AEJMC Archives

AEJMC Archives


View:

Next Message | Previous Message
Next in Topic | Previous in Topic
Next by Same Author | Previous by Same Author
Chronologically | Most Recent First
Proportional Font | Monospaced Font

Options:

Join or Leave AEJMC
Reply | Post New Message
Search Archives


Subject: AEJ 03 WagnerC ADV Anti-Drug Ads:Do Traditional Attitude Measures Exaggerate Their Effectiveness?
From: Elliott Parker <[log in to unmask]>
Reply-To:AEJMC Conference Papers <[log in to unmask]>
Date:Sun, 21 Sep 2003 14:42:23 -0400
Content-Type:text/plain
Parts/Attachments:
Parts/Attachments

text/plain (762 lines)


Anti-Drug Ads:
Do Traditional Attitude Measures Exaggerate Their Effectiveness?

Carson B Wagner
Department of Advertising
College of Communication
CMA 7.143
University of Texas at Austin
Austin, TX 78712

Voice:  (512) 471-3429
Fax:  (814) 471-7108
E-Mail:  [log in to unmask]



Paper submitted to the Advertising Division for presentation at the 2003
annual convention of the Association for Education in Journalism and Mass
Communication, Kansas City, MO, August, 2003

Anti-Drug Ads:
Do Traditional Attitude Measures Exaggerate Their Effectiveness?

A       B       S       T       R       A       C       T
Due to their obtrusiveness, the sensitive nature of illicit drugs, and
research situation demands, self-report attitude measures used in anti-drug
ad studies may produce exaggerated estimates of message effectiveness.  To
explore this possibility, a between-participants experiment (N = 25) was
run to compare traditional self-report measures with newly-emerging, less
obtrusive response latency attitude measures.  Results indicate that
self-report measures tend to magnify drug ad effects as compared to
response latency measures.


 Anti-Drug Ads:
Do Traditional Attitude Measures Exaggerate Their Effectiveness?

A proliferation of drug ad studies have demonstrated that these commercials
affect our attitudes.  But, the vast majority of this research has assessed
self-reported attitudes, and due to their obtrusive nature, such measures
have been shown to be highly susceptible to social desirability (see
Watkins, 1996), demand characteristics (Orne, 1969; Watt & van de Berg,
1995, p. 256) and situational norm confounds (Dovidio & Fazio, 1991; Fazio
& Towles-Schwen, 1999).  This is especially true when the measures concern
sensitive topics such as illicit drugs (Carifio, 1994; Carifio & Biron,
1978; Tourangeau & Smith, 1996).  When directly asking people to express
their attitudes about drugs, we run the risk that responses are not
indicative of the participants' genuine feelings, and so effectiveness
demonstrations may be exaggerated.
This is not to imagine simply that drug ad participants are lying.  People
can produce unfaithful responses both intentionally and unintentionally
(Dovidio & Fazio, 1991).  Certainly, individuals may knowingly hold a
socially undesirable attitude (e.g., pro-drug) and purposefully respond in
a way that doesn't match in order to deceive the researcher.  However, they
may unknowingly hold such an attitude and implicitly refuse to admit this
to themselves, thereby answering questionnaires in such a way as to present
"ideal" selves that reflect the ways they might like to be seen by others
or by themselves.  The appearance of an attitude where none exist can
likewise be created when answering a questionnaire (Fazio, 1986; Fazio,
Lenn, & Effrein, 1984), and such phenomena are decidedly unhelpful when
attempting to examine drug ad effectiveness.
However, newer measures are available to gauge attitudes less obtrusively
than by self-report.  Rather than directly asking participants to express
their attitudes, these scales examine the extent to which "priming"
participants with attitude objects (e.g., briefly exposing them to concepts
like "drugs") hinders or facilitates the speed with which they can
correctly categorize subsequently presented adjectives (see Fazio &
Towles-Schwen, 1999 for a review).   In doing so, response latency attitude
measures can circumvent the veridicality concerns that haunt self-report,
because one "need not be at all aware that his or her attitude is being
assessed" (Fazio, Sanbonmatsu, Powell, & Kardes, 1986, p. 237).  As a
result, response latency scales diminish the possibility that participants
will—knowingly or not—falsely represent themselves, and therefore the
measures can yield a clearer picture of drug ad effectiveness.
If psychological mechanisms such as social desirability do influence
self-reported attitudes in drug ad studies, and if response latency
measures help avoid those confounds, then the former scales would depict
attitudes more negatively than the latter.  That is, especially in research
situations, self-reported attitudes may exaggerate negative attitudes
toward drugs.  To test such a possibility, this paper presents a study
comparing the effects of drug ads on attitudes measured via self-report to
attitudes gauged using a response latency method.

Literature Review
A large body of research has documented drug ad effects on self-reported
attitudes, but comparatively little attention has been paid to response
latency measures (Wagner, 2001).  Prior research has investigated effects
across "various source, message, recipient, and channel variables" (Baker,
Petty, & Gleicher, 1991, p. 200), and two independent variable
categories—ad types and audience traits—are most commonly examined
(McGuire, 2001; Wagner & Sundar, 1999).
Message features including form, style, and context, have been shown to
play a role in changing attitudes (Perry, 1996, p. 99).  For instance,
rational appeals can be more convincing than emotional appeals (Perse,
Nathanson, & McLeod, 1996), while emotional appeals are more memorable
(Flora & Maibach, 1990).  Audience traits such as family communication
patterns (e.g., Skinner & Slater, 1995), rebelliousness (e.g., Slater &
Rouner, 1996), and sensation-seeking (e.g., Everett & Palmgreen, 1995) have
been investigated both in isolation and in combination with various
messages.  To illustrate, sensation-seeker studies have included variations
in message sensation value (Everett, 1993; Palmgreen, Donohew, Lorch,
Rogus, Helm, & Grant, 1991), style and form sensation values (Everett &
Palmgreen, 1995), and program context (Everett, 1993; Lorch, Palmgreen,
Donohew, Helm, Baer, & Dsilva, 1994).  This research shows that: a) more
sensational messages are better at increasing sensation seekers' anti-drug
attitudes; and b) this increases as ad context becomes more sensational.
In general, studies demonstrate that drug ads can change attitudes (e.g.,
Black, 1991;   Johnston, 1999, Oct. 14; Kelly & Edwards, 1992;  Reis,
Duggan, Adger, & DeAngelis, 1994).  However, the research has relied almost
exclusively on gauging attitudes via self-report, and directly asking
participants to express their attitudes—especially on sensitive topics such
as drugs (Carifio, 1994; Carifio & Biron, 1978; Tourangeau & Smith,
1996)—can produce erroneous results (Dovidio & Fazio, 1991; Fazio, 1986).
First, attitude questionnaires can provoke the generation of an attitude
(or its appearance) even if the individual responding holds no a priori
evaluation (Fazio, Lenn, & Effrein, 1984).  Simply asking participants to
respond to various posers can lead them to form attitudes on the spot or
otherwise generate specific responses in order to appear or feel
knowledgeable, and contextual cues in the research situation can guide such
responses (Fazio, 1986).  Given the presence of anti-drug ads as well as an
authority figure (i.e., the researcher), participants may display anti-drug
attitudes simply because such a position seems congruent with the
atmosphere of a drug ad study.
Next, if a given participant knowingly holds an attitude deemed socially
undesirable (i.e., pro-drug), he or she may intentionally misreport holding
a socially desirable attitude (i.e., anti-drug) in order to appear
acceptable (Dovidio & Fazio, 1991).  This phenomenon plagued stereotyping
research starting in the 1950s—when surveys began to show the widespread
disappearance of prejudice—and this prompted social psychologists to create
and seek out less obtrusive stereotyping measures (see e.g., Gaertner &
Dovidio, 2000; Park, Judd, & Ryan, 1991; Sears, 1988).  Similar to the
above instance, the research situation may heighten the salience of social
and situational norms, leading participants to display situation-congruent
attitudes in order to purposefully deceive the researcher (Dovidio & Fazio,
1991).  Even the promise of response anonymity is not sufficient to
override this tendency (Fazio, 1986).
Last, research participants can unknowingly hold undesirable attitudes,
unconsciously refuse to admit it, and respond to attitude questionnaires in
such a way as to present an "ideal self" (Dovidio & Fazio, 1991).  That is,
latent or implicitly held (Seger, 1994) attitudes may be stored but
suppressed by participants who wish to see themselves as "good people"
(Dovidio & Fazio, 1991).  However, despite that such attitudes may even be
inarticulable, their presence in memory can guide behavioral responses to
attitude objects (Fazio, 1990; Fazio & Towles-Schwen, 1999) at times when
social norms do not dictate or promote a socially desirable response.  If
activated by the presence of an attitude object (i.e., illicit drugs), such
stored information can prompt attitude-congruent behaviors (Fazio &
Towles-Schwen, 1999), in this case leading someone who would present
themselves as anti-drug on attitude questionnaires to yield to offers of
drugs in certain situations.
Under conditions similar to those of drug ad research, it is expected that
people would make decisions in line with attitudes expressed via
self-report (Dovidio & Fazio, 1991; Fazio, 1990), but it is uncertain how
often research and drug-taking situations exhibit comparable
conditions.  In other words, do drug offers normally occur under conditions
that similarly promote anti-drug norms?  When they don't, the above line of
reasoning suggests that self-report attitude measures likely would not
predict a participant's response to drug offers (Dovidio & Fazio, 1991;
Fazio, 1990), despite that attitudes are often thought to be the among the
variables most predictive of subsequent behaviors (McGuire, 2001).
When attitudes are assessed less obtrusively than by self-report, the
results can better reflect participants' underlying viewpoint—whether
articulable or not—as opposed to being guided by social and situational
norms (Dovidio & Fazio, 1991).  To examine attitudes unobtrusively,
researchers have employed a "primed response latency" measure (Fazio,
Sanbonmatsu, Powell, & Kardes, 1986; see Fazio & Towles-Schwen, 1999 for a
review) wherein one quickly primes participants with an object descriptor
and then records the time it takes the participant to correctly categorize
a subsequently presented positive or negative adjective.  The prime is used
to activate an a priori attitude, if one exists, and adjective/attitude
congruency speeds correct adjective categorization while incongruency slows
it.
For example, if one primes participants with an object about which they
hold a positive attitude—say, "puppies"—this will enhance their ability to
categorize words like "good" or "wonderful," while it will slow their
categorization of "bad" or "horrible," and vice versa for a negative
attitude.  The amount of facilitation or impedance, in turn, is referred to
as response latency.  So then, the tests don't ask participants to form
direct responses to an attitude object, making it very difficult for them
to misrepresent themselves, even on sensitive issues.  Attesting to the
measures' veridicality, across studies response latency tends to predict a
greater number of less sensitive attitudinal covariates as compared to
self-report (Dovidio & Fazio, 1991).
In sum, there are three routes by which self-report measures can mistakenly
reveal anti-drug attitudes, and as with stereotyping studies (see e.g.,
Eagly & Steffen, 1984; Hoffman & Hurst, 1990; Jost & Banaji, 1994; Weber &
Cook, 1972), drug ad research situations likely promote each process.  On
the other hand, response latency measures help avoid such confounds, and so
they would yield responses less influenced by anti-drug norms (i.e., more
positive attitudes).  To the extent that drug ad research situations
heighten anti-drug norms, self-report measures will depict attitudes more
negatively than their response latency counterparts, and as such
self-report measures likely exaggerate the effectiveness of anti-drug ads:

H1:     After viewing drug ads in a research situation, participants who
answer self-report questionnaires will display more negative drug-related
attitudes as compared to those who complete response latency measures.


Method
All participants (N=25) in a between-participants experiment were exposed
to six thirty second Partnership for a Drug-Free America anti-drug ads
targeted to young adults, and afterwards their drug-related attitudes were
measured.  Participants were randomly assigned to one of two
conditions.  In one, participants' attitudes were measured using a
self-report questionnaire, and in the other, participants' attitudes were
calculated using a response latency test (Wagner, 2001).  Twelve
participants were assigned to the self-report condition, and thirteen were
assigned to the response latency condition.  The two conditions were
identical, including the ads presented and the order in which they
appeared, with the exception of the attitude measure employed.

Participants
Twenty-five undergraduate students enrolled in introductory journalism
classes participated in the experiment for course credit.  The students
were invited in class to take part, and there they signed up for group
administration experimental sessions.  All participants signed an informed
consent form prior to their involvement in the study.

Procedure
Upon arrival at the study, participants were asked to sign an informed
consent form which described their rights as research participants.  This
document explained that the purpose of the study was to remain unknown to
them until after the procedure was finished.  After signing the forms,
participants viewed the ads, and afterwards they completed either a
self-report or a response latency attitude measure.  Throughout the
procedure, participants were seated in rows of classroom desks, with
sufficient distance among them so as to avoid revealing their responses to
one another, and the experimenter, either a male or a female, was seated at
front of the room.   Two experimental sessions were run for each condition,
for a total of four sessions.  In the self-report condition, there were six
participants in each session.  In the response latency condition, there
were six participants in one and seven in the other.  The two
experimenters—one male or one female—were counterbalanced across
conditions, but their presence did not qualify the reported results.


Stimulus Material
Six anti-drug ads produced by The Partnership for a Drug-Free America in
the year 2000 were used as the experimental stimulus.  Each was a thirty
second ad designed for young adults.  Three of the ads were celebrity
appeals, while the other three were fear appeals.  The presentation began
with a fear appeal then moved to a celebrity appeal.  It repeated this
pattern for the duration.  The ads are briefly described in Appendix A in
order of presentation.

Dependent Measures
In the self-report condition, a pencil-and-paper questionnaire measuring
drug-related attitudes was employed following ad presentation.  It was
comprised of eight five-point semantic differential scales anchored by a
positive and a negative adjective, and atop the scales were directions for
completing the measure.  This stated briefly:

"Below is a list of word pairs.  Circle one of the numbers near the word in
each pair that best describes how you feel about the following statement:
'FOR ME, USING DRUGS WOULD BE...'"

The measure was adapted from prior research on drug-related attitude change
via drug ad consumption (Palmgreen, Donohew, Lorch, Rogus, Helm, & Grant,
1991).  The instructions and six of the adjective pairs (good/bad,
pleasant/unpleasant, valuable/worthless, favorable/unfavorable,
acceptable/unacceptable, and nice/awful) were taken directly from the
original, and two sets of adjective pairs (wonderful/horrible and
excellent/poor) were added by Wagner (2001) in order to maintain
consistency with his response latency measure.  The order of the adjective
pairings was counterbalanced across groups of participants, but this did
not qualify the reported results.
In the response latency condition, a pencil-and-paper response latency
measure of attitudes was employed.  The measure was originally developed by
Lowery, Hardin, and Sinclair (2001) to investigate stereotyping, and it was
adapted to drug-related attitudes by Wagner (2001).  As with other response
latency tests (see Dovidio & Fazio, 1991), this version has been shown to
better predict less sensitive attitudinal covariates as compared to
self-report attitude measures (Wagner, 2002).  Also similar to various
response latency adaptations (see e.g., Dasgupta, McGhee, Greenwald, &
Banaji, 2000; Greenwald, McGhee, & Schwartz, 1998; Rudman, Greenwald,
Mellot, & Schwartz, 1999),  this measure uses five separate timed judgment
stages.  For each of the five stages, a column of words running down the
middle of each page comprises the judgment items, and evaluations are
indicated by checkmarks in the appropriate right and left-hand columns.
Before entering the judgment stages, participants are shown four lists of
words (contained in the measure packets) two at a time, and they are asked
to become familiar with the words before the experiment progresses.  The
first set of lists includes the names of both drugs and colors, and the
second set includes both positive and negative adjectives.  Eight words of
each type are shown on the lists, and these words are later used as items
in association tasks.
The list of drugs includes heroin, marijuana, hashish, glue, mushrooms,
LSD, cocaine, and crack, and the list of colors includes blue, orange,
pink, green, brown, yellow, purple, and red.  The lists of positive
adjectives includes good, pleasant, valuable, favorable, acceptable, nice,
wonderful, and excellent.  The list of negative adjectives includes bad,
unpleasant, worthless, unfavorable, unacceptable, awful, horrible, and poor.
After participants study each set of words and raise their heads to
indicate they are done, the researcher begins the judgment stages.  The
first two stages are "practice stages," wherein participants become
familiar with the activity of categorizing words before being assessed.  In
the first of these stages, the lists of drugs and colors run down the
middle of the page, mixed in a random fashion, and participants are given
fifteen seconds to categorize them by placing a checkmark on the
appropriate side as they move sequentially down the page.  Appropriate
sides are indicated at the top of the page (i.e., "drugs" is printed on the
left or right, with "colors" opposing), and participants are given verbal
instructions as to what the appropriate side would be prior to beginning
the timed judgment stage.  For example:

COLORS                                              DRUGS
MARIJUANA
YELLOW

The second stage is similar to the first, except that the list is of
positive and negative adjectives, and "positive" and "negative" anchor the
sides at the top of the page.
The third stage is a critical judgment phase, or one that is used to assess
participants' attitudes, and it includes all four types of words.  The list
begins with either a positive or negative adjective or a drug or color
name, with the next word coming from the opposite category (e.g.,
adjective) and the word after that coming from the initial category (e.g.,
drug or color), and so on in that fashion.  The appropriate judgment sides,
similarly indicated at the top of the page, combine both drugs or colors
and positive or negative words.  So then, one of the sides is the proper
side to check for either drugs and negative or positive, while the other is
the correct side for colors and the opposite kind of adjective.  The
specific sides match those used in the preceding practice stages for all
participants.  For example:

COLORS or positive                         DRUGS or negative
awful
MARIJUANA
good
YELLOW

Participants are again allotted fifteen seconds to categorize as many of
these terms as they can, moving sequentially down the page.  This phase
includes two such lists given one after the other.
The fourth stage is another practice stage.  As the measure calculates
attitudes by differencing the number of items correctly categorized when
pairing drugs with positive adjectives versus coupling drugs with negative
adjectives, the appropriate side for each drugs and colors in the fifth
critical stage is switched while keeping positive and negative
constant.  The fourth stage is introduced to afford participants
familiarity with categorizing drugs and colors on the page sides opposite
those they had just used, and the list therefore only includes names of
drugs and colors.
The fifth stage is again a critical phase, requiring simultaneous
categorization of both drug and color names and positive and negative
adjectives.  This phase is the same as the third stage except that the
appropriate side for the drug and color names is switched, and participants
are therefore categorizing these names with the opposite kind of adjective.
The order of pairing drugs with negative words and with positive words
(phases 3 and 5), along with the side participants check to categorize the
drugs and colors were counterbalanced across groups, but again this did not
qualify the reported results.

Data Analysis
To form a Self-Report Total Score Index, the eight drug-related self-report
items were summed with equal weighting (Palmgreen, Donohew, Lorch, Rogus,
Helm, & Grant, 1991).  To create a Response Latency Difference Score Index,
the scores for each of the two drug-related response latency critical
phases—drugs paired with positive and drugs paired with negative
adjectives—were summed into positive and negative indices, respectively,
and the negative phase scores were subtracted from the positive phase
scores (Lowery, Hardin, & Sinclair, 2001; Wagner 2001).

Results
In order to explore the relationship between the two types of attitude
measures, the indices were first transformed to achieve the same
theoretical ranges between the measures.  To do so, the Response Latency
Difference Score Index—which has a range of sixty-four to negative
sixty-four—was divided by four to create a Range Transformed Response
Latency Index.  The newer index has a range of sixteen to negative sixteen,
which is equal to that of the Self-Report Total Score Index.
Entering the resultant indices as dependent variables into a one-tailed
t-test with measure type as the dependent variable, a significant
difference was found [t(23) = -4.53, p <.0001] such that self-reported
attitudes after seeing drug ads (M= -10, SD=5.95) were significantly more
negative than attitudes measured via response latency (M= -2.09,
SD=1.97).  These results support H1, which predicts that self-report
attitude measures can exaggerate the effectiveness of anti-drug ads.
  However, in order to perform a more rigorous test on the present data,
the original Response Latency Difference Score Index was retransformed in
such a way as to attain identical standard deviations between the
measures.  To achieve this, the standard deviation of the self-report
results (5.95) was first divided by the standard deviation of the
untransformed response latency results (7.89).  Next, the original Response
Latency Difference Score Index was multiplied by the result (0.754) to
create a Standard Deviation Transformed Response Latency Index.  The newest
index has a standard deviation of 5.95, equal to that of the Self-Report
Total Score Index.
Again entering the resultant indices as dependent variables into a
one-tailed t-test with measure type as the independent variable, a
marginally significant difference was found [t(23) = -1.54, p =.06] such
that self-reported attitudes  (M= -10, SD=5.95) were more negative than
response latency attitudes (M= -6.32, SD=5.95).  These results also lend
support to H1, although to a lesser degree.

Discussion
The results demonstrate that self-report measures can exaggerate the
effectiveness of anti-drug ads as compared to response latency
measures.  This supports H1, which was based on the notion that the
heightened salience of anti-drug norms in drug ad research situations can
influence participants' self-reported attitudes.  Further, the results
suggest that by employing less obtrusive measures, we may avoid the
influence of social and situational norms, a finding that also supports
prior research on similarly sensitive topics (Dovidio & Fazio, 1991).
The present study has various implications for different drug ad research
streams.  With respect to surveys, it suggests that prior research may have
generated inflated claims of the ads' generalizable effects.  For instance,
findings from ongoing research such as the Institute for Social Research's
Monitoring the Future studies (e.g., Johnston, O'Malley, & Bachman, 2003),
which are often used to evaluate the Office of National Drug Control
Policy's Anti-Drug Media Campaign (e.g., Johnston, 1999, Oct. 14), may be
overstated as a function of the larger anti-drug climate created by the
recent prevalence of drug ads (see Sundar, 1999, Nov. 3).  To better asses
the ads ' broad impact, survey researchers might employ paper-and-pencil
versions of response latency measures—as was done in this study—or they
might otherwise construct web-based measures akin to Project Implicit's
implicit association tests (IAT Corporation, 2003) of stereotyping in order
to overcome the influence of norms on their findings.
The present results also have implications for experimental
research.  Historically, experiments often seek to determine which ad types
yield better results or which kinds of people are affected more favorably
by comparing participants' self-reported attitudes as a result of ad
consumption.  As with survey research, various findings may, at least in
part, be a function of the extent to which various types of ads stress the
existence/importance of situational norms, or, perhaps more likely, the
extent to which different kinds of individuals are susceptible to the
influence of norms.  For instance, participants of varying levels of
self-esteem (e.g., Rhodes & Wood, 1992), sensation-seeking (e.g., Palmgreen
et al., 1991), rebelliousness (e.g., Skinner & Slater, 1995), or need for
cognition (see Cacioppo & Petty, 1982) would differentially recognize norms
and/or respond in socially desirable ways.
In experiments that utilize pre- and post-consumption questionnaires,
participants can become especially sensitized toward the study's purpose
(Watt & van de Berg, 1995, p. 256), and it has been shown that if subjects
are able to determine the purpose of a study, they will tell the researcher
what he or she wants to hear (i.e. indicating that the ad worked as
intended) (Orne, 1969).  This is commonly known as "demand
characteristics," and it often occurs due to the effect of situational
norms (Watkins, 1996).
  Beyond the influence of norms, testing effects threats to validity
(Ayres, Hopf, & Will, 2000) are also a key concern in before/after
experimental designs that employ self-report measures rather than response
latency tests (Dovidio & Fazio, 1991).  In other words, measuring a
participant's attitude via response latency before viewing ads should not
influence results on the same measure when administered post-ad, whereas
testing effects often occur with self-report.  Although not a direct test
of this assumption, the lack of demonstrated response latency differences
pre- and post-ad in Wagner's (2001) drug ad study supports this argument,
especially given that self-report differences were shown using the same set
of commercials.  Future studies might examine the possibility in greater
detail.
Unfortunately, the present study raises more questions than it
answers.  Given the present data, the various effects of testing, demand
characteristics, and social and situational norms can not be
delineated.  It is also not possible to examine the extent to which
misrepresentation on self-report measures occurred intentionally or
unintentionally, or whether participants held drug-related attitudes a
priori.  Such questions can only be answered using more sophisticated
experimental designs and by employing more specific measures.  Perhaps,
though, this study does raise the proper questions, and it is a modest
first attempt to generate a useful route by which to begin answering them.
In sum, the present study helps demonstrate the value of employing response
latency attitude measures in drug ad research.  Although it has been shown
to be more difficult to demonstrate drug-related attitude change using
response latency measures as compared to self-report (Wagner, 2001),
differences have been shown (Wagner, 2002), and the results are likely to
better predict future drug-related behaviors (Dovidio & Fazio, 1991; Fazio
& Towles-Schwen, 1999), which might be the most appropriate test of drug ad
effectiveness.

 References

Ayres, J., Hopf, T., & Will, A. (2000). Are reductions in CA an
experimental artifact? A Solomon four-group answer.  Communication
Quarterly, 48 (1), 19-26.

Black, G. S. (1991).  Changing attitudes toward drug use: The effects of
advertising.  In L. Donohew, H. E. Sypher, & W. J. Bukowski (Eds.),
Persuasive Communication and Drug Abuse Prevention (pp.
157-191).  Hillsdale, NJ: Erlbaum.

Cacioppo, J. T., & Petty, R. E. (1982).  The need for cognition.  Journal
of Personality and Social Psychology, 42, 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.

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.

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.

Eagly, A. H., & Steffen, V. J. (1984).  Gender stereotypes stem from the
distribution of women and men into social roles.  Journal of Personality
and Social Psychology, 46(4), 735-754.

Everett, M. W. (1993).  Influence of sensation-seeking, message sensation
value, and program context on effectiveness of anti-cocaine
PSAs.  Dissertation Abstracts International, 54 (2-A), 355-356.

Everett, M. W., & Palmgreen, P. (1995).  Influences of sensation seeking,
message sensation value, and program context on effectiveness of
anti-cocaine public service announcements.  Health Communication, 7, 225-248.

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., Lenn, T. M., & Effrein, E. A. (1984).  Spontaneous attitude
formation.  Social Cognition 2, 217-234.

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.

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. 97-116).  New York: Guilford.

Flora, J., & Maibach, E. W. (1990).  Cognitive responses to AIDS
information: The effects of issue involvement and message
appeal.  Communication Research, 17(6), 759-774.

Gaertner, S. L., & Dovidio, J. F. (2000).  Reducing Intergroup Bias: The
Common Ingroup Identity Model.  Ann Arbor, MI: Sheridan.

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.

Hoffman, C., & Hurst, N. (1990).  Gender stereotypes: Perception or
rationalization?  Journal of Personality and Social Psychology, 58(2), 197-208.

IAT Corporation (2003).  Project Implicit.  [online].  Available
https://implicit.harvard.edu/implicit/

Johnston, L. D. (1999, Oct. 14).  Testimony submitted to the Subcommittee
on Criminal Justice, Drug Policy and Human Resources of the Government
Reform Committee United States House of Representatives for hearings on the
National Youth Anti-Drug Media Campaign held on October 14,
1999.  Washington, DC.

Johnston, L.D., O'Malley, P.M., & Bachman, J.G. (2003).  The Monitoring the
Future national survey results on adolescent drug use: Overview of key
findings, 2002 (NIH Publication No. 03-5374).  Bethesda, MD: National
Institute on Drug Abuse.

Jost, J. T., & Banaji, M. R. (1994).  The role of stereotyping in
system-justification and the production of false consciousness.  British
Journal of Social Psychology, 33, 1-27.

Kelly, K., & Edwards, R. (1992).  Observations: Does discussion of
advertising transform its effects?  Yes...sometimes: A case among college
students and their response to anti-drug advertising.  Journal of
Advertising Research, 32(4), 79-83.

Lorch, E. P., Palmgreen, P., Donohew, L., Helm, D., Baer, S. A., & Dsilva,
M. U. (1994). Program context, sensation seeking, and attention to
televised anti-drug public service announcements. Human Communication
Research, 20 (3), 390-412.

Lowery, B. S., Hardin, C. D., & Sinclair, S. (2001).  Social influence
effects on automatic racial prejudice.  Journal of Personality and Social
Psychology, 81 (5), 842-855.

McGuire, W. J. (2001).  Input and output variables currently promising for
constructing persuasive campaigns.  In R. E. Rice & C. K. Atkin (Eds.),
Public Communication Campaigns (3rd. ed., pp. 22-48).  Thousand Oaks, CA: Sage.

Orne, M. T. (1969).  Demand characteristics and the concept of
quasi-controls.  In  R. Rosenthal & R. L. Rosnow (Eds.), Artifact in
Behavioral Research.  New York: Academic Press.

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.

Park, B., Judd, C. M., & Ryan, C. S. (1991).  Social categorization and the
representation of variability information.  In W. Stroebe & M. Hewstone,
(Eds.), European Review of Social Psychology (Vol. 2), pp. 211-245.

Perry, D. K. (1996).  Theory and researh in mass communication.  Mahwah,
NJ: Erlbaum.

Perse, E. M., Nathanson, A.I ., & McLeod, D. M. (1996).  Effects of
spokesperson sex, public service announcements, and involvement on
evaluations of safe-sex PSAs.  Health Communication, 8(2), 171-189.

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, & W. J. Bukowski (Eds.),
Persuasive communication and drug abuse prevention (pp. 71-90).  Hillsdale,
NJ: Erlbaum.

Reis, E. C., Duggan, A. K., Adger, H., Jr., & DeAngelis, C. (1994).  The
impact of  anti-drug advertising: Perceptions of middle and high school
students.  The Archive of Pediatric and Adolescent Medicine, 148, 1262-1268.

Rhodes, N., & Wood, W. (1992).  Self-esteem and intelligence affect
influencibility: The mediating role of message reception.  Psychological
Bulletin, 111, 156-171.

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.

Sears, D. O. (1988).  Symbolic Racism.  In P. A. Katz & D. A. Taylor
(Eds.), Eliminating Racism: Profiles in Controversy (pp. 53-84).  New York:
Plenium.

Seger, C. A. (1994).  Implicit learning.  Psychological Bulletin, 115, 163-196.

Skinner, E. R., & Slater, M. D. (1995).  Family communication patterns,
rebelliousness, and adolescent reactions to anti-drug PSAs.  Journal of
Drug Education, 25, 343-355.

Slater, M. D., & Rouner, D. (1996).  Value affirmation and value-protective
processing of alcohol education messages that include statistical evidence
or anecdotes.  Communication Research, 23, 210-235.

Sundar, S. S. (1999, Nov. 3).  Questions (and responses) for the
record.   Submitted to the Subcommittee on Criminal Justice, Drug Policy
and Human Resources of the Government Reform Committee United States House
of Representatives for hearings on the National Youth Anti-Drug Media
Campaign held on October 14, 1999.  Washington, DC.

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.

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 (2002).  Unobtrusive measures and unreasoned action: Anti-drug
ads and attitude strength.  Unpublished doctoral dissertation, University
of Colorado at Boulder.

Wagner, C. B, & Sundar, S. S. (1999).  The curiosity-arousing function of
anti-drug PSAs. Paper presented to the Health Communication Division at the
49th annual conference of the International Communication Association, San
Francisco, CA.

Watkins, D. (1996).  The influence of social desirability on learning
process questionnaires.  Contemporary Educational Psychology, 21(1), 80-82.

Watt, J. H., & van de Berg, S. A. (1995).  Research Methods for
Communication Science.  Needham Heights, MA: Allyn & Bacon.

Weber, S. J., & Cook, T. D. (1972).  Subject effects in laboratory
research: An examination of subject roles, demand characteristics, and
valid inferences.  Psychological Bulletin, 77, 273-295.




 Appendix A: Stimulus Ad Descriptions (In order of presentation)
1) "Model" (Fear Appeal) -- This spot portrays a female model "dressing
down," presumably following a photo shoot.  Ominous-sounding pan flute
music plays in the background throughout the ad as the viewer sees the
model watching herself in a dressing mirror that is surrounded by light
bulbs.  The ad begins with the model confronting herself in the mirror and
letting her hair down.  It then moves through various shots of the model
removing her makeup, and each progressive shot shows her face to be more
aged and flawed.  At last, we are shown a close-up of the model removing
her false teeth, revealing both her missing teeth and the partially rotted
teeth that remain.  The screen then fades to black with the words "It's
hard to face what heroin can do to you" shown in white.  The screen again
fades to black and the words "Partnership for a Drug-Free America" appear
in white.

2) "Andy MacDonald" (Celebrity Ad) -- This ad centers around professional
skateboarder Andy MacDonald describing his job.  In it, he explains that
getting to the place he is in his career takes a lot of motivation, hard
work, and dedication.  Further, he says that he has been riding for
thirteen years, and that it took him six years just to "learn to
skate."  He claims that there are boarders out there who are just as
talented as any athlete in any professional sport and that, no matter who
it is, wiping out on a skateboard is part and parcel of the experience.  As
he speaks, several shots of him doing stuntwork, both on pavement and on a
half-pipe, are shown in quick procession, shot from oblique angles and
tinted in various bright colors.  Towards the end of the spot, he admits
that drugs "will only slow you down" and that he couldn't do what he does
if he took drugs.  The commercial ends with Mr. MacDonald stating "that,
right there, is my idea of getting high" as viewers are shown a shot of him
flying off the end of a half-pipe.  The ad then cuts to black, with the
words "Partnership for a Drug-free America" in white, centered on the screen.

3) "Ashley" (Fear Appeal) -- This commercial focuses on a female named
Ashley discussing her experience with heroin.  She first describes what it
was like to use heroin, saying that it gave her a warm feeling and made her
feel like she was floating.  She then says that she swore she would never
"shoot up" and that when she started "doing dope," the fighter inside her
and the part of her that found joy in day-to-day living died.  The
commercial, mainly composed of a black-and-white, close-up, still camera
shots, fades twice to and from color stills of Ashley ten and four years
previous, and she continues talking through both.  The first color shot
shows her at age eighteen, and a caption explains that at the time she was
president of her high school class.  The second color shot shows her at age
twenty-four as an advertising executive.  As the commercial closes, we see
a caption explaining that she is currently a twenty-eight year-old heroin
addict.  The image of Ashley then fades to black, with the words
"Partnership for a Drug-Free America®" in white, centered on the screen.

4) "Serena and Venus Williams" (Celebrity Ad) -- This ad centers around
Serena and Venus Williams, two professional tennis stars.  As the
commercial opens, Serena explains that "As a kid, I remember dreaming of
becoming the best."  The spot then cuts to Venus saying "Of course, I do
more than dream -- I also make plans."  Venus then explains that she is
always working hard at becoming better, looking for new plateaus to which
to raise her abilities.  The PSA then cuts back to Serena stating "I don't
have to mess around with the drugs, 'cause I know that it's not good for
me...it's not good for anything that I do."  The images that compose the ad
are quickly cut close-ups of various body parts of the two female athletes
juxtaposed with medium-range shots of each of them talking.  The commercial
closes with Serena stating "Drugs kill dreams -- it's just not worth it"
played over a black screen with the words "Office of National Drug Control
Policy" and "Partnership for a Drug-Free America®" shown in white, and,
finally, the ad ends with a shot of the two laughing as we hear one of them
say "It's your choice.  You just have to make the best one."

5) "Welcome to Heroin"  (Fear Appeal) -- This spot begins by showing a
subjective camera shot of a person's foot stepping into snow then breaking
through the ice below.  The shot then fades to several subjective camera
underwater shots, all connected with fades, of hands trying to break
through a sheet of ice confining the person below the surface.  Finally,
the commercial cuts to an objective camera shot from above the surface, and
below the ice is shown a blurry image of the person trying to break
free.  During this objective camera shot, we hear a voice-over stating
"Welcome to heroin.  Enjoy your stay."  The ad then cuts to black, with the
words "Partnership for a Drug-Free America®" in white, centered on the screen.

6) "Dixie Chicks" (Celebrity Ad) -- This PSA begins with the Dixie Chicks,
an all-female alternative rock band, introducing themselves and describing
themselves as being "dorks" in their youth.  The three band members then go
on to discuss being victims of peer pressure at a young age, but that
having a creative outlet such as music allowed them to overcome bad
influences from their cohort.  They say that that time was among the
hardest in their lives, but that it is also the time when one discovers his
or her talents and passions.  Throughout the discussion, the ad quickly
cuts back and forth between shots of the conversation (shot in black and
white) and stylized concert footage.  The commercial ends with one of the
band members stating "I couldn't imagine [living out my dreams] with
something like drugs hanging over my head" in a voice-over.  The image
shown as the spot closes is split-screen, with the band closing a concert
on top and the words "Partnership for a Drug-Free America®" and the logo
and words "Musicians Assistance Program" in white on black at the bottom.

Back to: Top of Message | Previous Page | Main AEJMC Page

Permalink



LIST.MSU.EDU

CataList Email List Search Powered by the LISTSERV Email List Manager