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Abstract Number: 2158

Do Numbers Make a Difference?

Liana Fraenkel1, Evan Wilhelms2 and Valerie Reyna2, 1Medicine, Section of Rheumatology, Yale University School of Medicine, Veterans Affairs Connecticut Healthcare System, New Haven, CT, 2Cornell University, Ithica, NY

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: risk

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Session Information

Title: ARHP Osteoarthritis - Clinical Aspects: Psychology/Social Sciences

Session Type: Abstract Submissions (ARHP)

Background/Purpose: Patients frequently overweigh the risks associated with rare adverse events (AEs). This is particularly true for biologics associated with extremely rare AEs. As a result, significant efforts have been made to determine how best to present numerical information when describing the probabilities of rare AEs. What is unclear, however, is whether precise numeric estimates influence decision making or behavioral intentions.

Methods: We administered a survey to college students to examine the influence of probabilities and risk perceptions (worry, riskiness and gist evaluations) on subjects’ stated likelihood of starting a medication. In this context, gist evaluations refer to the subjective meaning attached to the risk of the specified AE. We first described the impact of rheumatoid arthritis and subsequently asked subjects to imagine themselves as a patient with this disease in a clinical encounter during which a physician described a new treatment option to them. Route of administration, benefit, and cost were held constant. We varied current health state (able versus unable to maintain current level of activity and responsibilities), type of AE (pneumonia versus cancer) and probability of the AE (1 in 100, 1 in 1,000, 1 in 10,000 and 1 in 100,000). Each subject responded to a single, randomly-assigned scenario. Linear regression models were constructed to examine the association between current health state, type of AE, the probability of the AE and risk perceptions (worry, riskiness, and gist evaluations) with the likelihood of starting the medication (measured on a 5-point scale) after adjusting for age, gender, ethnicity, and numeracy (measured using the modified Lipkus-Peters numeracy scale). Levels of gist evaluations and ethnicity were treated as dummy variables.

Results:  415 subjects completed the survey. Their mean (SD) age was 19.8 (1.8). 72.5% were woman, and 55.7% were Caucasian, 5.5% were Black and 25.7% Asian. The mean (SD) numeracy score was 0.74 (0.20). Health state, type of AE, probability, worry, riskiness, and gist evaluations were associated with likelihood of taking the medication when evaluated separately. In the full model (containing all predictors and covariates), current health state and all three risk perceptions remained significantly associated with likelihood of taking the medication, while numeric probability was not (See Table).

Conclusion: Risk perceptions predict subjects’ willingness to take medication, while probabilistic information does not. The results suggest that decision support must extend beyond presentation of probabilistic information in order to ensure informed choice.

Table. Predictors of willingness to take the medication

Parameter Estimates

Parameter

B

Std. Error

Hypothesis Test

Wald Chi-Square

Sig.

(Intercept)

4.704

.7948

35.030

.000

Current Health State

.258

.0868

8.862

.003

Adverse Event

-.126

.0927

1.839

.175

Probability of Adverse Event

-.108

.1480

.531

.466

Gist = doesn’t matter how small risk is

-.458

.1309

12.241

.000

Gist = even though risk is small, unacceptable

-.727

.1471

24.387

.000

Gist = risk is so small, nothing to worry about

.532

.1146

21.577

.000

Gist = risk is small, but reasonable

Reference

 

 

 

Riskiness

-.178

.0608

8.591

.003

Worry

-.228

.0559

16.698

.000

Numeracy

-.494

.6697

.544

.461

Probability * Numeracy1

.209

.1919

1.183

.277

Gender

-.105

.0968

1.186

.276

Age

.009

.0239

.129

.720

Ethnicity = White Hispanic

-.150

.2059

.534

.465

Ethnicity = Other

-.315

.1702

3.431

.064

Ethnicity = Asian

-.215

.1019

4.456

.035

Ethnicity = Black

-.223

.1946

1.314

.252

Ethnicity = White non-Hispanic

Reference

 

 

 

1: Interaction term between probability and numeracy.

 


Disclosure:

L. Fraenkel,
None;

E. Wilhelms,
None;

V. Reyna,
None.

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