[Federal Register Volume 81, Number 53 (Friday, March 18, 2016)]
[Notices]
[Pages 14855-14859]
[FR Doc No: 2016-06126]

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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Food and Drug Administration

[Docket No. FDA-2015-N-3543]

Agency Information Collection Activities; Submission for Office
of Management and Budget Review; Comment Request; Quantitative
Information in Direct-to-Consumer Television Advertisements

AGENCY: Food and Drug Administration, HHS.

ACTION: Notice.

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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 April
18, 2016.

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:<PHONE_NUMBER>, or emailed to<EMAIL_ADDRESS>All
comments should be identified with the OMB control number 0910-New and
title ``Quantitative Information in Direct-to-Consumer Television
Advertisements.'' Also include the FDA docket number found in brackets
in the heading of this document.

FOR FURTHER INFORMATION CONTACT: FDA PRA Staff, Office of Operations,
Food and Drug Administration, 8455 Colesville Rd., COLE-14526, Silver
Spring, MD 20993-0002<EMAIL_ADDRESS>
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.

Quantitative Information in Direct-to-Consumer Television
Advertisements OMB Control Number 0910--NEW

I. Background

    Section 1701(a)(4) of the Public Health Service Act (42 U.S.C.
300u(a)(4)) authorizes FDA to conduct research relating to health
information. Section 1003(d)(2)(C) of the Federal Food, Drug, and
Cosmetic Act (the FD&C Act) (21 U.S.C. 393(d)(2)(C)) authorizes FDA to
conduct research relating to drugs and other FDA regulated products in
carrying out the provisions of the FD&C Act.
    A previous FDA study found that simple quantitative information
could be conveyed in direct-to-consumer (DTC) television ads in ways
that increased consumer's knowledge about the drug (OMB control number
0910-0663, ``Experimental Study: Presentation of Quantitative
Effectiveness Information to Consumers in Direct-to-Consumer (DTC)
Television and Print Advertisements for Prescription Drugs'') (Ref. 1).
However, this research only tested simple information (e.g., one
clinical trial, comparison to placebo). Drug information can be much
more complicated (e.g., complicated endpoints, multiple study arms).
The

following studies are designed to address the question of whether
consumers can use more complicated information when assessing
prescription drug information in television DTC ads. These studies will
build on previous research by: (1) Examining more complicated
quantitative information, (2) examining quantitative information for
both benefits and risks, and (3) examining how visuals designed to
represent efficacy interact with quantitative information.
    The objective of this project is to test consumers' understanding
of quantitative information about prescription drugs in DTC television
ads. In study 1, we plan to examine experimentally the presence and
complexity of quantitative benefit and risk information in DTC
television ads (table 1). We hypothesize that, replicating past
studies, adding simple quantitative information about benefits and
risks will lead to increased understanding among consumers. We will
test whether adding complex quantitative information results in the
same outcomes as simple quantitative information or whether it is too
much quantitative information for consumers to process. In study 2, we
plan to examine experimentally the presence of quantitative benefit
information and how the ad visually represents efficacy (by having no
images, images that accurately reflect the improvement in health that
could be expected with treatment, or images that overstate the
improvement in health that could be expected with treatment (table 2)).
We hypothesize that overstated images of improvement will lead
consumers to overestimate the drug's efficacy; however, adding a
quantitative claim may moderate this effect. To test these hypotheses,
we will conduct inferential statistical tests such as analysis of
variance (ANOVA). With the sample sizes described in this document, we
will have sufficient power to detect small-to medium-sized effects in
each study.
    All participants will be 60 years of age or older. We will exclude
individuals who work in health care or marketing. We selected a sample
of participants 60 years and older to increase the likelihood that
participants will be interested in the fictitious study drug and
therefore motivated to pay attention to the ad during the study. The
studies will be conducted with an Internet panel.
    In both studies, participants will be randomly assigned to one
experimental condition and view the corresponding television ad. The ad
will be for a fictitious drug to treat cataracts. The ads will be
created and pretested to ensure that consumers perceive different
levels of complexity across the ads in study 1 and different levels of
image accuracy in study 2. ``Pretests for a Study on Quantitative
Information in Direct-to-Consumer Television Advertisements'' was
submitted under OMB control number 0910-0695. After viewing the ad
twice, participants will complete a questionnaire that assesses
consumers' understanding of the drug information, their retention of
the information, and their perceptions of the drug. We will also
measure covariates such as demographics and numeracy. The
questionnaires are available upon request.

                                             Table 1--Study 1 Design
----------------------------------------------------------------------------------------------------------------

----------------------------------------------------------------------------------------------------------------
                                                                        Quantitative risk claim
----------------------------------------------------------------------------------------------------------------
                                                       No..............  Yes: General (e.g.,  Yes: Specific
                                                                          Side effects that    (e.g., Side
                                                                          occur in 10% or      effects that
                                                                          less of people who   occur in [6-10%,
                                                                          take Drug X          1-5%, and less
                                                                          include . . .).      than 1%] of
                                                                                people who take
                                                                                Drug X include .
                                                                                . .).
Quantitative Efficacy Claim.....  No.................
                                  Yes: Single outcome
                                   (e.g., 52% of
                                   people with
                                   cataracts improved
                                   their vision to 20/
                                   40 while taking
                                   Drug X compared to
                                   23% without Drug
                                   X. [starting at an
                                   average baseline
                                   of 20/70]).
                                  Yes: Multiple
                                   outcomes (e.g.,
                                   52% of people with
                                   cataracts improved
                                   their vision to 20/
                                   40 while taking
                                   Drug X compared to
                                   23% without Drug
                                   X. [starting at an
                                   average baseline
                                   of 20/70]. With
                                   Drug X, people
                                   could see an
                                   average of 85
                                   letters on a 100-
                                   letter eye chart,
                                   compared to 73
                                   letters without
                                   Drug X.).
----------------------------------------------------------------------------------------------------------------

                                             Table 2--Study 2 Design
----------------------------------------------------------------------------------------------------------------

----------------------------------------------------------------------------------------------------------------
                                                                         Images of improvement
----------------------------------------------------------------------------------------------------------------
                                                       None............  Accurate             Overstated
                                                                          improvement in       improvement in
                                                                          health conveyed in   health conveyed
                                                                          images.              in images.
Quantitative Benefit Claim......  No
                                  Yes (Single
                                   outcome).
----------------------------------------------------------------------------------------------------------------

    In the Federal Register of October 13, 2015 (80 FR 61433), FDA
published a 60-day notice requesting public comment on the proposed
collection of information. Four public comments were received. Two
comments called for direct-to-consumer prescription drug advertising to
be banned. These comments are outside the scope of the current project.
Other comments and their responses follow.
    (Comment 1) The first suggestion was that FDA should research the
health literacy of approved patient labeling before conducting research
on DTC television advertising.
    (Response) FDA has a program of research that includes studies on
both patient labeling and DTC television advertising (Refs. 1 to 3).
This study extends previous research and addresses issues unique to DTC
television advertising (e.g., visual representations of efficacy) (Ref.
1). The public is exposed to information about prescription drugs via
DTC television advertising and this advertising has a public health
impact (Refs. 4 and 5). We disagree that there is a need for approved
patient labeling research to be conducted before we study issues unique
to DTC television advertising.
    (Comment 2) The second suggestion is to consider that because low
numeracy individuals are not well-represented in online panels we
should implement mechanisms to help validate results across health-
literate populations.
    (Response) We agree that numeracy may be a crucial variable in this
study. We have added a second measure of numeracy (subjective numeracy)
and a question on health literacy. We will use these measures to
determine whether and how numeracy and health literacy affect our
results. If our sample has few individuals with low numeracy, we will
note this as a limitation.
    (Comment 3) The third suggestion is to use a mixed-method approach,
recruiting limited-literacy and low socioeconomic participants for in-
person administration of the study and using the Internet panel to
gather a broad sample.
    (Response) We acknowledge that Internet administration is not
perfect and have chosen this method to maximize our budget. We will
permit the survey to be taken on a variety of devices. We are excluding
phones because the stimuli cannot be fully viewed on a very small
screen.
    (Comment 4) The fourth suggestion is to use frequencies rather than
percentages in the questionnaire.
    (Response) A recent review of the literature did not support the
view that frequencies are more widely understood than percentages (Ref.
6). This review included two studies conducted in the context of DTC
advertising (Refs. 1 and 7). Given these findings, we plan to use
percentages in the questionnaire.
    (Comment 5) The fifth suggestion is to include a single-item health
literacy question to the screener.
    (Response) We agree this is an important measure and have added it
to the questionnaire.
    (Comment 6) This comment requests further rationale for the
selection of an older patient population and its impact on the
generalizability of study findings to advertisements targeted for
younger patient populations.
    (Response) Advertising studies often recruit participants who have
or who are at risk for the medical condition being advertised to
increase interest in the ad and motivation to pay attention to the ad.
Older participants are more likely to be at risk for cataracts. In
addition, older adults use more prescription drugs and watch more
television than younger adults do (Refs. 8 and 9). We will note that
the study is not broadly generalizable when we report our findings.
    (Comment 7) This comment suggests including a video compatibility
test to verify that participants can view the videos and precluding
participants from taking the survey using a smartphone device.
    (Response) We have added a video compatibility test to the study
and will preclude participants from using phones.
    (Comment 8) This comment also sought clarification on which stimuli
from study 1 will be used in study 2.
    (Response) The benefit information in study 2 will be the
``simple'' claim from study 1. Study 2 will not include quantitative
risk information. This means that the same ad will be used in the
``simple quantitative benefit claim/no quantitative risk claim''
condition in study 1 and the ``quantitative benefit claim/no images of
improvement'' condition in study 2.
    (Comment 9) This comment expresses concern that adding complex
benefit information in study 1 may cause the content to become
unmanageable and suggests adding study arms with more of fewer risks
and benefits to assess this.
    (Response) Based on this comment and peer reviewer feedback, we
will manipulate the complexity of quantitative efficacy claim by adding
a second benefit outcome. We have revised the study design tables to
reflect this (see tables 1 and 2). The number of risks will be constant
but we will manipulate whether and how the frequencies of the risks are
presented.
    (Comment 10) This comment recommended holding all other aspects
outside the variable being tested be held constant across the different
treatments.
    (Response) We agree with this recommendation. We will create one ad
that will be the basis of all the stimuli. We will manipulate this base
ad by adding quantitative benefit information, quantitative risk
information, and/or images of improvement to create the different
experimental conditions, while leaving other factors constant.
    (Comment 11) This comment recommends using scales with a neutral
midpoint.
    (Response) There are advantages and disadvantages to including
midpoints in scales (Refs. 10 and 11). Based on responses from similar
studies, we have decided to use scales without a midpoint. Instead, we
have included a ``don't know'' option for some items that may make
participants' responses easier to interpret than a neutral midpoint
would.
    (Comment 12) This comment noted that without the stimuli it was
difficult to tell whether the battery of questions measuring efficacy
accuracy was redundant or inapplicable.
    (Response) We did not create the stimuli before the public notice
so that the public and peer review comments, along with cognitive
interviews and pretesting, could inform the creation of the stimuli.
Based on peer review, we refined our efficacy claims. We tailored the
efficacy accuracy items to reflect the new claims. Some of these
questions are designed to measure participants' gist understanding of
the drugs' efficacy likelihood and magnitude (Ref. 12). They are not
redundant with the questions designed to measure participants' verbatim
understanding of the drugs' efficacy likelihood and magnitude. As in
previous research, participants in the control condition will not have
the information to answer all the accuracy questions (Ref. 1). Instead,
this condition serves as a baseline with which to compare the
experimental conditions. We added a ``don't know'' option so that these
participants can report that they do not know the answer.
    (Comment 13) This comment suggested reordering questions so that
the perception and intention questions appeared before the questions
about efficacy and risk information.
    (Response) Based on peer review, we moved the gist questions before
the accuracy questions, but we did not move intentions and perceptions
before gist and accuracy. We understand the value in getting obtaining
intentions and perceptions unbiased by the other

measures. However, we put the gist and accuracy measures first because
they are our primary measures; therefore, we want to decrease potential
memory decay and ensure the gist and accuracy measures are not biased.
    (Comment 14) This comment questioned whether three risk claim
accuracy questions in study 1 were redundant with each other and how
the stimulus will list frequencies for the risks.
    (Response) We updated table 1 to show how risks will be described
in each condition. The terms ``least common'' and ``most common'' will
not be used in the ads. The questions are not redundant. One question
(previously Q17) asks participants to report the frequency for each
risk. The other two questions (previously Q20 and Q21) ask participants
whether they got the ``gist'' of how common the risks are. If
participants are able to understand the gist of the information, then
those in the two quantitative risk information conditions should be
able to report that the most common risks had a frequency of roughly 10
percent and participants in the specific quantitative risk information
condition should be able to report that the least common risks had a
frequency of roughly 1 percent. We will cognitively test and pretest
these items.
    (Comment 15) This comment suggests adding ``don't know'' options to
the perceived efficacy and risk questions.
    (Response) We added a ``don't know'' option to the questions that
ask participants to compare the advertised drug's risks and benefits to
other treatments.
    FDA estimates the burden of this collection of information as
follows:

                                                 Table 3--Estimated Annual Reporting Burden \1\--Study 1
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                                                                 Number of
                  Activity                       Number of     responses per   Total annual           Average burden per response           Total hours
                                                respondents     respondent       responses
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Sample outgo................................          15,130  ..............  ..............  ..........................................  ..............
Number to complete the screener (10%).......           1,513               1           1,513  0.05 (3 minutes)..........................              76
Number eligible for survey (70%)............           1,059  ..............  ..............  ..........................................  ..............
Number to complete the survey (85%).........             900               1             900  0.33 (20 minutes).........................             297
                                             -----------------------------------------------------------------------------------------------------------
    Total...................................  ..............  ..............           2,413  ..........................................             373
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\1\ There are no capital costs or operating and maintenance costs associated with this collection of information.

                                                 Table 4--Estimated Annual Reporting Burden \1\--Study 2
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                                                                 Number of
                  Activity                       Number of     responses per   Total annual           Average burden per response           Total hours
                                                respondents     respondent       responses
--------------------------------------------------------------------------------------------------------------------------------------------------------
Sample outgo................................          15,130  ..............  ..............  ..........................................  ..............
Number to complete the screener (10%).......           1,513               1           1,513  0.05 (3 minutes)..........................           75.65
Number eligible for survey (70%)............           1,059  ..............  ..............  ..........................................  ..............
Number to complete the survey (85%).........             900               1             900  0.33 (20 minutes).........................             297
                                             -----------------------------------------------------------------------------------------------------------
    Total...................................  ..............  ..............           2,413  ..........................................          372.65
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\1\ There are no capital costs or operating and maintenance costs associated with this collection of information.

II. References

    The following references are on display in the Division of Dockets
Management (HFA-305), Food and Drug Administration, 5630 Fishers Lane,
Rm. 1061, Rockville, MD 20852, and are available for viewing by
interested persons between 9 a.m. and 4 p.m., Monday through Friday;
they are also available electronically at http://www.regulations.gov.
FDA has verified the Web site addresses, as of the date this document
publishes in the Federal Register, but Web sites are subject to change
over time.

1. O'Donoghue, A.C., H.W. Sullivan, K.J. Aikin, et al., ``Presenting
Efficacy Information in Direct-To-Consumer Prescription Drug
Advertisements,'' Patient Education and Counseling, 95(2):271-280,
2014.
2. Boudewyns, V., A.C. O'Donoghue, B. Kelly, et al., ``Influence of
Patient Medication Information Format on Comprehension and
Application of Medication Information: A Randomized, Controlled
Experiment,'' Patient Education and Counseling, 98(12):1592-1599,
2015.
3. Kish-Doto, J., M. Scales, P. Equino-Medina, et al., ``Preferences
for Patient Medication Information: What Do Patients Want?'' Journal
of Health Communication, 19(suppl 2):77-88, 2014.
4. Brownfield, E.D., J.M. Bernhardt, J.L. Phan, et al., ``Direct-To-
Consumer Drug Advertisements on Network Television: An Exploration
of Quantity, Frequency, and Placement,'' Journal of Health
Communication, 9(6):491-497, 2004.
5. Niederdeppe, J., S. Byrne, R.J. Avery, et al., ``Direct-To-
Consumer Television Advertising Exposure, Diagnosis With High
Cholesterol, and Statin Use,'' Journal of General Internal Medicine,
28(7):886-893, 2013.
6. Zipkin, D.A., C.A. Umscheid, N.L. Keating, et al., ``Evidence-
Based Risk Communication: A Systematic Review,'' Annals of Internal
Medicine, 161:270-280, 2014.
7. Woloshin, S. and L.M. Schwartz, ``Communicating Data About the
Benefits and Harms of Treatment: A Randomized Trial,'' Annals of
Internal Medicine, 155:87-96, 2011.
8. Zhong, W., H. Maradit-Kremers, J.L. St. Sauver, et al., ``Age and
Sex Patterns of Drug Prescribing in a Defined American Population,''
Mayo Clinic Proceedings, 88(7):697-707, 2013.
9. Depp, C.A., D.A. Schkade, W.K. Thompson, et al., ``Age, Affective
Experience, and Television Use,'' American Journal of Preventive
Medicine, 39:173-178, 2010.
10. Moors, G., ``Exploring the Effect of a Middle Response Category
on Response Style in Attitude Measurement,'' Quality & Quantity,
42(6):779-794, 2008.
11. Sturgis, P., C. Roberts, and P. Smith, ``Middle Alternatives
Revisited: How the Neither/Nor Response Acts as a Way of Saying ``I
Don't Know?'' Sociological Methods & Research, 43(1):15-38, 2014.
12. Reyna, V.F., ``How People Make Decisions That Involve Risk: A
Dual-Process Approach,'' Current Directions in Psychological
Science, 13:60-66, 2004.

    Dated: March 14, 2016.
Leslie Kux,
Associate Commissioner for Policy.
[FR Doc. 2016-06126 Filed 3-17-16; 8:45 am]
 BILLING CODE 4164-01-P