL scale provides a reliable, robust, and valid assessment of skills and risk communication preferences and evokes fewer negative emotional reactions than the OGL scale. Conclusions. The SGL scale can be suitable for use in clinical research and may be useful as a communication aid in clinical practice. Theoretical mechanisms involved in SGL, emerging applications, limitations, and open questions are discussed.
WatersEAWeinsteinNDColditzGAEmmonsKM.Reducing aversion to side effects in preventive medical treatment decisions. J Exp Psychol Appl. 2007;13(1):11–21.
2.
Zikmund-FisherBJFagerlinAUbelPA.Improving understanding of adjuvant therapy options by using simpler risk graphics. Cancer. 2008;113(12):3382–90.
3.
SpiegelhalterDPearsonMShortI.Visualizing uncertainty about the future. Science. 2011;333(6048):1393–400.
4.
Garcia-RetameroRCokelyET.Effective communication of risks to young adults: using message framing and visual aids to increase condom use and STD screening. J Exp Psychol Appl. 2011;17(3):270–87.
5.
Garcia-RetameroRCokelyET.Communicating health risks with visual aids. Curr Dir Psychol Sci. 2013;22(5):392–9.
6.
Garcia-RetameroRGalesicM.Transparent Communication of Health Risks: Overcoming Cultural Differences. New York, NY: Springer;2013.
7.
KellerCSiegristM.Effect of risk communication formats on risk perception depending on numeracy. Med Decis Making. 2009;29(4):483–90.
8.
Zikmund-FisherBJWittemanHODicksonM. Blocks, ovals, or people? Icon type affects risk perceptions and recall of pictographs. Med Decis Making. 2014;34(4):443–53.
9.
Garcia-RetameroRGalesicM.Who profits from visual aids: overcoming challenges in people’s understanding of risks. Soc Sci Med. 2010;70(7):1019–25.
10.
GalesicMGarcia-RetameroR.Graph literacy: a cross-cultural comparison. Med Decis Making. 2011;31(3):444–57.
11.
CokelyETGalesicMSchulzEGhazalSGarcia-RetameroR.Measuring risk literacy: the Berlin Numeracy Test. Judgm Decis Mak. 2012;7(1):25–47.
12.
SchwartzLMWoloshinSBlackWCWelchHG.The role of numeracy in understanding the benefit of screening mammography. Ann Intern Med. 1997;127(11):966–72.
13.
LipkusIMSamsaGRimerBK.General performance on a numeracy scale among highly educated samples. Med Decis Making. 2001;21(1):37–44.
14.
AndersonBLSchulkinJ.Numerical Reasoning in Judgments and Decision Making about Health. Cambridge, UK: Cambridge University Press; 2014.
15.
Garcia-RetameroRAndradeASharitJRuizJG.Is patient’s numeracy related to physical and mental health?Med Decis Making. 2015;35(4):501–11.
16.
RuizJGAndradeADGarcia-RetameroRAnamRRodriguezRSharitJ.Communicating global cardiovascular risk: are icon arrays better than numerical estimates in improving understanding, recall and perception of risk?Patient Educ Couns. 2013;93(3):394–402.
17.
GaissmaierWWegwarthOSkopecDMüllerABroschinskiSPolitiMC.Numbers can be worth a thousand pictures: individual differences in understanding graphical and numerical representations of health-related information. Health Psychol. 2012;31(3):286–96.
18.
Garcia-RetameroRCokelyET.The influence of skills, message frame, and visual aids on prevention of sexually transmitted diseases. J Behav Decis Making. 2014;27(2):179–89.
19.
OkanYGarcia-RetameroRCokelyETMaldonadoA.Individual differences in graph literacy: overcoming denominator neglect in risk comprehension. J Behav Decis Making. 2012;25(4):390–401.
20.
Garcia-RetameroRMuñozR.How to improve comprehension of medical risks in older adults. Rev Latinoam Psicol. 2013;45(2):253–64.
21.
OkanYGarcia-RetameroRCokelyETMaldonadoA.Improving risk understanding across ability levels: encouraging active processing with dynamic icon arrays. J Exp Psychol Appl. 2015;21(2):178–94.
22.
OkanYGalesicMGarcia-RetameroR.How people with low and high graph literacy process health graphs: evidence from eye-tracking. J Behav Decis Making. 2015;29(2–3):271–94.
23.
OkanYGarcia-RetameroRGalesicMCokelyET.When higher bars are not larger quantities: on individual differences in the use of spatial information in graph comprehension. Spatial Cogn Comput. 2012;12(2–3):195–218.
24.
Woller-CarterMMOkanYCokelyETGarcia-RetameroR.Communicating and distorting risks with graphs: an eye-tracking study. Proc Hum Fact Ergon Soc Annu Meet. 2012;56(1):1723–7.
25.
RodríguezVAndradeADGarcía-RetameroR. Health literacy, numeracy, and graphical literacy among veterans in primary care and their effect on shared decision making and trust in physicians. J Health Commun. 2013;18(Suppl 1):273–89.
26.
SharitJLisigurskiMAndradeAD. The roles of health literacy, numeracy, and graph literacy on the usability of the VA’s personal health record by veterans. J Usability Stud. 2014;9(4):173–93.
27.
OkanYGarcia-RetameroRCokelyETMaldonadoA. Biasing and debiasing health decisions with bar graphs: costs and benefits of graph literacy. Under review.
28.
GhazalSCokelyETGarcia-RetameroR.Predicting biases in very highly educated samples: numeracy and metacognition. Judgm Decis Mak. 2014;9(1):15–34.
29.
ReynaVFNelsonWLHanPKDieckmannNF.How numeracy influences risk comprehension and medical decision making. Psychol Bull. 2009;135(6):943–73.
30.
PetersE.Beyond comprehension the role of numeracy in judgments and decisions. Curr Dir Psychol Sci. 2012;21(1):31–35.
31.
PetersEBjalkebringP.Multiple numeric competencies: when a number is not just a number. J Pers Soc Psychol. 2015;108(5):802–22.
32.
DolanJGCherkaskyOALiQChinNVeaziePJ.Should health numeracy be assessed objectively or subjectively?Med Decis Making. 2015May6 [Epub ahead of print].
33.
FagerlinAZikmund-FisherBJUbelPAJankovicADerryHASmithDM.Measuring numeracy without a math test: development of the Subjective Numeracy Scale. Med Decis Making. 2007;27(5):672–80.
34.
Zikmund-FisherBJSmithDMUbelPAFagerlinA.Validation of the subjective numeracy scale: effects of low numeracy on comprehension of risk communications and utility elicitations. Med Decis Making. 2007;27(5):663–71.
35.
GalesicMGarcia-RetameroR.Statistical numeracy for health: a cross-cultural comparison with probabilistic national samples. Arch Intern Med. 2010;170(5):462–8.
36.
HessRVisschersVHSiegristMKellerC.How do people perceive graphical risk communication? The role of subjective numeracy. J Risk Res. 2011;14(1):47–61.
37.
Zikmund-FisherBJWittemanHOFuhrel-ForbisAExeNLKahnVCDicksonM.Animated graphics for comparing two risks: a cautionary tale. J Med Internet Res. 2012;14(4):e106.
38.
PaolacciGChandlerJIpeirotisPG.Running experiments on Amazon Mechanical Turk. Judg Decis Making. 2010;5(5):411–9.
39.
Garcia-RetameroRCokelyET.Promoting shared medical decision making in doctors and their patients. Manuscript in preparation. 2016.
40.
SchneiderRHStaggersFAlxanderCN. A randomised controlled trial of stress reduction for hypertension in older African Americans. Hypertension. 1995;26(5):820–7.
41.
ChanJMRimmEBColditzGAStampferMJWillettWC.Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men. Diabetes Care. 1994;17(9):961–9.
42.
ColditzGAWillettWCRotnitzkyAMansonJE.Weight gain as a risk factor for clinical diabetes mellitus in women. Ann Intern Med. 1995;122(7):481–6.
43.
KnowlerWCBarrett-ConnorEFowlerSE. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346(6):393–403.
44.
SuárezPSGarcíaAMPMorenoJB.Escala de autoeficacia general: Datos psicométricos de la adaptación para población española. Psicothema. 2000;12:509–13.
45.
FalcesCBriñolPSierraBBecerraAAlierE.Validación de la escala de necesidad de cognición y su aplicación al estudio del cambio de actitudes. Psicothema. 2001;13(4):622–8.
46.
GoslingSDRentfrowPJSwannWB.A very brief measure of the Big-Five personality domains. J Res Pers. 2003;37(6):504–28.
47.
Garcia-RetameroRGalesicM.Communicating treatment risk reduction to people with low numeracy skills: a cross-cultural comparison. Am J Public Health. 2009;99(12):2196–202.
48.
Garcia-RetameroRGalesicMGigerenzerG.Do icon arrays help reduce denominator neglect?Med Decis Making. 2010;30(6):672–84.
49.
BaronJ.Rationality and Intelligence. Cambridge, UK: Cambridge University Press; 2005.
50.
Garcia-RetameroRCokelyETHoffrageU.Visual aids improve diagnostic inferences and metacognitive judgment calibration. Front Psychol. 2015;6:932.
DavisFMLaurensonVGGillespieWJWellsJEFoateJNewmanE.Deep vein thrombosis after total hip replacement: a comparison between spinal and general anaesthesia. J Bone Joint Surg Br. 1989;71(2):181–5.
53.
SobelME.Asymptotic confidence intervals for indirect effects in structural equation models. Sociol Method. 1982;13(1982):290–312.
54.
LipkusIM.Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations. Med Decis Making. 2007;27(5):696–713.
55.
BuhrmesterMKwangTGoslingSD.Amazon’s Mechanical Turk a new source of inexpensive, yet high-quality, data?Pers Psychol Sci. 2011;6(1):3–5.
56.
JaeggiSMBuschkuehlMJonidesJShahP.Short- and long-term benefits of cognitive training. Proc Natl Acad Sci USA. 2011;108(25):10081–6.
57.
CokelyETKelleyCM.Cognitive abilities and superior decision making under risk: a protocol analysis and process model evaluation. Judg Decis Making. 2009;4(1):20–33.
58.
CokelyETKelleyCMGilchristAL.Sources of individual differences in working memory: contributions of strategy to capacity. Psychon Bull Rev. 2006;13(6):991–7.
59.
Garcia-RetameroRCokelyETWickiBJoerisA. Improving surgeons’ risk literacy with visual aids. Patient Educ Couns. In press.
60.
Schulte-MecklenbeckMKühbergerARanyardR.A Handbook of Process Tracing Methods for Decision Research: A Critical Review and User’s Guide. New York, NY: Psychology Press;2010.
61.
CronbachLJMeehlPE.Construct validity in psychological tests. Psychol Bull. 1955;52(4):281–302.
62.
MessickS.Validity of psychological assessment: validation of inferences from persons’ responses and performances as scientific inquiry into score meaning. Am Psychol. 1995;50(9):741–9.
63.
GigerenzerGGaissmaierWKurz-MilckeESchwartzLMWoloshinS.Helping doctors and patients make sense of health statistics. Psychol Sci Public Interest. 2007;8(2):53–96.
64.
Garcia-RetameroRCokelyET.Using visual aids to help people with low numeracy make better decisions. In: AndersonBLSchulkinJ, eds. Numerical Reasoning in Judgments and Decision Making about Health. Cambridge, UK: Cambridge University Press; 2014. p 153–74.
65.
GalesicMGarcia-RetameroR.Using analogies to communicate information about health risks. Appl Cognitive Psych. 2013;27(1):33–42.
