Agency Information Collection Activities; Submission for Office of Management and Budget Review; Comment Request; Quantitative Information in Direct-to-Consumer Television Advertisements, 14855-14859 [2016-06126]
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Federal Register / Vol. 81, No. 53 / Friday, March 18, 2016 / Notices
outcomes, effectiveness, and
appropriateness of health care services
and procedures to identify the manner
in which disease, disorders, and other
health conditions can be prevented,
diagnosed, treated, and managed
clinically. Section 1862(a)(1)(E) of the
Act allows Medicare to cover under
coverage with evidence development
(CED) certain items or services for
which the evidence is not adequate to
support coverage under section
1862(a)(1)(A) and where additional data
gathered in the context of a clinical
setting would further clarify the impact
of these items and services on the health
of beneficiaries.
The data collected and analyzed in
the TVT Registry will be used by CMS
to determine if the TAVR is reasonable
and necessary (e.g., improves health
outcomes) for Medicare beneficiaries
under Section 1862(a)(1)(A) of the Act.
Furthermore, data from the Registry will
assist the medical device industry and
the Food and Drug Administration
(FDA) in surveillance of the quality,
safety and efficacy of new medical
devices to treat aortic stenosis. For
purposes of the TAVR NCD, the TVT
Registry has contracted with the Data
Analytic Centers to conduct the
analyses. In addition, data will be made
available for research purposes under
the terms of a data use agreement that
only provides de-identified datasets.
Form Number: CMS–10443 (OMB
control number: 0938–1202); Frequency:
Annual; Affected Public: Individuals,
Households and Private Sector; Number
of Respondents: 14,871; Total Annual
Responses: 59,484; Total Annual Hours:
19,184. (For policy questions regarding
this collection contact Sarah Fulton at
410–786–2749.)
Dated: March 15, 2016.
William N. Parham, III,
Director, Paperwork Reduction Staff, Office
of Strategic Operations and Regulatory
Affairs.
[FR Doc. 2016–06188 Filed 3–17–16; 8:45 am]
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BILLING CODE 4120–01–P
DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Centers for Medicare & Medicaid
Services
[CMS–7040–N2]
Health Insurance MarketplaceSM,
Medicare, Medicaid, and the Children’s
Health Insurance Program;
Cancellation of the March 23, 2016
Advisory Panel on Outreach and
Education Meeting
Centers for Medicare &
Medicaid Services (CMS), HHS.
ACTION: Cancellation of meeting.
AGENCY:
On February 25, 2016, we
published a Federal Register notice (81
FR 9483) announcing a new meeting of
the Advisory Panel on Outreach and
Education (APOE) (the Panel), which
was scheduled for Wednesday, March
23, 2016. This notice announces the
cancellation of the March 23, 2016
meeting.
SUMMARY:
FOR FURTHER INFORMATION CONTACT:
Abigail Huffman, Designated Federal
Official, Office of Communications,
CMS, 7500 Security Boulevard, Mail
Stop S1–05–06, Baltimore, MD 21244,
410–786–0897, email
Abigail.Huffman1@cms.hhs.gov.
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Press inquiries are handled through the
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Dated: March 15, 2016.
Andrew M. Slavitt,
Acting Administrator, Centers for Medicare
& Medicaid Services.
[FR Doc. 2016–06206 Filed 3–17–16; 8:45 am]
BILLING CODE 4120–01–P
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.
The Food and Drug
Administration (FDA) is announcing
that a proposed collection of
SUMMARY:
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14855
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.
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:
202–395–7285, or emailed to oira_
submission@omb.eop.gov. 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, PRAStaff@
fda.hhs.gov.
ADDRESSES:
In
compliance with 44 U.S.C. 3507, FDA
has submitted the following proposed
collection of information to OMB for
review and clearance.
SUPPLEMENTARY INFORMATION:
Quantitative Information in Direct-toConsumer 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
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Federal Register / Vol. 81, No. 53 / Friday, March 18, 2016 / Notices
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-toConsumer 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 ..........
Quantitative Efficacy Claim ......
Yes: General (e.g., Side effects that occur in 10% or
less of people who take
Drug X include . . .).
Yes: Specific (e.g., Side effects
that occur in [6–10%, 1–5%,
and less than 1%] of people
who take Drug X include
. . .).
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.).
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TABLE 2—STUDY 2 DESIGN
Images of improvement
None ......
Quantitative Benefit Claim ........
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Accurate
improvement
in
health conveyed in images.
No
Yes (Single outcome)
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Overstated improvement in
health conveyed in images.
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Federal Register / Vol. 81, No. 53 / Friday, March 18, 2016 / Notices
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 inperson 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
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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.
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(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
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Federal Register / Vol. 81, No. 53 / Friday, March 18, 2016 / Notices
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
Number of
respondents
Activity
Number of
responses per
respondent
Total annual
responses
Average burden
per response
Total hours
Sample outgo ...........................................................
Number to complete the screener (10%) ................
Number eligible for survey (70%) ............................
Number to complete the survey (85%) ....................
15,130
1,513
1,059
900
........................
1
........................
1
........................
1,513
........................
900
....................................
0.05 (3 minutes) ........
....................................
0.33 (20 minutes) ......
........................
76
........................
297
Total ..................................................................
........................
........................
2,413
....................................
373
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
Number of
respondents
Activity
Number of
responses per
respondent
Total annual
responses
Average burden
per response
Total hours
Sample outgo ...........................................................
Number to complete the screener (10%) ................
Number eligible for survey (70%) ............................
Number to complete the survey (85%) ....................
15,130
1,513
1,059
900
........................
1
........................
1
........................
1,513
........................
900
....................................
0.05 (3 minutes) ........
....................................
0.33 (20 minutes) ......
........................
75.65
........................
297
Total ..................................................................
........................
........................
2,413
....................................
372.65
1 There
are no capital costs or operating and maintenance costs associated with this collection of information.
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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 https://
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,
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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
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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 DualProcess Approach,’’ Current Directions
in Psychological Science, 13:60–66,
2004.
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Federal Register / Vol. 81, No. 53 / Friday, March 18, 2016 / Notices
Dated: March 14, 2016.
Leslie Kux,
Associate Commissioner for Policy.
[FR Doc. 2016–06126 Filed 3–17–16; 8:45 am]
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DEPARTMENT OF HEALTH AND
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[Docket No. FDA–2016–D–0620]
Question-Based Review for the
Chemistry, Manufacturing, and
Controls Technical Section of Animal
Drug Applications; Draft Guidance for
Industry; Availability
AGENCY:
Food and Drug Administration,
HHS.
ACTION:
Notice.
The Food and Drug
Administration (FDA) is announcing the
availability of a draft guidance for
industry (GFI) #234 entitled ‘‘QuestionBased Review for the Chemistry,
Manufacturing, and Controls Technical
Section of Animal Drug Applications.’’
In order to improve the process for
submission and review of chemistry,
manufacturing, and controls (CMC)
information for animal drugs, the Center
for Veterinary Medicine (CVM) has
developed a series of questions that
focus on the critical scientific and
regulatory issues and pharmaceutical
attributes essential for ensuring the
quality of new animal drug substances
and products. Termed Question-based
Review (QbR), these questions provide a
general framework for original CMC
submissions to investigational new
animal drug (INAD) files, generic
investigational new animal drug
(JINAD) files, new animal drug
applications (NADAs), abbreviated new
animal drug applications (ANADAs),
conditional approval of applications for
conditional approval (CNADAs), and
veterinary master files (VMFs).
DATES: Although you can comment on
any guidance at any time (see 21 CFR
10.115(g)(5)), to ensure that the Agency
considers your comment on this draft
guidance before it begins work on the
final version of the guidance, submit
either electronic or written comments
on the draft guidance by May 17, 2016.
ADDRESSES: You may submit comments
as follows:
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SUMMARY:
Electronic Submissions
Submit electronic comments in the
following way:
• Federal eRulemaking Portal: https://
www.regulations.gov. Follow the
instructions for submitting comments.
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Comments submitted electronically,
including attachments, to https://
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manner detailed (see ‘‘Written/Paper
Submissions’’ and ‘‘Instructions’’).
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Submit written/paper submissions as
follows:
• Mail/Hand delivery/Courier (for
written/paper submissions): Division of
Dockets Management (HFA–305), Food
and Drug Administration, 5630 Fishers
Lane, Rm. 1061, Rockville, MD 20852.
• For written/paper comments
submitted to the Division of Dockets
Management, FDA will post your
comment, as well as any attachments,
except for information submitted,
marked and identified, as confidential,
if submitted as detailed in
‘‘Instructions.’’
Instructions: All submissions received
must include the Docket No. FDA–
2016–D–0620 for ‘‘Question-Based
Review for the Chemistry,
Manufacturing, and Controls Technical
Section of Animal Drug Applications.’’
Received comments will be placed in
the docket and, except for those
submitted as ‘‘Confidential
Submissions,’’ publicly viewable at
https://www.regulations.gov or at the
Division of Dockets Management
between 9 a.m. and 4 p.m., Monday
through Friday.
• Confidential Submissions—To
submit a comment with confidential
information that you do not wish to be
made publicly available, submit your
comments only as a written/paper
submission. You should submit two
copies total. One copy will include the
information you claim to be confidential
with a heading or cover note that states
‘‘THIS DOCUMENT CONTAINS
CONFIDENTIAL INFORMATION.’’ The
Agency will review this copy, including
the claimed confidential information, in
PO 00000
Frm 00038
Fmt 4703
Sfmt 4703
14859
its consideration of comments. The
second copy, which will have the
claimed confidential information
redacted/blacked out, will be available
for public viewing and posted on
https://www.regulations.gov. Submit
both copies to the Division of Dockets
Management. If you do not wish your
name and contact information to be
made publicly available, you can
provide this information on the cover
sheet and not in the body of your
comments and you must identify this
information as ‘‘confidential.’’ Any
information marked as ‘‘confidential’’
will not be disclosed except in
accordance with 21 CFR 10.20 and other
applicable disclosure law. For more
information about FDA’s posting of
comments to public dockets, see 80 FR
56469, September 18, 2015, or access
the information at: https://www.fda.gov/
regulatoryinformation/dockets/
default.htm.
Docket: For access to the docket to
read background documents or the
electronic and written/paper comments
received, go to https://
www.regulations.gov and insert the
docket number, found in brackets in the
heading of this document, into the
‘‘Search’’ box and follow the prompts
and/or go to the Division of Dockets
Management, 5630 Fishers Lane, Rm.
1061, Rockville, MD 20852.
Submit written requests for single
copies of the guidance to the Policy and
Regulations Staff (HFV–6), Center for
Veterinary Medicine, Food and Drug
Administration, 7519 Standish Pl.,
Rockville, MD 20855. Send one selfaddressed adhesive label to assist that
office in processing your requests. See
the SUPPLEMENTARY INFORMATION section
for electronic access to the draft
guidance document.
FOR FURTHER INFORMATION CONTACT: Julie
Bailey, Center for Veterinary Medicine
(HFV–145), Food and Drug
Administration, 7500 Standish Pl.,
Rockville, MD 20855, 240–402–0700,
julie.bailey@fda.hhs.gov.
SUPPLEMENTARY INFORMATION:
I. Background
Under sections 512(c)(2)(A)(i) and
(d)(1)(C), and 571(c)(1) of the Federal
Food, Drug, and Cosmetic Act (21 U.S.C.
360b(c)(2)(A)(i) and (d)(1)(C), and
360ccc(c)(1)), applicants must submit
information on CMC to support the
approval of NADAs and ANADAs or the
conditional approval of CNADAs. CVM
reviews the CMC information for new
animal drugs to ensure that applicants
have methods and controls in place for
manufacturing, processing, and
packaging that are adequate for assuring
E:\FR\FM\18MRN1.SGM
18MRN1
]]>Agencies
[Federal Register Volume 81, Number 53 (Friday, March 18, 2016)]
[Notices]
[Pages 14855-14859]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2016-06126]
-----------------------------------------------------------------------
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.
-----------------------------------------------------------------------
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: 202-395-7285, or emailed to oira_submission@omb.eop.gov. 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, PRAStaff@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.
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
[[Page 14856]]
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).
----------------------------------------------------------------------------------------------------------------
[[Page 14857]]
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
[[Page 14858]]
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
--------------------------------------------------------------------------------------------------------------------------------------------------------
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).......................... 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
--------------------------------------------------------------------------------------------------------------------------------------------------------
\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
--------------------------------------------------------------------------------------------------------------------------------------------------------
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
--------------------------------------------------------------------------------------------------------------------------------------------------------
\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 https://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.
[[Page 14859]]
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
