Notice: Agency Information Collection Activities; Proposed Collection; 
Comment Request; Experimental Study of Presentation of Quantitative 
Effectiveness Information to Consumers in Direct-to-Consumer Television 
and Print Advertisements for Prescription Drugs

Federal Register: June 22, 2009 (Volume 74, Number 118)               
                  Page 29490-29493

AGENCY: Food and Drug Administration, HHS.

ACTION: Notice.

SUMMARY: The Food and Drug Administration (FDA) is announcing an 
opportunity for public comment on the proposed collection of certain 
information by the agency. Under the Paperwork Reduction Act of 1995 
(the PRA), Federal agencies are required to publish notice in the 
Federal Register concerning each proposed collection of information and 
to allow 60 days for public comment in response to the notice. This 
notice solicits comments on the Experimental Study of Presentation of 
Quantitative Effectiveness Information to Consumers in Direct-to-
Consumer (DTC) Television and Print Advertisements for Prescription 
Drugs. This study is designed to communicate quantitative information 
about product benefits in DTC print and television ads.

DATES: Submit written or electronic comments on the collection of 
information by [August 21, 2009

ADDRESSES: Submit electronic comments on the collection of information 
to http://www.regulations.gov. Submit written comments on the 
collection of information to the Division of Dockets Management (HFA-
305), Food and Drug Administration, 5630 Fishers Lane, rm. 1061, 
Rockville, MD 20852. All comments should be identified with the docket 
number found in brackets in the heading of this document.

FOR FURTHER INFORMATION CONTACT: Liz Berbakos, Office of Information 
Management (HFA-710), Food and Drug Administration, 5600 Fishers Lane, 
Rockville, MD 20857, 301-796-3792.

SUPPLEMENTARY INFORMATION: Under the PRA (44 U.S.C. 3501-3520), Federal 
agencies must obtain approval from the Office of Management and Budget 
(OMB) for each collection of information they conduct or sponsor. 
``Collection of information'' is defined in 44 U.S.C. 3502(3) and 5 CFR 
1320.3(c) and includes agency requests or requirements that members of 
the public submit reports, keep records, or provide information to a 
third party. Section 3506(c)(2)(A) of the PRA (44 U.S.C. 3506(c)(2)(A)) 
requires Federal agencies to provide a 60-day notice in the Federal 
Register concerning each proposed collection of information before 
submitting the collection to OMB for approval. To comply with this 
requirement, FDA is publishing notice of the proposed collection of 
information set forth in this document.
    With respect to the following collection of information, FDA 
invites comments on these topics: (1) Whether the proposed collection 
of information is necessary for the proper performance of FDA's 
functions, including whether the information will have practical 
utility; (2) the accuracy of FDA's estimate of the burden of the 
proposed collection of information, including the validity of the 
methodology and assumptions used; (3) ways to enhance the quality, 
utility, and clarity of the information to be collected; and (4) ways 
to minimize the burden of the collection of information on respondents, 
including through the use of automated collection techniques, when 
appropriate, and other forms of information technology.

Experimental Study of Presentation of Quantitative Effectiveness 
Information to Consumers in Direct-to-Consumer (DTC) Television and 
Print Advertisements for Prescription Drugs--New

    The Federal Food, Drug, and Cosmetic Act (the act) requires that 
manufacturers, packers, and distributors (sponsors) who advertise 
prescription human and animal drugs, including biological products for 
humans, disclose in advertisements certain information about the 
advertised product's uses and risks.\1\ By its nature, the presentation 
of

[[Page 29491]]

this information is likely to evoke active trade-offs by consumers, 
i.e., comparisons with the perceived risks of not taking treatment, and 
comparisons with the perceived benefits of taking a treatment.\2\ FDA 
has an interest in fostering safe and proper use of prescription drugs, 
an activity that engages both risks and benefits. Therefore, an 
examination of ways to improve consumers' understanding of this 
information is central to this regulatory task.
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    \1\ For prescription drugs and biologics, section 502 of the act 
requires advertisements to contain ``information in brief summary 
relating to side effects, contraindications, and effectiveness'' (21 
U.S.C. 352(n)).
    \2\ See Swartz, L., S. Woloshin, W. Black, et al., The Role of 
Numeracy in Understanding the Benefit of Screening Mammography, 
Annals of Internal Medicine, 127(11), 966-72, 1997.
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    Under the act, FDA engages in a variety of communication activities 
to ensure that patients and health care providers have the information 
they need to make informed decisions about treatment options, including 
the use of prescription drugs. FDA regulations (21 CFR 201.57) describe 
the content of required product labeling, and FDA reviewers ensure that 
labeling contains accurate and complete information about the known 
risks and benefits of each drug.
    FDA regulations require that prescription drug advertisements that 
make (promotional) claims about a product also include risk information 
in a ``balanced'' manner (21 CFR 202.1(e)(5)(ii)), both in terms of the 
content and presentation of the information. This balance applies to 
both the front, display page of an advertisement, as well as including 
the brief summary page. However, beyond the ``balance'' requirement 
there is limited guidance and research to direct or encourage sponsors 
to present benefit claims that are informative, specific, and reflect 
clinical effectiveness data.
    Research and guidance to sponsors on how to present benefit and 
efficacy information in prescription drug advertisements is limited. 
For example, ``benefit claims,'' broadly defined, appearing in 
advertisements are often presented in general language that does not 
inform patients of the likelihood of efficacy and are often simply 
variants of an ``intended use'' statement. One content analysis of DTC 
advertising by Woloshin and Schwartz (2001)\3\ found that information 
about product benefits and risks is often presented in an unbalanced 
fashion. The researchers classified the ``promotional techniques'' used 
in the advertisements. Emotional appeals were observed in 67 percent of 
the ads while vague and qualitative benefit terminology was found in 87 
percent of the ads. Only 9 percent contained data. However, for risk 
information, half the advertisements used data to describe side-
effects, typically with lists of side-effects that generally occurred 
infrequently. Similarly, a content analysis by Frosch et al. (2007)\4\ 
found that only a small proportion of product-claim ads gave specific 
information about the population prevalence of the medical condition 
being advertised. The authors criticize DTC for presenting ``best-case 
scenarios that can distort and inflate consumers' expectations about 
what prescription drugs can accomplish'' (Froch et al., 2007, p. 12) 
without disclosing how many consumers are likely to experience that 
benefit.
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    \3\ Woloshin, S. and L. Schwartz, Direct to Consumer 
Advertisements for Prescription Drugs: What Are Americans Being 
Told, Lancet, 358, 1141-46, 2001.
    \4\ Frosch, D.L., P.M. Krueger, R.C. Hornik, et al., Creating 
Demand for Prescription Drugs: A Content Analysis of Television 
Direct-to-Consumer Advertising, Annals of Family Medicine, 5(1), 6-
13, 2007.
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    Some research has proposed that providing quantitative information 
about product efficacy enables consumers to make better choices about 
potential therapy. One possible format (termed the ``drug facts'' box 
by its creators) for this information has recently received 
attention.\5\ In these studies, the drug facts box format contained 
information about the product's efficacy and safety in terms of rate 
(how many people in the clinical trial experienced a benefit or side 
effect compared to placebo). As expected, this study showed that 
consumers who were provided efficacy information used it. Participants 
receiving efficacy information (without other potentially valuable 
information about the drug) were more likely to correctly choose the 
product with the higher efficacy than consumers who saw the brief 
summary that did not contain this information.
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    \5\ Schwartz, L.M., S. Woloshin, H.G. Welch, The Drug Facts Box: 
Providing Consumers With Simple Tabular Data on Drug Benefit and 
Harm, Medical Decision Making, 27, 655-692, 2007; Schwartz, L.M., S. 
Woloshin, H.G. Welch, Communicating Drug Benefits and Harms With a 
Drug Facts Box: Two Randomized Trials, Annals of Internal Medicine, 
150, 516-527, 2009; Woloshin, S., L.M. Schwartz, H.G. Welch, The 
Value of Benefit Data in Direct-to-Consumer Drug Ads, Health 
Affairs, Suppl Web Exclusives, W4-234-245, 2004.
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    Although these results are intriguing, additional research is 
necessary to uncover important information about how consumers 
understand effectiveness information about prescription drug products 
from DTC advertisements. For example, the research to date does not 
address whether simply adding efficacy rate information and qualitative 
summations to a consumer-friendly brief summary would enable consumers 
to find and report the correct answer, or if the presentation of 
information in a chart format itself increases comprehension.
    Further, these data cannot address the best way in which to convey 
numerical information; percents were used but another format, such as 
frequencies, may be more effective at communicating quantitative 
information. Previous research shows that individuals have great 
difficulty processing numerical concepts (e.g., Beyth-Marom, 1982; 
Bowman, 2002; Cohen, Ferrell, and Johnson, 2002).\6\ A few studies have 
attempted to determine what different formats make these concepts least 
troublesome (e.g., Fagerlin, Wang, and Ubel, 2005; Lipkus, 2007),\7\ 
however, most research into the communication of numerical concepts 
concentrates on risk information. We are not aware of research looking 
into the integration of quantitative information about effectiveness or 
benefits into the body of the advertisement itself. The addition of 
this information may help consumers make better healthcare decisions, 
provided they can understand it.
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    \6\ Beyth-Marom, R., How Probable is Probable? A Numerical 
Translation of Verbal Probability Expressions, Journal of 
Forecasting, 1, 257-269, 1982; Bowman, M.L., The Perfidity of 
Percentiles, Archives of Clinical Neuropsychology, 17, 295-303, 
2002; Cohen, D.J., J.M. Ferrell, N. Johnson, What Very Small Numbers 
Mean, Journal of Experimental Psychology: General, 131, 424-442, 
2002.
    \7\ Fagerlin, A., C. Wang, P.A. Ubel, 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, 
2005; Lipkus, I., Numeric, Verbal, and Visual Formats of Conveying 
Health Risks: Suggested Best Practices and Future Recommendations, 
Medical Decision Making, 27, 697-713, 2007.
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    It is also not known if ways of communicating product efficacy work 
equally well across print and television DTC media. To our knowledge, 
research on presenting quantitative information in risk communication 
has been conducted exclusively with static modalities. The ideal format 
for presenting quantitative information may vary as a function of 
presentation. The amount of mental processing capacity each individual 
can devote to understanding a message varies depending on how long 
individuals have to look at the material and whether the material is 
self-paced or presented at an uncontrollable speed. As a result, some 
forms of quantitative information may lend themselves to print, rather 
than broadcast. This particular understanding is crucial to the risk-
benefit tradeoff that patients must make with the consultation of a 
health care professional in order to achieve the best health outcomes.
    The proposed study will examine: (1) Various ways of communicating

[[Page 29492]]

quantitative efficacy in DTC print ads and (2) whether the findings 
translate to DTC television ads.
    Design Overview: This study will be conducted in two concurrent 
parts; one examining quantitative information in DTC print 
advertisements and the other examining such information in DTC 
television advertisements. Three factors will be examined: Drug 
efficacy, visual format, and type of statistic. Drug efficacy (low 
versus high) is defined by a quantifiable, objective metric that can be 
conveyed in graphical representations of the drug versus the comparator 
reference drug (in this case, placebo). ``High'' efficacy is noticeably 
better than the placebo, whereas ``low'' efficacy is minimally better 
than the placebo. Visual format is defined as various methods through 
which efficacy can be visually represented. We have chosen to 
investigate three different formats: Bar graph, pictograph, and pie 
chart. Type of statistic is defined as the type of statistical 
information conveyed: Frequency, relative frequency, or percentage. 
These factors will be combined in a partially crossed factorial design 
as follows:

                  Table 1.--Type of Visual Format x Type of Statistic Conveyed x Efficacy Level
----------------------------------------------------------------------------------------------------------------
                                                                           Type of Visual Format
----------------------------------------------------------------------------------------------------------------
       Type of Statistic              Efficacy Level          None        Pie Chart     Bar Chart    Pictograph
----------------------------------------------------------------------------------------------------------------
Frequency                       High Efficacy                 [check]       [check]       [check]       [check]
                               ---------------------------------------------------------------------------------
                                Low Efficacy                  [check]       [check]       [check]       [check]
----------------------------------------------------------------------------------------------------------------
Percentage                      High Efficacy                 [check]       [check]       [check]           N/A
                               ---------------------------------------------------------------------------------
                                Low Efficacy                  [check]       [check]       [check]           N/A
----------------------------------------------------------------------------------------------------------------
Combination Frequency +         High Efficacy                 [check]           N/A           N/A           N/A
 Percentage
                               ---------------------------------------------------------------------------------
                                Low Efficacy                  [check]           N/A           N/A           N/A
----------------------------------------------------------------------------------------------------------------
Relative Frequency              High Efficacy                 [check]           N/A           N/A           N/A
                               ---------------------------------------------------------------------------------
                                Low Efficacy                  [check]           N/A           N/A           N/A
----------------------------------------------------------------------------------------------------------------
Relative Frequency + Absolute   High Efficacy                 [check]           N/A           N/A           N/A
 Rate
                               ---------------------------------------------------------------------------------
                                Low Efficacy                  [check]           N/A           N/A           N/A
----------------------------------------------------------------------------------------------------------------
None                            N/A                           [check]           N/A           N/A           N/A
----------------------------------------------------------------------------------------------------------------

    The test product will be for the treatment of high cholesterol and 
modeled on an actual drug used to treat that condition (such as 
Lipitor[sscopy]). The product labeling will be used as the reference 
for defining the high- and low-efficacy levels and the objective 
metrics for clinical performances. Because both parts of the study will 
run concurrently, experimental conditions will be identical in both the 
print and television portions.
    Participants will read or view one ad version. After reading the 
ad, participants will make a series of judgments about the drug. The 
mean difference between the low- and high-efficacy condition will serve 
as the baseline for testing whether this difference varies across 
various graphical presentations, with the exception of the No 
Information (control) condition. In other words, our analyses will 
involve two steps. In step 1, within each format, we will test whether 
participants were able to distinguish between low- and high-efficacy 
drugs. In step 2, within each efficacy level, we will test whether 
participants' estimates of efficacy differ across formats and examine 
the accuracy of these estimates.
    Interviews are expected to last no more than 20 minutes. A total of 
4,500 participants will be involved in the 2 parts of the study. This 
will be a one time (rather than annual) collection of information.
    FDA estimates the burden of this collection of information as 
follows:
    The total respondent sample for this data collection is 4,500 
(2,225 in each part). We estimate the response burden to be 20 minutes, 
for a burden of 1,485 hours.
    The response burden chart is listed in table 2 of this document.

                                 Table 2.--Estimated Annual Reporting Burden\1\
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                         No. of        Annual Frequency     Total Annual        Hours per
  21 CFR Section      Respondents        per Response        Responses           Response         Total Hours
----------------------------------------------------------------------------------------------------------------
                               4,500                  1              4,500                .33              1,485
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Total                          4,500                  1              4,500                .33              1,485
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\1\There are no capital costs or operating and maintenance costs associated with this collection of information.



[[Page 29493]]

    Dated: June 15, 2009.
Jeffrey Shuren,
Associate Commissioner for Policy and Planning.

[FR Doc. E9-14501 Filed 6-19-09; 8:45 am]

BILLING CODE 4160-01-S