differences in the perception of blood transfusion risk between laypeople and physicians

T R A N S F U S I O N C O M P L I C A T I O N S

Differences in the perception of blood transfusionrisk between laypeople and physicians

D.H. Lee, M.D. Mehta, and P.D. James

BACKGROUND: There is little objective evidence tosupport the commonly held belief that laypeople per-ceive blood transfusion risk differently from physicians.Acknowledging and characterizing such differences mayimprove risk communication. The objective of this studywas to characterize how laypeople and physicians per-ceive the risks of blood transfusion in comparison with awide variety of other hazards.STUDY DESIGN AND METHODS: A total of 161 lay-people and 91 physicians and medical trainees weresurveyed in Kingston, Ontario, between March and Au-gust 2000. The perceived riskiness and other qualitativecharacteristics of blood transfusion and 9 other hazardswere measured by psychometric scaling and principalcomponents analysis.RESULTS: The overall return rate was 100 percent,with 86 percent of surveys having no missing re-sponses. Physicians perceived the risks of blood trans-fusion and most other hazards to be less dreaded andsevere, but also less understood and controllable thanlaypeople.CONCLUSION: Laypeople and physicians perceive riskdifferently for blood transfusion, but this perceptual gapbetween the groups for blood transfusion may be repre-sentative of a more generalized phenomenon thatspans different types of hazards, both medical and non-medical. Awareness of such differences may facilitaterisk communication and shared decision making be-tween physicians and their patients.

Understanding how laypeople perceive therisks of blood transfusion is of importance tohealth-care providers, policy makers, andthose who provide blood services and com-

ponents. For example, shared medical decision makingbetween patients and their physicians is best accom-plished when there is an appreciation of not only howlaypeople think, but how this differs from how physiciansthink. There is a commonly held, but unproven, beliefthat laypeople perceive blood transfusion to be “riskier”than physicians. While this may seem self-evident tosome, objective evidence to support this assumption islacking.

Over the past 25 years, studies based on the psycho-metric paradigm of risk perception have advanced ourunderstanding of how people think and feel about risk.This model uses psychometric scaling to produce quan-titative and spatial representations of risk perceptions.1,2

Hazards are characterized and judged not only by theprobability and severity of the adverse outcome, but alsoby qualitative characteristics such as dread, voluntari-ness, knowledge, and controllability. The observationthat experts have lower perceptions of risk than laypeoplelikely reflects differences in how these two groups incor-porate cognitive, affective, and personal factors into theirjudgments of risk.3-5 For example, it has been reportedthat experts tend to define risk in probabilistic terms,whereas laypeople tend to incorporate affective charac-teristics such as dread and catastrophic potential intotheir perceptions of risk.2 Consistent with this model, asubstantial proportion of the public in the US continue tohave significant concerns about the safety of the bloodsupply, with imagery of HIV and AIDS being evoked fre-quently by the phrase “blood transfusions.”6 In contrast,a different study reported that physicians’ perceptions ofrisk for a variety of hazards was found to correlate withthe objective death rates for those hazards.7 Blood trans-fusion was perceived by physicians (who may be re-garded as “experts”) to be of relatively low risk. Thus, theconjecture that physicians perceive blood transfusion tobe less risky than laypeople is supported by risk percep-tion theory and by indirect observational studies. How-ever, a lay-expert difference in the perception of bloodtransfusion risk has not been documented.

From the Department of Medicine, Queen’s University, Kings-

ton, Ontario; and the Department of Sociology, University of

Saskatchewan, Saskatoon, Saskatchewan, Canada.

Address reprint requests to: David H. Lee, MD, Etherington

Hall, Room 2013, Queen’s University, 94 Stuart Street, Kings-

ton, Ontario K7L 3 N6, Canada; e-mail: [email protected].

This study was supported by Grant 9912 from the Bayer

Blood Partnership Fund.

Received for publication September 3, 2002; revision re-

ceived January 11, 2003, and accepted January 17, 2003.

TRANSFUSION 2003;43:772-778.

772 TRANSFUSION Volume 43, June 2003

The objective of this study was to characterize andcompare how laypeople and physicians perceive bloodtransfusion risk, based on the hypothesis that physicians(as experts) would perceive blood transfusion to beless risky than laypeople. We also sought to determinewhether such differences in perceived risk, if pres-ent, are unique to blood transfusion or whether theyare simply representative of systematic differences inhow laypeople and physicians perceive risk in general.

MATERIALS AND METHODS

SubjectsThis study was approved by the Research Ethics Board atQueen’s University (Kingston, Ontario, Canada). Adultlaypeople residing in Kingston, Ontario, were recruitedby telephone using numbers from the local directory andby posting advertisements. Questionnaires were admin-istered at a centralized location under the direct super-vision of a research assistant to ensure that all question-naires were returned. Subjects received a small fee tocover transportation expenses. Physicians and trainees atKingston General Hospital were approached in personand questionnaires were completed on site.

QuestionnaireSubjects completed a demographics and risk perceptionquestionnaire in which they rated various hazards withrespect to a panel of qualitative risk characteristics. Thehazards included nuclear reactors, caffeine, sharing in-jection needles, genetically modified foods, blood trans-fusions, pesticides, bicycles, alcohol (causing disease, notaccidents), prescription drugs, and smoking (causing dis-ease, not fires). Each hazard was rated with a seven-pointLikert-style scale for the following qualitative risk char-acteristics: 1, overall riskiness (anchors: not risky, ex-tremely risky); 2, worry (anchors: not worried, extremelyworried); 3, dread (anchors: not dreaded, extremelydreaded); 4, benefits provided (anchors: little or no ben-efit, very important benefits); 5, the degree to which therisks are known to those exposed (anchors: risks notknown, risks well known); 6, the degree to which the risksare understood by scientists (anchors: risks not under-stood, risks understood); 7, the likelihood of fatal conse-quences (anchors: will not be fatal, certain to be fatal); 8,the degree to which exposure to the hazard is voluntary(anchors: involuntary, voluntary); 9, the amount of con-trol an average person has over the risk (anchors: no con-trol at all, complete control); and 10, the extent to whichfuture generations are threatened by the risk (anchors:not threatened at all, very seriously threatened).

Before its use in this study, the risk perception ques-tionnaire was administered to focus groups to ensurereadability and clarity. To ascertain test-retest reliability,

the questionnaire was readministered within 2 hours to asubgroup of consecutive subjects in the layperson group.

Statistical analysis and cognitivemapping of hazardsComparison of demographic variables between groupswas performed with t test and Fisher’s exact test as ap-propriate. Test-retest reliability of the questionnaire wasascertained by calculating the Pearson and intraclass cor-relation between repeat measures.8

Principal components analysis was applied to theraw questionnaire data. Principal components analysis isa method of reducing the number of data variables bycombining correlated variables into a smaller number ofhigher order components or dimensions. Each compo-nent captures the “essence” of its composite variables,thereby retaining information as the original data are re-duced. Computational extraction of the components oc-curs sequentially, with each successive component cap-turing information that is not captured by the precedingcomponent. In this fashion, the extracted componentsare independent of each other. Data that are reduced intothree components or dimensions can be expressed geo-metrically within the planes or space defined by x, y, andz axes. In this study, the number of components ex-tracted in the model was determined with the conven-tional criterion that retained components should extractat least as much variance as the equivalent of one originalvariable. Thus, only components with eigenvalues (vari-ances extracted by the components) of greater than 1were retained. While the axes of the solution can be ro-tated to explore the data further, the original solution wasunrotated to avoid imposing arbitrary manipulations onthe analysis. The appropriateness of the model was as-certained with Bartlett’s test of sphericity, which is ameasure of the likelihood that the correlated original dataare actually identical (i.e., that the correlation matrix isactually an identity matrix). In the current study, a cog-nitive map was produced by plotting mean values of Di-mension 2 versus Dimension 1 for each hazard.

To compare responses between the groups,MANOVA was performed for the dimensions of risk per-ception on physician and layperson status for each haz-ard. To identify demographic variables that were inde-pendently associated with risk perception, linearregression was performed on each dimension with thefollowing independent variables: age; sex; physician,trainee, or layperson status; marital status; having chil-dren; level of education; and the hazards. The hazardswere dummy coded in a binary fashion (0 or 1). A back-ward regression model with a removal threshold of p =0.2 was used. A conventional threshold of p < 0.05 wasused to accept the overall regression model.

For each subject, a general risk perception score foreach dimension was calculated by averaging the scores

PERCEPTION OF BLOOD TRANSFUSION RISK

Volume 43, June 2003 TRANSFUSION 773

for all hazards, excluding responses for blood transfusion.This general risk perception score was used for compari-son with responses for blood transfusion risk. All re-ported p values are two-tailed. All statistical procedureswere performed with computer software (SPSS version10.0, SPSS, Chicago, IL).

RESULTS

Subjects and demographicsBetween March and August 2000, 252 subjects (161 lay-people and 91 physicians and trainees) participated. Thephysician and trainee group consisted of attending phy-sicians (n = 33), residents (n = 43), and clinical clerks (n =15). The majority of physicians and residents were in thedisciplines of family medicine (n = 21), internal medicine(n = 19), and anesthesia (n = 17). Physicians and traineeswere of similar age and had a similar sex distribution tolaypeople, but a greater proportion of physicians andtrainees were married, had no children, and had a uni-versity education (Table 1). The laypeople were demo-graphically similar to the population of Kingston, whichhas a median age of 38 years, with 50 percent of thepopulation (over 15 years old) being married9 and 45 per-cent having a degree, diploma, or certificate from univer-sity or college.10

Questionnaire completion rate and reliabilityThe overall return rate was 100 percent. The completionrate (no missing responses) for the risk perception ques-tionnaire was 94 percent (238 of 252 participants). Theoverall completion rate for both the demographics andthe risk perception questionnaires was 86 percent (216 of252 participants). Evaluation of test-retest reliability ofthe entire risk perception questionnaire in the first 61laypeople yielded Pearson and intraclass correlations of0.82 (p < 0.001) and 0.90 (p < 0.001), respectively.

Principal components analysisPrincipal components analysis of raw data for all hazardsyielded three higher order components or dimensions

that accounted for 70 percent of the variance of the rawdata (Bartlett’s test of sphericity, p < 0.001). Dimension 1(accounting for 36% of total variance) was heavilyweighted in the characteristics of worry, dread, riskiness,and potential for fatal outcome. The degree to which ahazard is known or understood by those exposed and byscience, the controllability of the hazard, and the degreeto which exposure is voluntary were characteristics thatloaded heavily onto Dimension 2 (accounting for 23% ofthe total variance). The benefit of the hazardous activity,substance, or technology was the principal characteristicthat loaded onto Dimension 3 (accounting for 11% of thetotal variance). These loadings onto three dimensions didnot change when the data for individual hazards wereanalyzed separately or when laypeople and physician andtrainee groups were analyzed separately. Hence, thesedimensions were labeled dread and severity (Dimension1), knowledge and control (Dimension 2), and benefit (Di-mension 3). Values for each dimension were calculatedby averaging the score of the major component charac-teristics.

Univariate analysis and cognitivemapping of hazardsThe three dimensions are plotted for each hazard for thelayperson and physician and trainee groups in Fig. 1.Overall, physicians perceived 9 of the hazards to beless dreaded and severe (Dimension 1). There was a trendfor physicians to perceive all hazards to be less under-stood and controllable (Dimension 2) than laypeople,although significance was achieved for only 5 hazards.Perceived benefit (Dimension 3) was similar betweengroups for most hazards. Among the 10 hazards, bloodtransfusion was of intermediate ranking in Dimensions1 and 2; however, it was perceived to be very benefi-cial (Dimension 3). While physicians perceived lowerdread and severity for blood transfusion (Dimension 1),there were no differences in the scores of Dimensions2 and 3 for blood transfusion in comparison with lay-people. Perceptions of high dread and severity (Dimen-sion 1) for blood transfusion were associated with highergeneral risk perception scores in Dimension 1 for theremainder of the hazards (r2 = 0.30; p < 0.001). In otherwords, individuals who perceived blood transfusionrisk to be of greater dread and severity also tended toperceive greater dread and severity for the other 9 haz-ards.

A cognitive map of the hazards was created by plot-ting knowledge and control (Dimension 2) against dreadand severity (Dimension 1) as shown in Fig. 2. To test therobustness of this construct, the weighting of the indi-vidual risk characteristics that comprise each dimensionwas varied. The positions of the hazards within the mapremained similar, even when component individual risk

TABLE 1. Demographic variables of thestudy groups

Demographic variableLaypeople(n = 161)

Physicians(n = 91) p value

Mean age (years) 35 33 0.17Sex (% female) 59 51 0.19Marital status (% married) 28 54 < 0.001Children (% with children) 43 30 0.04Education (% with some

university or a universitydegree) 51 100 < 0.001

LEE ET AL.


Fig. 1. The three dimensions of perceived risk as derived from principal components analysis. For each hazard, box plots depict

the responses by physicians or trainees (open boxes) and laypeople (closed gray boxes). Responses between the 25th and 75th

percentiles are bound by the lower and upper borders of the box. The mean and median are represented by the solid diamond

and horizontal line through the box, respectively. Whiskers denote the 10th and 90th percentiles of data. *p < 0.05 and **p <

0.005 for comparisons between groups.



characteristics were omitted entirely from the equation(data not shown).

Multivariate analysisTo identify the independent variables that contribute toperceptions, linear regression of the demographic vari-ables and hazards on each of the three dimensions wasperformed. Table 2 summarizes the model fit statistics.These models explained 58.1, 49.5, and 65.8 percent ofthe variance of Dimensions 1, 2, and 3, respectively. Mostof the explained variance was accounted for by the haz-ards themselves. Several significant demographic factorswere identified, albeit each contributed only a small de-gree to the overall responses. Table 3 summarizes thestandardized regression coefficients for the demographicvariables in the final regression models. Physician or

trainee status, female sex, married status, and lower edu-cation level were independently associated with a greaterperception of dread and severity (Dimension 1). How-ever, physician or trainee status was not an independentvariable for Dimensions 2 and 3. Lower education wasindependently associated with the perception that haz-ards are understood and controllable (Dimension 2),

TABLE 2. Model fit statistics for finalregression models

Dimension

1 2 3

R2 0.581 0.495 0.658�R2 0.000 0.000 0.000p value < 0.001 < 0.001 < 0.001

Fig. 2. Cognitive mapping of risk perception. The mean values for Dimension 2 are plotted against Dimension 1. For each haz-

ard, responses for physicians or trainees (�) and laypeople (�) are joined with the dotted line to indicate the differences in po-

sition. Error bars denote SEM.

LEE ET AL.


whereas younger age, male sex, married status, andhigher education were independently associated withgreater perceived benefit for the activity, substance, ortechnology in question (Dimension 3).

DISCUSSIONThe current study provides evidence to support the com-monly held belief that physicians and laypeople perceiveblood transfusion risk differently. However, we also ob-served similar differences in the quality and magnitude ofperceived risk for most other hazards, suggesting that theperceptual gap between the groups for blood transfusionmay be representative of a more generalized phenom-enon that spans different types of hazards, both medicaland nonmedical. To our knowledge, these observationshave not previously been reported.

The psychometric paradigm was used to characterizehow laypeople and physicians or trainees perceive risk.Various qualities of a series of hazards were rated withpsychometric scales, which in turn were condensed intoa smaller number of higher order dimensions with prin-cipal components analysis, thus allowing the representa-tion of these hazards with spatial models. The psycho-metric paradigm has been found to be a robust andinformative way of conceptualizing how people perceiverisk and is the most frequently used model to explain riskperception.1,2,11,12 Using this construct, lay perceptionsof risk in the current study were found to be similar tothose reported in previous studies;2,13,14 however, therewas a systematic shift of the responses by physicians andtrainees toward the top left of the cognitive map, relativeto laypeople. Physicians and trainees had lower percep-tions of dread and severity than laypeople for all hazardsexcept smoking, an effect that was associated with phy-sician or trainee status, independent of a university-leveleducation and the other demographic variables enteredinto our model. These differences in risk perception wereobserved even for those hazards that are outside therealm of common medical expertise. Physicians andtrainees also judged hazards to be less understood andcontrollable than laypeople, but this effect was no longerdetectable when corrected for the level of education and

other demographic variables. Both groups perceivedsimilar benefits for most hazards.

Blood transfusion was perceived by laypeople to beof intermediate dread and severity, relative to the otherhazards. Other investigators have made similar observa-tions in different societal groups,3 yet a significant pro-portion of the public continue to express concerns aboutthe safety of the blood supply.6,15 In the current study,individuals who perceived blood transfusions to beriskier also tended to perceive other hazards as beingriskier, consistent with a previous report.6

Our results should be interpreted with several cave-ats. First, risk perception is difficult to characterize andno current model is capable of capturing all of its com-plexity.16 It is possible that other models of risk percep-tion may yield different results. Second, it is not knownwhether lay perceptions of medical risks can be general-ized to patients. Patients with real stakes may responddifferently from laypeople faced with hypothetical ques-tions about medical hazards. Third, why differences inrisk perception exist between the groups is not clear fromour data. Multivariate analysis of responses in Dimension1 suggests that physician or trainee status is a variable inrisk perception, independent of age, sex, university-leveleducation, marital status, and having children. However,a more detailed inventory of sociodemographic charac-teristics, world views, and other variables is required tostudy this question further.

For environmental, chemical, and technologic haz-ards, other investigators have found that “experts” tendto judge hazards to be less risky than laypeople.3-5 Thefrequently cited explanation is that experts define risk inprobabilistic terms, with science and experience notavailable to the average layperson. In the absence of suchknowledge, laypeople rely on a more intuitive and mul-tidimensional approach that incorporates several quali-tative risk characteristics such as dread, severity, control-lability, and social trust.17,18 Consequently, it is believedthat experts judge hazards that they are familiar with asbeing less risky than laypeople.4,19 Physicians are familiarwith many of the hazards in the current study, but theyare not usually considered experts in the risk assessmentof technologies such as nuclear reactors, pesticides, ge-

TABLE 3. Standardized regression coefficients and levels of significance for demographic variables*

Demographic variable

Dimension

1 2 3

� p value � p value � p value

Physician status −0.106 < 0.001 −0.028 0.133Age 0.020 0.193 −0.030 0.157 −0.032 0.023Female sex 0.050 < 0.001 −0.047 < 0.001Married status 0.039 0.014 0.034 0.015Children 0.041 0.053Education −0.058 0.001 −0.095 < 0.001 0.029 0.030

* Blank values indicate variables removed during backward regression.



netically modified foods, or even bicycles. Thus, someother element associated with physician or trainee statusmust account for the differences.

How are these data useful? Physicians who have agreater understanding of how patients think and feelabout risk, and consequently how they make decisions,have a greater opportunity to assist their patients in mak-ing optimal decisions.20 Sensitivity to patient values andpreferences may also enhance the satisfaction of thehealth-care consumer. Moreover, such observations maybe of great interest to the institutions and policy makersthat interact with the public at a societal level. Under-standing how public perceptions of risk differ from ourown may help these parties anticipate and understandpublic preferences and their reactions to decisions andpolicies involving risk. This may be particularly useful inview of the increasing public participation in the organi-zation, policies, and delivery of transfusion and otherhealth-care services.21-23

ACKNOWLEDGMENTS

The authors thank Heather Racz and David Carr for their as-

sistance with data collection.

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differences in the perception of blood transfusion risk between laypeople and physicians

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