Information in Direct-to-Consumer

Transcription

1 Experimental Study of Quantitative Benefit Information in Direct-to-Consumer Prescription Drug Advertising i Presented by Doug Rupert, MPH; Amie O Donoghue, PhD; Dhuly Chowdhury, MS, MBA; Helen Sullivan, PhD, MPH; Kathryn Aikin, PhD; Rebecca Moultrie, AS Presented at The 139th Annual Meeting of the American Public Health Association Washington, DC October 29 November 2, Phone (919) drupert@rti.org RTI International is a trade name of Research Triangle Institute

2 Disclosure No relationships to disclose. 2

3 Scope of DTC Drug Advertising Permitted only in U.S. and New Zealand Pharma spends more than $4.2 billion per year on DTC advertising 1 Increased DTC spending correlated with increased prescriptions and prescription drug use, especially for advertised products 1-3 DTC ads prompt consumers to request and seek more information about advertised drugs 4-7 3

4 DTC Advertising Challenges Unproven connection between DTC ads and informed medication decisions 5,8-9 Limited information on drug efficacy and risks in DTC ads Consumers struggle with concepts of efficacy / risk Consumers often overestimate drug efficacy 4,9 Clinically inappropriate requests for advertised drugs 4,9 4

5 Study Purpose What is the value of including quantitative benefit data in DTC drug ads? Ability to recall Perceptions and attitudes Behavioral intentions 5

6 Study Design Experimental study to evaluate how quantitative benefit information in drug advertisements influences consumers Study Sample (n=4,805) Online, probability based panel representing U.S. adults Diagnosed with high cholesterol Data Collection Random assignment (38 arms) Forced ad exposure Web-based survey 6

7 Study Design Experimental Arms Manipulated several factors: Ad Type Print Television Statistical Format Absolute frequency (65 out of 100) Percent (65%) Relative frequency (32 times more effective) Efficacy Level High (65 out of 100 people) p Low (10 out of 100 people) Control (no info) Visual Format Pie chart Bar chart Table Pictograph 7

8 8 Study Design Example Ads

9 Traditional DTC Ad Findings (Control Groups) (n=260) Preliminary Data 9

10 Benefit Recall Most participants i t recalled at least one drug benefit Recall higher in TV ad condition 100% 80% 90.9% 60% 68.6% 40% 20% 0% 28.5% 2.9% 2.2% 6.9% No Recall Incorrect Recall Accurate Recall 10 p < (vs. condition)

11 Benefit Recall Drug Use and Illness Severity Current prescription drug use did not affect recall Illness severity boosted recall in print ad condition 100% 100% 80% 70.1% 90.8% 91.1% 80% 60% 68.5% 60% 66.3% 71.6% 93.4% 86.2% 93.3% 83.5% 40% 40% 20% 20% 0% 0% Current Med Use No Med Use Less than and above 11

12 Risk Recall Most also recalled at least one drug side effect or risk No difference between print and TV ad conditions 100% 80% 60% 83.2% 87.8% 40% 20% 0% 12.1% 4.7% 9.3% 2.9% No Recall Incorrect Recall Accurate Recall 12

13 Risk Recall Drug Use and Illness Severity Current prescription drug use and illness severity had little effect on risk recollection 100% 80% 87.7% 76.9% 87.0% 89.8% 8% 100% 80% 82.1% 83.1% 77.5% 91.9% 97.5% 86.3% 60% 60% 40% 40% 20% 20% 0% 0% Current Med Use No Med Use Less than and above 13

14 Benefit and Risk Recall (Prompted) When prompted, participants i t recalled majority of drug benefits and risks Benefit Recall (Prompted) Risk Recall (Prompted) 6.36 Pi

15 Perceived Efficacy and Risk Moderate perceived efficacy and risk of advertised d drug TV ad exposure leads to slightly higher efficacy and lower risk perceptions Perceived Drug Efficacy Perceived Drug Risk

16 Perceived Efficacy and Risk Drug Use Current users perceive drug as more effective, less risky Perceived Drug Efficacy Perceived Drug Risk Current Med Use No Med Use Current Med Use No Med Use p < (vs. No Med Use)

17 Perceived Efficacy Illness Severity Perceived efficacy decreases as illness severity increases Perceived Drug Efficacy p < (vs. Higher Cholesterol Levels) Less than and above Less than and above

18 Perceived Risk Illness Severity Conversely, perceived risk increases with illness severity Perceived Drug Risk p < (vs. Higher Cholesterol Levels) Less than and above Less than and above

19 Behavioral Intentions Limited it intentions ti resulting from ad exposure Repetitive exposure might boost intentions Talk to Doctor Info Search Take Drug 19

20 Quantitative Benefit Findings (Coming Soon!) 20

21 Preliminary Interpretations Good Benefit / Risk Recall. Most consumers able to recall drug s benefits and risks after ad exposure. Moderate Perceived Efficacy and Risk. Consumers expect drug to work reasonably well and be reasonably safe. Medication Use Boosts Expectations. Higher perceived efficacy, lower perceived risk. Illness Severity Limits Expectations. Lower perceived efficacy, higher perceived risk. Ad Exposure Drug Seeking Behaviors. Limited intentions to request drug or seek out more info on it. 21

22 Next Steps Does quantitative benefit info in DTC drug ads Distract from benefit and risk recall? Inflate perceived efficacy? Deflate perceived risk? Create stronger intentions to ask about, research, and try drug? Lead to more informed, appropriate medication decisions? 22

23 Study Team & Authors RTI International ti U.S. Food and Drug Administration i ti Doug Rupert Amie O Donoghue Dhuly Chowdhury Helen Sullivan Rebecca Moultrie Kathryn Aikin Harley Rohloff Knowledge Networks Tania Fitzgerald Mike Lawrence Jennifer Gard Rick Li Karol Krotki 23

24 References 1 Government Accountability Office (GAO). (2006). Improvements needed in FDA s oversight of direct-to-consumer advertising. GAO Washington, DC: Government Accountability Office. 2 Gilbody, S., Wilson, P., & Watt, I. (2005). Benefits and harms of direct to consumer advertising: A systematic review. Quality and Safety in Health Care,14(4), Zachry, W.M. III, Shepherd, M.D., Hinich, M.J., et al. (2002). Relationship between direct-to-consumer advertising and physician diagnosing and prescribing. American Journal of Health-System Pharmacy, 59(1), Aikin, K. J., Swasy, J. L., & Braman, A. C. (2004). Patient and physician attitudes and behaviors associated with DTC promotion of prescription drugs. Washington DC: Food and Drug Administration. 5 Kaiser Family Foundation (2001). Understanding the Effects of Direct-to-Consumer Prescription Drug Advertising. Menlo Park, CA. 6 Murray, E., L,o B., Pollack, L., et al. (2004). Direct-to-consumer advertising: Public perceptions of its effects on health behaviors, health care, and the doctor-patient relationship. Journal of the American Board of Family Practice, 17(1), Mintzes, B., Barer, M.L., Kravitz, R.L., et al. (2002). Influence of direct to consumer pharmaceutical advertising and patients requests on prescribing decisions: Two site cross sectional survey. BMJ, 324(7332), Lipsky, M. S., & Taylor, C. A. (1997). The opinions and experiences of family physicians regarding direct-to-consumer advertising. Journal of Family Practice, 45, Murray, E., Lo, B., Pollack, L., Donelan, K., & Lee, K. (2003). Direct-to-consumer advertising: Physicians' views of its effects on quality of care and the doctor-patient relationship. Journal of the American Board of Family Practice, 16(6), Frosch, D.L., Krueger, P.M., Hornik, R.C., Cronholm, P.F., & Barg, F.K. (2007). Creating demand for prescription drugs: A content analysis of television direct-to-consumer advertising. Annals of Family Medicine, 5(1), Woloshin, S., Schwartz, L.M., & Welch, G. (2004). The value of benefit data in direct-to-consumer to consumer drug ads. 24

25 References 12 Cohen, D. J., Ferrell, J. M., & Johnson, N. (2002). What very small numbers mean. Journal of Experimental Psychology: General, 131(3), Bowman, M. L. (2002). The perfidy of percentiles. Archives of Clinical Neuropsychology, 17(3), 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(11), Fagerlin, A., Zikmund-Fisher, B.J., Ubel, P.A., Jankovic, A., Derry, H.A., & Smith, D.M. (2007). Measuring numeracy without a math test: Development of the Subjective Numeracy Scale. Medical Decision Making, 27(5), Zikmund-Fisher, B.J., Smith, D.M., Ubel, P.A., & Fagerlin, A. (2007). Validation of the Subjective Numeracy Scale: Effects of low numeracy on comprehension of risk communications and utility elicitations. Medical Decision Making, 27(5),