Boosting the Potency of Resistance Combining the Motivational Forces of Inoculation and Psychological Reactance

Human Communication Research ISSN 0360-3989

ORIGINAL ARTICLE

Boosting the Potency of Resistance:
Combining the Motivational Forces of
Inoculation and Psychological Reactance
Claude H. Miller1 , Bobi Ivanov2 , Jeanetta Sims3 , Josh Compton4 , Kylie J.
Harrison1 , Kimberly A. Parker5 , James L. Parker6 , & Joshua M. Averbeck7
1 Department of Communication, University of Oklahoma, Norman, OK 73019, USA
2 School of Journalism & Telecommunications, University of Kentucky, Lexington, KY 40506, USA
3 Department of Marketing, University of Central Oklahoma, Edmond, OK 73034, USA
4 Institute for Writing and Rhetoric, Dartmouth College, Hanover, NH 03755, USA
5 Department of Communication, Bellarmine University, Louisville, KY 40205, USA
6 Department of Student Affairs, Mansfield University, Mansfield, PA 16933, USA
7 Department of Communication, Western Illinois University, Macomb, IL 61455, USA

The efficacy of inoculation theory has been confirmed by decades of empirical research, yet
optimizing its effectiveness remains a vibrant line of investigation. The present research
turns to psychological reactance theory for a means of enhancing the core mechanisms of
inoculation—threat and refutational preemption. Findings from a multisite study indicate

reactance enhances key resistance outcomes, including: threat, anger at attack message
source, negative cognitions, negative affect, anticipated threat to freedom, anticipated
attack message source derogation, perceived threat to freedom, perceived attack message
source derogation, and counterarguing. Most importantly, reactance-enhanced inoculations
result in lesser attitude change—the ultimate measure of resistance.
doi:10.1111/j.1468-2958.2012.01438.x

Over the past 50 years, inoculation theory has emerged as the most consistent and
reliable method for conferring resistance to persuasion. This ‘‘grandparent theory of
resistance to attitude change’’ (Eagly & Chaiken, 1993, p. 561) has proven to be a
robust strategy across diverse social influence contexts, including interpersonal, mass
mediated, commercial, political, and health (see Compton & Pfau, 2005 for a detailed
review). If we consider inoculation to be ‘‘at maturity,’’ as Compton and Pfau (2005,
p. 97) suggest, based on its advancement and longevity within the communication
literature, we may be tempted to conclude the theoretical basis of inoculation is
settled, its contribution to resistance research exhausted, and its potential for further
development minimal. On the contrary, Compton and Pfau (2005) have noted that

The first two authors share equal responsibility for this research.
Corresponding author: Claude H. Miller; e-mail: chmiller@ou.edu

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while some may dismiss inoculation as ‘‘antiquated theory,’’ it continues to grow in its
theoretical development and application, and it is by no means ready for retirement.
One area in need of theoretical improvement concerns the function and operationalization of threat, perhaps the most basic aspect in the resistance process. Insko
(1967) was one of the first to suspect some other hidden mechanisms—beyond
those of threat and refutational preemption originally theorized by McGuire in
1961a, 1961b—may play key roles in conferring resistance. A number of researchers
have focused on uncovering such mechanisms; and although subsequent research
has successfully teased apart various structures and sequences within the process of
resistance, the very search seems to have shifted focus away from the traditional
mechanisms underlining the inoculation process. Moreover, this shift may have been
hasty, given that issues concerning the original core constructs of the theory—threat
and refutational preemption—have yet to be fully resolved. Questioning the premature reification of inoculation theory, Pfau (1997) recommended a return to the

construct’s core assumptions in experimental efforts to refine, extend, reformulate,
and test their logic in the laboratory.
Accordingly, the current investigation is focused on improving the potency of
inoculation treatments by incorporating psychological reactance (Brehm, 1966)—a
forceful mechanism of resistance in its own right—as a potentially powerful device for
boosting the threat component and fine-tuning the role of refutational preemption.
Contrary to the focus of virtually the entire reactance literature on attempts to avoid
or minimize the generally negative effects of reactance, the present research seeks to
exploit reactance within inoculation messages designed to transform and maximize
the nature and level of threat, and thus stimulate, redirect, and optimize the manner
of counterarguing output useful in prompting resistance to attitude change.
Inoculation theory: Tracing threat and refutational preemption

The conceptual origin of inoculation theory sprang from the medical analogy
of immunization against disease. McGuire (1964) believed inoculated cognitive
structures could be protected against counterattitudinal persuasive attacks just as
inoculated immune systems could be protected against biological attacks, and he
identified two mechanisms responsible: threat and refutational preemption.
According to McGuire (1962), threat, ‘‘the most distinguishing feature of inoculation’’ (Pfau, 1997, p. 137), is a requisite construct within the process of inoculation
(Compton & Pfau, 2005). Although the nature and optimal magnitude of threat

necessary to generate the highest levels of resistance has yet to be determined,
the essential importance of threat in resistance has been empirically supported by
research demonstrating how threat alone can lead to increased resistance (Freedman
& Sears, 1965; Kiesler & Kiesler, 1964; Wyer, 1974).
In McGuire’s early theorizing, threat was a primitive term, left as an unmeasured
construct, the presence of which he inferred from the introduction of the refutational
preemption component built into his inoculation messages (McGuire, 1961a, 1961b;
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McGuire & Papageorgis, 1961; Papageorgis & McGuire, 1961). Eventually, McGuire
introduced more explicit forewarnings of impeding attacks to manipulate threat
(McGuire & Papageorgis, 1962); yet, he never directly tested for its presence, nor did
he measure threat in any way.
In the late 1980s, inoculation researchers began to test levels of message-elicited

threat for the first time (Pfau & Burgoon, 1988; Pfau, Kenski, Nitz, & Sorenson,
1990), beginning a trend now commonly practiced in inoculation research (Banas
& Rains, 2010; Compton & Pfau, 2005). The results, however, have been largely
disappointing, with elicited threat levels appearing to be marginal at best (Godbold
& Pfau, 2000; Pfau, van Bockern, & Kang, 1992) and seldom exceeding the midrange
points on the various threat measures used (Compton & Pfau, 2005).
Perhaps not surprisingly, Banas and Rains’ (2010) recent meta-analysis of inoculation, which examined threat as a trichotomized measure, did not provide support
for the hypothesis that perceived threat plays a significant role in inoculation. These
findings, coupled with the generally small range of effect sizes obtained for threat in the
literature (ranging between r = 0.06 and 0.27), have lead researchers to question the
effectiveness of current threat manipulation methods, and to call for additional ways
of manipulating threat to increase its potency and effect, and ideally, the potency and
effectiveness of inoculation treatments (Banas & Rains, 2010; Compton & Pfau, 2005).
Following vested interest theory (Crano, 1995), Pfau et al. (2010) attempted to
enhance threat by altering a traditional forewarning to emphasize greater relevance,
certainty, immediacy, and seriousness (stake) of potential persuasive pressures on
current attitudes. They attempted to show that enhanced threat, when accompanied
by the increased response efficacy provided by refutational preemption, should
increase danger control processes (Witte, 1992). This increase, in turn, should
result in increased resistance, much the same way a successful fear appeal leads to

danger control. However, with one exception (increased attitudinal certainty), their
manipulations did not produce outcomes significantly different from traditional
forewarnings (Pfau et al., 2010).
Nevertheless, beyond instigating fear, threat can also function through the elicitation of anger—whether it is anger in its own right, or as a coping behavior for fear
(e.g., Ivanov, Pfau, & Parker, 2009b; Lee & Pfau, 1997; Pfau et al., 2001). Moreover,
relative to fear, anger may function as a more effective motivation to focus attention
and heighten desire to protect attitudes already in place, especially if those attitudes
are deemed important and/or hedonically relevant (Miller & Averbeck, in press).
Thus, an anger-induced, heightened state of motivation could be expected to generate
more effective and focused counterarguing activity (Ivanov et al., 2009b; Pfau et al.,
2009), which should in turn enhance resistance. However, focusing on anger alone to
enhance threat may also be shortsighted, especially when one considers the practice of
refutational preemption is perhaps foremost a function of the processing of negative
cognitions.
Whereas threat is posited as following from the forewarning of an impending
attack and the potential risk of counterattitudinal content, refutational preemption
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is thought to take advantage of that motivation by stimulating disputations of the
potential attack, and guiding the initial production of counterarguments (Compton
& Pfau, 2005; McGuire, 1964). Refutational preemption is assumed to provide
the defense-motivated individual with a sample of cognitive structures useful in
germinating subsequent counterarguments to rebut future attacking messages.
Beyond providing material useful in constructing such defenses, refutational
preemption is also thought to interact with threat to stimulate, exercise, and reinforce
resistance during what—again drawing from the medical analogy—might be thought
of as an incubation period. During this time, counterarguments, like cognitive
antibodies, may be developed in preparation for a potential counterattitudinal attack
(e.g., McGuire, 1961a, 1961b; McGuire & Papageorgis, 1961).
Given that inoculation seems to confer resistance through threat and refutational
preemption, the question becomes: How can both processes be enhanced to create
more effective inoculation treatments? To formulate an answer to this question, we
turn to the potential utility of Brehm’s (1966) theory of psychological reactance.
Psychological reactance: Drawing on threats to perceived freedoms

Psychological reactance theory (PRT) (Brehm, 1966, 1972; Brehm & Brehm, 1981)
posits individuals become psychologically aroused when others are perceived as
intending to threaten or eliminate their behavioral freedoms. According to PRT, the
aversive arousal—simply termed, reactance—motivates individuals to attempt to
restore the threatened freedom. Moreover, the potential magnitude of reactance is a
direct function of how aware the individual is of that freedom, and how subjectively
important the behavior associated with that freedom is perceived to be (Brehm, 1966;
Chandler, 1990).
In response to messages perceived to be intentionally persuasive, PRT delimits
a number of outcomes associated with methods individuals will use to restore their
threatened freedoms, including ignoring or rejecting the message, adopting the
contra-advocated position (termed a boomerang effect), and perhaps most damaging
of all, derogating and/or directing hostility at the message source. Furthermore, PRT
posits that if an attempt to restore a threatened or eliminated freedom is inhibited or
fails, the individual will tend to become more attracted to that freedom (Austin, 1980;
Chandler, 1990) and/or to others who are able to engage actively in that freedom
(Worchel & Brehm, 1971). In summary, reactance theory provides an explanation for
how individuals are likely to respond when they perceive important or hedonically
relevant freedoms to be threatened or removed by a persuasive message.

Generating reactance within the inoculation treatment

The potential for anger and negative cognitions aimed at the source of reactancegenerating messages is a central focus of the current research. Although PRT has
conventionally been used to model what should be done to prevent resistance (e.g.,
Dillard & Shen, 2005; Grandpre, Alvaro, Burgoon, Miller, & Hall, 2003; Miller,
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Burgoon, Grandpre, & Alvaro, 2006; Miller et al., 2007), the present investigation
concerns what can be done to cultivate resistance by exploiting reactant anger and
negative cognitions generated from the theoretically unique and potent form of
forewarning associated with threatened freedoms.
Framed in terms of appraisal theory (Lazarus, 1991; Roseman, 1996; Scherer,
1982; Smith & Lazarus, 1993), reactance should follow from an individual’s appraisal
of the relationship between self and a motivationally relevant and goal-incongruent

object or event in one’s social environment. In this regard, the degree of motivational
significance—and thus the potential for reactance—a threatened freedom holds
for an individual must be assessed via the appraisal process. This process involves
primary appraisals in reference to the individual’s current goals (in this case, involving
the holding of a particular attitude), and secondary appraisals in reference to the
implications the threatened freedom has for coping with interference with those goals
(i.e., with attacks on the held attitude) (Smith & Lazarus, 1993).
According to Roseman (1996), when a situation (e.g., an attack on one’s attitude),
or an implication of that situation, is inconsistent with one’s goals, the resulting
motivational inconsistency should elicit negative emotion, such as fear, when one
feels compelled to avoid and retreat from the threat; anger, when one is compelled
to approach and remove the obstacle in an aggressive way; and/or resentment, when
one feels displeased at an event presumed to be desirable for another, but undesirable
for the self (Ortony, Clore, & Collins, 1988). Beyond motivational inconsistency, an
appraisal of responsibility or blameworthiness will further reinforce these negative
emotions, especially if the individual feels resentment and holds another person (e.g.,
an attack message source) accountable (Roseman, 1996).
Based on their examination of the extant PRT literature, Dillard and Shen
(2005) characterized reactance as a motivational state prompting hostile feelings
linked or intertwined with anger and negative cognitions. Thus, exciting reactance

as part of an inoculation message should serve to enhance its ability to motivate the
counterarguing processes thought to occur between inoculation and attack. Based
on appraisal theory, anger should stimulate a message receiver to cope by advancing
upon and retaliating against a threatening source in order to protect held attitudes.
Based upon the intertwined model of reactance (2005), anger should interact with
negative cognitions to reinforce the effect and generate a heightened motivational
state of reactance. This heightened state should increase resentment, augment threat
sensitivity, bolster resistance toward the threatening agent (i.e., the attack message
source), energize the counterarguing stimulated by refutational preemption, and
ultimately lead to increased levels of resistance relative to traditional inoculation
treatments. Following this reasoning, we predict the following main effects for
inoculation pretreatment type:
H1: Relative to traditional inoculation treatments, reactance-enhanced treatments (i.e.,
those forewarning of attacks aimed at restricting attitudinal freedoms), generate
greater levels of: (a) message-elicited threat, (b) attack source threat to freedom of
choice, (c) anger at attack message source, and (d) negative cognitions.
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H2: Relative to traditional inoculation treatments, reactance-enhanced treatments result
in greater resistance to persuasion in the form of: (a) greater levels of counterarguing
output and (b) lesser attitude change after exposure to an attack message.
H3: Relative to traditional inoculation treatments, reactance-enhanced treatments result
in greater source derogation in the form of reduced levels of (a) perceived credibility
and (b) greater levels of negative affect directed at the attack message and its source.

Generating reactance within the attack

Inoculation studies have manipulated counterattitudinal attacks on inoculated attitudes in terms of both the number of attacks (Ivanov, Pfau, & Parker, 2009a) and the
cognitive versus. affective nature of the attacks (e.g., Pfau et al., 2001). In this study,
we introduce an additional type of counterattitudinal attack varying in intensity and
relative controllingness of language. The strength or intensity of language used in a
persuasive message is known to influence an individual’s response to an advocated
behavior (Burgoon, Jones, & Stewart, 1975; O’Keefe, 1997). Language intensity,
generally defined as the direction and degree of distance from neutrality conveyed
by a message source (Bowers, 1963), may also be expressed in terms of explicitness, or what Miller et al. (2007) refer to as controlling language. Such language
is characterized by increased use of imperatives (i.e., commands and directives)
as opposed to propositions or indirect suggestions (McLaughlin, Shutz, & White,
1980). Several studies have demonstrated persuasive messages using high-controlling
language lead to greater levels of reactance (e.g., Grandpre et al., 2003; Miller et al.,
2007). As a result, counterattitudinal attacks aimed at inoculated individuals should
be less effective if they use high levels of controlling language; consequently, we
predict:
H4: Relative to low-controlling language, counterattitudinal attack messages using
high-controlling language will be perceived as (a) more threatening to freedom of
choice, and generate greater levels of (b) anger at attack message source, and
(c) negative cognitions.
H5: Relative to low-controlling language, counterattitudinal attack messages using
high-controlling language will generate greater resistance to persuasion in the form of
(a) greater counterarguing output and (b) lesser attitude change.
H6: Relative to low-controlling language, counterattitudinal attack messages using
high-controlling language will generate greater source derogation in the form of
(a) lower levels of perceived credibility and (b) greater levels of negative affect directed
at the attack message and its source.

The effect of language manipulation within the attack message should be
compounded by the magnitude of heightened threat sensitivity generated by the
reactance-enhanced inoculation pretreatment. Thus, we expect an interaction—or,
more precisely, an additive effect—involving the nature of the forewarning in the
inoculation and the controllingness of language within the attack message.
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At one extreme, traditional forewarning inoculation pretreatments (merely threatening the attitude under attack) met by low levels of controlling language in the
attack message should result in the least resistance to attitude change. At the other
extreme, a reactance-enhanced inoculation message (designed to threaten the freedom to even hold the attitude under attack) met by high levels of controlling
language in the attack message should result in the greatest resistance to attitude
change.
The combination of traditional forewarning treatment and high-controlling
attack message, and reactance-enhanced forewarning treatment and low-controlling
attack message, should fall in-between the two extremes. The former should produce
more resistance than the latter. This prediction is based on the likelihood of a recency
effect favoring the proximal effects of controlling language in the attack message
relative to the more distal effects of the threat to freedom presented in the inoculation
message). Thus, we hypothesize the following additive effect:
H7: There is an additive effect involving the nature of the forewarning within the
inoculation pretreatment in combination with the level of controlling language within
the counterattitudinal attack message, such that, (a) the greatest resistance results from
a reactance-enhanced forewarning coupled with a high-controlling attack, and (b) a
lesser level of resistance results from a traditional forewarning coupled with a
high-controlling attack, and (c) a still lesser level of resistance results from an enhanced
forewarning coupled with a low-controlling attack, and (d) the lowest level of
resistance results from a traditional forewarning coupled with a low-controlling attack.

Resistance in the above relationships will be indicated by the same criterion
measures specified in H1–H6: greater threat to freedom of choice, anger at attack
message source, negative cognitions, negative affect, and counterarguing output, as
well as lesser attitude change and lower levels of perceived credibility attributed to
the source of the attack message.

Method
Issue selection

Issues selected for inoculation studies need to meet two criteria; the first requires
attitudes on an issue to be firmly in place at the time of inoculation, and the
second requires a division of opinions both in support of and in opposition to
key positions held regarding that issue (Pfau et al., 2009). The current experiment
employed four issues previously used in inoculation studies (see Pfau et al., 1997,
2005, 2009) addressing whether: (1) the U.S. should completely legalize the sale and
use of marijuana; (2) the government should restrict violent content on TV programs;
(3) the manufacture, sale, and possession of handguns should be banned throughout
the United States; and, (4) gambling should be completely legalized throughout the
United States.
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Participants

Participants (N = 420) within five universities from varied geographical regions
within the United States were recruited with IRB approval via e-mail and recruitment
flyers to participate in exchange for course extra credit. The recruitment materials
included a URL address sending participants to the first phase of a three-phase
experiment, which was the first inoculation study conducted exclusively online.
The five university data collection sites varied in size (1,200–30,000 students) and
region—two in the Southeast (one large and one small), two in the Southwest (one
medium and one large), and one in the North Central U.S. (medium). Participants’
initial attitudes toward the issues did not differ as a result of university size or location
(p = .90), nor were there differences on any of the dependent or manipulation check
variables (p = .17). Attrition rates were unaffected by location, and acceptable across
all three phases - retention rate of 87% from Phase 1 (n = 531) to Phase 2 (n = 461);
and 91% from Phase 2 to Phase 3 (n = 420).
Experimental materials

The investigation featured three types of attitude protection messages: inoculation
with traditional forewarning, inoculation with reactance-enhanced forewarning,
and control (no inoculation). Separate but equivalent inoculation messages were
designed for both supporting and opposing positions on each of the four issues,
and participants were queried as to the nature of their positions on all four issues.
As a result of the initial attitude position on the four issues, 55.6% of participants
were placed in a counteradvocacy condition, and 43.7% in a proadvocacy condition.
The experimental design allowed participants to subsequently be presented with an
inoculation message specifically designed to protect their established position on one
of the issues, regardless of whether their position was in support or opposition to the
issue.
Pfau (1995) considered threat to be an instrumental component in inoculation.
Thus, congruent with recent inoculation studies (e.g., Ivanov et al., 2009b; Pfau et al.,
2005, 2009), threat in both inoculation conditions was explicitly manipulated in the
opening paragraph of the inoculation messages. More specifically, participants were
warned that some of the counterattitudinal arguments they were likely to face on
the issue at hand would be ‘‘very persuasive, and they might cause [them] to rethink
[their] position on this issue.’’ Also within both inoculation conditions, refutational
preemption, the second component of an inoculation treatment, was operationalized by introducing counterattitudinal arguments in the opening sentences of the
paragraphs,1 which were successively countered by refutations.2
Following the refutational preemption component, the inoculation treatments
introduced a second forewarning to message recipients that differed for the two inoculation message types. The traditional treatments introduced a generic forewarning
about the function and intent of persuasive messages in general, while avoiding any
reference to participants’ freedom to choose their own behaviors or beliefs. The
reactance-enhanced treatments forewarned participants of a threat to their ‘‘beliefs
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and preferences regarding’’ the issue, but also specifically of the threat to their ‘‘very
freedom to hold’’ those relevant ‘‘beliefs and preferences’’ posed by those who would
argue the opposite side of the issue, threatening the participants’ freedom to hold
their attitudes, ‘‘or even choose how to think for [themselves]’’ (italicized for emphasis
within the messages).
The noninoculation control message, which pertained to the history and process
of regulation, used a factual and historical tone to provide innocuous information
about the issue. All inoculation and control messages were designed to be equivalent
in length and readability and were measured using Becker, Bavelas, and Braden’s
(1961) Index of Contingency. All messages—including controls—produced index
scores from 0.8 to 1.2, indicating relative equivalence, with the exception of one
traditional inoculation message on the issue of legalizing marijuana, which generated
a somewhat higher score than the rest.3 All messages were comparatively equivalent
in terms of reconstructability of sentences and readability. In addition, the FleschKincaid reading age index (Kincaid, Fishburne, Rogers, & Chissom, 1975), which
assesses the approximate reading age based on number of words per sentence and
syllables per word, indicated inoculation and control messages were roughly at or
below the grade and reading age level of all participants (range 13.9–21.2), thus
suggesting proper comprehension.
Two sets of randomly presented attack messages used in Phase 3, designed in a
similar manner and based on previous inoculation studies (see Pfau et al., 1997, 2005,
2009), provided participants with reasons they should change their positions on the
issues. The argument content of each attack message was different from the argument
content in each of the inoculation messages to ensure the potential effectiveness or
ineffectiveness of the attack messages would not solely be attributable to the specific
content of the inoculation messages themselves.
One set of message attacks, equivalent across all issues and experimental conditions, used low-controlling language closely resembling the wording style used in
previous inoculation studies (see Pfau et al., 1997, 2005, 2009).4 In contrast, another
set of attack messages, although comparatively equivalent in content across all issues
and experimental conditions, used more highly controlling language consisting of
explicit, reactance-producing imperatives, such as ‘‘should,’’ ‘‘ought,’’ and ‘‘must’’
(cf., Miller et al., 2007).5
Procedure

This experiment was conducted in three phases over a 5-week period.
Phase 1. Participants first logged on to a secure data collection site using a
link provided in a recruitment flyer. After consenting to participate, participants
completed a questionnaire designed to collect demographic information and gauge
attitudes toward the four message topics (legalization of marijuana, gun control legislation, legalization of gambling, and restriction of television violence). Participants
who provided only partial completion of Phase 1 were retained only if they provided complete answers on at least one issue (i.e., attitude toward that issue). These
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participants received a follow-up e-mail warning of the possibility of exclusion from
the study if they continued to supply incomplete information in subsequent phases.
Participants who did not provide attitudinal information on any of the issues were
excluded from the study. Upon completion of Phase 1, participants were informed
they would receive an e-mail notification from the research team with a link to the
next phase of the study, approximately 1 week later.
As mentioned, participants were assigned to conditions based on their initial
positions on the four issues. To avoid some of the drawbacks of using median or
mean splits to place individuals in groups, this investigation followed a method used
by Pfau and colleagues (2009) whereby participants were assigned to conditions based
on the valence and scale position of their initial attitudes on an 11-point, multi-item
averaged scale.
Participants whose average attitude position on a randomly assigned issue was
8.6 or higher were placed in the positive (pro-advocacy) condition. Conversely,
participants whose attitude position was 5.5 or lower were placed in the negative
(counter advocacy) condition. Those whose attitudes fell in the intermediate range
between 5.5 and 8.6 on that issue were randomly assigned to one of the other
three issues, and this procedure was repeated if participants’ attitudes fell in the
intermediate range on the second randomly selected issue as well. All participants
scored outside of the intermediate range on at least one of the four issues, thus all
participants were retained. The average time between participants’ completion of
Phase 1 and beginning of Phase 2 was 17 days.
Phase 2. Participants logged onto the secure data collection site using the link
provided in the follow-up e-mail, and were assigned to read either an inoculation
message (consistent with their position pro or con relative to the issue) on one of the
four issues, or a control message presented in text format on the computer screen.
After participants read their message, they completed a questionnaire to assess the
level of treatment message-elicited threat and anger they felt directed at the anticipated
attack message source. These emotions were operationalized as cognitions, affective
responses directed toward the potential attack message and its source, anticipated
credibility of that source, and threat to freedom of choice anticipated to come from
that source (in Phase 3). Finally, at the end of the Phase 2 materials, participants were
informed they would receive an e-mail reminder in approximately 1 week with a link
to the final phase of the study. The average time between participants’ completion of
Phase 2 and the beginning of Phase 3 was 16 days.
Phase 3. After logging onto the secure data collection site using the link provided
in the follow-up e-mail, participants were randomly assigned to a counterattitudinal attack message condition, also presented in a text format on the computer
screen, which featured either high- or low-controlling language designed to counter
their previously assessed position on the relevant issue. After reading the Phase 3
attack messages, participants completed a questionnaire designed to assess affective
responses toward the attack message and source (anger and negative affect), as well
as the perceived threat posed by the attack message to the participant’s freedom to
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hold his or her position; and once again, the credibility of and negative cognitions
toward the attack message and source. Finally, levels of counterarguing and attitudes
toward the relevant issue were assessed, after which participants were debriefed and
thanked for their involvement.
Dependent variables and manipulation check

Treatment-elicited threat. Threat to held attitudes introduced during the inoculation message was assessed in the second phase of the study with a scale used
extensively in previous inoculation research (e.g., Ivanov et al., 2009b; Pfau, 1992;
Pfau et al., 2005). Using the following bipolar adjectives, the scale addressed participants’ feelings concerning the possibility they may come into contact with
persuasive arguments designed to change their position on the relevant issue, asking
whether they find the possibility: nonthreatening/threatening, not harmful/harmful,
not dangerous/dangerous, not risky/risky, calm/anxious, and not scary/scary. This
scale demonstrated excellent internal consistency: 6-item α = 0.95 (M = 3.53;
SD = 1.60).
Anger at attack message source. Agitation-related emotion toward those who
would disagree with the participants’ position on the relevant issue and try to
persuade them to change was assessed in the second and third phases of the study
with a scale used in previous inoculation research (e.g., Ivanov et al., 2009b; Pfau
et al., 2001, 2009). This scale was comprised of three items concerning how much
anger, irritation, and annoyance participants anticipated (Phase 2) or felt following
the attack message (Phase 3). These items were disguised within a larger 14-item scale
(e.g., including cheerful, surprised, sad, fearful) measured on a 7-point (0 = ‘‘none
of’’ to 6 = ‘‘a great deal of’’ this feeling) scale, which demonstrated good internal
consistency: 3-item α = 0.86 (Phase 2; M = 4.07; SD = 1.57) and α = 0.90 (Phase
3; M = 3.79; SD = 1.62).
Threat to freedom. Perceived threat to freedom of attitudinal choice in Phase
2 (anticipated) and Phase 3 (perceived following the attack message) was assessed
with a 4-item scale adapted from Dillard and Shen (2005). This scale assessed how
‘‘those whose position on the issue differ from mine’’ (Phase 2), or ‘‘The message you
just read’’ (Phase 3) ‘‘threaten (threatened) my freedom to choose’’; ‘‘try (tried) to
manipulate me’’; ‘‘try (tried) to make a decision for me’’; and, ‘‘try (tried) to pressure
me.’’ All items were measured on a 5-point agree/disagree continuum. This scale
also demonstrated good internal consistency: 4-item α = 0.88 (Phase 2; M = 3.12;
SD = 1.04) and 0.90 (Phase 3; M = 3.07; SD = 1.17).
Credibility of the attack message source. The credibility of the attack message
source in Phase 2 (anticipated) and Phase 3 (perceived following the attack
message) was assessed with a 6-item semantic differential scale bound by bipolar adjectives: insincere/sincere; dishonest/honest; not dependable/dependable, not
trustworthy/trustworthy; not credible/credible; and unreliable/reliable (adapted from
McCroskey, 1966). This scale demonstrated excellent internal consistency: 6-item
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α = 0.90 (Phase 2; M = 3.54; SD = 0.93) and α = 0.94 (Phase 3; M = 4.21;
SD = 1.14).
Counterarguing. Participants’ counterarguing output following the attack message in Phase 3 was captured using three separate measures—two quantitative and
one qualitative. First, in a quantitative self-assessment, participants were asked for
their response to the counterattitudinal viewpoints presented in the attack message
on a 7-point scale (‘‘I accepted a lot of the arguments offered’’ = 1; ‘‘several of the
arguments offered’’ = 2; ‘‘at least one of the arguments offered’’ = 3; ‘‘I thought of
arguments both for and against the viewpoints in the message’’ = 4; ‘‘of at least one
argument against them’’ = 5; ‘‘of several arguments against them’’ = 6; ‘‘of a lot of
arguments against them’’ = 7) (M = 3.13; SD = 1.38).
Second, in a standard thought listing process used in previous inoculation research
(e.g., Pfau et al., 2009), participants were directed to list the thoughts and feelings that
came to mind as they read the attack message, regardless of attitudinal direction (i.e.,
pro or con). Once their thoughts were listed, participants were directed to go back to
each thought and label it as either pro- or counterattitudinal in nature, after which
they were asked to go back a second time and rate each for its perceived strength on a
7-point scale. Thus, this second aspect of counterargument output was assessed not
merely by the number of arguments but also by multiplying each argument listed
by its self-rating. This produced a weighted index value representing net output as
the difference between the calculated values of the total congruent and incongruent
listed arguments (e.g., Pfau et al., 2009) (M = 6.98; SD = 12.70).
The third measure of counterarguing output was assessed by content analyzing
Phase 3 qualitative data (following Kaid & Wadsworth’s, 1989, method) in the form
of open-ended responses coded for argument relevance and argument position. The
unit of analysis was each single argument provided. Argument relevance—indicated
by whether details in an argument were clearly connected or associated with the
participant’s assigned issue—was coded as either relevant or irrelevant. Argument
position—indicated by the extent to which details of an argument supported
the participant’s current attitudinal position—was coded as either proattitudinal,
neutral, or counterattitudinal. After assessing participants’ attitudinal position of
each argument the numerical difference between their pro- and counterattitudinal
arguments was calculated and served as the third counterattitudinal output measure
(range = −8 to 8; M = 0.83; SD = 2.40).
The same process of content analysis used for coding Phase 3 qualitative data was
also used to code Phase 2 qualitative data. Three coders evaluated all arguments in
both phases, and overall intercoder reliability from independent coding was π = 0.92
(Scott, 1955), with individual coding categories rated as: argument relevance, π =
0.98; argument position π = 0.90; negative cognition, π = 0.90; and negative affect,
π = 0.89. Negative cognition and negative affect were only coded after establishing
acceptable reliabilities (Krippendorff, 2005) concerning argument relevance and
argument position for all arguments. In both phases, only arguments meeting the
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criteria of being both relevant and proattitudinal were further coded for negative
cognitions and affect.
All three counterarguing measures (self-assessment, weighted index, and qualitative coder-assessed) in Phase 2 and Phase 3 of this experiment were used independently
to assess counterarguing output. Because the bivariate correlations between these
three measures were relatively low (below r = 0.50 in both phases), they were analyzed separately within the analyses below rather than being combined into a single
composite counterarguing variable.
Negative cognitions. This variable was defined as the extent to which details in
the argument contradicted or argued against the attack message or its source. It was
coded by assessing each proattitudinal argument for presence or absence of negative
cognitions (e.g., ‘‘the [message] argues that studies have shown violence viewed
on television is responsible for increased levels of violence. In reality, however, the
numbers and trends don’t support this conclusion’’). This variable was measured
separately in Phase 2 (M = 0.18; SD = 0.54) and Phase 3 (M = 0.17; SD = 0.55) as
the number of negative cognitions provided by each participant.
Negative affect. The extent to which details in an argument indicated negative
affect—in the form of anger, irritation, or frustration aimed at either the attack
message or its source—was assessed by coding the language within relevant proattitudinal arguments as either including the presence or the absence of negative affect
(e.g., ‘‘[I felt] annoyed that they were trying to. . .’’). As with negative cognitions,
negative affect was assessed also separately in Phase 2 (M = 0.62; SD = 1.08) and 3
(M = 0.65; SD = 1.08) by adding the number of negative affective accounts provided
by each participant.
Attitude change. Treatment-moderated attitude change on the relevant issues was
captured by computing Phases 1 and Phase 3 differences on an attitude assessment
scale used in previous inoculation research (e.g., Ivanov et al., 2009b; Pfau et al., 2009).
The scale measures participants’ attitudes toward the relevant issue with a series of
seven 11-point semantic differential items anchored by bipolar adjective pairs: negative/positive, bad/good, dislike/like, desirable/undesirable, unfavorable/favorable,
unacceptable/acceptable, and wrong/right. These measures demonstrated excellent
internal consistency across both phases: 7-item α = 0.94 (Phase 1) and α = 0.95
(Phase 3).
To control for initial Phase 1 attitudes (M = 9.38; SD = 1.35), and capture the
inoculation-moderated change, the final Phase 3 postattack attitudes (M = 8.18;
SD = 2.48) were subtracted from the initial Phase 1 preinoculation attitudes.6
The resulting inoculation-moderated attitude change index value (M = −1.20;
SD = 2.42) serves as a primary dependent variable in the analyses. An index value
of zero indicates no attitude change from Phases 1 to Phase 3, whereas positive
index values indicate strengthening, and negative index values weakening, of initial
attitudes.
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Table 1 Manipulation Checks—Traditional Inoculation vs. Control
Control
Condition
Outcome Variables

M

Phase 2
Message threat
3.02
Phase 3
Self-assessed counterarguing
2.28
Weighted index counterarguing
2.15
Attitude change (resistance)
−2.19
∗∗ p

Traditional
Inoculation

SD

M

SD

t

N

η2

1.46

3.40

1.54

1.82∗

246

0.01

1.01
10.82
2.96

2.95
5.94
−1.50

1.38
11.05
2.32

3.67∗∗
2.48∗
1.98∗

239
246
246

0.05
0.02
0.02

< .01. ∗ p < .05, df = (1, 304).

Results
Manipulation checks

First, manipulation checks using independent sample t-tests were performed to
ensure that, relative to no-inoculation (control) messages, traditional inoculation
treatments generated greater levels of message threat, counterarguing, and attitude
resistance. The results of the tests provided evidence of successful operationalization
(see Tables 1 and 2).
Preliminary analyses

A multivariate analysis of variance (MANOVA) test was conducted to examine the
influence of three factors: inoculation treatment (traditional/reactance-enhanced/no
inoculation control), counterattitudinal attack language (low-controlling/highcontrolling), and issue topic (legalizing marijuana/restricting TV violence/restricting
handgun use/ legalizing gambling) on a series of outcome variables (see Table 2).
The omnibus results of the 4 issues × 3 experiential condition × 2 counterattitudinal
attack MANOVA indicated statistically significant main effects for issue, experimental condition, and counterattitudinal attack and a statistically significant interaction
between inoculation treatment condition and counterattitudinal attack language (see
Table 3). No additional statistically significant interaction effects were discovered.
Although the univariate results demonstrated a statistically significant effect for
issue topic on a few outcome variables, these effects were relatively small, did not
appear to form a pattern, and were limited primarily to three Phase 2 dependent
variables (see Table 3). The unpredicted significant main effects on issue were
analyzed using Sheffe’s post hoc comparisons. Participants receiving the handguns
issue reported higher (Phase 2) message-induced threat (M = 3.99, SD = 1.76, n =
95), compared to participants receiving the gambling issue (M = 3.28, SD = 1.43,
n = 90), t(183) = 6.13, p < .01, η2 = 0.17. Participants receiving the TV violence
issue reported higher (Phase 2) anger at attack message source (M = 4.50, SD = 1.45,
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Table 2 Experimental Message Condition Mean Comparisons

Control
Phase 2 Outcome Variables
Message threat
3.02a
A
Anger
3.67a
Negative cognitions
0.04a
Negative affect
0.19a
Anticipated threat to
2.88a
freedom
Anticipated source
4.11a
B
credibility
Phase 3 outcome variables
AngerA
3.05a
Negative cognitions
0.05a
Negative affect
0.34a
Perceived threat to
2.45a
freedom
Perceived source
4.87a
B
credibility
Self-assessed
2.28a
counterarguing
Weighted index
2.16a
counterarguing
Coder-assessed
0.19a
counterarguing
Attitude change
−2.19a
(resistance)

n (SD)

Traditional
Inoculation

n (SD)

Enhanced
Inoculation

74 (1.46)
72 (1.52)
74 (.20)
74 (.39)
70 (1.15)

3.40a
3.97a
0.14a
0.53a
2.79b

172 (1.54)
161 (1.58)
174 (.42)
174 (.92)
167 (1.09)

3.88a
4.35a
0.28a
0.89a
3.88ab

172 (1.65)
160 (1.54)
172 (.71)
172 (1.33)
172 (1.65)

73 (.89)

3.67a

174 (1.01)

3.16a

172 (.67)

74 (1.67)
71 (.23)
74 (.60)
74 (1.21)

3.49a
0.09b
0.47a
2.78a

174 (1.56)
174 (.29)
174 (.79)
174 (1.20)

4.41a
0.30ab
0.96a
3.64a

172 (1.44)
172 (.78)
172 (1.38)
172 (.82)

74 (1.25)

4.27a

174 (1.04)

3.87a

172 (1.06)

74 (1.01)

2.95a

167 (1.38)

3.68a

171 (1.26)

74 (10.82)

5.94a

174 (11.05) 10.10a

74 (2.21)

0.46b

174 (2.07)

74 (2.96)

−1.50a

174 (2.32)

1.48ab
−0.49a

n (SD)

172 (14.17)
172 (2.64)
172 (2.04)

Note: Higher means indicate greater resistance (excepting attack message source credibility).
Means with matching letters indicate significant difference at p < .05.
A
Anger directed at attack message source.
B Source credibility applies to attack message source.

n = 63), compared to participants receiving the gambling issue (M = 3.75, SD =
1.61, n = 90), t(151) = 6.53, p < .01, η2 = 0.22. Also, participants receiving the
marijuana issue reported a higher level of (Phase 3) weighted index counterarguing,
(M = 13.05., SD = 15.54, n = 57), compared to participants receiving the handguns
issue (M = 6.35, SD = 12.49, n = 95), t(180) = 7.23, p < .01, η2 = 0.23. Finally,
participants receiving the TV violence issue reported higher (Phase 3) negative affect
(M = 1.21, SD = 1.45, n = 63), compared to participants receiving the handgun
issue (M = 0.38, SD = 0.77, n = 95), t(156) = 9.51, p < .01, η2 = 0.37. Moreover,
the single statistically significant Phase 3 variable was assessed by two additional
counterarguing measures for which the effect of issue topic was not statistically
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Table 3 MANOVA Results for Condition and Univariate Results for Issue
Independent Variables
Dependent variables
Issue
Phase 2 message threat
Phase 2 anger at attack message source
Phase 2 negative affect
Phase 3 weighted index counterarguing
Experimental condition
Counterattitudinal attack language
Condition × attack language
∗∗

F

df

η2p (η2 )

2.56∗∗
3.98∗∗
5.20∗∗
8.46∗∗
3.63∗
10.78∗∗
8.71∗∗
2.86∗∗

(45, 831)
(3. 304)
(3. 304)
(3. 304)
(3. 304)
(15, 275)
(15, 275)
(15, 275)

0.12
(0.04)
(0.05)
(0.01)
(0.03)
0.37
0.32
0.13

p < .01. ∗ p < .05.

Table 4 Inoculation (traditional vs. enhanced) Main Effect
Outcome Variables
Phase 2
Message threat
Anger at attack message source
Negative cognitions
Negative affect
Anticipated threat to freedom
Anticipated attack message source derogation
Phase 3
Anger at attack message source
Negative cognitions
Negative affect
Perceived threat to freedom
Perceived attack message source derogation
Self-Assessed Counterarguing
Weighted Index Counterarguing
Coder-Assessed Counterarguing
Attitude Change (resistance)
∗∗

F

η2