Research Artick
Attitude-Behavior Relations: A
Meta-Analysisof Attitudinal
Relevance and Topic
by Min-Sun Kim, University of Hawaii at Manoa, and John E. Hunter,
Michigan State University
The difficulty ofjinding a relationship between attitudes and
behavior is one of thegreatest controversies i n recent social
science research. Thepurpose of this study was to determine
whether attitudinal relevance substantially affects the magnitude of the correlation between attitudes a n d behavior,
and whether the effects are content-free. Using meta-analysis, we integratedjindings f r o m 138 attitude-behavior correlations with a total sample size of 90,908. The behaviors we
studied ranged over 19 different categories and a variety of
miscellaneous topics. Our results showed a strong overall attitude-behavior relationship (r = .791 when methodological
artifacts were eliminated. Aspredicted, the higher the attitudinal relevance, the stronger the relationship between attitudes and behavior. This effect held true across diverse content domains. Implications f o r communication theoly a n d
practice are discussed.
The concept of attitude, typically viewed as a stable underlying disposition,' has played a central role in explaining communication phenomena,
particularly the effects of persuasive messages. M o s t research in the area
Although formal definitions of attitude vary, most contemporary theorists seem to agree
that the characteristic attribute of attitude is its dispositional and evaluative nature. For instance, Ajzen (1988) defines an attitude as a disposition to respond favorably o r unfavorably
to an object, person, institution, or event. Rokeach (1967, 1968) also defines an attitude as a
set of interrelated predispositions to action organized around an object or situation.
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Min-Sun Kim is an assistant professor in the Department of Speech at the University of
Hawaii. John E. Hunter is a professor in the Department of Psychology at Michigan State
University. The authors wish to gratefully acknowledge the constructive comments and
suggestions o n earlier drafts of this paper provided by Professor Steven R . Wilson and Professor Gerald R. Miller of Michigan State University.
Copyright 0 1993Journal of Communication 43(1), Winter. 0021-9916/93/$0.0+.05
101
Journal of Communication, Winter 199.3
of communication and persuasion has centered around attempts to
change attitudes toward some object or target, seeking to build theories
that accurately explain and predict patterns of complex communication
behaviors. Underlying these efforts has been the implicit assumption that
behavior toward the object will change automatically with the attitude.
Evidence has not always supported this assumption, however, and the
difficulty of finding a strong, predictive relationship between attitudes
and behavioral tendencies has turned into one of the greatest controversies in the social sciences.
Scholars have widely debated the relationship between attitudes and
overt behavior (for reviews, see Canary & Seibold, 1984; Eagly & Himmelfarb, 1978; Fishbein bi Ajzen, 1972; Liska, 1975; Miller, 1968; Schuman &
Johnson, 1976; Seibold, 1975; Wicker, 1969).2As a result, three basic positions have emerged.
The first, argued mostly by the behaviorist camp, posits that since attitudes are cognitive events, they have no consequences for the way people act o r the way they perform those acts. Therefore, attitudes cannot
predict behavior (see Bandura, 1969; Blumer, 1955; Corey, 1937; Deutscher, 1966, 1973; Doob, 1947; Green, 1954; LaPiere, 1934; Larson & Sanders,
1975; Merton, 1949). Proponents of this position conceive of verbally expressed attitudes as behavior or as surrogates of behavior, hence attitude-behavior (A-B) relations are not particularly relevant or important.
They urge abandoning the general concept of attitude and directly studying overt behavior. For example, Bandura (1969) suggests that we might
better treat self-reports simply as another class of behavior rather than as
indices of an underlying state endowed with special causal powers. Similarly, Green (1954) and Larson and Sanders (1975) also claim that in
studying persuasion, we must be concerned primarily with how people
behave, not with their affective disposition.
A second group of scholars eschews the extreme behaviorist position
and claims that attitude is weakly and inconsistently related to behavior
(Bowers, 1968; Carr & Roberts, 1965; Crespi, 1971; DeFleur & Westie,
1963; Ehrlich, 1969; Hyman, 1949; Liska, 1974b; Tittle & Hill, 1967a;
Weissberg, 1965; Wicker, 1969, 1971). They declare a necessary inconsistency between verbal-scale scores and other overt actions, pointing to situational or individual factors as the crucial determinants of behavior.
Based largely on what Warner and DeFleur (1969) have termed the postulate of contingent consistency, this group argues that the influence of the
“other variables” is so overwhelming that we should expect little o r no direct relationship between verbally expressed attitudes and overt behav-
’ Another question of theoretical interest stems from the direction of the A-B
relationship.
While most A-B studies hold that attitudes cause behavior, some hold that behavior determines attitudes (Bern, 1968) or that the two are mutually reinforcing-that a recursive causal
relation exists (Kelman, 1974). Given that simple correlations say little about attitudinal versus behavioral forces, we d o not imply directional causality to findings of relationships.
102
Attitudc-Behavior Relations: A .Meta-Andy.sis
ior. Recently, researchers have tried to identify and explain more of these
other variables or conditions as determinants of behavior. Some of these
have included: (a1 individual characteristics, such as cognitive complexity (e.g., O’Keefe & Shepherd, 19821, self-monitoring (e.g., Snyder, 1982;
Snyder & Kendzierski, 1982; Snyder & Swann, 19761, private self-consciousness (e.g., Underwood & Moore, 19811, involvement (e.g., Sivacek
& Crano, 1982), and self-awareness (e.g., Pryor, Gibbons, & Wicklund,
1977); (b) attitudinal qualities, such as direct experience with the attitude object (e.g., Borgida & Campbell, 1982; Fazio, Powell, & Herr, 1983;
Fazio & Zanna, 1978a, 1978b, 1981; Regan & Fazio, 1977), attitude accessibility (e.g.,Fazio, 1986; Fazio, Chen, McDonel, & Sherman, 1982; Fazio,
Sanbonmatsu, Powell, & Kardes, 1986; Fazio & Williams, 19861, temporal
stability of attitudes (e.g., Kelly & Mirer, 1974; Schwartz, 1978), and the
consistency between affective and cognitive responses (e.g., Norman,
1975); and (c) situational normative factors, such as social constraints
(e.g., Frideres, 1971; Warner & DeFleur, 19691, norms (e.g., Bowers, 1968;
Fendrich, 19671, reference group norms (e.g., DeFriese & Ford, 19691,
and social support (e.g., Bellin & Kriesberg, 1967; Liska, 1974a, 1974b).
A third group of researchers has suggested that construct-valid attitudes
and corresponding behavioral tendencies are closely related to each
other, whatever the causal direction might be. One of the directional assumptions comes from the consistency theory, which claims that tendencies to reach consistency between behavior and attitude will act in both
directions (see Cohen, 1964; Festinger, 1957; Insko & Schopler, 1967; Kelman, 1974; Rosenberg, 1965). The most commonly evoked directional position, however, has been a causal link from attitudes to behavior (for empirical results, see Andrews & Kandel, 1979; Bentler & Speckart, 1979,
1981; Kahle & Berman, 1979; Kahle, Klingel, & Kulka, 1981). For example, Kahle and Berman (1979) reported a cross-lagged correlational
analysis showing that attitudes have causal priority over behavior. This
basic assumption of close linkage has prompted several prominent models explaining the extent to which people act according to their attitudes.
In the following section, we discuss this third position in more detail.
T h e R e l e v a n c e of R e l e v a n c e
While different theories contain different operational forms and conceptions of attitudes, it is not difficult to trace the common thread running
through these diverse approaches. We propose that different A-B models
can illustrate divergent approaches toward enhancing the conceptual
match between attitudinal and behavioral elements. We examine how
these explanations and theories strongly suggest that the key to predicting behavior via attitudes lies in increasing the conceptual linkage
(match, or relevance) between attitude construct and behavior.
Rokeach (1967, 1968) argued that the disappointing empirical findings
on A-B relations merely suggest the need for a clearer conceptualization
Journal of Communication, Winter 1993
of the attitude concept. To obtain some consistency between attitudes and
behavior, he proposed that attitude toward the situation be considered in
addition to the traditional measure of attitude toward the object. Rokeach
and Kliejunas (1972) showed that the two interacting attitudes reliably
predict behavior to some extent. Clearly, these findings show the need to
focus on both types of attitudinal elements as predictors of behavior.
In their model of reasoned action, Fishbein and Ajzen (1975) posited
two factors that are related to an underlying set of salient beliefs determining behavioral intentions: (a) the attitude toward the act (measured by
rating the specific act on evaluative semantic-differential scales), and (b)
normative beliefs (measured by questions about perceived expectations
of other people multiplied by degree of motivation to comply with these
expectations). Using empirical weights, Ajzen and Fishbein (1970, 1972,
1980) showed that these two factors, combined in a multiple regression
equation, predicted various behavioral intentions, and/or behavior. Expanding on Fishbein and Ajzen’s model, Kreitler and Kreitler (1976) proposed four cognitive orientation (CO) components-goal beliefs, general
beliefs, beliefs about norms and rules, and beliefs about self-as crucial
predictors of behavior. They found that the degree to which attitude
scales represent all C O components is related to the positive relation between attitudes and behavior.
In another attempt to increase the construct validity of attitudes, Rosenberg (1956) formulated the “instrumentality-value” model. Here, attitudes
were defined as some combination of beliefs about an object, either
blocking or facilitating an individual’s attempts to attain valued states.
The relationship between attitudes and behavior is influenced by an individual’s perceived expectancy of goal attainment. Behavior with reference to an attitude object may vary as a function of its perceived instrumentality, that is, the action’s perceived effectiveness in bringing about a
desired goal.
Attitudinal relevance, or the conceptual match between attitudinal and
behavioral elements (Ajzen & Fishbein, 1972; Kreitler & Kreitler, 1976;
Rokeach, 1968; Rosenberg, 19561, is the central focus of major explanations of A-B relationships. Various models of these relationships are different attempts to enhance attitudinal relevance by positing a combination of multiple attitudinal components such as the four CO components
(Kreitler & Kreitler, 19761, attitudes toward situation and object (Rokeach,
19681, attitude toward the act and normative belief (Ajzen & Fishbein,
19721, and instrumentality (Rosenberg, 1956). The theoretical implication
is that attitudinal relevance is the crucial factor in understanding the relationship between attitudes and behavioral intention. The expectation is
that the population correlation will increase noticeably with increasing attitudinal relevance, and construct-valid attitudes will have directive influence over behavior.
The major problem in testing the relationship between attitude and behavior is the selection of attitudinal constructs that are relevant to behav-
104
AttitudeBehavior Relations: A Meta-Analysis
ior; the attitude scales must be conceptually relevant to the behavioral
components being predicted. Since measures of attitude predict behavior
to the extent that they tap pertinent behavioral elements, attempts to
change behavior by changing attitude must consider the degree of attitudinal relevance to the behavior that is to be changed. Clearly, if there is
no conceptual basis for expecting that a given attitude will be relevant in
predicting behavior, the failure to find a relationship between the attitude
and the behavior cannot be taken as evidence that attitudes are unrelated
to behavior. The problem is to decide how pertinent and relevant the attitudinal construct is in predicting behavior. Specifically, the conceptual
validity of the attitudinal predictors must correspond to the behavioral
criterion.
A similar notion of congruence between attitude and behavior has been
somewhat wrongly referred to as “single-act”versus “multiple-act” by
Fishbein and Ajzen (1974). This means that traditional attitude-toward-object measures should not be expected to predict an isolated single act, but
should predict “multiple-act criteria.” While latent constructs with multiple indicators generally afford a higher possibility of understanding the
construct than those with a single indicator, this assumption is misleading
because the important matter is not the number of criteria, but the construct validity of the items. For instance, it is quite possible that multipleact criteria may completely depart from construct validity but still yield
quite a high correlation between attitudes and behavior, purely due to increased reliability of the measure. Thus, we have to ask how relevant and
conceptually valid the attitude construct is in predicting behavior. Given
that attitudinal relevance will be an important moderator in A-B relationships, we advance the following hypothesis:
H1: The higher the attitudinal relevance, the higher the correlation between attitudes and behavior.
A second objective of our research is to test whether the relation between attitudes and behavior is content-free. Are attitudes and behavior
related for some content categories (topics) but not others? By classifying
studies according to topic, we can estimate a true effect size of the A-B
relation within each subset. Specifically, we want to determine whether
content categories interact with the attitudinal relevance to affect the degree of A-B relation.
Until the 1960s few researchers studied the role of content categories as
potential moderators of the A-B relationship. Even then, the studies
mainly focused on race relations (Bastide & Berghe, 1957; Fendrich,
1967a; Linn, 1965) and marijuana use (Albrecht, DeFleur, 2% Warner,
1972). However, over the last 20 years researchers have conducted studies across a wide variety of content categories (e.g., voting behavior,
delinquency, drugs, alcohol, birth control, environmental protection, consumer behavior, games, blood donation, and religion).
105
Journal o_f’Communication,Winter 199.3
One way to investigate the role of behavioral topic would be to categorize studies under different topics that have been commonly investigated.
For instance, past reviewers (e.g., Ajzen & Fishbein, 1977; Schuman &
Johnson, 1976; Schwartz, 1978) identified voting as a unique behavior because it is strongly and consistently related to attitudes. Bentler and
Speckart (1979) also found that the effects of intention depend on the behavior domain chosen. Although the overall A-B correlation might differ
across topics, there is no conceptual basis for assuming that the effect of
attitudinal relevance holds true for some topics but not for others. By increasing conceptual validity of a given attitude in predicting behavior, we
should be able to increase the relationship between the attitude and the
behavior regardless of the topic area investigated. Therefore, we advance
the following hypothesis:
H2: The effect of attitudinal relevance will hold across all topics
In addition to diverse theoretical inquiries into the A-B relationship,
there have been persistent attempts to summarize the empirical findings.
A number of researchers have compiled reviews since Wicker first summarized many of the A-B studies in 1969. In the following section, we
present and discuss some of these review studies, pointing out their
weaknesses in integrating findings. Finally, we introduce meta-analysis as
a powerful and valid alternative to present review studies.
Our literature search yielded 11 review studies that attempted to draw
some conclusions about the A-B relationship (see Table 1). We excluded
theoretical review articles (e.g., Deutscher, 1966; Eagly & Himmelfarb,
1978; Ehrlich, 1969; Kelman, 1974; Liska, 19741).
Vastly different views about the usefulness of attitude constructs in predicting behavior were matched by varied review findings (see last column, Table 1). Initial investigators found low to nonexistent correlations
between attitudes and behaviors, and reviewers were quite pessimistic
about finding a relation. In his review of the A-B literature, Wicker (1969)
claimed, “It is considerably more likely that attitudes will be unrelated o r
only slightly related to overt behaviors than that attitudes will be closely
related to actions” (p. 65). Similarly, in 1964, Festinger expressed surprise
that everyone assumed attitudes caused behavior, yet few researchers had
sought evidence for the relationship. He searched the literature for such
studies and found only three-one, according to him, “of dubious relevance and one of which required reanalysis of data” (p. 405). A third
study was acceptable. He concluded that there was little research evidence of a link between attitudes and behavior.
Other reviewers pointed to different factors and conditions to explain
the low correlation. Tittle and Hill (1967a) listed 15 A-B studies and concluded that low correlations are in part due to the use of single-item measures (presumably low in reliability). Similarly, Fishbein and Ajzen (1 972)
106
AttitudtLBehuviw Relations: A Meta-An&sis
found that the general pattern of results is one of nonsignificance for
studies using the single observation of a single act. On the other hand,
they found that multiple-act criteria significantly relate to attitudes. Kreitler and Kreitler (1976) found 37 cases of positive relation, 68 cases of
“no”o r negative relation, and 15 cases of mixed relation. They concluded
that the number of CO components is evidently crucial for demonstrating
a positive relation. Ajzen and Fishbein (1977) reported that of 46 “not significant” A-B associations, all had low or partial target or action measurement correspondence. In contrast, of 39 “high”A-B associations, 35 had
high target and action measurement correspondence.
Others-such as Ajzen (19851, Ajzen and Fishbein (19731, Ryan and
Ronfield (19751, and Sheppard, Hartwick, and Warshaw (1988)-included
only studies that specifically tested Ajzen and Fishbein’s theory of reasoned action. While their findings concerning the theory were mostly
promising, their conclusions did not provide much insight into the general problem of A-B relationships. Thus, even though numerous reviewers
(some of whom have examined more than 100 studies) have tried to explain the nature of the A-B relationship, many investigators still argue
that the demonstrated relationship is essentially 0.
Artifacts of Method
Our critique points o u t problems regarding the quality of review procedures and explains why the variations in conclusions drawn by most reviews may have been spurious. As we show below, the standard review
practices contain serious methodological artifacts. In general, four broad
issues can be identified: examination of previous reviews, sampling procedure, type o f synthesis method, and the treatment of methodological
artifacts due to sampling error, error of measurement, and dichotomization of variables. Table 1 summarizes and evaluates the prior reviews
under those criteria.
Criterion I : Examination ofprevious reviews. The critical use o f previous review studies is important in judging the strengths and weaknesses
of earlier work. However, only one of the review studies in Table 1 provides any critique of previous reviews.
Criterion 2: Sampling procedure. The results of any integrative review
will be affected by the population of primary studies upon which the
review is focused, and by the manner in which studies are selected from
that population (cf. Jackson, 1980). Only 2 of the 11 review studies reported the sources (such as Social Science Citation Index) or the information retrieval systems used to locate primary studies for possible inclusion. When information o n the sources used for locating studies is not
available, it is impossible to ascertain the degree of bias in the review results. Another issue is whether a review analyzed a full set of existing
studies on a given topic, o r just a subset. Only 4 of the 11 reviews are
comprehensive in their selection of studies by considering the full set of
107
+
0
m
Selective
Comprehensive
Selective
Purposive
Selective
Could not be
determined
Tittle & Hill
( 1967a)
Wicker
( 1969)
Fishbein & Ajzen
( 1 972)
Ajzen & Fishbein
(1 973)
Seibold
(1 975)
Ryan & Bonfield
( 1 975)
Author
by date
No
No
No
No
No
No
Criteria for evaluation
Critique of
Sampling
previous
method
reviews
significance
21
35
Average
correlation
High/moderate/low
Significance
16
6 low, 1 moderate low, 2 moderate,
6 high.
Conclusions drawn
The average correlation between
BI and Ba was -44;
multiple correlation of attitude, social influence
on BI was .60.
Half low, half moderate, one high
Processes intervening between intention and behavior tend to reduce the relation.
A single observation of a single act
results in nonsignificant results,
while multiple-act criteria result in
significant relation.
Coefficient of associa- Correlations are rarely above
tion reported by
.30 and often 0.
investigators
Low/moderate/high
Synthesizing
method
14
47
15
K
Table 1 : Summary of Reviews on Attitude-Behavior Relationship
w
4
0
-
Q
Selective
Comprehensive
Ajzen
(1 985)
Sheppard et al.
(1 988)
Yes
No
and B designate behavioral intention and behavior.
bA-B designates attitude-behavior.
a BI
Note: K = number of studies.
Comprehensive
Ajzen & Fishbein
(1 977)
No
No
Comprehensive
Kreitler & Kreitler
(1 976)
Critique of
previous
reviews
No
Sampling
method
Criteria for evaluation
Schuman &Johnson Selective
(1 976)
Author
by date
Table 1, Continued
6
87
9
142
117
K
The theory of reasoned action can
provide accurate prediction of
intentions and behaviors that
are under one’s volitional control.
Low correspondence produces
mostly nonsignificant relation
while high correspondence results in high relation.
34 positive, 68 no or negative, 15
mixed relations.
Results vary from small to moderate.
Conclusions drawn
Estimation of population 0.53 for BI-B, 0.66 for A-Bb.
Significance
Low if r < .40,
high if r > 40.
Positivelnegativel
mixed
Significance
Synthesizing
method
b
9
F
b
Journal of Communication, Winter 1993
located studies; 6 of the reviews are explicitly s elective.^ Among those reviewers who tried to be comprehensive in sampling, Wicker (1969) included certain classes of studies whose classification as A-B research is
not conceptually justified. Much of the research cited by Wicker (1969)
correlates work-related attitudes with job performance, which is usually
not under one’s volitional control due to differing abilities, skill levels, resources, and so on. (For a discussion of other problems in Wicker’s review, see Dillehay, 1973.)
Criterion 3: Type of synthesis method. The way in which characteristics
of the primary studies are represented can substantially affect the results
and interpretation of the review. It is fairly common for a reviewer to report findings of primary studies in terms of statistical significance. The
significance tests d o not provide information on the magnitude and direction of differences or relationships. Furthermore, the 5% error rate in the
significance test is guaranteed only if the null hypothesis is true for the
population (i.e., if the population A-B correlation is 0). If the null hypothesis is false for the population, then the error rate can be as high as
95% (cf., Hunter, Schmidt, &Jackson, 1982). Even studies that d o not depend on significance tests (e.g., Ajzen & Fishbein, 1977) frequently adopt
an arbitrary threshold (e.g., r = .40) that divides studies into high and low
A-B relationships.
Criterion 4: Sampling error. Most reviews take all variations across
studies at face value and report the range of outcome values. This procedure ignores sampling error. Since most studies are done with small samples (i.e., N < 5001, the sampling error is actually quite large, which leads
to capitalization on chance in observed outcome values.
Criterion 5:Measurement error. Unreliable measurements attenuate the
size of the correlation between attitude and behavior. While several reviews address problems of imperfect measurement (e.g., Fishbein &
Ajzen, 1972; Tittle & Hill, 1967a), they fail to take the problem directly
into account. Variables in the social sciences often are measured poorly.
Thus, we would expect uniformity in the literature only if results were
corrected to eliminate error of measurement (cf., Hunter et al., 1982).
Poor quality in measures of attitude and behavior may have been responsible for many of the low A-B correlations. Therefore, the lack of concern
with establishing the reliability of the independent and dependent measure casts doubts upon the credibility of many of the results drawn by
past A-B reviews.
Criterion 6: Dichotomization. If either attitude or behavior is measured
as a dichotomous variable, the value of the A-B relation (actually a pointbiserial correlation) is artificially reduced. A point-biserial correlation is
maximum for a 50/50 split; the greater the departure from 50/50, the
The information provided by Ryan and Bonfield (1975) was insufficient for making a judgment on this matter.
110
AttitudeBehauior k'elutions; A Metu-Analysis
smaller the correlation. Thus, we need to correct for the departure from
the 50/50 split, which makes the point-biserial correlation smaller than it
could be. If the dichotomy is an extreme split, the reduction can be quite
large. Dichotomization of measurement has been quite frequent, especially in the nieasures of behavior in such areas as blood donation, migration, church attendance, and consumer behavior. None of the past reviewers, however, have taken the problem of dichotomization into
account, even though single-item, yes-no-type measures pose one o f the
most serious threats to valid inference in studies of A-€3 consistency.
As we have shown, all the review studies contain major methodological
difficulties or shortcomings. The conflicting conclusions drawn by them
may be due to spurious variations caused by the presence of any of a
number of different artifacts discussed above. In this study, we attempt to
minimize these problems by using meta-analysis as developed by Hunter
et al. (1982). In contrast to primary analysis, which uses the responses of
individuals as data, meta-analysis uses quantitative studies as the unit of
analysis. Once the studies are collected, the results of the studies are converted into correlations. While the correlation coefficient from an individual study can be subject to any number of different artifacts (e.g., sampling error, measurement error, range restrictions, artificial dichotomization, computational errors, typographical errors, etc.), we can correct
major sources of error at the level of meta-analysis. We expect that when
errors due to sampling, reliability of measures, and dichotomization are
removed, there will be a significant and substantial relationship between
attitudes and behavior unless attitudinal components severely depart
from construct validity.
To investigate whether our expectations had any factual support, we
conducted a series of meta-analyses of past studies. We integrated the
findings of 138 A-B correlations based on a total sample of 90,808 ranging over more than 20 different types of activities.
The single most useful source for selecting studies relevant to our
analysis was a comprehensive bibliography, Attitudes and Behavior: A n
Annotated Bibliography compiled by Canary and Seibold (1984). This annotated bibliography lists 600 articles covering theoretical, methodological, and applied aspects of the A-B relationship. Its bibliographic diversity is evident from the varied sources in which these articles appear,
including Southern Speech CommunicationJournal, Journal of Marriage
and the Family, Journal of Gerontology, Human Communication Research, Public Opinion Quarterly, Journal of Consumer Research, Journal of Marketing, Journal of Personality and Social Psychology, and other
major journals of the American Psychological Association and the American Sociological Association. While this list is evidently comprehensive,
the criteria for inclusion were far broader than what we wished to adopt
for this study; therefore we selected a subset of the articles, primarily
quantitative studies.
111
Journal of Communication, Winter 1993
In addtion, we used several indexes such as Social Science Citation
Index,and looked under the subject title “attitudes/behavior.” This was
especially helpful in finding studies published after 1984. We also obtained references from articles relevant to the topic, and major reviews
dealing with A-B relations in general (e.g, Fishbein & Ajzen, 1974; Kreitler & Kreitler, 1976; Schuman &Johnson, 1976; Wicker, 1969)) and in specific domains (e.g., Ryan & Bonfield, 1975; Sheppard et al., 1988;Tittle &
Hill, 1967a) for locating studies. This list may not represent all existing
studies; however, given the large data set generated by the literature
search, it is very unlikely that a few omitted studies could alter the general conclusions of this study. Once we had gathered our full set of located
studies, we carefully examined each study according to the criteria listed
below.
Meta-Analytic Strategy
First, a study had to focus explicitly on behavioral prediction based on
one’s attitudes. We excluded studies dealing with changes in attitudes or
behavior and studies testing the impact of behavior on attitude prediction
(e.g., Bruvold, 1972, 1973).
Second, each study had to include data that had not been published
previously. Thus, we excluded review articles and reanalyses (e.g., Alwin,
1973; Bagozzi & Burnkrant, 1979). In addition, in cases where studies
were published twice with the same data, we selected only one of each
(e.g., Smetana & Adler, 1979, 1980; Zunich, 1961, 1962).
Third, one or more attitude measures (affective and/or cognitive) and
behavior measures had to be measured in the study. Conceptually, the attitude construct has been developed from a unidimensional view of a person’s positive or negative affect toward an object (Allport, 1935) to a tripartite o r tricomponential view involving affect, cognition, and conation
(see, Bagozzi & Burnkrant, 1979; Kothandapani, 1971; Ostrom, 1969;
Rosenberg & Hovland, 1960; Seibold, 1975). Nevertheless, there are few
A-B studies that operationalize attitudes multidimensionally. As a matter
of fact, the trend is to conceive of attitudes, intentions, and behaviors sequentially (see Bagozzi, 1981; Fishbein & Ajzen, 1975).
Any method of attitude assessment that emphasizes its behavioral aspect introduces operational ambiguities, and thus is likely to blur the
issue theoretically and empirically. For our purposes, we considered an
attitude to be an evaluative feeling that is evoked by a given object,
which involves affect and/or cognition. Consequently, we excluded studies that operationalized attitudes as conation only. When a study used
conation as part of the attitudinal elements, we tried to separate responses of a conative nature (behavioral intention) from the attitude scale,
leaving only affect and cognition elements (Davidson & Morrison, 1983;
McGuinness, Jones, & Cole, 1977; Ostrom, 1969). However, we excluded
a study by Goodmonson and Glaudin (1971), because it mixed the cona-
112
AttitudeBehavior Relations: A Meta-Analysis
tion measure in a single scale with affective and cognitive components,
making it impossible to separate behavioral-intent items from the scale.
Fourth, studies had to involve intentional actions consisting of a choice
between alternatives, or under one’s volitional control. Theorists studying
A-B relations are becoming increasingly interested in the requirement
that the behavior of interest be under volitional control. A behavior is
completely under a person’s control if the person can decide at will to
perform or not perform it (see Ajzen & Madden, 1986; Sheppard et al.,
1988). To help predict behavior over which people have imperfect control, several investigators have proposed assessing “facilitating conditions” (Triandis, 1964); “behavioral control” (Ajzen, 1985); and “resources” (Liska, 1984). Recently, Ajzen and his associates (Ajzen, 1985;
Ajzen & Madden, 1986; Schifter & Ajzen, 1985) have proposed a “theory
of planned behavior,” which extends the theory of reasoned action by including the concept of behavior control. According to the theory of
planned behavior, the theory of reasoned action (which relies o n intention as the sole predictor of behavior) is insufficient whenever control
over the behavioral goal is incomplete. Researchers in cognitive psychology and artificial intelligence also have studied the factors undermining
volitional control over behavior in executing plans. They have proposed
assessing “resource limitation” (Wilensky, 1983), “ethical constraints”
(Bratman, 19871, and “necessary preconditions” such as cost, risk, ability,
ethical legitimacy, skill, etc. (Dyer, 1983).
If we focus on behavior over which individuals have only limited control, we are bound to observe some inconsistency between attitudes and
behavior. Consequently, this study focuses o n those behavioral domains
where most individuals are capable of exercising control over the behavior in question. This is an important criterion that typically has been overlooked in past review studies. Without volitional control, individuals
might not be able to perform given behaviors, despite their intentions o r
positive dispositions, and the relationship between behavioral intention
to overt behavior may be reduced. The amount of volitional control individuals have over their behavior varies along a continuum. Topics dealing
with strong emotional aversion rather than judgments, preferences, o r
evaluation may show low volitional control; therefore, we excluded the
following studies which dealt with strong emotional aversions: “snake
phobia” (Bandura, Blanchard, & Ritter, 1969), and “fear of insects,” involving the subject’s overt handling of a large cockroach (Fazio, 1969). In
addition, we excluded the following topics because of potentially large
differences in individuals’ volitional control: ability to control body
weight (Ajzen, 1988>,job performance or job absenteeism (e.g., Ilgen &
Hollenback, 1977), reading success (Lewis, 1980), and sitting posture
(Mehrabian, 1968).
Fifth, we excluded studies that used scales measuring personality traits
(e.g., dominance, independence, helpfulness) rather than affect and/or
beliefs. Distinguishing between attitudes and personality traits is admit-
113
Journal of Communication, Winter 199.3
tedly difficult. Attitudes are directed at a given object or target (a person,
thing, or event); personality traits represent general behavioral tendencies
without reference to a specific target, context, or time. (See Ajzen, 1988,
for further elaboration of the distinction between traits and attitudes.)
Finally, we excluded studies that did not supply sufficient information
to allow the computation of a correlation between attitude and at least
one of the pertinent dependent variable^.^ For example, Bickman (1972)
reported the absolute number of people picking u p litter but did not correlate people's attitude with behavior. Heise (1977) also provided insufficient data to compute an effect size. We also excluded studies that provided correlations between attitude and behavioral intention and
behavioral intention and behavior without providing the correlation between attitude and behavior.
Studies that met all of the above criteria were selected for meta-analysis. Our final selection included 138 correlations. Studies dealing with
multiple topics were analyzed separately (e.g., dating, studying, and exercising-Bentler & Speckart, 1981). We averaged correlations and reported
the data as a single study if each correlation was based o n responses to
fairly similar objects, such as three brands of fruit drinks (Bonfield, 1974)
and two best-selling toothpastes (Ryan, 1978).
We coded each study by design features that are potential moderator
variables. A moderator variable is a variable that causes differences in the
correlation between two other variables. If analysis shows that there is a
large corrected standard deviation, then it may be possible to explain the
variations across studies by relevant moderators.
We grouped the studies into categories on the basis of behavioral domains. The content categories present behavioral topics commonly investigated in A-€3 research. The primary criterion we used to select these categories was whether or not a topic was clearly distinguishable from other
topics. The following list of domains has been expanded from the topic
areas that Canary and Seibold (1984) used in their comprehensive bibliography:
1. Altruistic behavior: helping behavior, such as volunteering to help
blind children, volunteering to be a subject.
2. Consumer behavior: buying behavior, such as buying toothpaste,
fruit drinks, prescription drugs.
3 . Deviance: antisocial (delinquent) behavior, such as cheating, buying a term paper, gambling o n campus, stealing books from the library.
The attitudinal and normative components of Fishbein and Ajzen's behavioral intention
model have been argued by Miniard and Cohen (1981) to be operationally inseparable.
Ajzen and Fishbein (1970) proposed that attitudes and subjective norms were related to an
underlying set of salient beliefs. Consequently, for those studies testing the theory of reasoned action, we chose multiple correlations of attitude toward the act and normative belief
in predicting behavior.
114
AttztudeBehavzor h’elataons A Meta-Ana!yszs
4. Environment: conservation and pollution behaviors, such as littering, water conservation, energy saving.
5. Health care: service utilization, such as dental care; preventive
health care behavior, such as getting swine flu vaccination.
6. Groupparticipation: behavior such as joining a union, army reenlistment.
7. Race relations: treatment of minorities, behavior related to minority
issues.
8. Religion: religious activities, such as church attendance.
9. Voting: voting practices, such as participation, choice of a candidate.
10. Social activities: visiting exhibitions, watching TV, going to a party.
11. Maternal behavior: breast-feeding.
12. Drug and alcohol use: advocacy and use of drugs and alcohol; consumption, such as smoking marijuana, using minor tranquilizers, drinking
hard liquor or other alcoholic beverages.
13. Game behavior: game performance in laboratory setting.
14. Class attendance: attendance at college course.
15. Familyplanning: birth control, such as contraceptive use, having a
child.
16. Blood donation: donating blood.
17. Classroom behavior: speech communication performance.
18. Migration: moving, applying for public housing.
19. Verdict: mock court decision.
20. Miscellaneous: any other topics that d o not belong to any of the
above categories.
We attempted to code studies into three relevance categories (low,
moderate, and high), according to the degree of relevance of attitudinal
constructs with regard to corresponding behavior measures. Attitudinal
relevance is defined as the degree of match between attitudinal and behavioral elements. In this study we operationalized it in terms of the content validity of attitude items with regard to the behavior. The content validity of attitude constructs has been considered a condition of methodological correspondence between attitudinal and behavioral measures
(Ajzen & Fishbein, 19771, under various names: “generality equivalence”
(Liska, 1974a), “the principle of compatibility” (Ajzen, 1988), and “specificity hypothesis” (Page1 & Davidson, 1984).
The general tenet of this hypothesis states that predictor and criterion
are defined by four elements: action, the target toward which the action is
directed, the context in which the action is directed, and the time at
which the action occurs. Of the four entities, only action and the target toward which the action is directed have been used to study attitudinal relevance; virtually no studies have used time and context among their attitudinalhehavioral elements. Consequently, we used only action and
target to judge attitudinal relevance. Those studies that match both action
115
Journal of Communication, Winter 1993
and target were classified as high match, studies that had only target
match were classified as moderate match, studies that had neither action
nor target match were classified as low match.5 However, we found the
criterion of entity match inapplicable for studies involving multiple behaviors and/or multiple attitudes. Since it was impossible to judge degree
of match using entity match for these studies, we used another approach
to determine it.
First, studies with a general attitude involving only the target but coupled with behaviors (with regard to the target) across different contexts
were coded high match only if the behaviors were representative of the
general attitude. A study by Weigel and Newman (19761, for example,
correlated scores from an attitude scale measuring concern about the
broad category of environmental quality with scores on the comprehensive behavioral index, ranging from petition signing to litter pick-ups.
Second, studies involving comprehensive attitudes (using many different attitudinal criteria) and actions performed in different contexts (e.g.,
Werner, 1978) were coded high match only if the content of the attitude
items corresponded with behaviors predicted.
The basic purpose of meta-analysis is to obtain correct inferences about
population correlations given data on sample correlations. The correlation in each individual study can be subjected to three major sources of
error that we can eliminate at the level of meta-analysis: sampling error,
error of measurement, and artificial dichotomization of measure. (For a
comprehensive discussion of meta-analysis used in this study, see Hunter
and Schmidt, 1990; Hunter et al., 1982.)
To eliminate the effect of sampling error from a meta-analysis, we must
transform the distribution of observed correlations into a distribution of
population Correlations. Since sampling error cancels out in the average
correlation across studies, our best estimate of the mean population correlation is simply the mean of the sample correlations. However, sampling error adds to the variance of correlations across studies. Thus we
must correct the observed variance by subtracting the sampling error variance. The corrected variance is still biased upward because it contains
variance due to differences in reliability and dichotomization of measures. Hence, the correlation must be corrected for errors due to the remaining two artifacts.' Since there was a large corrected standard deviation in our meta-analysis, we tried to explain the variations across studies
by breaking the studies into measured study features (i.e., relevance and
topic). We conducted our meta-analyses using programs developed by
Hunter (1990a, 1990b,1990c).
The two authors compared classifications of match. The number of disagreements was so
small that no formal inter-coder reliabilities were calculated.
It is important to keep in mind that even a fully corrected meta-analysis will not correct for
all artifacts. Even when sampling error, error of measurement, and artificial dichotomization
of a continuous variable are compensated for, there still remains reporting error, bad data,
and so on (see Hunter et al., 1982).
116
Attitudt%Behavior Relations: A Meta-Analysis
Probing the Attitude-Behavior Link
Results are presented as follows: First, the overall correlations of attitude-behavior were identified and corrected for sampling error, measurement error, and dichotomization of variables. Then, in order to test the
overall moderating effect of attitudinal relevance (Hypothesis 11, we conducted a series of subgroup analyses. Finally, we conducted another series of subgroup analyses to test the effect of attitudinal relevance across
topics, or behavioral domains (Hypothesis 2).
Table 2 presents a summary of all the studies used in the present metaanalysis. The list demonstrates the wide variety of studies selected from
the viewpoint of topic or behavioral domain. We found pertinent data
from 138 correlations, based o n a combined sample of 90,808 participants.
We expected to find strong overall support for the general predictive
utility of the attitude construct when errors due to sampling, reliability of
measurement, and dichotomization were removed. A summary of the
overall correlation between attitude and behavior is presented in Table 3 .
The weighted mean of the correlation between the attitudes and behavior
(corrected for sampling error only) was .47. The standard deviation in this
distribution of correlations was .14. The chi-square test indicated that the
variance in this distribution of correlations was significantly greater than
that expected by sampling error alone: chi-square = 3148.61 (df= 137, p
< .OOl).
Sampling error was only one source of artifactual variation across the
studies. We should eliminate other sources of variance such as dichotomization of measures before we look for moderator variables. Of
the 138 studies, 14 studies dichotomized the attitude measures (mean p
value = ,371 and 60 studies dichotomized the behavior items (mean p
value = .34).’ The more the correlation departs from the 50/50 split, the
smaller the correlation is. For instance, in a 32/68 split, the point-biserial
correlation is 7% smaller than it would be for a 50/50 split. Correcting for
the attenuation due to the dichotomization of variables, the mean correlation between attitudes and behavior was .60 (corrected SD = .20). A chisquare test indicated that the variance in this distribution of correlations
was also significantly greater than that expected by sampling error alone:
chi-square = 3755.11 (df = 137, p < . O O l ) .
Measurement error systematically lowers the correlation between variables. If reliability information is available o n each study, then each correlation is separately corrected for attenuation. Of the 138 studies used in
our meta-analysis, only 55 reported reliabilities of attitude items or provided sufficient information to calculate reliabilities. Reliabilities of behavior measures were even more sporadic: 21 out of 138 studies. Since
’ Values of p were available for only 48 of the 60 studies with dichotomized behavior measures.
117
m
F
+
Topic (Category")
marijuana (1 2)
election (9)
voting (9)
marijuana (1 2)
marijuana (1 2)
religiosity (3)
marijuana (12)
college course (1 4)
race (7)
marijuana ( 1 2)
public housing (20)
alcohol (1 2)
marijuana (1 2)
hard drugs (1 2)
dating (10)
studying (1 7)
exercise (1 0)
fruit drinks (2)
environment (4)
speech communication (1 7)
destroy property (3)
shoplifting (3)
disorderly conduct (3)
stealing books (3)
underline books (3)
fake friendliness (3)
getting drunk (3)
illegal drinking (3)
gambling on campus (3)
overcutting class (3)
Author
Acock & DeFleur (1972)
Acock & Scott (1980)
Ajzen et al. 1 (1 982)
Ajzen et al. 2 (1982)
Albrecht et al. (1972)
Albrecht et al. (1977)
Andrews & Kandel(1979)
Babrow & O'Keefe (1 984)
Bastide & Berghe (1957)
Bearden & Woodside (1 978)
Bellin & Kriesberg (1967)
Bentler & Speckart 1 (1979)
Bentler & Speckart 2 (1979)
Bentler & Speckart 3 (1979)
Bentler & Speckart 1 (1981)
Bentler & Speckart 2 (1981)
Bentler & Speckart 3 (1981)
Bonfield (1974)
Borgida &Campbell (1982)
Bostrom (1 970)
Bowers 1 (1 968)
Bowers 2 (1 968)
Bowers 3 (1 968)
Bowers 4(1 968)
Bowers 5 (1 968)
Bowers 6 (1 968)
Bowers 7 (1 968)
Bowers 8 (1 968)
Bowers 9(1 968)
Bowers 10 (1 968)
Table 2: Summary of Studies on Attitude-Behavior Relationships
5,345
5,342
5,341
5,352
5,348
5,332
5,339
5,267
5,321
5,283
50
202
1,394
130
130
204
244
5,258
253
580
251
58
228
228
228
158
158
158
158
12
N
0.61
0.61
0.39
0.37
0.55
0.86
0.25
0.56
0.23
0.68
0.65
0.35
0.24
0.68
0.22
0.37
0.29
0.54
0.33
0.37
0.61
0.54
0.52
0.50
0.53
0.42
0.31
0.76
0.53
0.39
rob
2
1
3
3
3
3
3
3
2
1
2
3
3
3
3
3
3
3
3
3
3
1
3
3
3
3
3
1
2
3
Match
-~
%
Fa
i
L
L
a
Topic (Category")
energy ballot (4)
open housing (7)
lawful acts (3)
reclaimed water (4)
sex preference (20)
civil rights (7)
marijuana (1 2)
amphetamine (1 2)
minor tranquilizer (1 2)
beer (1 2)
cheating (3)
birth control pills (1 5)
having a child (15)
contraceptive use (15)
race (7)
cheat in college (3)
copy other's paper (3)
allow others to copy (3)
parental violence (3)
spousal violence (3)
community water (4)
civil rights (7)
volunteer (1)
game (1 3)
game (1 3)
race (7)
racial relations (7)
voting (9)
religion (8)
voting (9)
class attendance (14)
Author
Bowman & Fishbein (1978)
Brannon et al. (1973)
Brown (1 974)
Bruvold (1 972)
Calway-Fagen et al. (1979)
Carr & Roberts (1 965)
Cooketal. l(l980)
Cook et al. 2 (1980)
Cook et al. 3 (1980)
Cook et al. 4 (1980)
Corey (1937)
Davidson & Jaccard 1 (1979)
Davidson & Jaccard 2 (1 979)
Davidson & Morrison (1983)
DeFriese & Ford (1 969)
DeVries & Ajzen 1 (1 97 1 )
DeVries & Ajzen 2 (1 97 1 )
DeVries & Ajzen 3 (1 97 1 )
Dibble & Straus 1 (1980)
Dibble & Straus 2 (1 980)
Dillehay et al. (1 969)
Ewens & Ehrlich (1972)
Fazio & Zanna (1 978a)
Fazio & Zanna 1 (1 978b)
Fazio & Zanna 2 (1 978b)
Fendrich (1967a)
Fendrich (1967b)
Fishbein et al. (1986)
Fishbein & Ajzen (1 974)
Fishbein & Coombs (1974)
Fredericks & Dossett (1 983)
Table 2, Continued
77
640
26 1
99
56
332
349
349
349
349
67
244
244
35 1
262
146
146
146
1,070
2,048
145
83
141
33
43
189
24
66
62
318
234
N
0.84
0.53
0.48
0.22
0.30
0.28
0.69
0.66
0.51
0.70
0.02
0.57
0.54
0.85
0.39
0.37
0.43
0.46
0.28
0.20
0.68
0.32
0.32
0.52
0.59
0.30
0.68
0.74
0.75
0.73
0.23
b
3
3
3
1
1
1
3
3
2
3
1
3
3
3
1
3
3
3
3
3
2
2
3
2
2
2
2
3
3
2
1
Matchb
b
N
0
N
2,325
204
68
436
25
44
62
110
253
228
236
270
49
270
1,218
39
39
39
474
463
463
463
463
355
94
50
260
34
183
359
Topic (Category")
family planning (15)
marijuana (12)
marijuana (12)
marijuana (12)
erotica (20)
race (7)
unionization (6)
union (6)
game attendance (1 4)
army reenlistment (6)
army reenlistment(6)
birth control pills (15)
religiosity (8)
blood donation (16)
race (7)
dishonesty (3)
violence (3)
drug abuse (12)
outgoingness(1 0)
Carter candidacy (20)
Ford candidacy (20)
religion (8)
drinking (12)
drinking (12)
church attendance (8)
birth control (1 5)
Navy reenlistment (6)
race (7)
college cheating (3)
college cheating (3)
Author
Freedman et at. (1975)
Frideres et al. (1 97 1)
Frideres & Warner (1 980)
Frideres (1 97 1)
Gibbons (1975)
Green (1 972)
Hamner & Smith (1978)
Herman (1973)
Holman (1 956)
Homet al. (1979)
Hom & Hulin (1981)
Jaccard et al. 1 (1977)
Jaccard et al. 2 (1977)
Jaccard et al. 3 (1977)
Jackman (1 976)
Jones 1 (1980)
Jones 2 (1 980)
Jones 3 (1 980)
Kahle et al. (1981)
Kahle & Berman 1 (1979)
Kahle & Berman 2 (1979)
Kahle & Berman 3 (1979)
Kahle & Berman 4 (1979)
Kilty (1978)
King (1975)
Kothandapani (1 97 1)
LaRocco (1 983)
Linn (1 965)
Liska (1 974a)
Liska (1978)
Table 2, Continued
0.62
0.59
0.54
0.59
0.43
0.48
0.42
0.53
0.41
0.65
0.70
0.65
0.65
0.43
0.13
0.41
0.45
0.46
0.62
0.53
0.57
0.57
0.58
0.53
0.84
0.61
0.16
0.39
0.33
0.31
b
3
3
3
1
3
3
3
2
2
1
3
3
3
3
3
1
1
1
2
3
3
3
3
3
3
1
2
2
3
3
Matchb
F
N
F
Topic (Category”)
race (7)
infant feeding (1 1 )
paper recycling (4)
breast feeding (1 1 )
volunteer (1)
religiosity (8)
swine flu (5)
church (8)
verdict (1 9)
verdict (1 9)
blood donation (1 6)
nursing (1 1 )
capital punishment (20)
class attendance (1 4)
taking a loan (2)
voting (9)
altruism (1)
marrow donation (1 6)
energy saving (4)
legal drinking age (20)
comprehensive exam (1 7)
verdict (1 9)
verdict (1 9)
mobility (18)
energy (20)
political participation (9)
political participation (9)
drinking (1 2)
family planning (1 5)
voting (9)
race (7)
Author
Mann (1959)
Manstead et al. (1983)
McGuinness et al. (1977)
Newton & Newton (1 950)
Norman (1 975)
O’Keefe & Shepherd (1982)
Oliver & Berger (1979)
Ostrom (1 969)
Perry (1 976)
Perry & Gillspie (1976)
Pomazal & Jaccard (1 976)
Potter & Klein (1 957)
Prisiin (1 987)
Rokeach & Kliejunas (1972)
Ryan & Bonfield (1 980)
Sample & Warland (1 973)
Schwartz (1978)
Schwartz & Tessler (1 972)
Seligman et al. (1 979)
Sivacek & Crano 1 (1982)
Sivacek & Crano 2 (1982)
Snyder & Kendzierski (1 982)
Snyder & Swann (1976)
Speare (1 974)
Stutzman & Green (1 982)
Tittle & Hill (1 967a)
Tittle & Hill (1967b)
Veevers (1971)
Vinokur-Kaplan (1978)
Warland & Sample (1 973)
Warner & DeFleur (1969)
Table 2, Continued
N
102
215
132
91
189
313
792
145
66
66
270
25
71
81
93
243
192
195
56
93
96
132
120
700
364
30 1
151
75
239
279
73 1
0.28
0.70
0.28
0.29
0.38
0.62
0.26
0.53
0.66
0.66
0.38
0.70
0.68
0.61
0.32
0.29
0.39
0.38
0.74
0.23
0.60
0.53
0.22
0.30
0.34
0.62
0.50
0.72
0.42
0.26
0.10
b
1
2
2
2
3
3
3
3
2
2
3
2
2
2
2
1
2
3
1
2
2
2
2
1
2
3
3
3
2
1
1
Matchb
b
N
N
*
8 = religion
9 = voting
10 = social
1 1 = maternal
12 = drug/alcohol use
13 = game
14 = attendance
N
758
113
32
44
28
61
488
152
26
17
82
82
82
82
103
25 1
15 = family planning
16 = blood donation
17 = studying
18 = migration
19 = verdict
20 = miscellaneous
Topic (Category")
blood donation (1 6)
environment (4)
dental care (5)
environment (4)
quarter system (20)
birth control (15)
abortion (15)
church (8)
puzzle (1 3)
beverage (2)
buying container (4)
high-phosphate detergent (4)
unleaded gas (4)
colored paper (4)
religiosity (8)
blood donation (1 6)
Match (of attitudinal relevance to behavior): 1 = low, 2 = moderate, 3 = high
1 =altruism
2 = consumer
3 = deviance
4 = environment
5 = health
6 = group
7 = race
" Key to topic categories:
Author
Warshaw et al. (1986)
Weigel et al. (1974)
Weigel & Amsterdam (1 976)
Weigel & Newman (1976)
Weinstein (1 972)
Werner & Middlestadt (1 979)
Werner (1 978)
Wicker (1 97 1)
Wilson et al. (1984)
Wilson & Dunn (1986)
Winters l(1971)
Winters 2 (1971)
Winters3 (1971)
Winters 4 (1 97 1 )
Zanna et al. (1980)
Zuckerman & Reis (1978)
Table 2, Continued
b
3
3
0.54
0.36
0.34
0.33
0.33
3
2
3
1
3
3
2
2
Matchb
2
2
3
3
3
3
0.14
0.60
0.55
0.62
0.55
0.55
0.78
0.46
0.54
0.59
0.31
Attitude-Behavior Relations: A Metu-Analysis
Table 3: Overall Effect Sizes of Attitude-Behavior Relationship
Artifacts corrected
Sampling
error only
Number of r ( K >
Total number
of subjects
Mean correlation
Corrected SD
Homogeneity
chi-square
138
90,808
,473
,141
3,148.6 1
Sampling error
& dichotomization
Sampling error,
dichotomization, &
measurement error
138
138
90,808
90,808
,604
,200
3.755.1 1
,79
-
Note: df= 137.
only a small number of studies reported reliability of the measures, it was
impossible to correct each correlation o n an individual basis. On the
other hand, 125 out of 138 studies reported the number of attitude items,
and all 138 studies reported the number of behavior items. The greater
the number of items used, the more reliable the score will tend to be.
Consequently, we used the number of items employed to measure attitudes and behavior to estimate the average reliability of the measures.
The relationship between the number of items in the measure and its
reliability is given by the Spearman-Brown formula. Using this formula,
we can calculate the estimated reliabilities of a unit-length measure based
on the reliabilities provided. This in turn can be used to estimate the average reliability of measures with the average number of items. Using the
mean number of attitude items ( M = 7.16) and the mean number of behavior items (A4= 4.071, we calculated the mean reliabilities for each to
be r,, = .84 f o r attitudes, and r,, = .71 for behavior. Using the classic formula for correction for attenuation, we calculated the mean correlation
between attitude and behavior and found it to be r,, = .79.
The results suggest that a strong relationship between attitude and behavior exists, but that the relationship is substantially attenuated by
methodological artifacts. The overall average A-B correlation was .47.
When the effects of measurement error and dichotomization of variables
were removed, the mean correlation was quite substantial ( r = ,791. Since
the correction for sampling error indicated a substantial variation in population correlations across studies, it is reasonable to look for a potential
moderator variable to explain the variance.
Hypothesis 1 stated that the higher the attitudinal relevance, the higher
the correlation between attitudes and behavior would be. To examine the
potential moderating effect of attitudinal relevance, we conducted separate meta-analyses o n the studies within each of the three attitudinal relevance subcategories (low match, moderate match, and high match).
Hunter et al. (1982) suggested that a moderator variable shows itself in
123
Journal of Communication, Winter 1993
Table 4: Subgroup Analysis: Degree of Attitudinal Relevance as a Moderator
Artifacts corrected
Low match (df = 22)
Number of r ( k )
Total number
of subjects
Mean correlation
Corrected SD
Homogeneity
chi-square
Sampling
error only
Sampling error
& dichotomization
Sampling error,
dichotomization, &
measurement error
23
23
23
6,097
6,097
.31
.15
138.01
107.12
Moderate match (df = 37)
Number of r ( k )
38
Total number
of subjects
11,441
Mean correlation
.49
.14
Corrected SD
Homogeneity
chi-square
402.15
High match ( d f = 76)
Number of r ( k )
Total number
of subjects
Mean correlation
Corrected SD
Homogeneity
chi-square
6,097
.26
.13
77
38
38
11,441
11,441
.50
.15
.64
.19
453.44
77
73,270
.40
.19
77
73,270
73,270
.49
.13
.67
.18
2,133.60
2,166.12
.86
.23
two ways: (a) the average correlation will vary from subset to subset, and
(b) the corrected variance will be lower in the subsets than for the data as
a whole. As shown in Table 4, the results of these subgroup analyses
were consistent with the hypothesis, showing that the effect size in each
of the three conditions increased as attitudinal relevance increased.
When corrected for dichotomization, the average effect size (measured
as r ) was .31 ( k = 23; n = 6,097) in the low-match condition, .50 ( k = 38;
n = 11,441) in the moderate-match condition, and .67 ( k = 77; n =
73,270) in the high-match condition. Using the estimated average reliabilities for both attitude and behavior measures (raa= .84; r,, = .71), the
correlations were corrected for measurement error also, with these results: requaled .40 for low match, .64 for moderate, and .86 for high).
The magnitude of the increase in correlations was quite impressive, lending support to the important role of attitudinal relevance in the prediction
of behavior. In addition, the true variance in each of the three subgroup
estimates was less than the true variance in the overall estimate ( S D =
.20); corrected standard deviation was .15 for low match, .15 for moder-
124
Attitude-Behavior Relations: A Meta-Analysis
Table 5: Unit-length Reliabilities Across Topic
Unit-length reliability of measures
Topic"
Altruism
Deviance
Environment
Health
Group
Race
Religion
Voting
Social activity
Drug/alcohol
Attendance
Family planning
Blood donation
Studying
Miscellaneous
Overall
K
Attitude
Behavior
3
22
12
2
4
12
8
8
3
19
4
9
4
3
8
.11
.17
.35
.64
.52
.24
.28
.63
.32
.49
.47
.71
.42
.50
.47
.44
.24
.70
.43
.2 1
.46
.32
.5 1
121
.42
.44
.65
Note: K = number of studies.
Studies relating to consumer, maternal, game, migration, and verdict behaviors
were excluded because they did not report reliabilities for any attitude or behavior measures.
ate, and .18 for high). However, the obtained variance was larger than
that expected by chance. The chi-square tests indicated that the variance
in the distribution of correlation was significantly greater than expected
due to sampling error alone (see Table 4). Since there was a large amount
of variance across studies, it is still possible to test the second potential
moderator to explain that variance.
We hypothesized that the effect of attitudinal relevance would apply
across all content domains, so we conducted separate meta-analyses on
studies within different topic categories. Using the number o f items to estimate the average reliability permitted an accurate correction of correlations overall and for the match subgroup analysis. However, we decided
that the same procedure might not yield accurate correction for attenuation, since there was a substantial variation among reliabilities of single
item by topic (see Table 5 ) .
The variability of reliabilities in both attitude and behavior measure
across topics was quite substantial. For attitude reliability, the mean was
.42 ( S D = .17); for behavior reliability, the mean was .44 ( S D = .16). In
addition, 9 out of the 20 topics had three or fewer studies within a category. Using the number of items to estimate reliabilities works best when
there is a sufficient number of studies within each category. While at least
one study in most topics provided reliability for the attitude measure, in 5
of the 20 topic areas, not a single study provided reliability for the behav-
125
Journal of Communication, Winter 1993
Table 6: Subgroup Analysis: Topic by Match
Match level a
Topic
High
Moderate
Low
Altruism
Consumer
Deviance
Environment
Health
Group
Race
Religion
Voting
Social
Maternal
Drug/alcohol use
Game
Attendance
Family planning
Blood donation
Studying
Migration
Verdict
Miscellaneous
.35 (2)
.69 (1 8)
.57 (7)
.33 (1)
.85 (2)
.71 (2)
.60 (7)
.47 (5)
.46 (3)
.31 (2)
.40 (3)
.55 (1)
.25 (2)
.24 (7)
5 7 (1)
.34 (2)
-
.65 (16)
.73 (2)
.88 (6)
.46 (3)
.68 (1)
.64 (2)
.39 (1)
.41 (3)
.43 (2)
.49 (2)
.67 (1)
.46 (3)
.92 (1)
.65 (3)
.50 (3)
.56 (3)
.61 (1)
.72 (3)
.14(1)
.37 (2)
5 3 (4)
.53 (5)
Overall
.67 (77)
5 0 (38)
Total
correlation
Total
K
.23 (1)
.48 (1)
.47 (3)
.37
.41
.69
51
.34
.68
.31
.60
.49
.46
.65
.56
.56
.56
.83
.28
.46
.48
53
53
3
3
22
12
2
5
12
8
8
3
3
19
3
4
9
4
3
1
4
10
.31 (23)
.66
138
-
-
Note: Correlations are corrected for sampling error and artificial dichotomization.
Numbers in parentheses indicate k, number of studies on which correlation is
based.
ior measure. Consequently, there was a good possibility that a reliability
provided by a particular study within a topic was significantly lower or
higher than the actual value. This led to a substantial bias in the reliability
calculated with the Spearman-Brown formula using the number of items.
Consequently, it was not possible to correct for measurement error across
topics.
While no correction for measurement error could be made and hence
the correlations were lower than the true values, the effect of attitudinal
relevance certainly appeared to operate across topics (Table 6). Only 3 of
the 20 topics (altruism, health, and voting) did not conform to this pattern. However, this divergence occurred for those topics that had singlestudy cells in at least one of the match categories. Thus the deviation may
have been due to sampling error.
To summarize, the results from these subgroup analyses were mostly
consistent with the prediction that the higher the attitudinal relevance,
the stronger the relationship between attitudes and behavior. In addition,
the principle of match or relevance held true across a wide variety of
topics.
126
Attitude-Behavior Relations. A Meta-Analysis
We found that the relationship between attitudes and behavior was
strongly influenced by attitudinal relevance, that is, the degree of conceptual match between the attitude and the behavior being predicted. For a
high match, the mean correlation was .86. For a medium match, it
dropped to .64; and for a low match, it dropped to .40.
Could it be that these three correlations between attitudes and behavior
arose from chance? In all three match levels, the sample sizes for the average correlation were such that there was virtually no sampling error in the
mean correlation ( N = 73,270 for high match, N = 11,441 for medium
match, N = 6,097 for low match).
Could it be that the relationship was “inconsistent” in the sense that
only some correlations were positive while many were zero? The standard
deviations in Table 4 are overestimates because of failure to correct for
variations in reliability and for unmeasured artifacts. However, with this
overestimation in mind, confidence intervals were constructed using
these standard deviation estimates. The true intervals were narrower. The
95% confidence interval for the high match was .41 to 1.00, which excluded 0. The 95% confidence interval for the medium match was .27 to 1.00,
which excluded 0. The 95% confidence interval for low match was .03 to
.77.
Although the confidence interval did not get down to 0, a fully normal
distribution would. However, the probability of a deviation that extreme
is about 1 in 50. Since the standard deviation is known to be an overestimate, the true probability is considerably lower than that. Thus for a high
or medium level of relevance, the correlation between attitude and behavior will almost always be above 0. For a low match, there is a less than
1 in 50 chance that there will be a setting with a correlation of 0. This is a
critical observation because the meta-analysis controls for the effect of
sampling error, and allows us to discover the underlying uniformity in the
relationship between attitudes and behavior in terms of the moderator effect of attitudinal relevance.
The behaviors we studied ranged over 19 specified categories and a variety of miscellaneous topics. There were too few studies to fully fill the
60 cells for topic by match (20 topics X 3 relevance match levels), so we
were unable to compute a quantitative assessment of the extent of variation across topics. Examination of Table 6 shows that for every cell present, the mean correlation (attenuated) was positive. The lowest means
were .33 for the high match, .14 for the medium match, and .23 for the
low match. However, these low means all occurred for single-study cells
where sampling error was maximum. Searching for the lowest number
among a set of numbers with high sampling error caused a considerable
capitalization on chance. Thus, it was likely that each of the low cells was
low because of negative sampling error. If only cells with two or more
studies are considered, the lowest cell means are .35 for high match, .37
for the medium match, and .31 for the low match. These means are not
corrected for error of measurement: so the true minimum means are still
127
Journal of Communication, Winter 1993
higher. The data suggested that there is no topic for which the correlation
between attitude and behavior would be 0. The high-match cells with
three or more studies all had means that would correct to about the observed average across all high-match studies-that is, all were in a region
near .86.
W h y Others Erred
Using meta-analysis, we found uniformly positive correlations between
attitude and behavior with a very high correlation if the attitude was highly relevant to the behavior. How could so many narrative reviews and
other studies come to the conclusion that attitudes only sporadically predict behavior? The answer lies in the known methodological problems of
small-sample research in areas without established measurement scales.
The meta-analysis showed that past reviews were strongly influenced by
the randomness of sampling error, by attenuation due to measurement
error, and by attenuation due to artificial dichotomization.
Many researchers have based their conclusions on results from some
one study that they either personally favor or with which they were closely connected. But isolated studies are subject to massive sampling error
and hence massive error in the statistical significance test. Consider the
low-match studies. The mean uncorrected correlation (the basis for significance tests) was .26. Fifty percent of the studies were done with a sample
size of 102 or less (some much less). For a sample size of 102, a sample
correlation must be at least .20 to be significant at the .05 level. Since the
standard error of a correlation computed from 102 cases is '10, 27% of
such studies would find the correlation not significant. In our analysis,
correlations in the low-match condition were not homogeneous; the standard deviation of population correlations was .13. Thus, the standard deviation of sample correlations was .16, and the percentage of studies with
nonsignificant results was 36. Further, many studies had fewer than 102
subjects. Thus the error rate for the significance test in early low-match
studies was probably about 50%. The sampling error guaranteed that
about 50% of the researchers who worked in the area would falsely conclude on the basis of personal experience that attitudes d o not predict behavior.
Taking into account the sample sizes of typical social science studies,
the interpretation of isolated study results using the significance test is
subject to massive error. What about reviews that consider the results of
multiple studies? Nearly all reviews done before meta-analysis were narrative reviews in which the reviewer considered each study, one at a
time. Thus, reviewers who used the significance test (as most did) carried
over the high error rate for individual studies into their conclusions about
the set of studies. The full set of low-match studies would show that
about 50% of them found a significant correlation. Some reviewers in the
A-B area (especially behaviorists) interpreted this kind of finding to mean
128
AttitudeBehavior Relations: A Metu-Analysis
that attitudes are unrelated to behavior. That is, they assumed that if half
the studies found an effect while the other half did not, the effect was a
chance event and there was really no relationship. This reasoning is erroneous because it falsely assumes that the chance base rate is 50%. But the
significance test is designed so that the chance base rate is 5% rather than
50%. Thus, if 50% of studies find significance, that is 10 times higher than
the chance base rate.
Other reviewers made a similar error. They assumed that “significant”
equals “related“and “not significant” equals “not related.” Hence, they interpreted the 50% significance rate to mean that attitudes are related to
behavior in only 50% of all settings; causing what was termed “inconsistency in the A-B correlation.” This conclusion is also false. Even using the
overestimated standard deviation of .19 and assuming a normal distribution of true correlations, the number of settings with no correlation would
be fewer than 1 in 50.
Finally, our results suggest that a strong relationship exists between attitudes and behavior, but that the relationship is substantially attenuated
by methodological artifacts. The weighted mean of correlation between
attitudes and behavior (corrected for sampling error only) was .47. When
corrected for the artificial dichotomization of variables, the correlation
became .60. When the effects of both dichotomization and error o f measurement were removed, the correlation increased to .79. This result
showed a systematic downward bias in the average correlation due to
methodological artifacts. The implication is that improving measures of
attitudes and behavior will undoubtedly reduce, if not eliminate, the
problems affecting past research.
The extent to which attitudes are predictive of social behavior has been
viewed from at least three general viewpoints.
The first position begins with the premise that no necessary connection
exists at all and, thus, it may be desirable to abandon the attitude concept
and other verbal predictors and directly study the overt behavior of interest and the variables that affect that behavior. Despite the vast amount of
research that supports this pessimistic position, it is clearly negated by
the results of our meta-analyses. We found that the A-R relationship, far
from being “essentially zero,” is neither as inconsistent nor as inconclusive as it first appears. The average population correlation between attitudes and behavior was quite substantial ( r = .79, corrected for measurement error and dichotomization). As we have discussed, the correlation
between attitude and behavior will almost always be above 0 for a high o r
medium match. Even for low-match studies, there is a less than 1 in 50
chance that there would be a setting with a correlation of 0.
The second position, the “other variables” approach, posits that attitude
is weakly and inconsistently related to behavior due to situational or individual factors. ’This position assumes that the strength of A-B relations is
contingent on a variety of factors. For this argument to be true, only some
correlations would be positive; many would be 0. In our analysis, calcula-
129
Journal of Communication, Winter 199.3
tions of 95% confidence interval showed that correlations in both high
and medium match were uniformly positive. Further, in the high-match
condition, the relationship between attitudes and behavior was strong
enough ( r = ,841 to “override” the situational factors employed. While investigation into situational and contextual determinants of behavior is an
important area of research, the lack of an overarching theoretical framework on contingent consistency hinders our understanding of the A-B relationship.
Although a large number of personal and situational variables have
been suggested, accumulation of empirical data on those variables has
not produced an integrated understanding of A-B relationships. Our
meta-analysis suggests that the theoretical utility of relevant attitudes
seems to outweigh the effect of intervening variables, and thus the relevant attitudes should be the fundamental condition for the A-B relationship, rather than only one of the myriad of variables that are considered
when trying to predict overt behavior.
The third position, which claims that attitudinal prediction of behavior
depends on the conceptual relevance of the attitude construct, is most
consistent with our findings. We found that the population correlation noticeably increased with increasing attitudinal relevance. This evidence
supports our claim that the focus of A-B research should be the selection
of attitudinal constructs that are relevant with regard to behavior. According to our findings, attitudinal relevance is the crucial factor in understanding the relationship between attitudes and action tendencies. We observed evidence for the importance of attitudinal relevance across more
than 20 different types of activities, ranging from very simple strategy
choices in laboratory games to actions of considerable personal o r social
significance (e.g., having an abortion, smoking marijuana, reenlisting).
The Importance of Construct-ValidAttitude
To summarize, the results of our meta-analyses challenge both the postulate of contingent consistency and the postulate of no relationship between attitudes and behavior. Neither position adequately describes the
ways in which attitudes and actions are linked. Our series of meta-analyses offer clear-cut evidence that implies that construct-valid attitudes have
directive influence over behavior. Hence, we can unravel the mystery surrounding prediction and explanation of specific action tendencies by
turning our attention to construct-valid attitudes that correspond precisely
to the particular action tendency of interest.
An additional implication of the meta-analyses concerns the individual’s behavioral control. The strong overall A-B relationship ( r = .79) we
observed was due in part to the exclusion of studies involving behaviors
with relatively low volitional control. The predictive validity of attitudes
partly depends on the degree of volitional control over the behavior in
question-meaning that people can easily perform these behaviors if they
130
AttitudeBehauior Relatioras: A Meta-Analysis
are so inclined, or refrain from performing them if they decide against it.
Recently, many investigators have turned their attention to the question
of volitional control (e.g., Ajzen, 1988; Ajzen 6i Madden, 1986; Liska,
1784). The high A-B correlation lends indirect support to this issue. The
main implication is that actions that are determined mostly b y factors beyond an individual’s voluntary control fall outside the boundaries established for the A-B problem.
Most communication and persuasion research has centered around attempts to change attitudes toward some target. In contrast to those who
propose that we study affective relations independently of behavior
(Chaffee & Lindner, 1969), we must investigate the relationships between
underlying attitudes and behavioral indicators to understand and predict
the effects of human communication. Researchers have presumed that
changes in attitudes lead to changes in overt behavior. While the centrality of the attitude concept remains, researchers are disenchanted with the
usefulness of attitude constructs in predicting behavior (see Miller, 1980).
The present meta-analyses clearly imply that knowledge of relevant attitudes has important predictive utility. For communication researchers
dealing with political and social policy campaigns-who may be interested in knowing whether their efforts to change attitudes will help them
achieve their ultimate goal of changing behavior-the answer, under several constraints, appears to be yes. Specifically, three conditions are necessary to expect that attitudes will be translated into actions.
First, we must be sure that attitude scales are conceptually relevant to
the behavioral components being predicted. Since measures of attitudes
can help predict behavior to the extent that they tap the pertinent behavioral elements, attempts to influence behavior by means of attitude
change must also consider the degree of attitudinal relevance to the behavior that is t o be changed.
Second, we rnust exercise caution to ensure that the behavior in question is toward the volitional side of the continuum. That is, we must consider (from the subject’s perspective) the circumstantial factors surrounding the predicted behavior, especially since individuals may not be free o r
able to enact the predicted behavior. For instance, the relation of attitudes
to overt behavior may be reduced if the behavior is not entirely under the
person’s volitional control. Thus, individuals may not be able to perform
given behaviors, despite their intentions to d o so.
Third, we should use proper measures of attitude and behavior. Past
studies have rarely reported reliabilities of measures, and most still use
single-item dichotomized behavior measures (e.g., to donate blood o r
not). It is essential in A-B research to establish and report the reliability
of measures. If a behavior o r attitude is measured in a dichotomous manner, a suitable correction should be made.
Attitude-behavior relationships have been an interdisciplinary concern.
The underlying assumptions and corresponding empirical findings are
crucial not only to the theoretical development of human communication
131
Journal of Communication, Winter 1993
studies but also to other fields of applied social science, including consumer behavior, social policy, public campaigns, and others. Insko and
Schopler (1967) have suggested the possibility that much evidence showing a close relationship between attitudes and behavioral responses has
been obtained but never published because investigators and journal editors have considered such findings “unexciting” and “not worthy of publication.” Our meta-analyses should correct the impression that A-B inconsistency is the more common phenomenon. Providing a critical
analysis of the A-B literature makes an important contribution, not only
by affirming the utility of attitude constructs in predicting behavior, but
in avoiding immense wasted effort in replicating where data already exist
to solve the issue. Furthermore, studies that d o not have the characteristics necessary for demonstrating a substantial positive relation between
attitudes and behavior should not be taken as evidence that no such relation exists.
Ever since Gordon Allport (1935) described the attitude concept as the
primary building block in the edifice of social psychology, many researchers have attempted to clarify the A-B relationship. We have tried to
thoroughly explore the research literature on A-B relationships to integrate discrepant findings about the strength of such relationships. The results of our meta-analysis lead us to conclude that it is no longer very
meaningful to ask “Are attitudes necessary?” Nor does the crucial issue
have to d o with searching for more “other variables.” Instead, evidence
from the accumulated literature affirms the following position: Relevant
attitudes strongly predict volitional behavior.
References
Acock, A. C., & DeFleur, M. L. (1972). A configurational approach to contingent consistency in the attitude-behavior relationship. American Sociological Review, 3 7, 714-726.
Acock, A. C., & Scott, W. (1980). A model for predicting behavior: The effect of attitude
and social class o n high and low visibility political participation. Social Psychology
Quarterly, 43(1), 59-72.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In K. Kuhl & J
Beckman (Eds.), Action-control: From cognition to behavior (pp. 11-39). Heidelberg,
Germany: Springer Publishing Company.
Ajzen, I. (1988). Attitudes, personality, and behavior. Milton Keynes: Open University
Press,
Ajzen, I., & Fishbein, M. (1970). The prediction of behavior from attitudinal and normative
variables. Journal of Experimental Social Psychology, 6, 466-487.
Ajzen, I . , & Fishbein, M. (1972). Attitudes and normative beliefs as factors influencing behavioral intentions. Journal of Personality and Social Psychology, 21(1), 1-9.
Ajzen, I . , & Fishbein, M . (1973). Attitudinal and normative variables as predictors of specific behaviors. Journal of Personality and Socialpsychology, 27, 41-57.
132
Attitude-Behavior Relations: A Meta-Analysis
Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84, 888-918.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes andpredicting social behavior.
Englewood Cliffs, NJ: Prentice-Hall, Inc.
Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitude, intentions,
and perceived behavioral control. Journal of Experimental Social Psychology, 22,
453-474.
Ajzen, I., Timko, C . , & White, J. (1982). Self-monitoring and the attitude-behavior relation.
Journal of Personality and Social Psychology, 4x31,426-435.
Albrecht, S. L., Chadwick, B. A., & Alcorn, D. S. (1977). Religiosity and deviance: Application of an attitude-behavior contingent consistency model. Journalf o r the Scientzfic
Study ofReligion, 16(3), 263-274.
Albrecht, S., DeFleur, L., & Warner, L. (1972).Attitude-behavior relationships: A reexamination of the postulate of contingent consistency. Paczjic Sociological Review (April),
145-168.
Allport, G. (1935). Attitudes. In C . Murchinson (Ed.), A Handbook of Social Psychology (pp.
798-844). Worcester, MA: Clark University Press.
Alwin, D. F. (1973).Making inferences from attitude-behavior correlations. Sociomety, 36,
253-278.
Andrews, K. H., & Kandel, D. B. (1979).Attitude and behavior: A specification of the contingent consistency hypothesis. American Sociological Review, 44, 298-310.
Babrow, A,, & O'Keefe, D. (1984). Construct differentiation as a moderator of attitude-behavior consistency: A failure to confirm. Central States SpeechJournal, 35, 160-165.
Bagozzi, R. P. (1981).Attitudes, intentions, and behavior: A test of some key hypotheses
Journal of Personality and Social Psychology, 41(4), 607-627.
Hagozzi, R. P., & Burnkrant, R. E. (1979). Attitude organization and attitude behavior relationship. Journal OfPersonality and Social Psychology, 3 7, 913-929.
Bandura, A. (1969).Principles of behavioral modzfication. New York: Holt, Rinehart, &
Winston.
Bandura, A., Blanchard, E. R., Ritter, B. (1969). Relative efficiency of desensitization and
modeling approaches for inducing behavioral, affective, and attitudinal changes. Journal
of Personality and Social Psychology, 13, 173-199.
Bastide, R., & Berghe, P. (1957). Stereotypes, norms and interracial behavior in Sao Paulo,
Brazil. American Sociological Review, 22, 689-694.
Bearden, W. O., & Woodside, A. G. (1978). Situational and extended attitude models as
predictors of marijuana intentions and reported behavior. Journal of Social Psychology,
106, 57-67.
Bellin, S. S., & Kriesberg, L. (1967). Relationship among attitudes, circumstances, and behavior: The case of applying for public housing. Sociology and Social Research, 51,
453-469.
Bem, D. J. (1968). Attitudes as self-descriptions: Another look at the attitude-behavior link.
133
Journal of Comm u n ication, Winter 199.3
In A. G . Greenwald, T. C. Brook, & T. M . Ostrom (Eds.), Psychological foundations of attitudes (pp. 197-215). New York: Academic Press.
Bentler, P. M., & Speckart, G. (1979). Models of attitude-behavior relations. Psychological
Review, KG( 5), 452-464.
Bentler, P. M., & Speckart, G. (1981). Attitudes “cause” behaviors: A structural equation
analysis. Journal of Personality and Social Psychology. 40(2), 226-238.
Bickman, I.. (1972). Environmental attitudes and actions. Journal of Social Psycholog.y, 87,
32 3-3 24.
Blumer, H. (1955). Attitudes and the social act. Social Problems, 3, 59-64.
Bonfield, E. H. (1974). Attitude, social influence, personal norm, and intention interactions
as related to brand purchase behavior. Journal qfMarketing Research, XI, 379-389.
Borgida, E., 8r Campbell, B. (1982). Belief relevance and attitude-behavior consistency:
The moderating role of personal experience. Journal ofpersonality and SocialPs.ychology,4x21, 239-247.
Bostrorn, R. N.(1970). Affective, cognitive, and behavioral dimensions o f communicative
attitudes. Journal of Communication, 20, 359-369.
Bowers, W. J. (1968). Normative constraints o n deviant behavior in the college context. Sociometry, 31, 370-385.
Bowman, II., & Fishbein, M. (1978). Understanding public reaction to energy proposals: An
application of the Fishbein model. Journal ofApplied Social Psychology, 8, 319-340.
Brannon, R., Cyphers, G., Hesselbart, S., Keane, R., Schuman, H., Viccaro, T., & Wright, D.
(1973). Attitude and action: A field experiment joined to a general population survey.
American Sociological Review, 38, 625-636.
Bratman, M. E. (1987). Intention, plans, andpractical reason. Cambridge, MA: Harvard
University Press.
Brown, D. W. (1974). Adolescent attitudes and lawful behavior. Public Opinion Quarterly,
38, 98-106.
Bruvold, W. H. (1972). Consistency among attitudes, beliefs, and behavior. Journal of SocialPsychology, 86, 127-134.
Bruvold, W. H. (1973). Belief and behavior as determinants of attitude. Journal of Social
Psychology, 90, 285-289.
Calway-Fagen, N., Wallston, B. S., & Gabel, H. (1979). The relationship between attitudinal
and behavioral measures of sex preference. Psychology of Women Quarterly, 4, 274-280.
Canary, D. J., & Seibold, D. R. (1984). Attitudes and behavior: A n annotated hihliography.
New York: Praeger Publishers.
Carr, C., & Roberts, S. (1965). Correlates of civil-rights participation. Journal ofsocial Ps.y
chology, 67, 259-267.
Chaffee, S., & Lindner, J . (1969). Three processes of value change without behavior
change. Journal of Communication, 19, 30-40.
Cohen, A. R. (1964). Attitude change and social influence. New York: Basic Books.
Cook, M . P., Lounsbury, J. W., & Fontenelle, G. A. (1980). An application of Fishbein and
Ajzen’s attitudes-subjective norms model to the study of drug use. Journal ofSocial Psychology, 110, 193-201.
134
Attitudc-Behauior Relations: A Meta-Analysis
Corey, S. M. (1937).Professed attitudcs and actual behavior. Journal qf Educational P~sy
chology, 28,271-280.
Crespi, I . (1971). What kinds of attitude measures are predictive of behavior? Public Opinion Qua rtcrly, 3 S , 3 27-334,
rhviclson, A. K., & Jaccarcl,J. J . ( 1979). Variables that moderate the attitude-behavior relation: Results of a longitudinal survey. ,Journalof I’ersonali[y and Social Psycholqy, ?. 7,
1364-1376.
Davidson, A. K., 8 Morrison, D. M .(1983). Predicting contraceptive behavior from attitudes: A comparison of within- versus acmss-subjects procedures. Journal of Personality
and Social Psycho1og.y. 4 5(5), 997- 1009.
DeFleur, M. L., Kr Westie, F. R. (1963). Attitude as a scientific concept. SocialForces, 4.2,
17-31,
DeFriese, G . H., & Ford, W. S. (1969). Vcrtnl attitudes, overt acts, and the influence of so
cia1 constraint in interracial behavior. Social Problems, 16, 493-504.
Deutscher, I. (1966). Words and deeds: Social science and social policy. Social Problems.
I-XWinter), 235--254.
Deutscher, I. (1973). What u’e.say/uhat U J C do: Sentiments and acts. Glenview, IL: Scott,
Foresman and Company.
DeVries, D. L., & Ajzen, I. (1971). The relationship of attitudes and normative beliefs t o
cheating in college. Jozrrnal qfSocial Rsychology, 8.3, 199-207.
Dibhle. V., Kr Straus, M. A. (1980). Some social structure determinants o f inconsistency hetween attitudes and behavior: The case 0 1 family violence. Journal ofMarriage and the
Family, 42, 71-80.
Dillehay, R. C. (1973). On the irrelevance o f the classical negative evidence concerning the
effects o f attitiidcs on behavior. American Psychologist, 28, 887-891.
Doob. L. W. (1947). The Ixhavior of attitudes. Psychological Reuiew, 23,667-673
Dyer, M. G. (1983) In-depth understanding; A computer model of integratedprocessiljor
narrative comprehension. Cambridge, MA: MIT Press.
Eagly, A. H., 81 Hinimelfarb, S . (1978). Attitudes and opinions. Annual Review ofPsycholog . ~ 29,
,
517-554.
Ehrlich, H. J . (1969). Attitudes, behavior. and the intervening variables. The American Sociologist, 4(1),29-34.
Ewens, W. L., & Ehi-lich, €1. I. (1972). Referent-other support and ethnic attitudes as predictors of intergroup behavior. Sociological Quarterly, I 3 , 348-360.
Fazio, A . F. (1969). Verbal and overt-behavioral assessment of a specific fear. journal of
Consulting and Clinical Psychology, 3.3, 705-709.
Fazio, R. H. (1986). How d o attitudes guide behavior? In R. M. Sorrentino & E. T. Higgins
(Eds.), 7be handbook of motivation and cognition. Foundations ofsocial behavior New
York: Guilford Press.
Fazio, R . H., Chen, J., McDonel, E. C., & Sherman, S. J. (1982). Attitude accessibility, attitude-behavior consistency, and the strength of the object-evaluation association. Journal of Experimental Social Psychology, 18, 339-357.
Fazio, R. H., Powell, M . C.. & Herr, P. M . (1983). Toward a process model of the
attitude-behavior relation: Accessing one’s attitude upon mere observation of the atti
tude object. Journal ofPersonality and Social Psychology, 44, 723-735.
135
Journal of Communication, Winter 1 9 3
Fazio, R. H., Sanbonmatsu, D. M., Powell, M. C., & Kardes, F. R. (1986). O n the automatic
activation of attitudes. Journal of Personality and Social Psychology, 50(2), 229-238.
Fazio, R. H., &Williams, C. J. (1986). Attitude accessibility as a moderator of the attitude
perception and attitude-behavior relations: An investigation of the 1984 presidential
election. Journal ofPersonality and Social Psychology, 51, 505-514.
Fazio, R. H., & Zanna, M. P. (1978a). Attitudinal qualities relating t o the strength of the attitude-behavior relationship. Journal of Experimental Social Psychology, 14, 398-408.
Fazio, R. H., & Zanna, M. P. (1978b). O n the predictive validity of attitudes: The roles of direct experience and confidence. Journal of Personality, 46, 228-243.
Fazio, R. H., & Zanna, M. P. (1981). Direct experience and attitude-behavior consistency
In L. Berkowitz (Ed.), Advances in Experimental Social Psychology, 14, 161-202.
Fendrich, J. M. (1967a). Perceived reference group support: Racial attitudes and overt behavior. American Sociological Review, 32, 960-970.
Fendrich, J. M. (1967b). A study of the association among verbal attitudes, commitment and
overt behavior in different experimental situations. Social Forces, 45, 347-355.
Festinger, L. (1957). A theo y of cognitive dissonance. Stanford, CA: Stanford University
Press.
Festinger, L. (1964). Behavioral support for opinion change. Public Opinion Quarterly, 28,
404-4 17.
Fishbein, M., & Ajzen, I. (1972). Attitudes and opinions. Annual Review of Psychology, 23,
487-544.
Fishbein, M., & Ajzen, I. (1974). Attitudes towards objects as predictors of single and multiple behavioral criteria. Psychological Review, 81(1), 59-74.
Fishbein, M., & Ajzen, I. (1975). BelieJ;attitude, intention, and behavior: An introduction
to the0 y and research. Reading, MA: Addison-Wesley.
Fishbein, M., & Coombs, F. S. (1974). Basis for decision: An attitudinal analysis of voting
behavior. Journal ofApplied Social Psychology, 4, 95-124.
Fishbein, M., Middlestadt, S., & Chung, J. (1986). Predicting participation and choice: Firsttime voters in U.S. partisan elections. In s. Kraus & R. M. Perlott (Eds.), Mass media and
political thought: An information-processinR approach (pp. 65-82), Berverly Hills, CA:
Sage.
Fredericks, A , , & Dossett, D. (1983). Attitude-behavior relations: A comparison of the Fishbein-Ajzen and the Bentler-Speckart Models. Journal of Personality and Social Psycholog ~45(3),
,
501-512.
Freedman, R., Hermalin, A,. & Change, M. (1975). Do statements about desired family size
predict fertility? The case of Taiwan, 1967-1970. Demography, 1x31,407-416.
Frideres, J. (1971). Situational and personality variables as influencing the relationship between attitudes and overt behavior. Canadian Review of Social Anthropology, 8, 91-105.
Frideres, J., & Warner, L. (1980). Attitude-action relationships. Canadian Review of Social
Anthropology, 1 7 ( 2 ) , 109-121.
Frideres, J., Warner, L . , & Albrecht, S. (1971). The impact of social constraints o n the relationship between attitudes and behavior. Social Forces, 50, 102-112.
Gibbons, F. X. (1975). Sexual standards and reactions to pornography: Enhancing behavioral consistency through self-focused attention. Journal of Personality and Social Psychology, 36(9), 976-987.
136
AttitudeBehavior Relations: A Meta-Analysis
Goodmonson, C., & Glaudin, V. (1971). The relationship of commitment-free behavior and
commitment behavior: A study of attitude toward organ transplantation. Journal of Social
Issues, 4, 171-183.
Green, B. F. (1954). Attitude measurement. In G. Lindzey (Ed.), Handbook of socialpsychology (Vol. 1). Reading, MA: Addison-Wesley.
Green, J . A. (1972). Attitudinal a n d situational determinants of intended behavior towards
blacks. Journal ofPersonality and Social Psychology, Z X l l ) , 13-17.
Hamner, W. C., & Smith, F. (1978). Work attitudes as predictors of unionization activity
Journal ofApplied Psychology, 63(4), 415-421.
Heise, D. (1977). Group dynamics and attitude-behavior relations. Sociological Methods G
Research, 5(3), 259-288.
Herman, J. B. (1973). Are situational contingencies limiting job attitude-job performance
relationships? Organizational Behavior and Human Performance, 10, 208-224.
Holman, P. (1956). Validation of a n attitude scale as a device for predicting behavior. Journal ofApplied Psychology, 40(5), 347-349,
Hom, P., & Hulin, C. (1981). A competitive test of the prediction of reenlistment by several
models. Journal ofApplied Psychology, 66(1),23-39.
Hom, P., Katerberg, R., & Hulin, C. (1979). Comparative examination of three approaches
to the prediction of turnover. Journal ofApplied Psychology, 64(3), 280-290.
Hunter, J . E. (1990a). METADICH: Aprogram to do meta-analysis of correlations corrected
f o r dichotomization. East Lansing: Michigan State University, Department of Psychology.
Hunter, J . E. (1990b). METADIRL: Aprogram to do meta-analysis correcting f o r dichotomization and random error of measurement. East Lansing: Michigan State University, Department of Psychology.
Hunter, J . E. ( 1 9 9 0 ~ ) RELMETA:
.
Aprogram to do meta-analysis of Spearman-Brown reliabilities. East Lansing: Michigan State University, Department of Psychology.
Hunter, J . E., & Schmidt, F. L. (1990). Methods of meta-analysis. Newbury Park, CA: Sage
Hunter, J. E., Schmidt, F. L., &Jackson, G. B. (1982). Meta-analysis: Cumulating research
@dings across studies. Beverly Hills, CA: Sage.
Hyman, H. H. (1949). Inconsistencies as a problem in attitude measurement. Journal of Social Issues, 5(Summer), 38-42.
Ilgen, D. R., & Hollenback, J. H. (1977). The role of job satisfaction in absence behavior.
Organizational Behavior and Human Performance, 19, 148-161.
Insko, C. A., & Schopler, J. (1967). Triadic consistency: A statement of affective-cognitiveconative consistency. Psychology Review, 74, 361-376.
Jaccard, J., King, G. W., & Pomazai, R. (1977). Attitudes and behavior: An analysis of specificity of attitudinal predictors. Human Relations, 30, 817-824.
Jackman, M. R. (1976). The relation between verbal attitude and overt behavior: A public
opinion application. Social Forces, 54,646-668.
Jackson, G. B. (1980). Methods for integrative reviews. Reviews of Educational Research,
~50(3),438-460.
Jones, J. W. (1980). Attitudinal correlates of employees' deviance: Theft, alcohol use, and
nonprescribed drug use. Psychological Reports, 47, 71-77.
137
rournal
of
Communication, Winter 199.3
Kahle, L. R., & Berman, J . J. (1979). Attitudes cause behaviors: A cross-lagged panel analysis. Journal of Personality and Social Psychohgy, .? X 3 ) , 315-321.
Kahle, L. R., Klingel, D. M., & Kulka, R. A. (1981). A longitudinal study of adolescents’ attitude-behavior consistency. Public Opinion Quarterly, 45, 402-414.
Kelly, S., & Mirer, R. W. (1974). The simple act of voting. ilmerican Political Science Review, 68, 572-591.
Kelman, H. C . (1974). Attitudes are alive and well and gainfully employed in the sphere o f
action. American Psychologist, 29, 310-324.
Kilty, K. M. (1978). Attitudinal and normative variables as predictors of drinking behavior
Journal ofstudies on Alcohol, 39, 1178-1194.
King, G. W. (1975). An analysis of attitudinal and normative variables as predictors of in
tentions and behavior. Speech Monographs, 42, 237-244.
Kothandapani, V. (1971). Validation of feeling, belief, and intention to act as three components of attitude and their contribution to prediction of contraceptive behavior. Journal
of Personality and Social Psychology, lR3), 321-333.
Kreitler, H., & Kreitler, S. (1976). Cognitive orientation and behavior. New York: Springer
Publishing Company.
LaPiere, R. T. (1934). “Attitude vs Actions.” Social Forces, 13, 230-237
LaRocco, J . M. (1983). Job attitudes, intentions, and turnover: An analysis of effects using
latent variables. Human Relations, 36(9),813-826.
Larson, C., tk Sanders, R. (1975). Faith, mystery, and data: An analysis of “scientific” studies
of persuasion. Quarterly Journal of Speech, 61, 178-194.
Lewis, J. (1980). The relationship between attitudes toward reading and reading success
Educational and Psychological Measurement, 40, 261-262.
Linn, L. (1965). Verbal attitudes and overt behavior: A study of racial discrimination. Social
Forces, 4.3(3), 353-364.
Liska, A. E. (1974a). Attitude-behavior consistency as a function of generality equivalence
between attitude and behavior objects. Journal of Psychology, 86, 217-228.
Liska, A. E. (1974b). Emergent issues in the attitude-behavior consistency controversy.
American Sociological Rez/iew, 39, 261-272.
Liska, A . E. (Ed.). (1975). The consistency controz)ers.y:Readings on the impact of attitude
on behavior. New York: Academic Press.
Iiska, A. E. (1978). Deviant involvement, associations and attitudes: Specifying the underlying causal structures. Sociology and Social Research, 6.?, 73-89.
Liska, A. E. (1984). A critical examination of the causal structure o f the Fishbein/Ajzen attitude-behavior model. Social Psychology Quarterly, 4 X l), 61-74.
Mann, J. H . (1959). The relationship between cognitive, affective, and behavioral aspects of
racial prejudice. Journal of Social Psychology, 49, 223-228.
Manstead, A . S., Proffitt, C., tk Smart, J. L. (1983). Predicting and understanding mothers’ inpdnt-feeding intentions and behavior: Testing the theory of reasoned action. Journal of
Personality and Social Psychology, 44(4),657-671.
McGuinness, J., Jones, A. I>., & Cole, S. G . (1977). Attitudinal correlates of recycling behavior. Journal ofApplicd Psychology, 6X4), 376-384.
Mehrabian, A. (1968). Relationship of attitude to seating posture, orientation, and distance.
Journal of Personality and Social Psychology, 10, 26-30.
Merton, R. K. (1949). Discrimination and the American creed. In R. M. MacIver (Ed.), Dis-
138
AttitudcLBehatdor Relations: A Meta-Ana@is
crimination and national welfare (pp. 99-126). New York: Institute for Religious and
Social Studies.
Miller, G. It. (1968). Communication and persuasion research: Current problems and
prospects. &zuzrterly.rournal of Speech. 54, 268-276.
Miller, G. R. (1980). Afterword. In D. P. Cushnian Kr R. D. McPhee (Eds.), Messagc-attitudebehauior relationship: Theoy , mcJthodolog,y,and application New York: Academic
Press.
Miniard, P. W., Sr Cohen, J. B. (1981). An examination o f the Fishbein-Ajzen hehavioral in
tentions model’s concepts and measures. Journal gfExperimentu1 Social Psycholog?;, 17,
309-399.
Newton, N. R., & Newton, M. (1950). Relationship o f ability t o breast feed and maternal attitudes toward I)reast feeding. Pediatrics, 5, 869-875.
Norman, R. (1975). Affective-cognitive consistency, attitudes, and behavior. Journal of Personality and Social Psychology, 32, 83-91,
O’Keefe, I>. J . , 8r Shepherd, G . J . (1982). Interpersonal construct differentiation, attitudinal
confidence, and the attitude-behavior relationship. Central States Speech Jour?zal,3.1.
4 16-423,
Oliver. K. L., 8r BerSer, P. K. (1979). A path analysis of preventive health care decision models. Journal of C‘onszimerResearch, 6: 113-122.
Ostrom, T. M. ( 1969). The relationship between the affective, behavioral, and cognitive
components o f attitude. Journal ofllxperimental Social Psychology, 5,12-30.
Kr Ihvidson, A. R. (1984). A comparison of three social-psychological models
Pagel, M. I].,
of attitude and Ixhavioral plan: Prediction o f contraceptive behavior. Journal ofpersonality and Social~.s.sycholog,y,47(3),517-533.
Perry, R. W. (1976). The effects of apparent guilt and prior attitudes on the verdicts o f s t u
dent juries. Eirropean Journal ofSocia1 I-’sychologly. 6(1),115-1 18.
Perry, R. W., 8; Gillespie, 11. F. (1976). An analysis o f intervening variables in the
attitude-behavior relationship. Joz*riral oJ’SociulPs-ychology,98, 287-288.
I’omazal, R . J , , & Jaccard, J . .J. (1976). An informational approach to altruistic behavior.
,/ournu1ofPersonulity and Social Psycholog-v,-?-3(3),317-326.
Potter, €1. W., & Klein, €3. R. (1057). On nursing lxhavior. P.sychintly, 20. 39-46.
Prislin, R. (1987). Attitude-behavior relationship: Attitude relevance and Iiehavior relevance. European jou rnal qf Social t’syc h olog.y, 1 7, 483-485.
Pryor, J . B., Gibbons, F., 8r Wicklund, R. A . (1077). Self-focused attention and self-report validity. Journul ofPersonalif-y,45, 513-527.
Regan 11. T., Kr Fazio, R. H. (1977). On the consistency between attitudes and behavior:
Look t o the method of attitude formation. ,/ozir7aal qfExperimenta1 Social Psychology. 1.3,
28-45.
Rokeach, M. (1967). Attitude change and behavioral change. Public Opinion Quurtcrly, 30,
529-550.
Rokeach, M . (1968) Reliqfi, attitiida, and ualites. San Francisco: Jossey-Bass
Rokeach, M., Kr Kliejunas, I-’. ( 1972). Behavior as a function of attitude-toward object and
attitude-toward-situation. Journal oJI’ersoriulity and Social Ps-vchology,2 3 2 1 , 194-201
Rosenberg, M. J . ( 1956). Cognitive structure and attitudinal affect. Journal ofAbnormal
U T ZSocial
~
Psychologj: 53, 367-372.
139
Journal of Communication, Winter 199.3
Rosenberg, M. J. (1965). When dissonance fails: On eliminating evaluation apprehension
from attitude measurement. Journal of Personality and Social Psychology, 1, 28-42.
Rosenberg, M. J., & Hovland, C. I. (1960). Cognitive, affective, and behavioral components
of attitudes. In C. I. Hovland & M. J. Rosenberg (Eds.), Attitude organization and change
(pp. 1-14). New Haven, CT: Yale University Press.
Ryan, M. J. (1978). An examination of an alternative form of the Behavioral Intention
Model’s normative component. In H. K. Hunt (Ed.), Advances in consumer research 5
(pp. 283-389). Provo, UT: The Association for Consumer Research.
Ryan, M. J., & Bonfield, E. (1975). The Fishbein extended model and consumer behavior
Journal of ConsumerResearch, 2, 118-136.
Sample, J., & Warland, R. (1973). Attitudes and prediction of behavior. Social Forces, 51,
292-304.
Schifter, D. B., & Ajzen, I. (1985). Intention, perceived control, and weight loss: An application of the theory of planned behavior. Journal of Personality and Social Psychology, 49,
843-85 1.
Schuman, H., &Johnson, M. P. (1976). Attitudes and behavior. In A. Inkeles, J. Coleman, &
N. Smelser (Eds.), Annual Review of Sociology, 2, 161-207.
Schwartz, S. H. (1978). Temporal instability as a moderator of the attitude-behavior relationship. Journal of Personality and Social Psychology, 36, 715-724.
Schwartz, S. H., & Tessler, R. C. (1972). A test of a model for reducing measured
attitude-behavior discrepancies. Journal of Personality and Social Psychology, 24,
225-236.
Seibold, D. R . (1975). Communication research and the attitude-verbal report-overt behavior relationship: A critique and theoretical reformulations. Human Communication Research,
3-32.
al),
Seligman, C., Kriss, M., Darley, M., Fazio, R. H., Becker, L. J., & Pryor, J . B. (1979). Predicting summer energy consumption from homeowners’ attitudes. Journal ofApplied Social
Psychology, g l ) , 70-90.
Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A
meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15, 325-343.
Sivacek, J., & Crano, W. D. (1982). Vested interest as a moderator of attitude-behavior consistency. Journal of Personality and Social Psychology, 43(2), 210-221.
Smetana, J. G., & Adler, N. E. (1979). Decision-making regarding abortion: A value x e x pectancy analysis. Journal of Population, 2, 338-357.
Smetana, J. G., & Adler, N. E. (1980). Fishbein’s value xexpectancy model: An examination
of some assumptions. Personality and Social Psychology Bulletin, 6(1), 89-96.
Snyder, M. (1982). When believing means doing: Creating links between attitudes and behavior. In M. P. Zanna, E. T. Higgins, & C. P. Herman (Eds.), Consistency in social behavior: The Ontario Symposium, Vol. 2 (pp. 105-130). Hillsdale, NJ: Lawrence Erlbaum Associates.
Snyder, M., & Kendzierski, D. (1982). Acting on one’s attitudes: Procedures for linking attitude and behavior. Journal of Experimental Social Psychology, 18, 165-183.
Snyder, M., & Swann, W. B. (1976). When actions reflect attitudes: The politics of impression management. Journal of Personality and Social Psychology, 34(5), 1034-1042.
140
Attitude-Behavior Relations: A Meta-Analysis
Speare, A. (1974). Residential satisfaction as a n intervening variable in residential mobility.
Demography, 11(2), 173-188.
Stutzman, T. M., & Green, S. €3. (1982). Factors affecting energy consumption: Two field
tests of the Fishbein-Ajzen Model. Journal of Social Psychology, 11 7, 183-201.
Tittle, C. R., 81 Hill, R. J. (1967a). Attitude measurement and prediction of behavior: An
evaluation of conditions and measurement techniques. Sociomety, 30, 199-213.
Tittle, C. R., & Hill, R. J . (1967b). The accuracy of self-reported data and prediction of political activity. Public Opinion Quarterly, 31, 103-106.
Triandis, H. C. (1964). Exploratory factor analyses of the behavioral component of social
attitudes. Journal of Abnormal and Social Psychology, 68, 420-430.
Underwood, B., & Moore, B. S. (1981). Sources of behavioral consistency. Journal of Personality and Social Psychology, 40, 780-785.
Veevers, J. E. (1971). Drinking attitudes and drinking behavior: An exploratory study. Journal of Social Psychology, 85, 103-109.
Vinokur-Kaplan, 1). (1978). To have o r not t o have another child: Family planning attitudes,
intentions, a n d behavior. Journal of Applied Social Psychology, Cyl), 29-46.
Warland, R. H., & Sample, J. (1973). Response certainty as a moderator variable in attitude
measurement. Rural Sociology, 38, 174-186.
Warner, L., & DeFleur, M. L. (1969). Attitude as a n interactional concept: Social constraint
and social distance as intervening variables between attitudes and action. American Sociological Review. 34(2), 153-169.
Warshaw, P. R., Calantone, R., &Joyce, M. (1986). A field application o f t h e Fishbein and
Ajzen Intention Model. Journal ofsocial Psychology, 126(1), 135-136.
Weigel, R. H., & Amsterdam, J. T. (1976). The effect of behavior relevant information o n attitude-behavior consistency. Journal of Social Psychology, 98, 247-251.
Weigel, R. H., & Newman, L. S. (1976). Increasing attitude behavior correspondence b y
broadening the scope of the behavioral measure. Journal of Personality and Social Psychology, 33, 793-802.
Weigel, R. H., Vernon, D., & Tognacci, L. N. (1974). Specificity of the attitude a s a determinant of attitude-behavior congruence. Journal of Personality and Social Psychology,
.30(6), 724-728.
Weinstein, A. C . (1972). Predicting behavior from attitudes. Public Opinion Quarterly, .?6,
355-360.
Weissberg, N. (1965). O n DeFleur and Westie’s “Attitudes as a scientific concept.” Social
Forces, 43, 422-425.
Werner, P. D. (1978). Personality and attitude-activism correspondence. Journal of Personality and Social Psycholog,y,36(12), 1375-1390.
Werner, P. D., & Middlestadt, S. E. (1979). Factors in the use of oral contraceptives by
young women. ,JournalofApplied Social Psychology, %6>,537-547.
Wicker, A. W. (1969). Attitudes vs. actions: The relationship of verbal and overt behavioral
responses to attitude objects. Journal of Social Issues, 25, 41-78.
Wicker, A. W. (1971). An examination of the “other variables” explanation of attitude-behavior inconsistency. Journal of Personality and Socialpsychology, IXl), 18-30.
Wilensky, R. (1983). Planning and understanding: A computational approach to human
reason. Reading, MA: Addison-Wesley.
141
Journal of Communication, Winter 199.3
Wilson, T. D., & Dunn, D. S. (1986). Effects of introspection o n attitude-behavior consistency: Analyzing reasons versus focusing o n feelings. Journal of Experimental Social Psychology, 22, 249-263.
Wilson, T. D., Dunn, D. S., Bybee, J. A., Hyman, D. B., & Rotonde, J. A. (1984). Effects of
analyzing reasons o n attitude-behavior consistency. Journal of Personality and Social
Psychology, 47, 5-16.
Winters, L. C. (1971). Measuring attitudes and behavior toward ecologically significant
products. Psychological Reports, 29, 893-894.
Zanna, M. P., Olson, J. M., & Fazio, R. H. (1980). Attitude-behavior consistency: An individual difference perspective. Journal of Personality and Social Psychology, 38, 432-440.
Zuckerman, M., & Keis, H. T. (1978). Comparison of three models for predicting altruistic
behavior. Journal of Personality and Social Ps.ychology, 36, 498-510.
Zunich, M. (1961). A study of relationships between child rearing attitudes and maternal
behavior. Journul uf Experimental Educalion, . 3 @ 2 ) , 231-241.
Zunich, M. (1962). Relationship between maternal behavior and attitudes toward children.
Journal of Genetic Psychology, 100, 155-165.
142