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

Federal Register: January 5, 2010 (Volume 75, Number 2)              
                  Page 373-379

AGENCY:  Food and Drug Administration, HHS.

ACTION:  Notice.

SUMMARY:  The Food and Drug Administration (FDA) is announcing that a 
proposed collection of information has been submitted to the Office of 
Management and Budget (OMB) for review and clearance under the 
Paperwork Reduction Act of 1995.

DATES: Fax written comments on the collection of information by 
February 4, 2010.

ADDRESSES:  To ensure that comments on the information collection are 
received, OMB recommends that written comments be faxed to the Office 
of Information and Regulatory Affairs, OMB, Attn: FDA Desk Officer, 
FAX: 202-395-6974, or e-mailed to oira_submission@omb.eop.gov. All 
comments should be identified with the OMB control number 0910-New and 
title Experimental Study: Presentation of Quantitative Effectiveness 
Information to Consumers in Direct-to-Consumer (DTC) Television and 
Print Advertisements for Prescription Drugs. Also include the FDA 
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, Elizabeth.Berbakos@fda.hhs.gov.

SUPPLEMENTARY INFORMATION: In compliance with 44 U.S.C. 3507, FDA has 
submitted the following proposed collection of information to OMB for 
review and clearance.

Experimental Study: Presentation of Quantitative Effectiveness 
Information to Consumers in Direct-to-Consumer (DTC) Television and 
Print Advertisements for Prescription Drugs--(OMB Control Number 0910-
New)

I. Background

    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 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 (Ref. 1). 
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.
---------------------------------------------------------------------------

    \1\ For prescription drugs and biologics, the act requires 
advertisements to contain ``information in brief summary relating to 
side effects, contraindications, and effectiveness'' (section 502(n) 
of the act (21 U.S.C. 352(n)).
---------------------------------------------------------------------------

    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 
information ``in brief summary'' about the advertised product's ``side 
effects, contraindications, and effectiveness''\2\ usually, but not 
always, on a separate 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.
---------------------------------------------------------------------------

    \2\ See section 502(n) of the act.
---------------------------------------------------------------------------

    FDA has recently provided guidance to sponsors about ways to 
present risk information in prescription drug advertisements (Ref. 2). 
This guidance notwithstanding, research addressing specifically 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) 
(Ref. 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) (Ref. 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'' (see p. 12 of Frosch et al.) (Ref. 4) without 
disclosing how many consumers are likely to experience that benefit.
    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 
(Refs. 5, 6, and 7). 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

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the brief summary that did not contain this information.
    Although these results are intriguing, additional research is 
necessary to uncover important information about how consumers 
understand effectiveness information about prescription drug products 
from direct-to-consumer 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) (Refs. 8, 9, and 10). 
A few studies have attempted to determine what different formats makes 
these concepts least troublesome (e.g., Fagerlin, Wang, and Ubel, 2005; 
Lipkus, 2007) (Refs. 11 and 12), 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 health care decisions, provided they can 
understand it.
    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 
quantitative efficacy in DTC print ads and (2) whether the findings 
translate to DTC television ads.
    In the Federal Register of June 22, 2009 (74 FR 29490), FDA 
published a 60-day notice requesting public comment on the proposed 
collection of information. FDA received four comments.

II. Comments on the Information Collection

    In the following section, we outline the observations and 
suggestions raised in the comments and provide our responses.
    (Statement 1) All four comments expressed support for the research 
to explore issues of quantitative benefit information. They all 
described the collection of data as a worthy endeavor which will 
provide useful information on how best to communicate information in 
DTC ads.
    (Statement 2) Two comments suggested enhancing or supplementing the 
existing behavioral intention questions (questions 13a through d in the 
questionnaire).
    (Response) We took this as an opportunity to examine our behavioral 
intention questions thoroughly. We decided to maintain three of our 
four behavioral intention questions but remove one of them because of 
possible redundancy. We also added a new item to this question on the 
basis of a comment from one of our peer reviewers. Although we took 
seriously the suggestion to inquire about use of the Internet, one of 
our existing questions already covers this issue. In the interest of 
brevity, we have decided to streamline this section.
    (Statement 3) One comment suggested including some questions about 
the risk/benefit tradeoff.
    (Response) We plan to do so and these questions can be seen in 
questions 23a through d of the questionnaire. We labeled this variable 
``attitude toward drug'' because it is easier to analyze and interpret 
using this term.
    (Statement 4) Three comments suggested adding different types of 
participants to our sample, including: (1) A general population sample, 
(2) a sample of participants suffering from a medical condition that 
they can diagnose themselves, and (3) samples of at least three 
different medical conditions.
    (Response) We selected high cholesterol because it is prevalent in 
the population and is commonly advertised DTC. We think adding a 
medical condition that is symptomatic or can otherwise be self-
diagnosed is an excellent suggestion. We hope to explore the research 
questions in the current study in a variety of other medical conditions 
in future research.
    (Statement 5) Two comments suggested comparing the test ad with 
either the standard of care or with multiple other comparators instead 
of simply comparing it to placebo.
    (Response) In response, we remind readers that this is the first 
study to examine issues of quantitative benefit information in print 
and television DTC ads and that existing literature paints a grim 
picture of the amount of numerical information viewers may be likely to 
absorb. Thus, we are using the simplest comparison for this first 
study. We agree that future studies should examine other types of 
comparisons; however, we remind readers that only comparisons that are 
in the approved product labeling can be displayed in promotional 
pieces.
    (Statement 6) One comment recommended the use of the Newest Vital 
Sign health literacy test.
    (Response) We examined this test and considered it for use in our 
design, but ultimately decided against it for a number of reasons. 
First, we would have to modify the test so that it could be 
administered over the Internet rather than in person. It is unclear how 
some aspects of the test could be altered in such a way. Second, the 
test takes approximately 3 minutes when administered in person and may 
take as long or longer to administer via computer. We believe that 
numeracy is the key component of health literacy that will influence 
the results of our study, and we have devoted considerable space in the 
questionnaire to its measurement (see questions 29a through f, 30a 
through d, and 31a through d of the questionnaire). Because of time 
constraints and the key role of numeracy, we will maintain our current 
questions to thoroughly examine numeracy and provide basic information 
on health literacy. We will also include a one-item subjective health 
literacy item (see question 28 in the questionnaire). We will continue 
to examine the Newest Vital Sign measure for future research.
    (Statement 7) Two comments expressed concern that our study does 
not address the role of the health care provider and overstates the 
decisions that consumers can make about their prescription drugs.
    (Response) We agree that the health care provider is the best 
person to interpret clinical data and that the consumer or patient does 
not make the final prescribing decision. Nonetheless,

[[Page 375]]

DTC is currently directed at consumers in such a way that they have 
information about the risk side of the risk/benefit tradeoff but no 
specific information about the benefit side. This study is designed to 
assess whether adding specific benefit information will help consumers 
understand how well the product works, which may ultimately result in 
better-informed conversations with their health care providers.
    (Statement 8) One comment suggested looking at the results of this 
study in conjunction with the results of another study we are 
conducting concerning the role of distraction in television ads in 
order to inform the development of future research.
    (Response) This is an excellent suggestion that shows a strong 
understanding of the Division of Drug Marketing, Advertising and 
Communications' (DDMAC) long-term research goals. We plan to use the 
results of these two studies, in part, to strengthen the development of 
our future research.
    (Statement 9) One comment recommended the inclusion of open-ended 
recall questions in the questionnaire.
    (Response) We have included some open-ended questions in the 
revised questionnaire (see questions 4 and 15 in the questionnaire).
    (Statement 10) One comment suggested including questions about 
perceptions of safety and efficacy. A related comment suggested using 
personal framing rather than asking about ``the average person.''
    (Response) We have included questions about safety and efficacy 
perceptions and these are shown in the revised questionnaire (see 
questions 15, 16, 17, and 20 in the questionnaire). We combed through 
the questionnaire to determine the best framing for each question. 
Where possible we added personalizing language, but in portions of the 
questionnaire that measure recall of the words in the ad, we mimicked 
the language of the ad (see questions 14a through h and 18a through i 
in the questionnaire).
    (Statement 11) One comment suggested copy testing our mock ad 
before it is included in the protocol.
    (Response) This is an excellent suggestion that cannot be 
implemented due to limited resources. Nevertheless, we conducted 
extensive pretesting of the stimuli ad for a previous project and 
applied the same procedures and concepts to the creation of the current 
mock ad. Moreover, we conducted limited cognitive testing (of fewer 
than nine people) to address such issues and these interviews provided 
some assurance that our ads were acceptable as were the ads for the 
other project.
    (Statement 12) One comment suggested that we show the ads to 
participants as they would view them at home, i.e., in a clutter reel 
of ads for the television component and in a group of magazine ads in 
the magazine component.
    (Response) Although embedding our stimuli within other ads would 
more closely mimic real viewing, we have several research questions to 
answer before we reach that point. We are not confident participants 
will understand any numerical information even when specifically 
directing them to one ad because this type of information seems to be 
so difficult for people to understand. We need to establish the basic 
parameters of statistical and visual information presentation before we 
can manipulate the realism of the situation and begin to examine other 
issues such as stopping power and attention.
    (Statement 13) One comment recommended against using the Internet 
to administer the study and instead suggested the use of a mall-
intercept protocol.
    (Response) Although we recognize that one study cannot address all 
questions and repeat that the current study is planned to be the first 
among future studies, we do require several experimental conditions to 
answer basic presentation and comprehension questions. The resources 
necessary to conduct this study using a mall-intercept procedure give 
us less than half of the participants we are currently utilizing. Given 
that we are using a nationally representative, random digit dialing-
based Internet panel to collect our experimental data, we feel that we 
are obtaining the best value for our funds. We do not feel that the 
tradeoffs in terms of external validity regarding mall-intercepts are 
favorable to that method.
    (Statement 14) One comment recommended including an analysis plan 
for review, specifically one that addresses what result(s) would 
support a conclusion that the test ad has achieved a balanced 
presentation.
    (Response) In response to the first part of this comment, we have 
included an analysis plan in this current document. In response to the 
second part of this comment, the primary research question in this 
study is not whether the information is balanced, but simply how well 
participants can understand numerical benefit information. Although we 
will address questions of balance and risk/benefit tradeoff in our 
questionnaire (see questions 23a through d in the questionnaire), our 
main dependent variables concern the recall and understanding of the 
benefit information, independent of the other information in the ad. 
Secondarily, we will examine recall and comprehension of risk 
information to assess whether it is affected by the inclusion of 
benefit information and the form the benefit information takes. 
Finally, we will look at the intersection of benefit and risk 
information, primarily in risk and benefit perception questions. Our 
main analyses, however, involve the understanding of benefit 
information and not in the balance of benefit and risk information. 
That is an excellent suggestion for future research.
    (Statement 15) One comment expressed concern that high efficacy may 
not be the only reason to select one drug over another.
    (Response) We agree. The current research is not designed to 
examine the multiple factors that a physician or a consumer considers 
when prescribing or deciding to take a drug. The scope of this project 
is to investigate the presentation of quantitative benefit information. 
We have chosen to vary the efficacy of the product (high versus low) as 
a simple method for determining whether viewers can understand how well 
the product works when this information is presented in different 
forms. We maintain that the efficacy of the drug is a major 
consideration in this decision and therefore represents a reasonable 
variable to use in this study.
    (Statement 16) One comment was concerned that data presentation, 
and in particular the relative frequency presentation, would confuse 
consumers.
    (Response) This comment reflects the very reason we are conducting 
the study. Before considering the idea of adding quantitative benefit 
information to DTC advertising, we want to ensure that we are not 
causing people to become more confused about their options. We have 
included the relative frequency condition specifically because we 
believe consumers do have trouble understanding this format. Sponsors 
have expressed interest in using this format in their ads and therefore 
this is a particularly important experimental condition for testing.
    (Statement 17) One comment suggested that we ask questions about 
participant age and education.
    (Response) We ask these and other demographic questions in this 
study (see questions 39 through 45 in the questionnaire).
    (Statement 18) One comment mentioned that subjective measures of 
drug efficacy may confuse viewers.

[[Page 376]]

    (Response) We will define high and low efficacy quantitatively 
based on the range of efficacy currently found in the drug class. We 
will ask perception questions on Likert scales (e.g., strongly agree to 
strongly disagree) as well as numerical scales.
    (Statement 19) One comment suggested that we are basing our entire 
study on an outdated study from 2001.
    (Response) First, we provided information about the 2001 study to 
provide background information because it is relevant to the current 
study but have not based our entire research on it. Second, it is 
unclear what basic principles of human communication will have changed 
in the 8 years that have passed since the publication of this one 
study. Finally, although this one study shows that researchers in the 
field are investigating similar issues, no research currently exists to 
answer our research questions about the understanding of quantitative 
information in print and television DTC advertisements.
    (Statement 20) One comment suggested that 20 minutes is not 
adequate for participants to complete this study.
    (Response) We have completed similar studies in the past within 20 
minutes. We will conduct cognitive testing before the administration of 
the study to ensure that the protocol can be completed within 20 
minutes. Interviews lasting longer than 20 minutes have shown that 
participants tend not to want to spend that much time on them. 
Therefore, we will maintain the study at 20 minutes or less.

III. Revised Study

    Based in part on these comments, further research discussions, and 
the input of three external reviewers, we propose the following revised 
design, hypotheses, and analysis plan.

A. 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, statistical format, and visual 
format.
    We will investigate two levels of drug efficacy (low versus high), 
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). Specifically, high efficacy will be 
defined by a large, noticeable difference compared with no treatment; 
whereas low efficacy will be defined by a minimal difference between 
the drug and no treatment. We will examine two levels of efficacy to 
determine whether participants can accurately distinguish between these 
levels within various formats.
    We will investigate five statistical formats, defined as the type 
of statistical information conveyed: Frequency, percent, frequency plus 
percent, relative frequency, and frequency plus relative frequency. 
Based on existing literature, we will use the frequency statistical 
format in all of our visual formats for consistency.
    Visual format is defined as various methods through which efficacy 
can be visually represented. We have chosen to investigate four 
different formats: Pie chart, bar chart, table, and pictograph.
    Additionally, we will have a control condition with no specific 
efficacy information provided. Please see the sample stimuli for the 
operationalization of each of these conditions. The factors will be 
combined in a partially crossed factorial design as follows:


--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                 Statistical Format
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                                                          Frequency +
                                                               Frequency           Percent          Frequency +          Relative           Relative
                                                                                                      Percent           Frequency          Frequency
--------------------------------------------------------------------------------------------------------------------------------------------------------
Efficacy                                              Low  .................  .................  .................  .................  .................
                                       -----------------------------------------------------------------------------------------------------------------
                                                     High  .................  .................  .................  .................  .................
--------------------------------------------------------------------------------------------------------------------------------------------------------

and


--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                     Visual Format
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                     None            Pie Chart          Bar Chart            Table          Pictograph
--------------------------------------------------------------------------------------------------------------------------------------------------------
Efficacy                       Low                            .................  .................  .................  .................  ..............
                              --------------------------------------------------------------------------------------------------------------------------
                               High                           .................  .................  .................  .................  ..............
--------------------------------------------------------------------------------------------------------------------------------------------------------

+ 1


------------------------------------------------------------------------

------------------------------------------------------------------------
No Statistical Format/No Efficacy                      .................
------------------------------------------------------------------------

B. Procedure

    This study will be administered over the Internet. A total of 2,250 
interviews involving print ads will be completed. Participants in this 
part of the study will be randomly assigned to view one version of the 
magazine promotion page and the brief summary page of a prescription 
drug ad. Following their perusal of this document, they will answer 
questions about their recall and

[[Page 377]]

understanding of the benefit and risk information, their perceptions of 
the benefits and risks of the drug, and their intent to ask a doctor 
about the medication.
    A total of 2,250 interviews involving television ads will be 
completed. Participants in this part of the study will be randomly 
assigned to view one version of a television ad twice and answer the 
same questions described in the previous paragraph.
    For both parts, demographic and health care utilization information 
will be collected. The entire procedure is expected to last 
approximately 20 minutes. This will be a one-time (rather than annual) 
information collection.

C. Participants

    Data will be collected using an Internet protocol. Participants 
will all have reported that a health care professional has diagnosed 
them with high cholesterol and will represent a range of education 
levels. Because the task presumes basic reading abilities, all selected 
participants must speak English as their primary language. Participants 
must be 18 years or older.

D. Hypotheses

1. Preface
    The proposed research has two main objectives. First, we plan to 
test several statistical formats to determine whether the presentation 
of efficacy information in different formats affects perceptions of 
efficacy. The risk communication literature suggests that presenting 
numerical risk information as an absolute frequency (e.g., N out of 
100) may be the most easily understood format (Fagerlin et al., 2007) 
(Ref. 13). Percent, and a combination of absolute frequency and 
percent, represent increasingly complex statistical formats; however, 
they may not differ from the baseline of absolute frequency for average 
consumers. In contrast, the risk communication literature suggests that 
presenting numerical risk information as a relative frequency (e.g., 10 
times higher) is a markedly more complex statistical format that biases 
perceptions (Fagerlin et al., 2007) (Ref. 13). Thus, presenting 
efficacy information as a relative frequency, compared to absolute 
frequency, may affect perceptions of efficacy. Presenting the 
combination of absolute frequency and relative frequency may mitigate 
this effect.
    Second, we plan to test several visual formats to determine whether 
the presentation of a visual format, in conjunction with the 
presentation of absolute frequency information, affects perceptions of 
efficacy. The risk communication literature suggests that the addition 
of visual formats such as bar charts, tables, and pictographs increase 
peoples' understanding of numerical information (Ancker et al., 2006; 
Lipkus and Hollands, 1999) (Refs. 14 and 15). However, not all visual 
formats are always helpful; for instance, pie charts may only help when 
people are comparing proportions (Lipkus, 2007) (Ref. 12). Thus, 
presenting efficacy information with a bar chart, table, and 
pictograph--but not necessarily with a pie chart--may affect people's 
understanding of efficacy information, in comparison to when there is 
no visual format.
    Measuring numeracy will allow us to assess the magnitude of these 
effects across participants. Similarly, the separate TV and print 
portions of the study will allow us to assess the magnitude of these 
effects across these modalities.
2. Specific Hypotheses
    a. Efficacy effects in print and TV ads.
    (1) Behavioral intentions, attitude toward drug, and perceived 
efficacy will be higher in high efficacy conditions than in low 
efficacy conditions.
    (2) We will explore whether there are differences between the no 
efficacy condition (control) and the low and high efficacy condition on 
behavioral intentions, attitude toward drug, and perceived efficacy.
    (3) Benefit accuracy will be higher in the low and high efficacy 
conditions than in the no efficacy condition. There will be no 
difference between the low and high efficacy conditions.
    (4) The effects tested in hypotheses (1) and (2), explained 
previously in section III.D.2 of this document, will be modified by 
numeracy, such that high numeracy participants will be more likely to 
show these effects than will low numeracy participants.
    (5) Risk recall will not differ by efficacy level (no, low, high).
    (6) Perceived risk will be lower in the high efficacy condition 
compared with the low efficacy condition because, according to the 
Affect Heuristic (Slovic and Peters, 2006) (Ref. 16), people perceive 
things that are more beneficial as less risky.
    b. Statistical format effects in print and TV ads.
    (1) We will test competing hypotheses for behavioral intentions, 
attitude toward drug, and perceived efficacy.
    (1a) Overestimation hypothesis: The first hypothesis rests on the 
assumption that in the absence of any quantitative information people 
overestimate the effectiveness of drugs. Accordingly, we would predict 
that behavioral intentions, attitude toward drug, and perceived 
efficacy will be higher for participants in the no statistical format 
condition, compared to all other statistical format conditions. Support 
for this interpretation will be found if estimates of the benefits are 
higher in the no statistical format condition than in all other 
statistical format conditions.
    (1b) Peripheral cue hypothesis: The competing hypothesis rests on 
the assumption that any statistical information will be used as a 
peripheral cue; that is, participants will not process the quantitative 
information provided in the various statistical formats but will rather 
view it as ``scientific proof'' of the drug's efficacy. Accordingly, we 
would predict that behavioral intentions, attitude toward drug, and 
perceived efficacy will be lower for participants in the no statistical 
format condition, compared to all other statistical format conditions. 
Support for this interpretation will be found if, in addition to 
perceived efficacy effects, estimates on attitude toward the ad 
``peripheral cue'' measures--ratings of how believable, persuasive, 
informative, etc., the ad is--are lower in the no statistical format 
condition than in all other statistical format conditions.
    (2) Based on the risk communication literature, we predict that the 
absolute frequency, percent, and absolute frequency and percent 
conditions may not differ on behavioral intentions, attitude toward 
drug, or perceived efficacy. However, we predict that behavioral 
intentions, attitude toward drug, and perceived efficacy will be higher 
in the relative frequency condition than in the absolute frequency, 
percent, absolute frequency + percent, and absolute frequency + 
relative frequency conditions.
    (3) The effects tested in hypotheses (1) and (2) will be modified 
by numeracy. (See sections III.D.1 through 2 of this document.) For 
instance, we expect that the difference between the relative frequency 
and the absolute frequency + relative frequency conditions will be 
greater for high numeracy participants than for low numeracy 
participants (because high numeracy participants will be more likely to 
use the additional information provided by the absolute frequency).
    (4) Benefit accuracy will be lowest in the no statistical format 
condition and highest in the absolute frequency condition (Slovic, 
Monahan, and MacGregor, 2000) (Ref. 17). Tests of other relations 
between statistical formats will be exploratory. For instance, we might 
see information overload with some formats (e.g., absolute frequency 
and relative

[[Page 378]]

frequency) which impedes benefit accuracy.
    (5) The effects tested in hypothesis (4) will be modified by 
numeracy, such that low numeracy participants will show greater 
differences in benefit accuracy across statistical formats than will 
high numeracy participants (Peters, Vastfjall, et al., 2006) (Ref. 18).
    (6) We expect that risk recall will not differ by statistical 
format, but we will conduct exploratory analyses to determine whether 
information overload impedes risk recall.
    (7) We expect that perceived risk will be lowest in the relative 
frequency condition if perceived benefit is indeed highest in this 
condition (see Slovic and Peters, 2006, reference 16 of this document).
    c. Visual format effects in print and TV ads.
    (1) We will test competing hypotheses for benefit accuracy, 
behavioral intentions, attitude toward drug, and perceived efficacy.
    (1a) Visual information facilitation hypothesis: The first 
hypothesis rests on the assumption that participants will, to the 
extent possible, process and use the information in the visual formats. 
The risk communication literature suggests that visual representations 
of risk can increase understanding, and that people have a more 
difficult time processing this kind of information in pie charts, as 
compared to other visual formats. Therefore, our first hypothesis is 
that benefit accuracy will be higher in the bar chart, table, and 
pictograph conditions--but not necessarily the pie chart condition--
than in the no visual format condition. Tests of other relations 
between visual formats will be exploratory.
    (1b) Information overload hypothesis: Alternatively, there may be 
no differences across visual formats on behavioral intentions, attitude 
toward drug, perceived efficacy, or benefit accuracy if the visual 
serves as a distraction or is too much information to process.
    (1c) Peripheral cue hypothesis: Behavioral intentions, attitude 
toward drug, and perceived efficacy--but not benefit accuracy--may be 
higher in all visual conditions than in the no visual condition if the 
visual information serves as a peripheral cue.
    (2) The effects tested in hypothesis (1) will be modified by 
numeracy. For instance, we expect that high numeracy participants will 
be more likely to process the information in the visual formats, and 
thus more likely to show the pattern of effects outlined in 1a, 
compared to low numeracy participants.
    (3) We expect that perceived risk and risk recall will not differ 
by visual format but we will conduct exploratory analyses to determine 
whether information overload impedes risk recall.

E. Analysis Plan

    We will conduct the following statistical analyses separately for 
the print and television versions of the ad.
    Efficacy effects in print and TV ads: We will conduct Analysis of 
Variance (ANOVAs) to test whether the no statistical format/no efficacy 
condition differs from the low and high efficacy condition on the 
dependent measures (i.e., benefit accuracy, behavioral intentions, 
attitude toward drug, perceived efficacy, perceived risk, and risk 
recall, peripheral cue measures). We will conduct these analyses both 
with and without covariates (e.g., demographic and health 
characteristics) included in the model. In addition, we will test 
whether any main effects are moderated by other measured variables 
(e.g., numeracy, demographic, and health characteristics). If the main 
effect of efficacy is significant, we will conduct pairwise-comparisons 
to determine which conditions are significantly different from one 
another. We will also conduct planned comparisons in line with our 
hypotheses (see section III.D of this document). In addition, the main 
effect of efficacy (low vs. high) and any interaction it has with 
statistical format or visual format will be tested in the ANOVAs 
presented in the following two sections.
    Statistical format effects in print and TV ads: We will conduct 
ANOVAs to test whether the no statistical format/no efficacy condition 
differs from the other statistical format conditions on the dependent 
measures. In addition, we will examine the main effect of statistical 
format in ANOVAs predicting our dependent measures from statistical 
format, efficacy level, and their interaction. We will conduct these 
analyses both with and without covariates included in the model. In 
addition, we will test whether any main effects are moderated by other 
measured variables. If the main effect of statistical format is 
significant, we will conduct pairwise-comparisons statistical tests to 
determine which conditions are significantly different from one 
another. We will also conduct planned comparisons in line with our 
hypotheses. (See section III.D of this document.)
    Visual format effects in print and TV ads: To test our hypotheses 
regarding visual format, we will examine the main effect of visual 
format in ANOVAs predicting our dependent measures from visual format, 
efficacy level, and their interaction. We will conduct these analyses 
both with and without covariates included in the model. In addition, we 
will test whether any main effects are moderated by other measured 
variables. If the main effect of visual format is significant, we will 
conduct pairwise-comparisons to determine which conditions are 
significantly different from one another. We will also conduct planned 
comparisons in line with our hypotheses. (See section III.D of this 
document.)
    The total annual estimated burden imposed by this collection of 
information is 1,755 hours for this one-time collection (table 1 of 
this document).

                                 Table 1.--Estimated Annual Reporting Burden\1\
----------------------------------------------------------------------------------------------------------------
                        No. of         Annual Frequency       Total Annual       Hours per
    Activity         Respondents         per Response          Responses          Response        Total Hours
----------------------------------------------------------------------------------------------------------------
Screener                      9,000                     1              9,000             2/60                270
----------------------------------------------------------------------------------------------------------------
Questionnaire                 4,500                     1              4,500            20/60              1,485
----------------------------------------------------------------------------------------------------------------
Total                                                                                                      1,755
----------------------------------------------------------------------------------------------------------------
\1\There are no capital costs or operating and maintenance costs associated with this collection of information.


[[Page 379]]

    These estimates are based on FDA's experience with previous 
consumer studies.

IV. References

    The following references have been placed on display in the 
Division of Dockets Management (HFA-305), Food and Drug Administration, 
5630 Fishers Lane, rm. 1061, Rockville, MD 20852, and may be seen by 
interested persons between 9 a.m. and 4 p.m., Monday through Friday.
    1. Schwartz, 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.
    2. Draft Guidance for Industry: Presenting Risk Information in 
Prescription Drug and Medical Device Advertising, available at 
http://www.fda.gov/downloads/Drugs/
GuidanceComplianceRegulatoryInformation/Guidances/UCM155480.pdf.
    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.
    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.
    6. Schwartz, L.M., S. Woloshin, H.G. Welch, Communicating Drug 
Benefits and Harms Wth a Drug Facts Box: Two Randomized Trials, 
Annals of Internal Medicine, 150, 516-527, 2009.
    7. Woloshin, S., L.M. Schwartz, H.G. Welch, The Value of Benefit 
Data in Direct-to-Consumer Drug Ads, Health Affairs, Web Exclusive 
Supplement, W4-234-245, 2004.
    8. Beyth-Marom, R., How Probable is Probable? A Numerical 
Translation of Verbal Probability Expressions, Journal of 
Forecasting, 1, 257-269, 1982.
    9. Bowman, M.L., The Perfidity of Percentiles, Archives of 
Clinical Neuropsychology, 17, 295-303, 2002.
    10. Cohen, D.J., J.M. Ferrell, N. Johnson, What Very Small 
Numbers Mean, Journal of Experimental Psychology: General, 131, 424-
442, 2002.
    11. 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.
    12. Lipkus, I., Numeric, Verbal, and Visual Formats of Conveying 
Health Tasks: Suggested Best Practices and Future Recommendations, 
Medical Decision Making, 27, 697-713, 2007.
    13. Fagerlin, A., P.A. Ubel, D.M. Smith, et al., Making Numbers 
Matter: Present and Future Research in Risk Communication, American 
Journal of Health Behavior, 31, Supplement 1: S47-56, 2007.
    14. Ancker, J.S., Y. Senathirajah, R. Kukafka, et al., Design 
Features of Graphs in Health Risk Communication: A Systematic 
Review, Journal of the American Medical Information Association, 13, 
608-618, 2006.
    15. Lipkus, I., J.G. Hollands, The Visual Communication of Risk, 
Journal of the National Cancer Institute Monographs, 25, 149-163, 
1999.
    16. Slovic, P. and E. Peters, Risk Perception and Affect, 
Current Directions in Psychological Science, 15, 322-325, 2006.
    17. Slovic, P., J. Monahan, DG MacGregor, Violence Risk 
Assessment and Risk Communication: The Effects of Using Actual 
Cases, Providing Instruction, and Employing Probability Versus 
Frequency Formats, Law and Human Behavior, 24, 271-96, 2000.
    18. Peters, E., D. Vastfjall, P. Slovic, et al., Numeracy and 
Decision Making, Psychological Science, 17, 407-13, 2006.

    Dated: December 23, 2009.
David Horowitz,
Assistant Commissioner for Policy.
[FR Doc. E9-31200 Filed 1-4-10; 8:45 am]

BILLING CODE 4160-01-S