Changing Attitudes toward “Thinking” with TV Concept Placement

The Big Bang Thinking:
Changing Attitudes toward “Thinking” with Concept Placement
Emily Sun
B.S.J. Student
E.W. Scripps School of Journalism
363 Richland Ave., Apt. 254
Ohio University
Athens, OH 45701
Voice: (614) 725-6218
E-Mail: es172709@ohio.edu
&
Carson B Wagner*
Asst. Professor and
Director, ViDS Effects Laboratory
E.W. Scripps School of Journalism
204 Schoonover Center
Ohio University
Athens, OH 45701
Voice: (740) 593-9808
E-Mail: wagnerc1@ohio.edu
Paper presented to the Mass Communication & Society Division at the 2014 Midwinter
Conference of the Association for Education in Journalism and Mass Communication, Norman,
OK, February 28 – March 1, 2013.

Changing Evaluations with Concept Placement – 2
Introduction
Product Placement (PPL) in movies
(Matthes, 2012) and TV shows (Andriasova
& Wagner, 2004) have been shown to
subconsciously persuade viewers, changing
“implicit associations” (see Greenwald,
McGhee, & Schwartz, 1998), or
subconscious evaluations of brands. Similar
responses have been shown with regard to
consuming other subtle stimuli such as
sports sponsorships (Wagner & Clark, 2013)
and music in advertising (Johnson &
Wagner, 2011). Even anti-drug ads, when
participants’ motivation and/or opportunity
to process the ads “centrally,” or with a
relatively high degree of effort (see Petty &
Cacioppo, 1986), were diminished with
experimental manipulations, such that the
ads could only be processed “peripherally,”
or with little effort, demonstrated the
importance of peripheral processing in
creating strong anti-drug implicit
associations. While tangible products, such
as fabric softener, food, and beverages–
subjects of prior studies’ findings–might be
placed purposefully, could intangible
concepts on which a program is based cause
concept evaluation changes, even if the
“placement” of the concept is unintentional?
Prior research including the above
suggest they can, and we might call such
instances “concept placements,” or CPL,
because although most product placements
today may be purchased, with products
shown intentionally, product placements can
occur unintentionally, as well (Russell,
1998). The same is true of major concepts
that serve as the basis for media texts.
Concept Placement has been defined
“simply as the presence of a concept within
a media text” (Wagner, Sun, & Clark, 2013,
p. 4) and it is distinguished from Product
Placement in two ways: 1) PPLs require the
presence of a brand via a brand identifier,
but with CPL, any concept can be promoted
or degraded; and 2) brands have multiple
attributes, whereas, with CPL, a single
concept, as opposed to a construct, is the
target for belief evaluation (see Bem, 1970).
An initial examination of CPL
showed that differences liking levels for a
TV show could elicit significant differences
in expressed evaluations toward the show’s
main CPL, based on the Underlying Subject
Matter (USM; Biglan, 1973). The show
examined was “The Big Bang Theory,” and
differences in evaluations toward the
concept “thinking,” as well as significant
differences in Need for Cognition (Cacioppo
& Petty, 1982), which refers to the extent to
which one will “enjoy thinking,” were
shown as a function of liking more of liking
less/disliking a TV show and its characters.
However, the study could not show change
in evaluations of the CPL, “thinking.”
That experiment was purposefully
designed to provide the best chance to elicit
significant difference in evaluations of the
CPL, because, if, given such a chance, no
differences were found, then it could be
concluded that CPLs would likely not cause
differential responses of any kind (Sundar,
1999). However, given that differences
were found, it was suggested that research
investigate the possibility of evaluation
change, as opposed to difference or
modification (see Bennett & Iyengar, 2008,
2010; Wagner, 2001). To do so requires a
comparison of responses to consuming
media, wherein a difference is shown
between a pre-test and a post-test measure,
or that a difference is shown between a
control group that sees no stimulus and an
experimental group that sees a stimulus. So
then, to continue investigating the potential
of CPL, this article presents a controlled,
between-participants laboratory experiment,
comparing responses of an experimental
group that viewed a set of clips from “The
Big Bang Theory” to a control group that
saw no stimulus.

Literature Review
Due to their subtlety, prior research
on product placements (PPLs; e.g., Matthes,
2012; Andriasova & Wagner, 2004), sports
sponsorships (Wagner & Clark, 2013), and
music in advertising (Johnson & Wagner,
2011) help provide the groundwork for a
hypothesis about the potential of CPLs to
change belief evaluations toward the
concept, because CPL is also a subtle
occurrence (unintentional) or tactic
(intentional) that could potentially change
evaluations of the main CPL concept.
Product placement has had many
definitions, over the years, increasingly
more of which differ from larger, more
inclusive definitions of product placement
that frame it as the inclusion of a brand in a
media text, whether done intentionally or
unintentionally. For instance, some have
defined it as “The practice of placing brand
name products in movies as props” (Gupta
& Gould, 1997), “The conceived insertion of
a brand within a movie, broadcast,
computer…and etc.,” (Soba & Aydin,
2013), or “A product and/or brand
intentionally placed in a cultural medium,”
(Lehu & Bressoud, 2008).
The last in that list is perhaps most
inclusive, but along with the others, it does
not include the unintentional appearance of
brands in media texts, likely because, in
recent years, PPL has become much more
used as a strategic communication tactic that
is done intentionally, in order to embed
brand-related content into a media text in
such a way so that it cannot be avoided by
the audience, unless they willingly avoid
parts of the media text, itself, which would,
in turn, lead to missing (perhaps crucial)
elements of a story. However, 90% of
media consumers have expressed that they
often “skip over” traditional ads (Soba &
Aydin, 2013) not embedded in the media
text, itself.
The study of PPLs as a marketing
strategy has, in recent years, quickly grown
in popularity, mostly in television (Lehu &
Bressoud, 2008). With its generally
inexpensive and simple execution, marketers
have increasingly utilized product placement
as a method of brand building (Soba &
Aydin, 2013).
However, incidental inclusion of
brands in media texts, it could be argued,
also constitute “product placement,”
according to those who provide broader
definitions of the concept, for the process of
theory building (see, e.g., Fisher & Wagner,
2004; Matthes, 2012; Russell, 1998), such
that theories about the phenomenon can be
as complex as the phenomenon, itself.
Similarly, the definition of “concept
placement,” or CPL, also includes the
(consciously) unintentional inclusion of
major Underlying Subject Matter (USM;
Biglan, 1973) in media texts. It is akin to
“Selective Attention,” which, as per the
words used to describe the theory, it is
implied–if not denoted–that intention plays a
role. That is because the description includes
“selective,” which at least suggests that one
has chosen to pay attention. However, the
definition of “Selective Attention,” which
refers to the “allocation of effort,” includes
both voluntary, intentional attention, as well
as involuntary, unintentional attention (see
Kahneman, 1973). In order to explain the
spectrum of instances in which we pay
attention to some things but not others,
involuntary attention must also be included
in the definition.
Persuasion and Influence as a Function of
Subtle Stimuli
It has been shown in many prior
studies that subtle persuasion–or that to
which we may not even be paying conscious
attention–can persuade us (see, e.g.,
Andriasova & Wagner, 2004; Gilbert,
Tarafodi, & Malone, 1993; Hawkins &

Hoch, 1992; Johnson & Wagner, 2011;
Wagner & Clark, 2013; Wagner & Sundar,
2009). Such studies may be particularly
interesting, because their findings are often
very counterintuitive. Many, if not a large
majority of, advertisers and PR professionals
continue to believe that attention is a
necessary factor in persuasion, as was
presumed in early persuasion models such as
the “Message-Learning Approach” (see
Hovland, Janis, & Kelley, 1953).
A relatively early study of
subconscious influence showed that, at least
at the moment of comprehension, we believe
what we have consumed (Gilbert, Tarafodi,
& Malone, 1993), the researchers used a
number of different combinations to
demonstrate the phenomenon. Various sets
of participant groups were randomly
assigned to different conditions – one of
which could read statements as they crossed
a computer screen, without distraction.
However, the other groups’ limited
cognitive capacity were filled with the
distractor task of tapping keys on a button
box that “matched” squares that would
appear in the corners of the screen, as they
read. All groups were told that information
about a target to be judged would scroll
across the screen, and that information that
appeared in white letters was “true”
information, while information that was
false would appear in red letters. In the
comparisons made between all of the sets of
groups, those who had the extra task of
pushing buttons that matched appearing
boxes, it was shown, used the information in
red significantly more than those who read
the information without distraction – and the
task was to decide the guilt or innocence of
a suspect, as well as to suggest a length of
the prison sentence, if one were to say the
suspect was guilty! While it would seem to
make life vastly easier, if we had the “super
power” to see all false information written in
red letters, the results of the study suggest
that, given today’s fast-paced (media)
environment, we would still be persuaded by
and use the information we saw printed in
red letters, unless we took the time to make
a mental note that the information were
printed in red and was therefore false.
Product placements can be viewed
by consumers as making media texts seem
more “real,” and in such a process, they are
generally consumed without much effortful
evaluation (Gupta & Gould, 1997).
However, if PPLs are too obvious,
consumers can become very aware of them
and suspicious about their intentional
placement. In turn, consumers can process
the PPLs more consciously and become less
receptive to them (Dens, Pelsmacker,
Wouters, & Purnawirawan, 2012).
Especially when PPLs seem
“natural” in a storyline, they are likely
processed without much cognitive effort, or
rather “peripherally” (Petty & Cacioppo,
1986). It has been shown that PPLs can
persuade more “subconsciously,” such that
people don’t report being persuaded.
Nonetheless, response latency measures of
implicit associations (IATs; Greenwald,
McGhee, & Scwartz, 1998) have shown that
the same participants formed more positive
associations with the products placed, as
compared to those who did not watch a PPL
stimulus (Andriasova & Wagner, 2004). As
such, while PPLs may not generally
persuade at the conscious level, they can be
influencing us subconsciously.
Wagner’s (2004) and Wagner and
Sundar’s (2003; 2009) studies have shown
that participants who are manipulated to
view anti-drug ads peripherally–by lowering
the participants’ motivation and/or
opportunity to view the stimulus–exhibited
significantly more negative drug-related
implicit associations, as compared to those
who watched centrally – or those whose
motivation and opportunity were
manipulated to be as high as possible.

In studies examining “wear-out” and
“wear-in” of music in advertising (see
Johnson & Wagner, 2011), it was shown in a
“wear-out” study that while participants
expressed evaluations of the brand were
more negative, due to the commercials being
shown often over a long period of time,
participants’ implicit associations were more
positive, when the ads’ music was played.
In a follow-up “wear-in” study, with
commercials that had a new musical score, it
was shown that expressed attitudes were
more positive when the music was played,
as opposed to being turned off, but
participants implicit associations with the
brand and its attributes were more negative
when the music was turned on as opposed to
being turned off.
Examining sports sponsorships, a
study (Wagner & Clark, 2013) wherein a
fictional brand was displayed on a banner
across the bottom of the screen, it was found
with an American audience that, when
shown clips of the United States winning
against Russia and the Soviet Union
(positive moments), participants’ implicit
associations with the brand and its attributes
were more positive, as compared to a control
group and a group who saw Russia and the
USSR beating the US. The reverse was also
true: that when the US lost to Russia and the
USSR (negative moments), associations
with the brand and its attributes became
more negative. However, for expressed
attitudes, differences were only shown
between the positive and negative sports
moments.
Evaluation Types and Decision-Making
It is commonly assumed that almost
all decisions, to some extent, are based on
conscious decision-making and the intention
to act (Bargh, 2002). To the contrary, most
consumer decisions are functions of
subconscious psychological processes (Alba,
2000). The inability of consumers to justify
their reasoning for making “high-
involvement” purchases is considerably
common (Rossiter, Percy, & Donovan,
1991). And when confronted on their
reasoning consumers commonly respond by
attempting to “fill in the gaps” with possible
clauses because they were not consciously
aware of their decision process (Nisbett &
Wilson, 1977). These studies help
demonstrate that, while we may think that
we more often make “rational,” effortful
decisions based on our known evaluations,
instead, we are more likely to make
decisions that are in line with our implicit
associations.
Product placement studies have
relied heavily on self-report measures (Law
& Braun-LaTour, 2004), and in previous
literature there is the assumption that
placements are not as effective as traditional
advertisements due to the lack of significant
differences shown in study findings.
However, because people often are not
aware of the reasoning for their decisions, it
can be argued that lack of effects in self-
reported measures is not as crucial as may
be commonly assumed (Bargh, 2002). It has
also been argued that because of this, data
from subconscious responses produced by
memory contents may be equally, if not
more, valuable than showing effects as
measured by self-reports (Fazio, 1990). In
other words, subconscious changes are
likely the better method of determining the
effectiveness of placements on evaluations.
Changing Concept Evaluations with
Concept Placement
Many shows revolve around specific,
abstract concepts–many that are not overtly
mentioned repeatedly, but rather simply
provide the basis for a media text–or, rather,
“underlying subject matter” (USM; Biglan,
1973). USMs are, by definition, relatively
subtle and generally implied by the focus of
a story, as opposed to being made explicit

(Biglan, 1973) and so it can be predicted
that the same cognitive mechanisms will be
at work with USMs, which are likely subtly
recognized (see Petty & Cacioppo, 1986), as
those mechanisms are with other subtle
stimuli. CPLs, in turn, derive from the
(major) USM(s) of media texts, and so it is
not that CPLs–as unintentional occurrences
or intentionally-driven persuasive tactics–
are overtly, specifically mentioned or shown
in the way that PPLs name, show, or
otherwise presented a brand identifier. Such
logic also helps further distinguish CPLs
from PPLs, in adding to the exploratory CPL
literature (Wagner, Sun, & Clark, 2014).
“Attitude objects”–despite that the
word “object” denotes something tangible–
can also be intangible ideas (Fazio, 1986;
1990) and, therefore, subtly-presented CPLs
are likely to be processed psychologically
in the same manner as brands and products.
We argue that that is likely even the case
despite that brands and products, as “attitude
objects,” reflect constructs, as opposed to
concepts (see Bem, 1970), meaning that a
concept is, almost by definition, of less
depth than a construct.
So, in order to demonstrate that
evaluation change can occur as a function of
Concept Placement, it is necessary to choose
and use a CPL for which the USM is
particularly positively portrayed. That is
among the same reasons why “The Big
Bang Theory,” with its strong but subtle
promotion of the major CPL, “thinking,”
was initially chosen to demonstrate that
differences can be elicited in evaluations of
the major placed concept (Wagner, Sun, &
Clark, 2014). The other reasons are that the
show is among the most watched among the
target audience of 18-24 year-olds–which
matches the population from which the
convenience sample for that study and this
were drawn–and, perhaps beyond the
implications for systematic demonstrations
of CPL’s potential, it was deemed a concept
that is seen as positive including and beyond
those who would seek to maintain the status
quo. In other words, “thinking,” in and of
itself, could be argued to be the basis of a
well-functioning democracy. Therefore, the
study would also have more practical
import.
That said, among the various studies
of subtle stimuli persuasion, sports
sponsorships, used as subtle brand
presentations, were demonstrated to be able
to persuade both consciously and
subconsciously, and in both negative and
positive ways, depending on the manner in
which the brand was framed (Wagner &
Clark, 2013). Therefore, insofar as “concept
placement” should work similarly to product
placements and sports sponsorships, in a
higher order of abstraction–that is, as subtle,
persuasive stimuli, at the structural level–
even though tangibility, among other
factors, differ. While it may be more
difficult to detect evaluation change as a
function of CPLs, as compared to PPLs, the
similarities of (subtle) media text
embededness and (particularly) positive or
negative framing, as a function of the CPL
context, again, the same psychological
mechanisms should be at work with CPLs as
with PPLs. Those mechanisms are that by
which we make positive or negative
associations with the CPL, much as we
would with an attitude object viewed
peripherally, or without much effort (see
Petty & Cacioppo, 1986). As such, based on
theory and research about the effects of
subtle (or peripherally-processed) but
strongly-valenced contextual framing of
brands (and drugs), it can be predicted that:
H1a: Viewers who see a main,
positively-presented CPL will show more
positive implicit evaluations toward the CPL,
as compared to those who do not see the
stimulus.

H1b: Viewers who see a main,
positively presented CPL in a TV show
will show more positive implicit CPL
evaluations, as compared to those who do
not see the stimulus.
Lastly, based on the findings of CPL
research examining CPL evaluation
response differences based on differential
liking of a program, which showed that
one’s “Need for Cognition” (Cacioppo &
Petty, 1982) varied with the level of liking
for the show (Wagner, Sun, & Clark, 2014),
it can also be predicted that:
H1c: Viewers who see a main,
positively-presented CPL will show higher
Need for Cognition, as compared to those
who do not see the stimulus.
Methodology
In a two-condition between-
participants experiment, all participants’
(N=67) product-related implicit associations
and self-reported belief evaluations toward a
placed concept were measured with paper-
and-pencil scales. Prior to measurement,
participants were randomly assigned to
either an experimental or a control
condition. Experimental condition
participants first viewed a twelve-minute TV
program compilation designed to maximize
the positive portrayal of the main CPL,
“thinking,” of the program, “The Big Bang
Theory,” in order to determine whether an
evaluative change can be demonstrated, as
compared to a control group who saw no
stimulus but simply completed the
measures. Between groups, all participants
completed the same measures in the same
order, and both groups were told that they
were participating in a general study
examining the effects of media.
Participants
Sixty-seven undergraduate students
from a strategic communication class
participated in the study for a course
requirement introducing them to social
science research methods. Each condition
was run within individual sessions over a
course of two weeks. 31 participants were
randomly assigned to the experimental
group and 36 participants were assigned to
the control group. Participants were simply
told that they were participating in a study
“examining the effects of media.” All
participants signed an informed consent
form prior to participating in the study.
Procedure
Upon arrival at each of the study
sessions, which examined responses one
participant at a time, participants were asked
to draw a slip of paper that contained their
identification (ID) numbers, which in turn
signified their condition assignment, from an
unsealed ZiplocTM
bag that contained ID
numbers for both conditions. The ID
number sheets were approximately 1 inch by
1 inch squares that were folded into quarters
before being placed in the baggie, so that
participants could not see which numbers
were on which sheets, through the clear
baggie. As such, participants were randomly
assigned to conditions.
After randomly selecting ID
numbers, participants were asked to sign
Informed Consent Forms (ICFs). The ICF
documents explained their rights and
responsibilities as research participants, and
they contained the contact information of the
principal investigators of the project.
Following ICF administration, participants
were then instructed— depending upon the
condition to which they were randomly
assigned–– to either watch a video and fill
out questionnaires afterwards, or simply fill
out the questionnaires.

Dependent Measures
Dependent measures were
administered to all participants in the same
order. Experimental condition participants
completed the measures following stimulus
presentation, while control group
participants simply did so after signing
informed consent forms. The first measure
was an Implicit Attitude Test (IAT;
Greenwald, McGhee, & Schwartz, 1998)
developed by Lowery, Hardin, and Sinclair
(2001) and demonstrated to measure
differences in implicit attitudes. The
measures were originally designed for
stereotyping research and have been adapted
to drug-related attitudes (Wagner, 2001;
2003; 2004; Wagner & Sundar, 2003; 2009),
product placement brands (Andriasova &
Wagner, 2004), brands advertised with
jingles (Johnson & Wagner, 2011), and
attitudes toward homosexuals (Liu &
Wagner, 2013). They were similarly adapted
by the authors for this study, to examine
concept placement effects on evaluations of
the concept “thinking.”
As with other variations on the IAT
(e.g., Dasgupta, McGhee, Greenwald, &
Banaji, 2000; Greenwald, McGhee, &
Schwartz, 1998; Rudman, Greenwald,
Mellot, & Schwartz, 1999), the Lowery et.
al (2001) measure uses five separate timed
judgment stages. For each of the five stages,
a list of words printed singularly in the
middle of each page comprised the judgment
items, and evaluations were indicated by
checkmarks in the appropriate right and left-
hand columns.
Before entering the judgment stages,
participants were shown two lists of words
(contained in the questionnaire packets) one
at a time, and they were asked to become
familiar with the words before the
experiment progressed. The first set of
words included names of both thinking-
related words and colors, and the second
included both positive and negative
adjectives. Eight words of each type were
shown on the lists, and these words would
later be used as judgment items for the
evaluation tasks.
The list of thinking words included
the eight synonyms attributed to Thinking:
Analysis, Contemplation, Logic, Intellect,
Inquiry, Cognition, Reasoning, and
Theorizing. The list of colors included blue,
orange, pink, gray, brown, yellow, purple,
and red.
The list of positive adjectives
included: good, pleasant, valuable,
favorable, acceptable, nice, wonderful, and
excellent. The list of negative adjectives
included: bad, unpleasant, worthless,
unfavorable, unacceptable, awful, horrible,
and poor. The same adjectives appear on
the semantic differential scales for the
explicit evaluation measures used in this
study, which have similarly been adapted
from a prior evaluation assessment
questionnaire (Palmgreen, Donohew, Lorch,
Rogus, Helm, & Grant, 1991) to assess
evaluations of various brands, drugs, and
sexuality.
After participants studied each set of
words and raised their heads to indicate that
they had completed this portion of the
measure, we began the judgment stages. The
first two stages were “practice stages,”
where participants could become familiar
with the activity of categorizing words
before being measured. In the first of these
stages, the lists of thinking words and colors
ran down the middle of the page, mixed in
an unordered fashion, and participants were
given twenty seconds to categorize them by
placing a checkmark on the appropriate side
as they moved sequentially down the page.
Appropriate sides were indicated at the top
of the page (i.e., “Thinking” was printed on
the left or right, with “colors” opposing),
and participants were given verbal
instructions as to what the appropriate side

would be prior to beginning the timed
judgment stage. For example:
Colors Thinking
Red
Inquiry
The second stage was like the first,
except that the list was of the positive and
negative adjectives and “positive” and
“negative” anchored the sides.
The third stage was a critical
judgment phase, or one that was measured,
and it included all four sets of words. The
list began with either a positive or negative
adjective, or a thinking word or color name,
with the next word coming from the
opposite category (name or adjective) and
the word after that coming from the initial
category, and so on and so forth. The
appropriate judgment side was a
combination of both thinking words or
colors and positive or negative words. In
other words, one of the sides would be the
appropriate side for either thinking words
and negative or positive, while the other
would be for colors and the opposite type of
adjective. Further, the sides matched those
used in the preceding practice stages for all
participants. Participants were again allotted
twenty seconds to categorize as many of
these terms as they could, moving
sequentially down the page. This phase
included two such lists given one after the
other.
The fourth stage was another
practice stage. As the measure calculates
attitudes by differencing the number of
items correctly categorized when pairing
negative words with negative adjectives
against thinking coupled with positive
adjectives, the appropriate side for each
thinking word and color in the fifth critical
stage would need to be switched while
keeping positive and negative constant. This
stage was introduced to allow participants
familiarity with categorizing thinking words
and colors on the sides opposite those they
had just done, and the list therefore only
included thinking words and colors.
The fifth stage was again a critical
phase, requiring simultaneous categorization
of both names and adjectives. This phase
was the same as the third stage except that
the appropriate side for thinking words and
color names was switched, and participants
were therefore categorizing these names
with the opposite kind of adjective.
Following SOA assessment,
participants self-reported their evaluations of
the concept, “thinking,” using a measure that
has been adapted from prior research
(Palmgreen, et al, 1991) to measure
evaluations of drugs (e.g., Wagner &
Sundar, 2009), brands (e.g., Andriasova &
Wagner, 2004; Johnson & Wagner, 2011;
Wagner & Clark, 2013), and homosexuals,
in general (Liu & Wagner, 2013). The
measure consists of eight five-item semantic
differential scales with positive and negative
anchors – the same adjectives as those that
were used in the implicit, response latency
measures. The instructions for this measure
read: Below is a list of word pairs. Circle
one of the numbers near the word in the pair
that best describes how you feel about the
following statement: “I believe thinking
is…”
Lastly, participants reported their
attitudes towards the extent to which they
“enjoy thinking” with the Need for
Cognition scale (Cacioppo & Petty, 1982).
The scale contains 18 nine-point Likert scale
items on which responses range from -4 to
+4, indicating participants’ levels of
(dis)agreement with the 18 statements. The
instructions read: Describe the extent to
which you agree with each statement using
the following values: -4 = very strong
disagreement, -3 = strong disagreement, -2

= moderate disagreement, -1 = slight
disagreement, 0 = neither agreement nor
disagreement, +1 = slight agreement, +2 =
moderate agreement, +3 = strong
agreement +4 = very strong agreement.
Data Analysis
To test the three hypotheses, we
entered each dependent variable (the
Explicit CPL Attribute Evaluation Index, the
Implicit CPL Attribute Evaluation Index,
and the Need for Cognition index) per
hypothesis, into a one-tailed t-test, with
condition (Experimental and Control) as the
independent variable.
To test H1a, which said that those
who saw the positively-presented CPL
would show higher explicit attribute
evaluations about the program’s main CPL,
“Thinking,” as compared to those who did
not see the stimulus, we entered the
“Explicit CPL Attribute Evaluation Index”
as the dependent variable. No significant
difference was found [t(65)=-0.40, p=.65],
such that those who liked the program more
did not show higher scores on the Explicit
CPL Attribute Evaluation Index (M=12.33,
SD=3.60), as compared to those who liked
the program less (M=11.86, SD=5.34).
Therefore, H1a was not supported.
To test H1b, which said that those
would show higher explicit attribute
evaluations about the program’s main CPL,
“Thinking,” as compared to those who did
not see the stimulus, we entered the
“Implicit CPL Attribute Evaluation Index”
as the dependent variable. A marginally-
significant difference was found
[t(65)=1.49, p=.07), such that there was a
marginally-significant difference between
the implicit CPL evaluations of the attribute
between the group who saw CPL in the
stimulus (M=3.35, SD=7.25) and those who
did not (M=0.41, SD=8.86). Therefore,
H1b was marginally supported.
To test H1c, which said that those
would demonstrate a higher Need for
Cognition–a measure that shows how much
one would “enjoy thinking” (Cacioppo &
Petty, 1982, p. 116) the study’s main CPL–
as compared to those who did not see the
stimulus, we entered the “Need for
Cognition Index” as the dependent variable.
No significant difference was found [t(65)=-
1.11, p=.13], such that those who saw the
positively-presented CPL did not show
higher scores on the Need for Cognition
Index (M=7.80, SD=10.23), as compared to
those who did not see the stimulus (M=4.94,
SD=10.47). Therefore, H1c was not
supported.
Discussion
Overall only one of our three
hypotheses received support, and that
support was marginal (p=.07). H1b, which
predicted that implicit associations toward
the concept of “thinking” would be more
positive for those who saw the stimulus, as
compared to those who did not, received that
support, which suggests that it may have
been the only measure sensitive enough to
capture CPL evaluation change as a function
of watching the stimulus for this study. In
light of the prior research upon which this
study was built, the result is not completely
surprising. That is, in studies examining
responses to anti-drug ads (e.g., Wagner,
2004; Wagner & Sundar, 2009) and product
placements (PPLs; Andriasova & Wagner,
2004), only differences in implicit
associations were shown, although explicit
attitudes were also measured.
Due to findings from prior research
(e.g., Wagner 2001), Wagner’s (2003) study
was run specifically to determine whether
traditional, self-report evaluation measures
“exaggerate” the effectiveness of anti-drug
ads, and the findings suggested that they do.

However, in the case of anti-drug ads, it was
hypothesized that self-report report
measures magnified the effects of anti-drug
ads, due to the social undesirability of
responding positively to drugs (Carifio,
1994; Carifio & Biron, 1978; Tourangeau &
Smith, 1996), especially after watching an
anti-drug ad, which could highlight the
social undesirability, particularly in a study
of their effects.
With socially-sensitive issues such as
drugs, self-report measures have the
disadvantage of affording participants the
motivation and opportunity to ruminate
about the responses they would like to give,
prior to responding, which can lead to
misrepresentation in two different ways
(Dovidio & Fazio, 1991). People may
knowingly hold positive attitudes toward
drugs but respond in an opposite manner, as
a function of imagining that the researcher
(or others) may see their (socially
undesirable) responses. Alternatively,
people may unknowingly misrepresent
themselves by presenting an “ideal self.”
That is, they may consciously (want to) hold
anti-dug attitudes, despite that they may
subconsciously associate drugs with
positivity.
Implicit association measures,
though, were designed to investigate
stereotyping in an “unobtrusive” manner,
such that participants should not be able to
control their responses (Fazio, 1990;
Dovidio & Fazio, 1991). First, being a
measure of response latency, wherein
participants are simply asked to categorize
various words while being “primed”
(Berkowitz, 1984) with the object to be
evaluated, such that semantically-related
thoughts (e.g., memories concerning drugs)
are brought to mind, along with the
evaluations one may have formed, in the
past, such that, if positive thoughts come to
mind, upon being primed to think about
drugs, then the prime will speed one’s
ability to categorize positive words and slow
one’s ability to categorize negative words,
and vice versa, for those who hold negative
implicit associations. Hence, such measures
are referred to as “response latency”
measures, meaning that they depend on the
amount of time it takes one to respond in
categorizing positive and negative adjectives
(Fazio, 1990; Dovidio & Fazio, 1991).
In general, though, because the
subject matter, “thinking,” has not been
shown to be a particularly sensitive topic,
especially in the same sense as drugs, it
would stand to reason that we would not
need to use response latency, implicit
association measures to capture the effects
of CPLs on evaluations of that concept.
However, on a college campus such
as that from which the participants were
drawn, it would seem more likely that the
idea of “thinking” would be thought of as
socially desirable. In turn, that could lead
participants to over-report positive
evaluations of “thinking,” such that we may
not be able to find differences between
groups due to a “ceiling effect,” wherein all
participants may have reported their liking
of “thinking” so highly that there would be
no room, at the top of the scale, to be able to
find any effects. However, a review of the
data clearly suggests that a ceiling effect
was not the basis for not finding effects on
the two self-report measures.
On the other hand, the product
placement (Andriasova & Wagner, 2004)
and sports sponsorship (Wagner & Clark,
2013) studies employed response latency
measures because they have been shown to
be more sensitive in measuring evaluations
(Fazio, 1990; Dovidio & Fazio, 1991; Fazio
& Towles-Schwen, 1999). That is
especially true of those responses that stem
from psychological processes and
mechanisms to which we do not have
“introspective access” (Nisbett, 1977), or
cannot consciously realize–and therefore

would not report a difference in–our
evaluations of the target. That is, if we do
not imagine that we have been given good
reason to change our evaluations of a target–
such as a straightforward persuasive
argument that can lead us to change our
belief evaluations (see Fishbein & Ajzen,
1975)–then we likely will not change those
evaluations (Andriasova & Wagner, 2004).
Similar to product placements, which do not
(or at least almost never) present reasons
which we might believe and evaluate as
positive, thereby changing our evaluation of
the target. In other words, PPLs don’t offer
arguments as to why audiences should
change their beliefs and/or attitudes about a
product, and as such, we are given no
rational reason to change our evaluation
(Fishbein & Ajzen, 1975).
Those are among the reasons
Andriasova and Wagner (2004) explored
implicit association tests (IATs; Greenwald,
McGhee, & Schwartz) as a potential
measure of PPL effectiveness, and those
same arguments are true of CPLs, due to
their similarities: embededness in media
texts and that we are (generally) not given
(a) specific reason(s) to like the USM that
founds the CPL. Therefore, that argument
seems most to be the most likely explanation
for finding marginally-significant CPL
evaluation change but not finding self-report
change–with either the straightforward
semantic differential questionnaire designed
to gauge evaluations of thinking, or using
the Need for Cognition scale–in this study.
Based on the logic of
experimentation (see Aronson, Carlsmith, &
Brewer, 1985), potential reasons for not
finding differences on those self-report
measures are that: 1) the stimulus was not
strong enough to elicit target CPL evaluation
change; 2) the measures were not sensitive
enough to gauge differences in responses; or
3) we may need to continue the study by
adding more participants to it, which would
give us a better chance to show the change
as it was sought.
Conversely, other comparisons of
CPL evaluations, showed significant
differences between the group who liked the
show and characters more, as compared to
the group who liked them less/disliked
them–on both the same explicit evaluation
measure and Need for Cognition Scale used
here, as well as having shown the exact
same stimulus–but no difference between
the groups was shown, in terms of implicit
associations (Wagner, Sun, & Clark, 2014).
Moreover, those comparisons included far
fewer participants than the present ones. So,
it would seem that all three of the
explanations based on the logic of
experimentation can be ruled out, in
considering the comparisons and
significance of difference across the three
measures, even though the differences
shown here using the implicit association
tests were marginal.
However, while each explanation
was ruled out individually, the three were
not ruled out, in tandem. By this we mean
that by increasing the strength of the
manipulation (perhaps by making it longer
and/or more subtle and positive, with regard
to the CPL), heightening the sensitivity of
the measures (by using computerized
response latency measures such as Cedrus’
SuperLab or Empirisoft’s MediaLab, which
can analyze response time differences with
much greater sensitivity), and by increasing
the number of participants, we may be able
to show a stronger difference between the
control and experimental groups and
demonstrate change across all three
measures.
In continuing research on Concept
Placement–beyond showing evaluation
change, which has been argued to possibly
be too difficult to find, given today’s media
environment (Bennett & Iyengar, 2010)–it is
suggested that the findings of prior Product

Placement research and persuasion research
be considered. For example, the concept
placed should not be so obvious as to arouse
suspicions of the audience members about
the intent of the placement (DeLorme, Reid,
& Zimmer, 1994; Dens, Pelsmacker,
Wouters, & Purnawirawan, 2012). Also, the
mood of the scene(s) should reflect the
valence one wishes to attach to the placed
concept (Axelrod, 1963), and the CPL
should fit with the plot of the media text
(Russell, 2002). Lastly–although the
entirety of the literature would offer far
more suggestions–Concept Placement is
likely to work better if the audience
members desire to emulate the character(s)
who reflect the main CPL (DeLorme &
Reid, 1999).
In conclusion, this research report
contributes to the CPL literature in setting
up and suggesting methods for examining
change as a function of Concept Placement
– beyond that of simply listing experimental
design types that allow us to show change.
It gives specific theoretical and
methodological suggestions for
demonstrating evaluation change as a
function of CPL. Moreover, with regard to
subconscious influence, in particular, it
suggests that perhaps more media texts with
main CPL’s such as “thinking”–not in a
certain way, but rather simply “thinking,” in
and of itself–because rational thinking
serves as the foundation for a well-
functioning democracy. As such, to the
extent we can map out ways in which media
texts might promote ideas such as thinking–
or rather, develop an understanding of the
ways in which such ideas that have benefit
beyond those who would seek to maintain
the status quo–those ideas are useful and
might be used to promote shifts in power
structures and, in turn, the concentration of
wealth and power within society as it exists,
today (see, e.g., Varoufakis, 2014). This is
hopefully at least a very modest step in that
direction.
References
Alba, J. W. (2000). Dimensions of
consumer expertise...or lack thereof.
Advances in Consumer Research, 27, 1-9.
Andriasova, A. V., & Wagner, C. B
(2004). Are product placements too subtle to
persuade? Proposing strength of association
as a measure of effectiveness. Top Research
Paper presented to the Advertising Division
at the 87th annual meeting of the
Association for Education in Journalism and
Mass Communication, Toronto, Canada.
Aronson, E., Brewer, M., &
Carlsmith, J. M. (1985). Experimentation in
social psychology. In G. Lindzey & E.
Aronson (Eds.), The Handbook of Social
Psychology (Vol. 1, pp. 441-486). New
York: Random House.
Axelrod, J. (1963). Induced moods
and attitudes toward products. Journal of
Advertising Research, 3, 19-24.
Baboulene, D. (2010). The Story
Book - Guidance for Writers on Story
Creation, Optimisation and Problem
Resolution.. DreamEngine Media Ltd.:
Brighton, UK.
Bargh, J. A. (2002). Losing
consciousness: Automatic influences on
consumer judgment, behavior, and
motivation. Journal of Consumer Research,
29, 280-285.
Bem, D. J. (1970). Beliefs, Attitudes,
and Human Affairs. Belmont, Calif.:
Brooks/Cole.
Bennett, W. L., & Iyengar, S (2010).

The shifting foundations of political
communication: Responding to a defense of
the media effects paradigm. Journal of
Communication, 60, 35-39.
Berkowitz, L. (1984). Some effects
of thoughts on anti- and pro-social
influences of media events: A cognitive-
neoassociation analysis. Psychological
Bulletin, 95, 410- 427.
Biglan, A. (1973). The
characteristics of subject matter in different
academic areas. Journal of Applied
Psychology, 57(3), 195-203.
Cacioppo, J. T., & Petty, R. E.
(1982). The need for cognition. Journal of
Personality and Social Psychology 42(1),
116-131.
Carifio, J. (1994). Sensitive data and
students’ tendencies to give socially
desirable responses. Journal of Alcohol &
Drug Education, 39(2), 74-84.
Carifio, J., & Biron, R. (1978).
Collecting sensitive data anonymously: The
CDRGP technique. Journal of Alcohol &
Drug Education, 23(2), 47-66.
Clarkson, J.J., Tormala, Z.L., &
Leone, C. (2011). A self-validation
perspective on the mere thought effect.
Journal of Experimental Social Psychology,
47, 449-454.
Dasgupta, N., McGhee, D. E.,
Greenwald, A. G., & Banaji, M. R. (2000).
Automatic preference for white Americans:
Eliminating the familiarity explanation.
Journal of Experimental Social Psychology,
36, 316-328.
DeLorme, D., Reid, L., & Zimmer,
M. (1994). Brands in Films: Young
Moviegoers’ Experiences and
Interpretations. In K. W. King (Ed.), The
proceedings of the 1994 conference of the
American Academy of Advertising (pp. 90-
96). Athens, GA: Henry W. Grady College
of Journalism and Mass Communication.
Dens, N., De Pelsmacker, P.,
Wouters, M., & Purnawirawan, N., (2012).
Journal of Advertising, 41, 3, pp. 35-54.
Dovidio, J. F., & Fazio, R. H.
(1991). New technologies for the direct and
indirect assessment of attitudes. In J. M.
Tanur (Ed.), Questions about Questions:
Inquiries into the Cognitive Bases of
Surveys, pp. 204-237. New York: Russell
Sage.
Experian Simmons (2012). Simmons
Spring 2012 National Consumer Survey
[Data file].
Fazio, R. H. (1986). How do
attitudes guide behavior? In R. M.
Sorrentino & E. T. Higgins (Eds.),
Handbook of Motivation and Cognition (pp.
204-243). New York: Guilford.
Fazio, R. H. (1990). Multiple
processes by which attitudes guide behavior:
The MODE model as an integrative
framework. Advances in Experimental
Social Psychology, 23, 75-109.
Fazio, R. H., & Towles-Schwen, T.
(1999). The MODE model of attitude-
behavior processes. In S. Chaiken & Y.
Trope (Eds.), Dual-Process Theories in
Social Psychology (pp. 97116). New York:
Guilford.
Fazio, R. H., Sanbonmatsu, D. M.,
Powell, M. C., & Kardes, F. R. (1986).On
the automatic activation of attitudes. Journal
of Personality and Social Psychology, 50(2),
229-238.

Fiske, S. T., & Taylor, S. E. (1984).
Social cognition (1st ed.). Reading, MA:
Addison-Wesley.
Fishbein, M., & Ajzen, I. (1975).
Belief, Attitude, Intention, and Behavior: An
Introduction to Theory and Research.
Reading, MA: Addison-Wesley.
Fisher, T. L., & Wagner, C. B
(2004). Who? Sees what products? In which
content? And under what conditions? A
broader product placement framework.
Mass Communication, Toronto, Canada.
Greenwald, A. G., McGhee, D. E., &
Schwartz, J. L. K. (1998). Measuring
individual differences in implicit cognition:
The Implicit Association Test. Journal of
Personality and social Psychology, 74,
1464-1480.
Gupta, P. & Gould, S. (1997).
Consumers’ perceptions of the ethics and
acceptability of product placements in
movies: product category and individual
Differences. Journal of Current Issues and
Research in Advertising, 19(1), 37 –50.
Hawkins, S. A., & Hoch, S. J.
(1992). Low-involvement learning: Memory
without evaluation. Journal of Consumer
Research, 19, 212–225.
Heider, F. (1958) The Psychology of
Interpersonal Relations. Hoboken, NJ: John
Wiley & Sons.
Hoffner C., & Cantor J. (1991).
Perceiving and responding to mass media
characters. In J. Bryant & D. Zillmann
(Eds.), Responding to the Screen. Hillsdale,
NJ: Lawrence Erlbaum.
Hovland, C.I., Janis, I.L., & Kelley,
H.H. (1953). Communication and
persuasion. New Haven, CT: Yale
University Press.
Kahneman, D. (1973). Attention and
Effort. Englewood Cliffs, NJ: Prentice-Hall.
Karrh, J. A. (1994). Effects of brand
placements in motion pictures. In K. W.
King (Ed.), The proceedings of the 1994
conference of the American Academy of
Advertising (pp. 90- 96). Athens, GA: Henry
W. Grady College of Journalism and Mass
Communication.
Karrh, J. A. (1998a). Brand
placement: A review. Journal of Current
Issues and Research in Advertising, 20, 31-
49.
Karrh, J. A. (1998b). Why (Some)
Brand placements are effective: Insights
from Impression Management Research. In
D. D. Muehling (Ed.), The proceedings of
the 1998 conference of the American
Academy of Advertising (pp. 306-307).
Pullman, WA: Washington State University.
Karrh, J. A., McKee, K. B., &
Pardun, C. J. (2003). Practitioners’ evolving
views on product placement effectiveness.
Journal of Advertising Research, 43(2), 138-
149.
Law, S., & Braun-LaTour, K. A.
(2004). Product placements: How to
measure their impact. In L. J. Shrum (Ed.),
The psychology of entertainment media:
Blurring the lines between entertainment
and persuasion. Lawrence Erlbaum:
Mahwah, NJ.
Lehu, J.M., Bressoud, E. (2007) La
Londe conference marketing
communications and consumer behavior.

Journal of Business Research, 61(10), 1083-
1090.
Lowery, B. S., Hardin, C. D., &
Sinclair, S. (2001). Social influence effects
on automatic racial prejudice. Journal of
Personality and Social Psychology, 81(5),
pp. 842-855.
Matthes, J. (2012). Child exposure to
food and beverage placement in movies:
Toward an implicit persuasion model. Top
paper presented to the Advertising Division
Mass Communication, Chicago, Il.
Nisbett, R. E., & Wilson, T. D.
(1977). Telling more than we can know:
Verbal reports on mental processes.
Psychological Review, 84, 231-259.
Palmgreen, P., Donohew, L., Lorch,
E. P., Rogus, M., Helm, D., & Grant, N.
(1991). Sensation seeking, message
sensation value, and drug use as mediators
of PSA effectiveness. Health
Communication, 3(4), 217-227.
Petty, R. E., Baker, S. M., &
Gleicher, F. (1991). Attitudes and drug
abuse prevention: Implications of the
elaboration likelihood model of persuasion.
In L. Donohew, H. E. Sypher, &
Petty, R. E., & Cacioppo, J. T.
(1986). The Elaboration Likelihood Model
of Persuasion. In L. Berkowitz (Ed.),
Advances in Experimental Social
Psychology (Vol. 19, pp. 123- 205). New
York: Academic.
Petty, R. E., & Wegener, D. T.
(1999). The elaboration likelihood model:
Current Status and controversies. In S.
Chaiken, & Y. Trope (Eds.), Dual-Process
Theories in Social Psychology (pp. 41-72).
New York: Guilford.
Pickton, D., & Broderick, A. (2005).
Integrated Marketing Communications (2nd
ed., p. 242). Pearson Educates Limited,
Harlow, UK.
Rudman, L. A., Greenwald, A. G.,
Mellot, D. S., & Schwartz, J. L. K. (1999).
Measuring the automatic components of
prejudice: Flexibility and generality of the
implicit association test. Social Cognition,
17, 437-465.
Russell, C. (1998). Toward a
framework of product placement:
Theoretical propositions. Advances in
Consumer Research, 25, 357-362.
Russell, C. (2002). Investigating the
effectiveness of product placements in
television shows: The role of modality and
plot connection on brand memory and
attitude. Journal of Consumer Research,
29(3), 306-318.
Rossiter, J. R., Percy, L., &
Donovan, R. J. (1991). A better advertising
planning grid. Journal of Advertising
Research, 31, 11-21.
Balasubramania, S. K., Karrh, J. A.,
Patwardhan, H. (2006). Journal of
Advertising, 35, 3, pp. 115-141.
Soba, M., & Aydin, M. (2013).
Product Placement Efficiency in Marketing
Communication Strategy. International
Journal of Business & Management (Vol. 8
Issue 12), p111-116. 6p.
Soba, M., & Aydin, M. (2013).
Product Placement Efficiency in Marketing
Communication Strategy. International

Journal of Business & Management (Vol. 8
Issue 12), p111-116. 6p.
Sundar, S. S. (1999). Questions (and
responses) for the record. Submitted to the
Subcommittee on Criminal Justice, Drug
Policy and Human Resources of the
Government Reform Committee for the
United States House of Representatives
hearings on the National Youth Anti-Drug
Media Campaign, Washington, DC.
Tesser, A., & Leone, C. (1977).
Cognitive schemas and thought as
determinants of attitude change. Journal of
Experimental Social Psychology, 13, 340-
356.
Tourangeau, R., & Smith, T. W.
(1996). Asking sensitive questions: The
impact of data collection mode, question
format, and question context. Public
Opinion Quarterly, 60(2), 275-304.
Varoufakis, V. (2014, February 22).
Can the internet democratize capitalism?
International Policy Digest. Retrieved
February 22, 2014 from
http://www.internationalpolicydigest.org/20
14/02/22/can-internet-democratize-
capitalism/
Wagner, C. B (2001). Implicit
attitudes and anti-drug PSAs: Automatic
processes and unreasoned action. Paper
presented at the 84th annual conference of
the Association for Education in Journalism
and Mass Communication, Washington, DC.
Wagner, C. B (2003). Anti-drug ads:
Do traditional attitude measures exaggerate
their effectiveness? Paper presented to the
Advertising Division at the 86th annual
meeting of the Association for Education in
Journalism and Mass Communication,
Kansas City, MO.
Wagner, C. B (2004). Changing the
nature of unreasoned actions: A test of the
anti-drug ad viewing styles hypothesis.
at the 87th annual conference of the
Mass Communication, August 2004,
Toronto, Canada.
Wagner, C. B, & Clark, J. (2013).
Unwilling Sources And Unwilling
Consumers: Uncovering The Mental Labor
In Associating Sports heroics and
Sponsorships. Paper presented to the Mass
Communication & Society Division at the
2013 Midwinter Conference of the
Mass Communication, March 1-2, 2013,
Norman, Oklahoma.
Wagner, C. B, & Sundar, S. S.
(2003). Automatic activation of drug
attitudes: Anti-drug ad viewing styles and
strength of association. Top Faculty Paper
presented to the Communication Theory and
Methodology Division at the 86th annual
conference of the Association for Education
in Journalism and Mass Communication,
July 2003, Kansas City, MO.
Wagner, C. B, & Sundar, S. S.
(2009). Sneaking it in: The importance of
peripheral processing in promoting strong
anti-drug attitudes. American Journal of
Media Psychology, 2(1), 9-43.
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