Attitude-Behavior Relations: A Meta-Analysis of 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 in recent social science research. Thepurpose of this study was to determine whether attitudinal relevance substantially affects the mag- nitude of the correlation between attitudes and behavior, and whether the effects are content-free. Using meta-analy- sis, we integratedjindings from 138 attitude-behavior corre- lations 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 at- titude-behavior relationship (r = .791 when methodological artifacts were eliminated. Aspredicted, the higher the attitu- dinal relevance, the stronger the relationship between atti- tudes and behavior. This effect held true across diverse con- tent domains. Implications for communication theoly and practice are discussed. The concept of attitude, typically viewed as a stable underlying disposi- tion,' has played a central role in explaining communication phenomena, particularly the effects of persuasive messages. Most 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 in- stance, Ajzen (1988) defines an attitude as a disposition to respond favorably or 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. 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 on earlier drafts of this paper provided by Professor Steven R. Wilson and Pro- fessor Gerald R. Miller of Michigan State University. Copyright 0 1993 Journal of Communication 43(1), Winter. 0021-9916/93/$0.0+.05 ~~ .. . ~~ ... ~~~~~~~~~ ~ ~ 101 Research Artick
Transcript
Attitude-Behavior Relations: A Meta-Analysis of 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 mag- nitude of the correlation between attitudes and behavior, and whether the effects are content-free. Using meta-analy- sis, we integratedjindings f rom 138 attitude-behavior corre- lations 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 at- titude-behavior relationship (r = .791 when methodological artifacts were eliminated. Aspredicted, the higher the attitu- dinal relevance, the stronger the relationship between atti- tudes and behavior. This effect held true across diverse con- tent domains. Implications f o r communication theoly and practice are discussed.
The concept of attitude, typically viewed as a stable underlying disposi- tion,' has played a central role in explaining communication phenomena, particularly the effects of persuasive messages. Most 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 in- stance, Ajzen (1988) defines an attitude as a disposition to respond favorably or 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.
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 on earlier drafts of this paper provided by Professor Steven R . Wilson and Pro- fessor Gerald R. Miller of Michigan State University.
Copyright 0 1993 Journal of Communication 43(1), Winter. 0021-9916/93/$0.0+.05
~~ .. . ~~ ... ~~~~~~~~~ ~ ~
101
Research Artick
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 controver- sies in the social sciences.
Scholars have widely debated the relationship between attitudes and overt behavior (for reviews, see Canary & Seibold, 1984; Eagly & Himmel- farb, 1978; Fishbein bi Ajzen, 1972; Liska, 1975; Miller, 1968; Schuman & Johnson, 1976; Seibold, 1975; Wicker, 1969).2 As a result, three basic posi- tions have emerged.
The first, argued mostly by the behaviorist camp, posits that since atti- tudes are cognitive events, they have no consequences for the way peo- ple act o r the way they perform those acts. Therefore, attitudes cannot predict behavior (see Bandura, 1969; Blumer, 1955; Corey, 1937; Deutsch- er, 1966, 1973; Doob, 1947; Green, 1954; LaPiere, 1934; Larson & Sanders, 1975; Merton, 1949). Proponents of this position conceive of verbally ex- pressed attitudes as behavior or as surrogates of behavior, hence atti- tude-behavior (A-B) relations are not particularly relevant or important. They urge abandoning the general concept of attitude and directly study- ing 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. Simi- larly, 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 inconsis- tency between verbal-scale scores and other overt actions, pointing to sit- uational or individual factors as the crucial determinants of behavior. Based largely on what Warner and DeFleur (1969) have termed the postu- late of contingent consistency, this group argues that the influence of the “other variables” is so overwhelming that we should expect little o r no di- rect 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 deter- mines 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 ver- sus 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 complexi- ty (e.g., O’Keefe & Shepherd, 19821, self-monitoring (e.g., Snyder, 1982; Snyder & Kendzierski, 1982; Snyder & Swann, 19761, private self-con- sciousness (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 atti- tude object (e.g., Borgida & Campbell, 1982; Fazio, Powell, & Herr, 1983; Fazio & Zanna, 1978a, 1978b, 1981; Regan & Fazio, 1977), attitude acces- sibility (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).
and corresponding behavioral tendencies are closely related to each other, whatever the causal direction might be. One of the directional as- sumptions comes from the consistency theory, which claims that tenden- cies to reach consistency between behavior and attitude will act in both directions (see Cohen, 1964; Festinger, 1957; Insko & Schopler, 1967; Kel- man, 1974; Rosenberg, 1965). The most commonly evoked directional po- sition, however, has been a causal link from attitudes to behavior (for em- pirical results, see Andrews & Kandel, 1979; Bentler & Speckart, 1979, 1981; Kahle & Berman, 1979; Kahle, Klingel, & Kulka, 1981). For exam- ple, 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 mod- els explaining the extent to which people act according to their attitudes. In the following section, we discuss this third position in more detail.
A third group of researchers has suggested that construct-valid attitudes
T h e Relevance of Relevance
While different theories contain different operational forms and concep- tions 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 predict- ing 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 deter- mining 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. Ex- panding on Fishbein and Ajzen’s model, Kreitler and Kreitler (1976) pro- posed 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 CO components is related to the positive relation be- tween attitudes and behavior.
In another attempt to increase the construct validity of attitudes, Rosen- berg (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 indi- vidual’s perceived expectancy of goal attainment. Behavior with refer- ence to an attitude object may vary as a function of its perceived instru- mentality, 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 explana- tions of A-B relationships. Various models of these relationships are dif- ferent attempts to enhance attitudinal relevance by positing a combina- tion 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 rela- tionship between attitudes and behavioral intention. The expectation is that the population correlation will increase noticeably with increasing at- titudinal relevance, and construct-valid attitudes will have directive influ- ence over behavior.
The major problem in testing the relationship between attitude and be- havior 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 attitu- dinal 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 atti- tudinal 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-ob- ject measures should not be expected to predict an isolated single act, but should predict “multiple-act criteria.” While latent constructs with multi- ple 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 con- struct validity of the items. For instance, it is quite possible that multiple- act criteria may completely depart from construct validity but still yield quite a high correlation between attitudes and behavior, purely due to in- creased 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 relation- ships, we advance the following hypothesis:
H1: The higher the attitudinal relevance, the higher the correlation be- tween attitudes and behavior.
A second objective of our research is to test whether the relation be- tween 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 de- gree of A-B relation.
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 stud- ies across a wide variety of content categories (e.g., voting behavior, delinquency, drugs, alcohol, birth control, environmental protection, con- sumer behavior, games, blood donation, and religion).
Until the 1960s few researchers studied the role of content categories as
105
Journal o_f’Communication, Winter 199.3
One way to investigate the role of behavioral topic would be to catego- rize 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 be- cause it is strongly and consistently related to attitudes. Bentler and Speckart (1979) also found that the effects of intention depend on the be- havior 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 in- creasing 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 sum- marized 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).
dicting behavior were matched by varied review findings (see last col- umn, 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 rele- vance and one of which required reanalysis of data” (p. 405). A third study was acceptable. He concluded that there was little research evi- dence 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 con- cluded that low correlations are in part due to the use of single-item mea- sures (presumably low in reliability). Similarly, Fishbein and Ajzen (1 972)
Vastly different views about the usefulness of attitude constructs in pre-
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. Kre- itler 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 sig- nificant” A-B associations, all had low or partial target or action measure- ment 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 rea- soned action. While their findings concerning the theory were mostly promising, their conclusions did not provide much insight into the gener- al problem of A-B relationships. Thus, even though numerous reviewers (some of whom have examined more than 100 studies) have tried to ex- plain 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 proce- dures and explains why the variations in conclusions drawn by most re- views 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 pro- cedure, type o f synthesis method, and the treatment of methodological artifacts due to sampling error, error of measurement, and dichotomiza- tion of variables. Table 1 summarizes and evaluates the prior reviews under those criteria.
Criterion I : Examination ofprevious reviews. The critical use o f previ- ous review studies is important in judging the strengths and weaknesses of earlier work. However, only one of the review studies in Table 1 pro- vides 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 re- ported the sources (such as Social Science Citation Index) or the informa- tion retrieval systems used to locate primary studies for possible inclu- sion. When information on the sources used for locating studies is not available, it is impossible to ascertain the degree of bias in the review re- sults. 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
Tab
le 1
: Su
mm
ary
of R
evie
ws o
n A
ttitu
de-B
ehav
ior
Rel
atio
nshi
p
Crit
eria
for
eval
uatio
n Crit
ique
of
Aut
hor
Sam
plin
g pr
evio
us
Syn
thes
izin
g b
y d
ate
m
etho
d re
view
s K
met
hod
Con
clus
ions
dra
wn
Titt
le &
Hill
Sel
ectiv
e N
o 15
Lo
w/m
oder
ate/
high
6
low
, 1 m
oder
ate
low
, 2 m
oder
ate,
( 1
967a
) 6
high
.
Wic
ker
Com
preh
ensi
ve
No
47
Coe
ffici
ent o
f ass
ocia
- C
orre
latio
ns a
re ra
rely
abo
ve
( 196
9)
tion
repo
rted
by
.30
an
d o
ften
0.
inve
stig
ator
s
Fish
bein
& A
jzen
S
elec
tive
No
14
Sig
nific
ance
A
sin
gle
obse
rvat
ion
of a
sin
gle
act
(1
972)
re
sults
in n
onsi
gnifi
cant
resu
lts,
whi
le m
ultip
le-a
ct c
riter
ia re
sult
in
sign
ifica
nt re
latio
n.
Ajz
en &
Fis
hbei
n P
urpo
sive
N
o 21
si
gnifi
canc
e P
roce
sses
inte
rven
ing
betw
een
in-
tent
ion
an
d b
ehav
ior t
end
to r
e-
du
ce th
e re
latio
n.
(1 9
73)
Sei
bold
(1
975)
S
elec
tive
No
16
Hig
h/m
oder
ate/
low
H
alf l
ow, h
alf m
oder
ate,
one
hig
h
Rya
n &
Bon
field
C
ould
not
be
N
o 35
A
vera
ge
The
aver
age
corr
elat
ion
betw
een
tion
of a
ttitu
de, s
ocia
l inf
luen
ce
on B
I was
.60.
(1 97
5)
dete
rmin
ed
corr
elat
ion
BI a
nd
Ba w
as -44; m
ultip
le c
orre
la-
4 w
- 0 Q
Tabl
e 1,
Con
tinue
d
Crit
eria
for
eval
uatio
n Crit
ique
of
Aut
hor
Sam
plin
g pr
evio
us
Syn
thes
izin
g b
y d
ate
m
etho
d re
view
s K
m
eth
od
C
oncl
usio
ns d
raw
n
Sch
uman
&Jo
hnso
n S
elec
tive
(1 9
76)
Kre
itler
& K
reitle
r C
ompr
ehen
sive
(1
976
)
Ajz
en &
Fis
hbei
n C
ompr
ehen
sive
(1
977)
Ajz
en
(1 98
5)
Sel
ectiv
e
She
ppar
d et
al.
Com
preh
ensi
ve
(1 98
8)
No
6 S
igni
fican
ce
Res
ults
var
y fro
m s
mal
l to
mod
erat
e.
No
117
Pos
itive
lneg
ativ
el
34 p
ositi
ve, 6
8 no
or n
egat
ive,
15
mix
ed
mix
ed re
latio
ns.
No
142
Low
if r
< .4
0,
Low
cor
resp
onde
nce
prod
uces
m
ostly
non
sign
ifica
nt re
latio
n w
hile
hig
h co
rres
pond
ence
re-
sults
in h
igh
rela
tion.
high
if r
> 40
.
No
9 S
igni
fican
ce
The
theo
ry o
f rea
sone
d ac
tion
can
pr
ovid
e ac
cura
te p
redi
ctio
n of
in
tent
ions
and
beh
avio
rs th
at
are
unde
r one
’s v
oliti
onal
co
n-
trol
.
Yes
87
Est
imat
ion
of p
opul
atio
n 0.
53 fo
r BI
-B,
0.66
for
A-Bb
.
Not
e: K
= nu
mbe
r of s
tudi
es.
a BI
an
d B
des
igna
te b
ehav
iora
l int
entio
n a
nd
beh
avio
r.
bA-B
des
igna
tes
attit
ude-
beha
vior
.
b 9
F
b
Journal of Communication, Winter 1993
located studies; 6 of the reviews are explicitly s elective.^ Among those re- viewers who tried to be comprehensive in sampling, Wicker (1969) in- cluded 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, re- sources, and so on. (For a discussion of other problems in Wicker’s re- view, 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 re- port findings of primary studies in terms of statistical significance. The significance tests do not provide information on the magnitude and direc- tion 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 hy- pothesis is false for the population, then the error rate can be as high as 95% (cf., Hunter, Schmidt, &Jackson, 1982). Even studies that do not de- pend 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.
studies at face value and report the range of outcome values. This proce- dure ignores sampling error. Since most studies are done with small sam- ples (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 re- views 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 respon- sible for many of the low A-B correlations. Therefore, the lack of concern with establishing the reliability of the independent and dependent mea- sure 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 point- biserial correlation) is artificially reduced. A point-biserial correlation is maximum for a 50/50 split; the greater the departure from 50/50, the
Criterion 4: Sampling error. Most reviews take all variations across
The information provided by Ryan and Bonfield (1975) was insufficient for making a judg- ment 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, espe- cially in the nieasures of behavior in such areas as blood donation, migra- tion, church attendance, and consumer behavior. None of the past re- viewers, 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 con- verted into correlations. While the correlation coefficient from an individ- ual study can be subject to any number of different artifacts (e.g., sam- pling error, measurement error, range restrictions, artificial dichotomiza- tion, 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 rang- ing over more than 20 different types of activities.
analysis was a comprehensive bibliography, Attitudes and Behavior: An Annotated Bibliography compiled by Canary and Seibold (1984). This an- notated bibliography lists 600 articles covering theoretical, methodologi- cal, and applied aspects of the A-B relationship. Its bibliographic diversi- ty 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 Re- search, Public Opinion Quarterly, Journal of Consumer Research, Jour- nal of Marketing, Journal of Personality and Social Psychology, and other major journals of the American Psychological Association and the Ameri- can 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.
The single most useful source for selecting studies relevant to our
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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 ob- tained references from articles relevant to the topic, and major reviews dealing with A-B relations in general (e.g, Fishbein & Ajzen, 1974; Kreit- ler & Kreitler, 1976; Schuman &Johnson, 1976; Wicker, 1969)) and in spe- cific 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 gener- al 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 at- titude construct has been developed from a unidimensional view of a per- son’s positive or negative affect toward an object (Allport, 1935) to a tri- partite 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 se- quentially (see Bagozzi, 1981; Fishbein & Ajzen, 1975).
Any method of attitude assessment that emphasizes its behavioral as- pect 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 stud- ies that operationalized attitudes as conation only. When a study used conation as part of the attitudinal elements, we tried to separate respons- es 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-
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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 con- trol, several investigators have proposed assessing “facilitating condi- tions” (Triandis, 1964); “behavioral control” (Ajzen, 1985); and “re- sources” (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 in- cluding the concept of behavior control. According to the theory of planned behavior, the theory of reasoned action (which relies on inten- tion as the sole predictor of behavior) is insufficient whenever control over the behavioral goal is incomplete. Researchers in cognitive psychol- ogy 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 con- trol, we are bound to observe some inconsistency between attitudes and behavior. Consequently, this study focuses on those behavioral domains where most individuals are capable of exercising control over the behav- ior in question. This is an important criterion that typically has been over- looked 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 indi- viduals 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,” in- volving 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).
(e.g., dominance, independence, helpfulness) rather than affect and/or beliefs. Distinguishing between attitudes and personality traits is admit-
Fifth, we excluded studies that used scales measuring personality traits
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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 up litter but did not cor- relate people's attitude with behavior. Heise (1977) also provided insuffi- cient data to compute an effect size. We also excluded studies that pro- vided correlations between attitude and behavioral intention and behavioral intention and behavior without providing the correlation be- tween attitude and behavior.
Studies that met all of the above criteria were selected for meta-analy- sis. Our final selection included 138 correlations. Studies dealing with multiple topics were analyzed separately (e.g., dating, studying, and exer- cising-Bentler & Speckart, 1981). We averaged correlations and reported the data as a single study if each correlation was based on 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 do- mains. The content categories present behavioral topics commonly inves- tigated in A-€3 research. The primary criterion we used to select these cat- egories 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 bibli- ography:
1. Altruistic behavior: helping behavior, such as volunteering to help
2. Consumer behavior: buying behavior, such as buying toothpaste,
3 . Deviance: antisocial (delinquent) behavior, such as cheating, buy-
blind children, volunteering to be a subject.
fruit drinks, prescription drugs.
ing a term paper, gambling on 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 rea- soned 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 litter-
5. Health care: service utilization, such as dental care; preventive
6. Groupparticipation: behavior such as joining a union, army reen-
7. Race relations: treatment of minorities, behavior related to minority
8. Religion: religious activities, such as church attendance. 9. Voting: voting practices, such as participation, choice of a candi-
date.
ing, water conservation, energy saving.
health care behavior, such as getting swine flu vaccination.
listment.
issues.
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; con-
sumption, 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
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
child.
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 be- havioral elements. In this study we operationalized it in terms of the con- tent validity of attitude items with regard to the behavior. The content va- lidity of attitude constructs has been considered a condition of method- ological correspondence between attitudinal and behavioral measures (Ajzen & Fishbein, 19771, under various names: “generality equivalence” (Liska, 1974a), “the principle of compatibility” (Ajzen, 1988), and “speci- ficity 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 to- ward which the action is directed have been used to study attitudinal rel- evance; virtually no studies have used time and context among their atti- tudinalhehavioral elements. Consequently, we used only action and target to judge attitudinal relevance. Those studies that match both action
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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 be- haviors 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 cou- pled 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 comprehen- sive behavioral index, ranging from petition signing to litter pick-ups.
Second, studies involving comprehensive attitudes (using many differ- ent 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.
population correlations given data on sample correlations. The correla- tion 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 cor- relation is simply the mean of the sample correlations. However, sam- pling error adds to the variance of correlations across studies. Thus we must correct the observed variance by subtracting the sampling error vari- ance. The corrected variance is still biased upward because it contains variance due to differences in reliability and dichotomization of mea- sures. Hence, the correlation must be corrected for errors due to the re- maining two artifacts.' Since there was a large corrected standard devia- tion 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).
The basic purpose of meta-analysis is to obtain correct inferences about
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Attitudt%Behavior Relations: A Meta-Analysis
Probing the Attitude-Behavior Link
Results are presented as follows: First, the overall correlations of atti- tude-behavior were identified and corrected for sampling error, measure- ment error, and dichotomization of variables. Then, in order to test the overall moderating effect of attitudinal relevance (Hypothesis 11, we con- ducted a series of subgroup analyses. Finally, we conducted another se- ries 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 meta- analysis. 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 on a combined sample of 90,808 partici- pants.
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 < . O O l ) .
Sampling error was only one source of artifactual variation across the studies. We should eliminate other sources of variance such as di- chotomization 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 correla- tion between attitudes and behavior was .60 (corrected SD = .20). A chi- square 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 vari- ables. If reliability information is available on each study, then each cor- relation is separately corrected for attenuation. Of the 138 studies used in our meta-analysis, only 55 reported reliabilities of attitude items or pro- vided sufficient information to calculate reliabilities. Reliabilities of be- havior 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 mea- sures.
of subjects 90,808 90,808 90,808 Mean correlation ,473 ,604 ,79 Corrected SD ,141 ,200 Homogeneity
-
chi-square 3,148.6 1 3.755.1 1 -
Note: df= 137.
only a small number of studies reported reliability of the measures, it was impossible to correct each correlation on 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 atti- tudes 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 aver- age reliability of measures with the average number of items. Using the mean number of attitude items ( M = 7.16) and the mean number of be- havior items (A4 = 4.071, we calculated the mean reliabilities for each to be r,, = .84 fo r attitudes, and r,, = .71 for behavior. Using the classic for- mula for correction for attenuation, we calculated the mean correlation between attitude and behavior and found it to be r,, = .79.
havior 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 pop- ulation 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 sepa- rate meta-analyses on the studies within each of the three attitudinal rele- vance subcategories (low match, moderate match, and high match). Hunter et al. (1982) suggested that a moderator variable shows itself in
The results suggest that a strong relationship between attitude and be-
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Journal of Communication, Winter 1993
Table 4: Subgroup Analysis: Degree of Attitudinal Relevance as a Moderator
Low match (df = 22) Number of r ( k ) 23 Total number
of subjects 6,097 Mean correlation .26 Corrected SD .13 Homogeneity
chi-square 138.01
Moderate match (df = 37) Number of r ( k ) 38 Total number
of subjects 11,441 Mean correlation .49 Corrected SD .14 Homogeneity
chi-square 402.15
High match (df= 76) Number of r ( k ) 77 Total number
of subjects 73,270 Mean correlation .49 Corrected SD .13 Homogeneity
chi-square 2,133.60
23
6,097 .31 .15
107.12
38
11,441 .50 .15
453.44
77
73,270 .67 .18
2,166.1 2
23
6,097 .40 .19
38
11,441 .64 .19
77
73,270 .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 reliabil- ities for both attitude and behavior measures (raa = .84; r,, = .71), the correlations were corrected for measurement error also, with these re- sults: requaled .40 for low match, .64 for moderate, and .86 for high). The magnitude of the increase in correlations was quite impressive, lend- ing 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 (SD = .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" K Attitude Behavior
Altruism Deviance Environment Health Group Race Religion Voting Social activity Drug/alcohol Attendance Family planning Blood donation Studying Miscellaneous
Overall
3 22 12 2 4
12 8 8 3
19 4 9 4 3 8
121
.11
.17
.35
.64
.52
.24
.28
.63
.32
.49
.47
.71
.42
.50
-
.42
.65
- .47 .44
.24
.70
.43
.2 1
.46
.32
.5 1
-
.44
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 behav- ior 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 es- timate the average reliability permitted an accurate correction of correla- tions overall and for the match subgroup analysis. However, we decided that the same procedure might not yield accurate correction for attenua- tion, 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 (SD = .17); for behavior reliability, the mean was .44 (SD = .16). In addition, 9 out of the 20 topics had three or fewer studies within a catego- ry. 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-
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 pat- tern. However, this divergence occurred for those topics that had single- study 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 concep- tual 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 aver- age 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 exclud- ed 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 overesti- mate, the true probability is considerably lower than that. Thus for a high or medium level of relevance, the correlation between attitude and be- havior 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 ef- fect of attitudinal relevance.
The behaviors we studied ranged over 19 specified categories and a va- riety 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 varia- tion across topics. Examination of Table 6 shows that for every cell pres- ent, 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 ob- served average across all high-match studies-that is, all were in a region near .86.
Why Others Erred
Using meta-analysis, we found uniformly positive correlations between attitude and behavior with a very high correlation if the attitude was high- ly relevant to the behavior. How could so many narrative reviews and other studies come to the conclusion that attitudes only sporadically pre- dict 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 close- ly 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 signif- icance 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 stan- dard deviation of population correlations was .13. Thus, the standard de- viation 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 con- clude on the basis of personal experience that attitudes do not predict be- havior.
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 nar- rative 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 erro- neous 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 in- terpreted the 50% significance rate to mean that attitudes are related to behavior in only 50% of all settings; causing what was termed “inconsis- tency in the A-B correlation.” This conclusion is also false. Even using the overestimated standard deviation of .19 and assuming a normal distribu- tion 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 at- titudes 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 mea- surement 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 inter- est 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 inconclu- sive as it first appears. The average population correlation between atti- tudes and behavior was quite substantial ( r = .79, corrected for measure- ment 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 indi- vidual 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-
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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 in- vestigation into situational and contextual determinants of behavior is an important area of research, the lack of an overarching theoretical frame- work on contingent consistency hinders our understanding of the A-B re- lationship.
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 rele- vant attitudes should be the fundamental condition for the A-B relation- ship, 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 no- ticeably 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. Accord- ing to our findings, attitudinal relevance is the crucial factor in under- standing the relationship between attitudes and action tendencies. We ob- served 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 or social significance (e.g., having an abortion, smoking marijuana, reenlisting).
The Importance of Construct-Valid Attitude
To summarize, the results of our meta-analyses challenge both the postu- late of contingent consistency and the postulate of no relationship be- tween attitudes and behavior. Neither position adequately describes the ways in which attitudes and actions are linked. Our series of meta-analy- ses offer clear-cut evidence that implies that construct-valid attitudes have directive influence over behavior. Hence, we can unravel the mystery sur- rounding 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 individ- ual’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
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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 be- yond an individual’s voluntary control fall outside the boundaries estab- lished for the A-B problem.
Most communication and persuasion research has centered around at- tempts 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 centrali- ty 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 atti- tudes has important predictive utility. For communication researchers dealing with political and social policy campaigns-who may be interest- ed in knowing whether their efforts to change attitudes will help them achieve their ultimate goal of changing behavior-the answer, under sev- eral constraints, appears to be yes. Specifically, three conditions are nec- essary 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 behav- ioral elements, attempts to influence behavior by means of attitude change must also consider the degree of attitudinal relevance to the be- havior that is t o be changed.
Second, we rnust exercise caution to ensure that the behavior in ques- tion is toward the volitional side of the continuum. That is, we must con- sider (from the subject’s perspective) the circumstantial factors surround- ing 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 do 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 or 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 man- ner, 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
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studies but also to other fields of applied social science, including con- sumer behavior, social policy, public campaigns, and others. Insko and Schopler (1967) have suggested the possibility that much evidence show- ing a close relationship between attitudes and behavioral responses has been obtained but never published because investigators and journal edi- tors have considered such findings “unexciting” and “not worthy of pub- lication.” Our meta-analyses should correct the impression that A-B in- consistency 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 do not have the characteris- tics necessary for demonstrating a substantial positive relation between attitudes and behavior should not be taken as evidence that no such rela- tion exists.
Ever since Gordon Allport (1935) described the attitude concept as the primary building block in the edifice of social psychology, many re- searchers have attempted to clarify the A-B relationship. We have tried to thoroughly explore the research literature on A-B relationships to inte- grate discrepant findings about the strength of such relationships. The re- sults 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 do 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 consisten- cy 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 on 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 be- havioral intentions. Journal of Personality and Social Psychology, 21(1), 1-9.
Ajzen, I . , & Fishbein, M . (1973). Attitudinal and normative variables as predictors of specif- ic 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 re- view 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: Applica- tion of an attitude-behavior contingent consistency model. Journal for the Scientzfic Study ofReligion, 16(3), 263-274.
Albrecht, S., DeFleur, L., & Warner, L. (1972). Attitude-behavior relationships: A reexami- nation 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 con- tingent consistency hypothesis. American Sociological Review, 44, 298-310.
Babrow, A,, & O'Keefe, D. (1984). Construct differentiation as a moderator of attitude-be- havior 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 rela- tionship. 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 be- havior: 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 Com m u n ication, Winter 199.3
In A. G. Greenwald, T. C. Brook, & T. M. Ostrom (Eds.), Psychological foundations of at- titudes (pp. 197-215). New York: Academic Press.
Bentler, P. M., & Speckart, G. (1979). Models of attitude-behavior relations. Psychological Review, KG( 5), 452-464.
analysis. Journal of Personality and Social Psychology. 40(2), 226-238. Bentler, P. M., & Speckart, G. (1981). Attitudes “cause” behaviors: A structural equation
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.ycholo- gy, 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 on deviant behavior in the college context. So- ciometry, 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 So- cialPsychology, 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: An annotated hihliography. New York: Praeger Publishers.
Carr, C., & Roberts, S. (1965). Correlates of civil-rights participation. Journal ofsocial Ps.y chology, 67, 259-267.
change. Journal of Communication, 19, 30-40. Chaffee, S., & Lindner, J . (1969). Three processes of value change without behavior
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 Psy- chology, 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 Opin- ion Qua rtcrly, 3 S , 3 27-334,
rhviclson, A. K . , & Jaccarcl, J. J . ( 1979). Variables that moderate the attitude-behavior rela- tion: Results of a longitudinal survey. ,Journal of I’ersonali[y and Social Psycholqy, .? 7, 1364-1376.
Davidson, A. K. , 8 Morrison, D. M. (1983). Predicting contraceptive behavior from atti- tudes: 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 he- tween 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
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
effects o f attitiidcs on behavior. American Psychologist, 28, 887-891.
narrative comprehension. Cambridge, MA: MIT Press.
Eagly, A. H., 81 Hinimelfarb, S. (1978). Attitudes and opinions. Annual Review ofPsycholo- g.~, 29, 517-554.
Ehrlich, H. J . (1969). Attitudes, behavior. and the intervening variables. The American Soci- ologist, 4(1), 29-34.
Ewens, W. L., & Ehi-lich, €1. I. (1972). Referent-other support and ethnic attitudes as predic- tors of intergroup behavior. Sociological Quarterly, I 3 , 348-360.
Fazio, A. F. (1969). Verbal and overt-behavioral assessment of a specific fear. journal of
Fazio, R. H. (1986). How d o attitudes guide behavior? In R. M. Sorrentino & E. T. Higgins
Consulting and Clinical Psychology, 3.3, 705-709.
(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, atti- tude-behavior consistency, and the strength of the object-evaluation association. Jour- nal of Experimental Social Psychology, 18, 339-357.
attitude-behavior relation: Accessing one’s attitude upon mere observation of the atti tude object. Journal ofPersonality and Social Psychology, 44, 723-735.
Fazio, R. H., Powell, M. C.. & Herr, P. M. (1983). Toward a process model of the
135
Journal of Communication, Winter 1 9 3
Fazio, R. H., Sanbonmatsu, D. M., Powell, M. C., & Kardes, F. R. (1986). On the automatic activation of attitudes. Journal of Personality and Social Psychology, 50(2), 229-238.
Fazio, R. H., &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.
tude-behavior relationship. Journal of Experimental Social Psychology, 14, 398-408.
rect experience and confidence. Journal of Personality, 46, 228-243.
In L. Berkowitz (Ed.), Advances in Experimental Social Psychology, 14, 161-202.
havior. American Sociological Review, 32, 960-970.
overt behavior in different experimental situations. Social Forces, 45, 347-355.
Fazio, R. H., & Zanna, M. P. (1978a). Attitudinal qualities relating to the strength of the atti-
Fazio, R. H., & Zanna, M. P. (1978b). O n the predictive validity of attitudes: The roles of di-
Fazio, R. H., & Zanna, M. P. (1981). Direct experience and attitude-behavior consistency
Fendrich, J. M. (1967a). Perceived reference group support: Racial attitudes and overt be-
Fendrich, J. M. (1967b). A study of the association among verbal attitudes, commitment and
Festinger, L. (1957). A theo y of cognitive dissonance. Stanford, CA: Stanford University
Festinger, L. (1964). Behavioral support for opinion change. Public Opinion Quarterly, 28,
Fishbein, M., & Ajzen, I. (1972). Attitudes and opinions. Annual Review of Psychology, 23,
Fishbein, M., & Ajzen, I. (1974). Attitudes towards objects as predictors of single and multi-
Fishbein, M., & Ajzen, I. (1975). BelieJ; attitude, intention, and behavior: An introduction to the0 y and research. Reading, MA: Addison-Wesley.
behavior. Journal ofApplied Social Psychology, 4, 95-124. Fishbein, M., & Coombs, F. S. (1974). Basis for decision: An attitudinal analysis of voting
Fishbein, M., Middlestadt, S., & Chung, J. (1986). Predicting participation and choice: First- time 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 Fish- bein-Ajzen and the Bentler-Speckart Models. Journal of Personality and Social Psycholo- g ~ , 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 be- tween 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, 17(2 ) , 109-121.
Frideres, J., Warner, L . , & Albrecht, S. (1971). The impact of social constraints on the rela- tionship between attitudes and behavior. Social Forces, 50, 102-112.
Gibbons, F. X. (1975). Sexual standards and reactions to pornography: Enhancing behav- ioral consistency through self-focused attention. Journal of Personality and Social Psy- chology, 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 socialpsy- chology (Vol. 1). Reading, MA: Addison-Wesley.
Green, J . A. (1972). Attitudinal and 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 an attitude scale as a device for predicting behavior. Jour- nal ofApplied Psychology, 40(5), 347-349,
models. Journal ofApplied Psychology, 66(1), 23-39. Hom, P., & Hulin, C. (1981). A competitive test of the prediction of reenlistment by several
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 for dichotomization. East Lansing: Michigan State University, Department of Psychology.
Hunter, J . E. (1990b). METADIRL: Aprogram to do meta-analysis correcting f o r di- chotomization and random error of measurement. East Lansing: Michigan State Universi- ty, Department of Psychology.
Hunter, J . E. (1990~). RELMETA: Aprogram to do meta-analysis of Spearman-Brown relia- bilities. 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 So- cial 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.
conative consistency. Psychology Review, 74, 361-376. Insko, C. A., & Schopler, J. (1967). Triadic consistency: A statement of affective-cognitive-
Jaccard, J . , King, G. W., & Pomazai, R. (1977). Attitudes and behavior: An analysis of speci-
Jackman, M. R. (1976). The relation between verbal attitude and overt behavior: A public
Jackson, G. B. (1980). Methods for integrative reviews. Reviews of Educational Research,
ficity of attitudinal predictors. Human Relations, 30, 817-824.
opinion application. Social Forces, 54, 646-668.
~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 analy-
Kahle, L. R., Klingel, D. M., & Kulka, R. A. (1981). A longitudinal study of adolescents’ atti-
Kelly, S., & Mirer, R. W. (1974). The simple act of voting. ilmerican Political Science Re-
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 compo- nents 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
Larson, C., tk Sanders, R. (1975). Faith, mystery, and data: An analysis of “scientific” studies
Lewis, J. (1980). The relationship between attitudes toward reading and reading success
Linn, L. (1965). Verbal attitudes and overt behavior: A study of racial discrimination. Social
Liska, A. E. (1974a). Attitude-behavior consistency as a function of generality equivalence
sis. Journal of Personality and Social Psychohgy, .? X 3 ) , 315-321.
tude-behavior consistency. Public Opinion Quarterly, 45, 402-414.
view, 68, 572-591.
latent variables. Human Relations, 36(9), 813-826.
of persuasion. Quarterly Journal of Speech, 61, 178-194.
Educational and Psychological Measurement, 40, 261-262.
Forces, 4.3(3), 353-364.
between attitude and behavior objects. Journal of Psychology, 86, 217-228.
American Sociological Rez/iew, 39, 261-272.
on behavior. New York: Academic Press.
Liska, A. E. (1974b). Emergent issues in the attitude-behavior consistency controversy.
Liska, A. E. (Ed.). (1975). The consistency controz)ers.y: Readings on the impact of attitude
Iiska, A. E. (1978). Deviant involvement, associations and attitudes: Specifying the underly-
Liska, A. E. (1984). A critical examination of the causal structure o f the Fishbein/Ajzen atti-
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’ in- pdnt-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 behav- ior. 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-
ing causal structures. Sociology and Social Research, 6.?, 73-89.
tude-behavior model. Social Psychology Quarterly, 4 X l), 61-74.
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.
tudebehauior relationship: Theo y , mcJthodolog,y, and application New York: Academic Press.
Miller, G. R. (1980). Afterword. In D. P. Cushnian Kr R. D. McPhee (Eds.), Messagc-atti-
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 at-
Norman, R. (1975). Affective-cognitive consistency, attitudes, and behavior. Journal of Per-
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 mod-
Ostrom, T. M. ( 1969). The relationship between the affective, behavioral, and cognitive
els. Journal of C‘onszimerResearch, 6: 113-122.
components o f attitude. Journal ofllxperimental Social Psychology, 5, 12-30.
Pagel, M. I]., Kr Ihvidson, A. R. (1984). A comparison of three social-psychological models of attitude and Ixhavioral plan: Prediction o f contraceptive behavior. Journal ofperson- ality and Social~.s.sycholog,y, 47(3), 517-533.
dent juries. Eirropean Journal ofSocia1 I-’sychologly. 6(1), 115-1 18. Perry, R. W. (1976). The effects of apparent guilt and prior attitudes on the verdicts o f stu
Perry, R. W., 8; Gillespie, 11. F. (1976). An analysis o f intervening variables in the
I’omazal, R . J , , & Jaccard, J . .J. (1976). An informational approach to altruistic behavior.
,/ournu1 ofPersonulity 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 rele- vance. European jou rnal qf Social t’syc h olog.y, 1 7, 483-485.
lidity. Journul ofPersonalif-y, 45, 513-527. Pryor, J . B., Gibbons, F., 8r Wicklund, R. A . (1077). Self-focused attention and self-report va-
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 Z ~ Social 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.
Journal of ConsumerResearch, 2, 118-136. Ryan, M. J., & Bonfield, E. (1975). The Fishbein extended model and consumer behavior
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 applica- tion of the theory of planned behavior. Journal of Personality and Social Psychology, 49,
Schuman, H., &Johnson, M. P. (1976). Attitudes and behavior. In A. Inkeles, J. Coleman, &
843-85 1.
N. Smelser (Eds.), Annual Review of Sociology, 2, 161-207.
Schwartz, S. H. (1978). Temporal instability as a moderator of the attitude-behavior rela-
Schwartz, S. H., & Tessler, R. C. (1972). A test of a model for reducing measured
tionship. Journal of Personality and Social Psychology, 36, 715-724.
attitude-behavior discrepancies. Journal of Personality and Social Psychology, 24, 225-236.
Seibold, D. R . (1975). Communication research and the attitude-verbal report-overt behav- ior relationship: A critique and theoretical reformulations. Human Communication Re- search, al), 3-32.
Seligman, C., Kriss, M., Darley, M., Fazio, R. H., Becker, L. J . , & Pryor, J . B. (1979). Predict- ing 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 re- search. Journal of Consumer Research, 15, 325-343.
sistency. Journal of Personality and Social Psychology, 43(2), 210-221. Sivacek, J . , & Crano, W. D. (1982). Vested interest as a moderator of attitude-behavior con-
Smetana, J. G., & Adler, N. E. (1979). Decision-making regarding abortion: A value xex- 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 be- havior. In M. P. Zanna, E. T. Higgins, & C. P. Herman (Eds.), Consistency in social behav- ior: The Ontario Symposium, Vol. 2 (pp. 105-130). Hillsdale, NJ: Lawrence Erlbaum Asso- ciates.
Snyder, M., & Kendzierski, D. (1982). Acting on one’s attitudes: Procedures for linking atti- tude and behavior. Journal of Experimental Social Psychology, 18, 165-183.
sion management. Journal of Personality and Social Psychology, 34(5), 1034-1042. Snyder, M., & Swann, W. B. (1976). When actions reflect attitudes: The politics of impres-
140
Attitude-Behavior Relations: A Meta-Analysis
Speare, A. (1974). Residential satisfaction as an intervening variable in residential mobility. Demography, 11(2), 173-188.
tests of the Fishbein-Ajzen Model. Journal of Social Psychology, 11 7, 183-201.
evaluation of conditions and measurement techniques. Sociomety, 30, 199-213.
ical activity. Public Opinion Quarterly, 31, 103-106.
attitudes. Journal of Abnormal and Social Psychology, 68, 420-430.
sonality and Social Psychology, 40, 780-785.
nal of Social Psychology, 85, 103-109.
intentions, and behavior. Journal of Applied Social Psychology, Cyl), 29-46.
measurement. Rural Sociology, 38, 174-186.
Stutzman, T. M., & Green, S. €3. (1982). Factors affecting energy consumption: Two field
Tittle, C. R., 81 Hill, R. J. (1967a). Attitude measurement and prediction of behavior: An
Tittle, C. R., & Hill, R. J . (1967b). The accuracy of self-reported data and prediction of polit-
Triandis, H. C. (1964). Exploratory factor analyses of the behavioral component of social
Underwood, B., & Moore, B. S. (1981). Sources of behavioral consistency. Journal of Per-
Veevers, J. E. (1971). Drinking attitudes and drinking behavior: An exploratory study. Jour-
Vinokur-Kaplan, 1). (1978). To have o r not t o have another child: Family planning attitudes,
Warland, R. H., & Sample, J. (1973). Response certainty as a moderator variable in attitude
Warner, L . , & DeFleur, M. L. (1969). Attitude as an interactional concept: Social constraint and social distance as intervening variables between attitudes and action. American Soci- ological Review. 34(2), 153-169.
titude-behavior consistency. Journal of Social Psychology, 98, 247-251.
broadening the scope of the behavioral measure. Journal of Personality and Social Psy-
Warshaw, P. R., Calantone, R., &Joyce, M. (1986). A field application o f t h e Fishbein and
Weigel, R. H., & Amsterdam, J. T. (1976). The effect of behavior relevant information on at-
Weigel, R. H., & Newman, L. S. (1976). Increasing attitude behavior correspondence b y
chology, 33, 793-802.
Weigel, R. H., Vernon, D., & Tognacci, L. N. (1974). Specificity of the attitude as a determi- nant 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,
Weissberg, N. (1965). On DeFleur and Westie’s “Attitudes as a scientific concept.” Social
355-360.
Forces, 43, 422-425.
ality and Social Psycholog,y, 36(12), 1375-1390.
young women. ,Journal ofApplied Social Psychology, %6>, 537-547.
responses to attitude objects. Journal of Social Issues, 25, 41-78.
havior inconsistency. Journal of Personality and Socialpsychology, IXl), 18-30.
reason. Reading, MA: Addison-Wesley.
Werner, P. D. (1978). Personality and attitude-activism correspondence. Journal of Person-
Werner, P. D., & Middlestadt, S. E. (1979). Factors in the use of oral contraceptives by
Wicker, A. W. (1969). Attitudes vs. actions: The relationship of verbal and overt behavioral
Wicker, A. W. (1971). An examination of the “other variables” explanation of attitude-be-
Wilensky, R. (1983). Planning and understanding: A computational approach to human
141
Journal of Communication, Winter 199.3
Wilson, T. D., & Dunn, D. S. (1986). Effects of introspection on attitude-behavior consis- tency: Analyzing reasons versus focusing on feelings. Journal of Experimental Social Psy- chology, 22, 249-263.
Wilson, T. D., Dunn, D. S., Bybee, J. A., Hyman, D. B., & Rotonde, J. A. (1984). Effects of analyzing reasons on attitude-behavior consistency. Journal of Personality and Social Psychology, 47, 5-16.
products. Psychological Reports, 29, 893-894.
Zanna, M. P., Olson, J . M., & Fazio, R. H. (1980). Attitude-behavior consistency: An individ- ual 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.
Winters, L. C. (1971). Measuring attitudes and behavior toward ecologically significant
