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Recent Research in Psychology
Seymour L. ZelenEditor
New Models,New Extensions ofAttribution TheoryThe Third Attribution-Personality TheoryConference, CSPP-LA, 1988
With 18 Illustrations
Springer-VerlagNew York Berlin Heidelberg LondonParis Tokyo Hong Kong Barcelona
Seymour L. ZelenCalifornia School of Professional PsychologyLos Angeles CampusLos Angeles, CA 90057USA
Library of Congress Cataloging-in-Publication DataAttribution-Personality Theory Conference (3rd : 1988 : CSPP-LA)
New models, new extensions of attribution theory / the ThirdAttribution-Personality Theory Conference, CSPP-LA, 1988 ; SeymourL. Zelen, editor.
p. cm. - (Recent research in psychology)Includes bibliographic references and index.ISBN-13:978-0-387-97492-7l. Attribution (Social psychology)-Congresses. I. Zelen,
Seymour L. 11. Title. Ill. Series.HM29l.A875 1991302'.12-dc20 90-22660
C1P
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© 1991 Springer-Verlag New York Inc.All rights reserved. This work may not be translated or copied in whole or in part without the wriuenpermission of the publisher (Springer-Verlag New York, Inc., 175 Fifth Avenue, New York, NY10010, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use inconnection with any form of information storage and retrieval, electronic adaptation. computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden.The use of general descriptive names, trade names, trademarks, etc., in this publication. even if theformer are not especially identified, is not to be taken as a sign that such names, as understood bythe Trade Marks and Merchandise Marks Act, may accordingly be used freely by anyone.
Camera-ready copy prepared by the editor.
987654321
ISBN-13 :978-0-387-97492-7 e- ISBN-13 :978-1-4612-3126-4DOl: 10.1007/978-1-4612-3126-4
Acknowledgments
I would like to acknowledge the continuous support of the students and theadministration of the California School of Professional Psychology-Los Angeleswho helped make this series of conferences possible. No book emerges as it isfirst presented. I wish to express my thanks to David Cutler for his .carefulformatting and editing and his dedication in producing this volume and theprevious volume.
Contents
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . v
Attribution Theory: New Models and Applications,an Ongoing Scientific Phenomenon
Seymour L. Zelen .
Wisdom and Humanity:Remarks Honoring Dr. Bernard Weiner
Seymour L. Zelen .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . 4
Self Reflections: The Origins of anAttribution Theorist
Bernard Weiner 7
Attributions as Decisions: A TwoStage Information Processing Model
Craig A. Anderson 12
The Measurement of Attribution Process:Trait and Situational Approaches
Daniel W. Russell . . . . .. .. . . . .. . . ... . . . . . . . . . . . . . . .. . . . . .. . . . . . . . . . . . . . . . . . . . . . . . 55
Existential Versus Causal Attributions:The Social Perceiver as Philosopher
Paul T.P. Wong 84
Perceptions of Success in Work EnvironmentsIrene Hanson Frieze, Mira Moss, andJosephine E. Olson 126
viii
Understanding Close Relationships:An Attributional Perspective
Frank D. Fincham 163
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
Attribution Theory: New Modelsand Applications, an OngoingScientific Phenomenon
Seymour L. ZelenCalifornia School of Professional Psychology,Los Angeles
There is a saying from the Talmud: "There is no one that
does not have a future, and there is nothing that does not have
its hour." It seems to me that this is essentially the message of
the United States and, even more so, the purpose of its
educational institutions. Universities and graduate schools are the
keepers of the established knowledge, but at the same time, they
function to provide new knowledge through research. It is with
this in mind that CSPP-LA has sponsored, and, hopefully will
continue to sponsor, the Attribution-Personality Theory
Conferences. Every learned conference should have at least two
main purposes: (1) to integrate and synthesize existing theoretical
and research positions and (2) by raising questions, offer new
explanations and novel points of view leading to new and useful
directions in the area to which the conference is addressed.
In each of the first two Attribution-Personality Theory
Conferences we have emphasized innovative theoretical thinking,
model building and empirical research. In the present conference
we have continued to work toward these goals. It is my
2
continuing hope that this kind of blend will provide the
stimulation for further imaginative steps and the forum to present
them. But always imaginations must be coupled to a process of
empirical validation. In this present conference, each presentation
puts forward this necessary blend.
It has been said that there is no single, unified "Attribution
Theory" -- only a set of mini-theories tied together by a common
phenomenon, the cognitive-ascriptive process. This level of
integration, or perhaps lack of integration, is often true when the
basic data of the specific area of interest are at a beginning or
entry level. The fact that we are offered, at this conference, a
further number of mini-theories then should not be perceived as a
point against "attribution theory," but rather merely speaks to the
youth and vigor of this approach. In the cycles of investigation
of any science or body of knowledge these mini-theories arise and
seem discrete. Then as more data evolve and more maturity
develops they become increasingly integrated and unified into a
"grander -- if not grand -- theory." So in this conference we are
putting forth a two stage model of the attributional-cognitive
decision process presenting how attributions/explanations may be
primed and then evaluated. Following this we will deal with a
trait versus state dichotomy, an attempt to cope with a long-term
problem in psychology. The third chapter poses another
dichotomy, that of providing meaningful explanations within a
causal context and secondly that of providing existential, perhaps
even cross-cultural explanations of meaning in people attempting
to make sense and/or purpose out of what is happening to them.
3
All of these papers are supported by empirical data, so that
we are not confronted with so much intellectual verbiage, "blowing
in the wind," but rather by dilemmas with empirical solutions
and integration.
In the fourth chapter we can grapple -- along with our
presenter -- with the problems of how the scripts that people
create for themselves (i.e. complex, serial explanations/attributions
developed in advance) dictate or influence subseque'nt outcomes
and our feelings about them. The relation of attribution theory
to script theory is clearly illuminated here.
The final chapter illustrates how attribution theory can be
applied to the problems of couples in marital therapy. All too
frequently in the past, clinicians have worked with patients from a
position based on outcome data rather than from an input
p'!'edictive approach. Our last presenter makes a fresh start using
attributional approaches to marital-couples therapy. Each chapter
presents new issues and new research in examining attributions
from such diverse points of view as existential attributions to
information processing and decision making to examining feelings
of success in terms of corporate scripts in the workplace.
All in all new light will be shed by our participants in
developing their own research.
However, I would like to take an additional moment to say a
few words about our honoree, Dr. Bernard Weiner.
Wisdom and Humanity: RemarksHonoring Dr. Bernard Weiner
Seymour L. ZelenCalifornia School of Professional Psychology,Los Angeles
When I was much younger, and in graduate school, I
published my first article. I was proud of it, and ordered
reprints - with covers - and presented one to my parents. My
mother, whose father had written for the Yiddish papers in Russia
was quite proud and praised me. My father, who was a
businessman, on the other hand asked me what they paid me for
the article. When I replied "nothing," he asked me: "Then why
did you do it?"
We can ask Bernie Weiner, "why did you do it?" many
times over. And the answer, I expect we would get is: "Because
I was interested in finding something out and then informing
others." We have to be very thankful for Bernie's inquiring and
logical mind.
Bernie is not only a prolific researcher, (he has published
extensively, with four books which he has authored and
coauthored and three books which he has edited and contributed
to.) He has also written fifteen chapters in books and published
(as of now) 79 articles. He is a professor of psychology at
5
UCLA and has served as a consulting editor for five
different journals.
It is he, more than anyone else, who has wedded attribution
to motivation. It was he who brought achievement motivation to
the world of attribution theories. It is he who first and most
clearly made the case that explanations do not take place in a
vacuum. Particularly in our culture where achievement is so
valued, ascriptions about behavior take on the added dimension
of the judgement of success or failure (i.e. the value of
achievement and the "worthlessness" of failure).
This enriched viewpoint has been most fortunate for
psychology, particularly for personality theory and clinical
psychology. It, as much as anything else, helped provide the
intellectual substrate for the reformulated theory of learned
helplessness and for a host of other clinical applications. When
Weiner's contributions are added to those of Heider, Kelley and
Jones, we have a straight line of research, inducing attribution
theory to leap the bonds of a laboratory social-psychology into
real-life, personality theory.
Aside from even these major contributions which led directly
to a more comprehensive and better integrated understanding of
the psychology of self-presentation, Bernie Weiner's research and
logical analyses have sparked an interest in another major
dimension of attribution theory, namely intentionality. This in
turn, has influenced research (some of it his own) in excuse
theory and script theory, or how people use excuses to influence
the behavior of others.
6
If Kelly established many of the dimensions of attribution
theory (after Heider) and Jones provided a new perspective for
attribution theory, Weiner established the logic and the
motivational factors in attribution theory, for example when he
along with Dan Russell and David Lerman demonstrated the
emotional consequences of different patterns of attribution.
By developing this pattern or multi-dimensional approach, he
pioneered the way for many of the clinical applications of
attribution theory, as for example the multidimensional approach
of Abramson and Seligman incorporating an attributional approach
in their reformulated theory of learned helplessness.
His has been an original mind which has stimulated countless
others and has produced a host of estimable doctorates and post
doctoral students, of whom we have four on our program. So, as
is the custom from preceding conferences, we honor Dr. Bernard
Weiner for all these things and for much more that may have
been unmentioned, in the knowledge that much more will come in
the future. We now present to you, Bernard Weiner, this plaque
honoring you for showing us the answer to my father's question
not only why you did it, but how to do it.
Self Reflections: The Origins ofan Attribution Theorist
Bernard WeinerUniversity of California, Los Angeles
The attainment of an award provides the occasion for self
reflection, a time to be self-indulgent, and even perhaps the
opportunity to provide guidance to others striving for
accomplishment and recognition. Hence, at this time I would like
to think back autobiographically and reconstruct some of the past
to explain, in my own biased way, what events might have been
responsible for the receipt of this award.
I think I am best known for a 2 x 2 taxonomy of causal
attributions that was presented in 1971 and for my analysis of the
dynamics associated with causal explanations. These related ideas
all originated with the same event that happened to me somewhat
early in my life -- actually, when I was in the 5th grade.
While in the 5th grade, I decided to run for student
government. A number of different positions were being
contested in our class of 25 students. I first considered running
for student president. That had the highest utility, but typically
the president is the most popular student in class. Hence, I
rejected that possibility. Note, then, that already I had decided
8
to embrace Expectancy X Value theory, recognizing that if
expectancy of success is zero, then the action should not, and will
not be pursued.
Next I considered the possibility of vice president. That also
had high utility. Unfortunately, that position is held usually by
the second most popular class member. Guided again by
Expectancy X Value theory, I therefore dismissed that idea also.
Treasurer was next on my hierarchy of desired offices, but that is
held by the most trusted class member, and I had to discard that
thought. Finally, I considered being class secretary. But that
post is held by the person with the best handwriting. Those of
you who know me will immediately understand why I gave up on
that pursuit.
There was one possibility left -- becoming a member of
student council. I reasoned as follows: Each of the offices of
president, vice-president, treasurer, and secretary will be pursued
by two students. This eliminated eight of the most successful of
my peers from seeking to be on the council, and leaving
seventeen class members. Of these, seven are elected to serve on
the council. Quick calculation revealed that my probability was at
least .50 of a victory, and being on the council did have some
prestige and other perqs. I thus threw my hat into the council
member ring. Unfortunately, I lost.
Now, the reader may be wondering what on earth does this
have to do with taxonomies and classifications, and how does this
relate to the dynamics of causal attribution? That is easily
answered. At this time I noticed who was elected president, and
9
knew that this person had received numerous other awards and
plaudits. I also recognized others in my class who had never
been recognized for any of their major or minor accomplishments.
And it then dawned on me that there were two kinds of people
in the world -- those who received honors, awards, social
recognition, and the like, and those that do not. This was my
very first psychological taxonomy, and it came to be during the
fifth grade. It also became clear that, in my classification, I was
included with the non-recipients. This taxonomy, like many of the
later ones in psychology, basically contrasted the "good guys" or
the winners, with the "bad guys" or the losers.
Now, I then asked one of my first attributional questions:
"Why did the winners if fact win, and why did the losers lose?"
And the first answer was that it was deserved. The president, by
virtue of his merits and accomplishments, "should" be president,
and similarly for the vice-president, treasurer, secretary, and the
members of the student government. Antedating Kelley but not
perhaps Hume, I presumed that the covariation between
accomplishments and election results would provide a causal
explanation. But this proved to be incorrect. Close analysis of
the participants revealed that the president indeed deserved his
position, but this was not true of the vice-president nor the
treasurer. Similarly, about on-half of the members of the student
council in my estimation deserved their position, but not the other
one-half. That is, deservingness proved to be entirely independent
of award winning. In this manner I developed my first 2 x 2
taxonomy, which on one dimension included winners and losers,
10
and on the other dimension was anchored with deserved and
not deserved.
It was clear that I was a loser on one of the dimensions, and
another fact was also clear to me -- I deserved to be a winner.
Now, this might now be called "hedonic bias," and in fact I take
credit for discovering the phenomenon while I was in the fifth
grade, in the year 1946, well before the Heider book.
This world-view served me well for more than forty years. It
explained many facts in my environment; it was a very convenient
and useful construct system. And it provided the foundation for
my later attributional work related to taxonomy and dynamics.
But now I am thrown into turmoil. With this award, I have
to change my position in the 2 x 2 table. had assumed that
being a loser was a trait -- it had long-term stability. Now I find
that I am no longer a loser, but actually a winner. I have to
change my construct system, and those of you who are followers
of George Kelly know that any impending change in construct
systems produces threat. And, moving from winner to loser, has
elicited another source of anxiety. Do I really deserve it?
Perhaps some of the readers will find out that the most
complicated statistic I can do is a Chi-Square; they will be told
that I do not know where the computer center is; they will
discover that I write with a typewriter; they will read that my
latest references are in the 70's; and they will learn that I do not.
have plans for a forthcoming research program. That is , I may
have gone from a person who did not deserve to lose to a person
11
who did not deserve to win! I fear I may be uncovered as an
imposter. As you know, this is labeled "The Imposter Syndrome."
I thus have learned that receiving an award has its costs, as
well as its benefits. I have gone from self-righteous indignation
to fear and guilt.
But, I must admit that on balance I prefer the latter state.
I want to thank Sy Zelen and the California School of
Professional Psychology for this award. I feel very happy (an
outcome-dependent affect); increased self-esteem (an attribution to
sustained effort, which also results in the tendency to bask in my
glory); and great gratitude (based on my ascription of success to
my many students and colleagues). Thank you so much, Dr.
Zelen and the Professional School, for providing me this
fine honor.
Attributions as Decisions: ATwo Stage InformationProcessing Modef,2
Craig A. AndersonUniversity of Missouri
Attribution theory is the most important development in
social psychology. This audience hardly needs convincing; for
skeptics all we need to do is to point out the dominance of
attribution articles in the journals, chapters in edited volumes, and
original books. Attribution theory has contributed to our
understanding of traditional social psychology problems such as
attitude change and resistance to change (e.g., Jones & Harris,
1967; McGuire, 1985), impression formation (e.g., Schneider,
Bastorf, & Ellsworth, 1979), helping and altruism (e.g., Bradand &
Lerner, 1975; Meyer & Mulherin, 1980), conformity (e.g., Ross,
Bierbrauer, & Hoffman, 1976), aggression (e.g., Dyck & Rule,
1978; Zillman, 1978), and stereotyping (e.g., Hamilton, 1981).
Less purely social areas have also been influenced by attributional
work. For instance, the literatures on judgment and decision
making (e.g., Nisbett & Ross, 1980), clinical problems (e.g.,
Anderson & Arnoult, 1985a; Arkin & Baumgardner, 1985), and
lThis paper is based on a talk presented at the Third AttributionConference, honoring Bernie Weiner, at the California School of ProfessionalPsychology, Los Angeles, 1988.
2Please address all comments, criticisms, and suggestions to: Craig A.Anderson, Department of Psychology, University of Missouri, Columbia, Mo.
13
memory for traits and behaviors (e.g., Crocker, Hannah, & Weber,
1983) all have benefited by attribution theory. Of course,
attribution theory also has advanced in sophistication and accuracy
from a liberal borrowing of ideas from a variety of areas.
Types of Attribution Models
Normative Models
Much attribution work can be classified as being of one of
three general types. The first is what I call normative models.
These are models of the attribution process that specify how a
rational, accurate attribution process may proceed. In many
instances, such models represent ideal types, or what people
should do for the sake of accuracy. They are prescriptive in
nature. To some extent, they also describe what people can do
under fairly restrictive, special, and ideal circumstances. The
most obvious example of such a normative model comes from Hal
Kelley's work (Kelley, 1967; 1973). Kelley has proposed proper
attributional processes (analogous to the scientist role) for
multiple instance cases (e.g., the covariation principle, the
ANDVA cube) as well as for single instance cases (e.g.,
discoun ti ng, a ugmen ting principles).
The primary role of normative models, in my view, is as
point of comparison for examination of what people really do in a
variety of situations. Deviations from optimal or normative
attribution processes are not to be seen as "defects" for the
models, because nobody (well, almost nobody) ever seriously
believed that people used the normative processed perfectly.
14
Rather, deviations are useful because they tell us where to look
for the actual processes people use. Indeed, "accuracy" may come
about via a variety of processes; biases and errors point the way
to the processes people actually use.
True Process Models
A number of researchers and theorists have occasionally
mistaken normative models for what I call "true process" models.
By process models I mean models of the attribution process
designed to represent how people actually go about making
attributions. Thus, Kelley's ANOVA cube has been interpreted as
a model of what people actually do. Although it is true that the
processes Kelley popularized (Le., covariation detection,
discounting, augmenting) are used by people under some
circumstances, it is equally true that people do no typically think
in the rational way suggested by the model. Other, more
complicated processes are at work.
Three additional types of process models deserve brief
mention here. Jones and Davis 1965; (see also Jones & McGillis,
1976) proposed a theory of correspondent inferences as a model
of how people infer dispositions from behavior. An admittedly
oversimplified summary of this model is that people infer
dispositions that correspond to the observed (and labeled)
behaviors. Thus, aggressive behavior is seen as being caused by
aggressive dispositions. Jim Uleman's work on spontaneous
attributions (Uleman, 1987) confirms that such correspondent
inferences are fairly common and are made quickly and with little
15
effort or awareness. Jones and Davis (and others) have noted a
number of variables that influence this process.
Motivational models posit a direct influence of deep (usually
hidden) motives or needs on the attribution selection process
(Zuckerman, 1979). Unfortunately, such models have usually been
without a theoretically meaningful process, usually relying on a
homunculus (ego) defending itself against threatening information.
Claims that a particular attribution pattern is the result of an
ego-defensive process require proof beyond the circular argument
that the effects defend the ego. Specifically, some theoretical
process is needed, as is independent empirical support for the
process. In my view, neither the process nor supporting data
currently exist. It is clear that self-serving "patterns" of
attributions (i.e., accepting more responsibility for success than for
failure outcomes) may be found in a wide array of situations
(Arkin, Cooper, & Kolditz, 1980; Bradley, 1978). But no clear
theoretical process has been proposed or tested, leaving the
cognition/motivation debate in this area unresolved (Tetlock &
Levi, 1982).
A final type of process model has received relatively little
attention, but warrants development. This is the type called
"Bayesian" decision models (Wetzel, 1982). The key point to
these, one usually ignored by motivational models, is that prior
beliefs influence the current attribution process. Obviously,
people do not compute Bayesian probabilities when making a
decision, but just as obviously, they do take into account the
16
strength of the prior belief as well as the subjective reliability of
the new data for the attributional case at hand.
As is readily apparent, the first two types of attribution
models, normative and true process, overlap considerably. This is
because even the normative models are process oriented. The
distinguishing feature used to tell when a model (e.g., Kelley's, or
a Bayesian one) is being used as a normative one versus as a
true process one lies in whether the scholar involved claims that
the model truly represents what people do, or simply is seen as
similar to what people can and should do.
Effects of Attributions
The third general type of attribution work focuses on the
"effects" of attributions on other variables. Although hUlldreds
(thousands?) of scholars have contributed to this work, one
scholar in particular is identified with this approach -- Bernie
Weiner (1986). Bernie has, of course, contributed much to the
development of process models as well (e.g., Wong & Weiner,
1981), but in my view he has dominated and continues to
dominate the attribution effects scene (along with his many
excellent students, who are well represented at this conference).
The kinds of questions asked by effects scholars are: What types
of attributions do people make (e.g., Frieze, 1976)? What is the
underlying organization or structure of attributions (Wimer &
Kelley, 1982)? and most importantly, What are the effects of
attributions on variables such as affect, success expectancies,
motivation, performance, interpersonal interactions (e.g., Fincham,
17
1985; Weiner, Nierenberg, & Goldstein, 1976; Weiner, Russell, &
Lerman, 1979)?
In short, much progress has been made over the last 30
years (since Heider's seminal work in 1958). This is particularly
true, in my view, for Effects models. We know a great deal
about how people respond to particular attributions for successes
and failures, in both the achievement and the interpersonal
domains. We know when people will get angry, depressed, happy,
proud. We know when they will work harder, quit, or try a
different approach.
However, our understanding of the attribution process itself is
still quite limited. We know that people with different
perspectives will often give different attributions (e.g., actor
observer differences). People with different information sets will
often make different attributions -- this certainly is the major
aspect of actor/observer differences (Eisen, 1979; Monson &
Snyder, 1977). Numerous researchers have proposed that ego
defensive needs directly influence the attribution process, but I
have not yet seen a convincing process model of how motive
manipulations and features influence attributions. In all cases, the
underlying "motives" or motive manipulations produce informational
differences that by themselves are sufficient to account for
observed attributional patterns.
Similarly, Kelley's ANOVA cube describes what people can do
under ideal circumstances. The proposed processes (or more
likely, analogous judgmental heuristics) are sometimes used.
18
In general, though, the model does not describe well how people
actually make attributions.
Correspondent inference theory does little more than describe
a truism relevant to those cases where a person attribution is
being made -- aggressive behaviors are produced by an aggressive
person, not a shy one. To be sure, the theory (and subsequent
data) suggest conditions which promote or preclude correspondent
inferences, but it does not really tell us much about attribution
processes in general (nor was it intended to do so).
Overview of Today's Presentation
My goal today is to describe a process theory of attributions,
and to present a few scattered tests of it. The theory has not
been tested extensively, and several similar versions of it can
account for the results I am going to present. This doesn't
bother me, because all acceptable versions must change radically
the way we look at the attribution process in order to account for
the results. That is, the traditional models (e.g., Kelley's cube,
correspondent inference theory, motivational models) are either
silent on the research questions to be addressed, or they are
contradicted by the empirical data to be presented. Three fairly
common assumptions in particular are contradicted by the theory
and data. First, it has been assumed (almost always implicitly)
that people carry around (in their heads) a list of attributions,
and apply the list to every attributional situation that arises. The
2-stage theory assumes, instead, that people have both specific
and generic knowledge structures concerning various situations and
19
sit.uation types, and that one part of the knowledge structures
consists of a relatively small set of likely causes for the specific
outcome. That is, there is a general causal structure for each
type of situation, and these causal structures differ for different
situations types.
Second, many scholars have assumed that people have deep,
hidden needs that directly influence the attribution process. The
2-stage theory assumes that the attribution process proper (i.e.,
final selection of an attribution) is unaffected by such hidden
needs. However, situational manipulations or features that
activate such vaguely defined motives as ego-involvement, ego
defensiveness, self esteem motives, and so on, change the
information seen as relevant or appropriate to an objective
attributional analysis. Thus, motivational effects occur before the
attribution process, and occur for nonmotivational reasons.
A third common assumption also is contradicted to some
extend, but I haven't thought about it long enough yet to feel
comfortable declaring its overthrow; I also lack sufficiently
powerful data for this task. Nonetheless the assumption is worth
discussing here, for this group is most likely to benefit from
whatever insight I have here, and (more importantly) is most
likely to improve my own thinking on it. Here it is recent
work (sparked again by Bernie Weiner) has noted the importance
of the location of a cause on several dimensions -- locus, stability,
controllability. This dimensional approach assumes that the
location of a cause in multidimensional space determines its
effects; two specific causes sharing the same location should yield
20
the same effects on variables such as success expectancies, affect,
motivation (effort and direction of effort), and performance. My
own work (as well as others) on attributional styles of depressed,
lonely, and shy people has benefited from this dimensional
approach (Anderson & Arnoult, 1985b; Feather, 1983; Seligman,
Abramson, Semmel, & von Baeyer, 1979).
However, people do not think in dimensional terms, unless
asked to do so by some nosy psychologist (there may be two
exceptions to this -- liking and intelligence -- but my own recent
work on implicit personality theory suggests otherwise). People
do not attribute their recent miserable performance on a blind
date to something that is internal, stable and uncontrollable; they
attribute it to their social incompetence. This is not a problem
for the dimensional approach if one regards dimensions as "second
order" concepts useful to scientists (again, as pointed out by
Weiner, and others). The problem, though, is that the kinds of
attributions people make carry more information than the
dimensional locations. Thus, I suspect that one can find
attributions that are located in (essentially) the same place in
multidimensional space, but that have different effects.
As an example, consider two possible attributions for initial
failure at the task of persuading people to donate blood -- lack
of effort, use of a poor strategy. Both attributions are in the
same multidimensional space -- internal, unstable, and controllable.
The primary implication of a lack-of-effort attribution is that one
try harder. The person may try different strategies, or may not.
The strategy attribution, though, implies that one should continue
21
trying hard, and that one should try a different strategy. Thus, if
the task is one in which strategies are both important and non
obvious, the strategy attribution should lead to greater
improvements in performance over time. However, if the task is
one in which effort is important, and strategies are unimportant
or are so obvious that the person selects the best one initially,
the effort attribution should lead to greater improvements. I
hope to have time to discuss this later, but as it is not central to
the 2-stage theory, let's move on now.
Let me summarize this introduction by referring to Figure 1
and discussing it briefly. First, note that Bernie and his students
have contributed to both the attribution process and the
attributional effects sides of this figure. Attribution process
questions include asking when it occurs, how it occurs, and what
the contents or outcomes of the process are. The contents, of
course, are attributions, and the effects of various contents have
been documented across a wide array of important variables such
as success expectancies, motivation, performance quality, and
affect.
FIGURE 1. Attribution Process versus Attribution Effects
Attribution Process
*When*How*CoI\tents
vs. Attributional Effects
Effects of Content on:
*Success Expectancies*Motivation*Performance Quality*Affective Reactions
22
The Two Stage Model
Testing Strategies
My focus today will be on my work concerning how the
attribution process proceeds. There are two ways of testing
process models, as can be seen in Figure 1. Most obviously, one
can assess attributions and other cognitive contents of the process.
In the first three sets of studies to be presented this approach
was used. Alternatively, one can assess the various effects
manipulating process variables to see if and when theoretically
relevant manipulations produce important changes in them. The
second set of studies to be presented used this approach.
The Two Stage Model
Here, then is the two stage model of attributional processing.
I should point out that this model borrows heavily from Arie
Kruglanski's (1980) work on lay epistemological processes.
Problem Formulation. The first stage, problem formulation, is
one in which the causal candidates are generated and information
relevant to testing them is brought to mind. First, a guiding
knowledge structure is selected, based on a variety of criteria
such as its accessibility (salience, chronic usage or recent
priming). It is featural similar to the problem at hand (for
example, only interpersonal knowledge structures will be recruited
for use in explaining an interpersonal outcome), and goal
congruency (two major goals are public self-presentation, which we
are not concerned with today, and private attributions, which are
intended to be accurate). The guiding knowledge structure
23
FIGURE 2. The Two Stage Model of Attribution Processing
Stage 1
Problem Formulation
1. Select AppropriateKnowledge Structure* Accessibility* Featural Similarity* Goal Congruency
2. Collect Information* Past Experiences* Current Situation
Outcome
Stage 2
Problem Resolution
1. Kelley Type Analysis* Covariance* Discounting* Augmenting
2. Bayesian TypeAnalysis
1. Make Attribution or
2. Return to Stage 1 or
3. Abandon Search
contains information about the plausible causes for the specified
outcome (i.e., the causal candidates) and about what further
information is needed to test each of the causal candidates.
24
This guiding knowledge structure also prompts a search for this
additional information, which may come from the person's past
and from the current situation. It is at this stage that I
propose to locate motivational effects. Specifically,
motivational variables influence the kind of information seen as
relevant to the attributional analysis, via activation of various
knowledge structures.
Problem Resolution. At stage two the information gathered
at stage one is assessed via the kinds of processes postulated by
a variety of scholars (though imperfectly). Covariation detection
is done (to the extent possible by the "lay statistician"), the
discounting and augmenting principles come into play (but less so
than would be expected by a perfect judge), prior beliefs and
probabilities are revised (or not). The outcome of all of this
depends upon a variety of factors. If one of the causal
candidates garners enough support, it becomes the attribution. If
not, then one of two things can happen. The process may return
to stage one and begin again, but with a different guiding
knowledge structure. Alternatively, the search may be abandoned.
The amount of time and resources available, as well as the
perceived importance of attributional search will determine which
of these courses will be followed.
This is a bit vague, but two unique points are worth
mentioning. First, the model emphasizes the importance of real
world knowledge brought to bear on the problem by the
attributor. Attributions are not made in a vacuum, but in a
historical context. Second, there are a variety of cognitive
25
processes going on, and a variety of nonnormative effects arise
from these processes. For instance, priming various knowledge
structures or causal candidates will influence the final outcome.
In addition, various cognitive judgmental processes (such as
covariation detection) differ from what a normative model
specifies (Crocker, 1981; Lane, Anderson, & Kellam, 1985).
Empirical Tests of the Two Stage Model
Consideration of this model leads to a variety of unique
predictions. Let's turn to several of these, and to the
relevant data.
Different Causal Structures for Different Situation Types
The first assumption I wish to challenge is that people carry
around one generic list of causal candidates that is used in
different types of situations. Specifically, the two stage model
assumes that people have specific knowledge structures for
different types of situations, and that these knowledge structures
include a small set of plausible causal candidates relevant to the
particular type of situation. In essence, there is a causal
structure of situations that varies from one type of situation to
another. What this means operationally is that if you ask people
to think about a particular type of situation and to generate
plausible causal candidates for the specified outcome (i.e., success
or failure), you will get different lists of causes for different types
of situations. At one operational level this prediction is trivially
true; playing professional sports requires an extremely high level
26
of physical ability whereas conducting original basic scientific
research requires an extremely high level of intellectual ability.
There are two operational levels at which the prediction is
not trivial. First, one can examine the generated causes to see if
different general types emerge for different types of situations.
In the sports and science examples just mentioned, the causes
(extremely high physical and intellectual ability) are of the same
general type, namely, ability. Thus, we can test to see if such
general types of causes are equally likely to be generated as
plausible causal candidates for different types of situations.
Second, one can examine the dimensional location of the
gc:nerated causes to see if generated causes for different types of
situations are differentially located in multidimensional space.
Again, the previous sports and science examples yielded causes
that are located in the same multidimensional space (i.e., internal,
stable, uncontrollable) despite being quite different at a very
specific level. Thus, to test the causal structure prediction in a
nontrivial way one must look at the generated causal candidates
(generated in response to different types of situation) from a
more general perspective, either in terms of types (or clusters) of
causes or in terms of multidimensional space location.
Several years ago I conducted research to examine this
question (Anderson, 1983a). Three groups of subjects participated
in this work. The first group examined four types of hypothetical
situations contained in the Attributional Style Assessment Test
(version I) (Anderson, Horowitz, & French, 1983) -- interpersonal
success, interpersonal failure, noninterpersonal success, and
27
noninterpersonal failure. There were five situations of each type.
These subjects were instructed to generate several plausible causal
candidates for each situation (not attributions). Two researchers
examined these causal candidates and rewrote them into a more
general form, eliminating duplicates. For example, "worked hard
at making friends" became "worked hard." This resulted in a set
of 63 causal candidates, each worded in both a success and a
failure direction (e.g., worked hard; did not work hard).
These 63 (success/failure) causal candidates were typed on
individual cards and presented to a second group of subjects,
whose task was to sort them into similar piles. These similarity
sort data were then subjected to a cluster analysis procedure.
Thirteen clusters, or general types of causes, emerged. This
empirically derived classification scheme was then used to classify
the causes generated by the original subjects in response to the
four types of situations. Specifically, for each type of cause I
examined (via 2 x 2 ANOVAs) the frequency with which it was
generated as a function of the two independent variables of
interpersonal versus noninterpersonal and success versus failure.
The two stage model predicts that general causal types will not
be generated with equal frequency across types of causes. The
results strongly supported this prediction. There were quite a few
main effects and interactions involving the type of situation
variables. Figure 3 shows the interpersonal versus
noninterpersonal main effect results.
28
FIGURE 3. Frequency of Generation of General Causal Types asa Function of the Interpersonalness of the Situation Types
Mean frequency of causes as a function of typeof situation (Range: 0-10)
Causal Clustero 0.5
I1.0
I1.5
I2.0
I2.5
I
Behavioralpre pa ra tion
Effort level
In terperso naltra i ts
Experience &skills
Externalfactors
Generalknowledge
Interpersonalskills & concern
Av.ailability ofItems ofinformation
Charismaticstyle
Intelligence
Physicalattributes
Friendships
*wr~~Wj~~~-8m~fiW
•
I0.5
I1.0
®ill!! Interpersonal situations_ Noninterpersonal situations
ii;~1'~~~M~!liif~~lii~lit~~~~
29
The third group of subjects rated the 63 causes on each of
six causal dimensions, derived from previous attribution work.
Thus, for each causal candidate one could derive scores indicating
its location in multidimensional space. These scores were assigned
for each dimension for each causal candidate generated by the
first group of subjects. Thus, it was possible to see if the
dimensional location of causes differed as a function of the type
of situation that led to its generation. The results of this
analysis also strongly supported the two stage model predication;
there were many main effects and interactions involving the
interpersonal versus noninterpersonal and success versus failure
variables. Figure 4 shows only the interpersonal versus
noninterpersonal main· effect results. Again, the original report
has more detailed results.
In sum, different types of situations do seem to have
different causal structures. Thus, people do not consider the
same set of causal candidates for different types of situations.
This work demonstrates that interpersonal situations differ from
noninterpersonal ones, and that the causal structure of success
differs from that for failure, even for the same task. Obviously,
there are other ways of partitioning situations; I suspect that
many of them would yield comparable causal structure effects.
Causal Structure/Attribution Relation
A second prediction from the two stage model concerns the
effects of causal structure, which is a feature of stage one
processes, on attributions at stage two. Knowing the causal
30
FIGURE 4. Mean Dimensional Location of Causal Candidates asa Function of the Interpersonalness of the Situation Types
Mean dimension of causes as a function of typeof situation (Range:0-9)
Causaldimension
5.0I
5.5I
6.0I
6.5I
7.0I
Changeablity
Locus
Globality
Stability
Intentionality
Con trolla bili ty
I5.0
I5.5
I6.0
I6.5
I7.0
rum Interpersonal situations_ Noninterpersonal situations
structure of a set of situations should allow one to predict the
attributions that will be made for those situations. That is, there
should be a correlation between causal structure and attributions.
A corollary to this involves the different information available for
actor and observer subjects. In general, observers will have less
relevant information than will actors. Thus, observer attributors
are particularly dependent on the causal structure information.
31
Actor attributors, however, tend to have more individuating
information such as their own past performance in past similar
situation. Thus, actor attributors are more likely to reject the
causal structure suggested by the first run through the two stage
process, and are more likely to search for alternative knowledge
structures (with different causal candidates). There is some
evidence in support of this, in terms of processing times to
certain kinds of attributional questions (see Smith, 1984). The
main point here, though, is that actor attributions are expected to
deviate more from the causal structure than observer attributions
because of actors' superior information base.
Both of these predictions were tested in a recent study of
mine (Anderson, 1985). Subjects made attributions for themselves
and for an unknown other person, for each of the hypothetical
situations used in the earlier causal structure research. The
correlations between causal structure of these situations and the
attributions generated for them were computed separately for
actors and observers. As expected, knowing the causal structure
of the situation did allow very good prediction of the attributions,
as shown by the high correlations presented in Figure 5. Also as
predicted, observer attributions correlated significantly higher with
the causal structure than did the actor attributions.
Relocating Motivational Effects
The third prediction to be considered today concerns recent
work on the effects of motivational manipulations. As mentioned
earlier, numerous scholars in this area subscribe to the notion
32
FIGURE 5. Correlation Between Observer and Actor Attributionsand Causal Structure Across Situational Types
Causal structure correlations with actor andobserver attributions
Observer r = .97
Actor r = .88t(diff) = 3.91 .p < .002
that the motivational state of the person can directly influence
the attribution process. That is, an ego-involved person will make
attributions that protect or enhance the ego. In my view, the
motivation/cognition debate in attribution theory has consisted of
two separate patterns. The motivation theorists have
demonstrated a variety of interesting and important effects, such
as the finding that people typically accept more responsibility for
successful outcomes than they do for failure ones. They have
then assumed that the result of this attributional pattern (i.e.,
self-enhancement or protection) is also the cause of it. But no
process, other than some magical, circular, or teleological one, has
been proposed. The cognitive theorists (e.g., Miller & Ross,
1975), on the other hand, have devoted considerable energy to
explaining away the important phenomena discovered by the
motivational theorists, but in nonmotivational terms. Indeed, they
have provided a variety of cognitive processes through which such
seemingly motivational effects occur. For example, people are
more likely to perceive a covariation between their behaviors and
33
success than between their behaviors and failure, primarily because
success is congruent with their intentions, their efforts, and
their expectations.
The most recent motivational paradigm was designed to rule
out such cognitive process differences between the success and
failure situations, by manipulating motivational factors (e.g., ego
involvement) after the success or failure experience has taken
place. For example Miller (1976) had subjects succeed or fail on
a "social perceptiveness" test. Afterwards, they were given
information about the supposed validity of the test in order to
manipulate ego-involvement. High involvement subjects were told
that the test was very valid, had been given to many people, was
used in job candidate selection, and was related to marital
satisfaction and other social perceptiveness type variables. Low
involvement subjects were told that the test was new, hadn't been
given to many people, and didn't seem to correlate with much of
anything. Then, subjects were asked to attribute responsibility for
their performance on the test. Because the ego-involvement
manipulation took place after the outcome feedback, the
informational differences supposedly had been ruled out. Thus, if
the high ego-involvement subjects showed a stronger self-serving
pattern of attributions (i.e., more personal responsibility for
success than failure) than low ego-involvement subjects, the effect
must be due to a motivational impact on the attribution process.
However, this line of reasoning assumes that the cognitive sets of
the two ego-involvement groups will be the same at the time
the attribution process is engaged, an assumption that is
34
demonstrably false. The two state model predicts that the
motivational manipulation changes the knowledge structures
brought to bear on the attributional problem. Specifically, highly
ego-involved subjects are more likely to see their past
performances in related domains as being relevant to the current
analysis. This informational difference, arising from stage one
processes, produces the attributional difference seen at the end of
stage two processes. The model essentially relocates motivational
effects from attribution selection (stage two) to problem
formulation (stage one). Furthermore, it provides a clear process
model for motivational influences, and it is (in my view) a
cognitive one, though I have no strong objection to those who
wish to call it motivational. Figure 6 displays this relocation.
FIGURE 6. Relocating Motivational Variables
Relevant, SalientAvailable, Information
MotivationalVariables
Priva teAttributions
PublicAttributions
Model depicting motivational influences on the attribution process.
MotivationalVariables
SituationalVariables
Relevant, SalientAvailable, Information
IPrivate Attributions r
IPublic Attributions I
Model depicting motivational influences on the informationselection process, both not on the attribution process.
35
The simplest way to test this idea consists of several steps.
First, one must show that motivational manipulations do produce
knowledge structure differences in problem formulation. The best
way is to do this with uninvolved observer subjects, because
obtained informational differences cannot be attributed to ego
involvement. In one such study (Anderson & Slusher, 1986,
experiment 1), I gave observer subjects the same high versus low
ego-involvement instructions used by Miller, though of course, they
were not ego-involved because they did not take the "social
perceptiveness" test and knew they were not going to do so.
They were asked to indicate what kinds of information abcut
another person they would deem useful in interpreting that
person's performance on the test. We predicted that those who
saw the High involvement description of the test would be more
likely to ask for relevant information, such as marital satisfaction.
Next, subjects rated several different pieces of potential
supplementary information for how relevant it would be in
interpreting a target person's performance. Some of the items
were "relevant" (e.g., marital satisfaction); some were not (e.g.,
eye-hand coordination). Figure 7 presents the results. As
expected the so-called ego-involvement manipulation influenced the
knowledge structures used in problem formulation by these
uninvolved observer subjects. High involvement descriptions of
test validity led to more requests of relevant information, and
higher relevance rating of relevant information than did low
involvement descriptions.
36
FIGURE 7. Observer Requests for and Ratings of RelevantInformation as a Function of the Ego-Involvement Instruction Set
Ego-involvement InstructionsHigh Low High-Low
Involvement Involvement Difference
% Subjects Spontaneously 77% 33 % 44 %Requestin~ at least 1Relevant iece of info.
Average Relevance Ratings 7.05 5.86 1.19of Relevant Information
Average Relevance Ratings 3.84 4.27 -.43of Irrelevant Information
In two subsequent experiments we (Anderson & Slusher,
1986) demonstrated that this stage one informational difference
was sufficient to reproduce the exaggerated self-serving pattern of
attributions in observer subjects who made attributions about some
unknown other person. Figure 8 presents the results from one of
these experiments. Because these observer subjects were not
making self-attributions, we concluded that there was no evidence
that the motivation manipulations in this paradigm had any
influence on the stage two attribution process. Rather, motivation
manipulations seem to have their impact on stage one knowledge
structure selection processes.
37
FIG URE 8. Observer Responsibility Attributions
Test Performance
6-Success
4-
AttributedPersonal 2-Responsibility
0-
-2-Failure
ILow
Involvement Information
IHigh
Priming Causal Candidates
The final two predictions I wish to discuss concerning priming
effects. The two stage model suggests that by changing the
knowledge structure used at stage one, the attributions made at
stage two as well as subsequent behaviors may be changed. In
particular, if one makes different sets of causal candidates
available at stage one, and if the candidates available include
truly plausible ones (i.e., they are likely to be accepted at stage
two), then one should be able to influence success expectancies,
motivation, and performance (as well as other variables).
38
Figure 9 presents a simple attributional model of motivation
and performance, with the two stage model detailed as "Generate
Causal Candidates" (stage one) and "Test Causal Candidates"
(stage two). I will not describe the model in detail here, both
because it is fairly self-explanatory, and because more detailed
models of a similar nature have been presented elsewhere by
Bernie, of course, and others (e.g., Anderson & Arnoult, 198?).
My point here is that knowing something about the effects of
various types of attributions allows one to test attribution process
models by manipulating variables designed to influence
attributions, and then measuring various outcome effects. One
could also attempt to measure attributions, but the realistic
situations in which I'm interested tend to elicit public attributions
influenced by self-presentation concerns rather than private
attributions. Thus, we get better tests of the model by looking at
other types of effect variables.
Priming In and Out of Context. The fourth prediction, then,
is that by priming a particular cause (thereby changing the stage
one knowledge structures and causal candidate list) one should be
able to change the performance of people in a given task.
Furthermore, the priming effect should occur in situational
contexts that are very different from the priming situation. For
example, priming someone to attribute failure at a basketball
shooting task to lack of ability should influence reactions of
failure in that task, and to failure in a subsequent interpersonal
task as well.
39
FIGURE 9. Attribution Model, With Attribution Process Detailed
Attribution Process
PerformanceOutcome
Attribution foroutcome
AffectiveReaction
Of particular interest to me is people's performance after
exposure to initial failures at a task. The main reason for this
interest is that many people display self-defeating reactions to
failure, and attributions play an important role in these reaction.
In a recent experiment (Anderson, in preparation), these
priming notions have been tested, though I should note that I
want to replicate the study before concluding the predictions are
entirely confirmed. Subjects performed two tasks. In one they
40
tried to score as many points as possible in one minute in a
basketball shooting task, using a child's basket and a foamball.
Subjects had to shoot with their non-preferred hand, and were
allowed to choose to shoot from one of several places marked on
the floor. The locations had varying point values, and there were
several one minute trials. The second task consisted of preparing
and delivering (on several trials) a one minute TV commercial
designed to persuade people to donate blood to a local blood
bank. In both tasks, subjects received failure feedback on initial
trials. Also, subjects were video taped performing both tasks.
Order of task was counterbalanced across subjects.
The priming manipulation was delivered by a confederate. As
the subject entered the lab, the confederate walked out with the
experimenter. While discussing the task with the experimenter
(whichever one the subject was going to do first), the confederate
mentioned one of three types of causes -- ability, strategy, or
effort. The conversation was staged such that the subject had to
hear it. These three causes were chosen because the effects
literature suggests that they produce clear and different outcomes.
Ability attributions for failure typically produce lower motivation
and performance quality, whereas strategy and effort attributions
typically produce higher motivation and (often) improved
performance. These effects are often context dependent, but
seemed applicable to the tasks at hand. Strategy and effort were
both used as a preliminary test of the notion that dimensional
locations of causes do not capture all the important information
contained in an attribution. Specifically, strategy and effort
41
attributions are located close to each other dimensionally (they
are internal, unstable, controllable). But I expected them to
produce some different effects.
After the subjects completed the first task, the experimenter
primed the cause again, but related it to the first task. Thus,
the primed cause was never mentioned in conjunction with the
second task.
Only two of the various dependent measures are of interest
in the present context. One was a measure of the number of
strategy changes subjects displayed across trials. Even though
effort and strategy attributions are located in essentially the same
multidimensional space, they have slightly different meanings.
Failure attributed to effort should lead to increased effort, and
perhaps to a few strategy changes. That is, trying harder often
involves trying something else, but does not guarantee trying
something else. Failure attributed to use of a poor strategy
should lead to continued high effort, but also guarantees a shift
in method or strategy. Thus, the priming manipulation should
result in more strategy changes in the strategy primed subjects
than in the ability primed subjects, with effort primed subjects
showing an intermediate level of strategy changes.
For each task, strategy changes scores were converted to
z-scores so that an overall analysis could be done. The results,
as shown in Figure 10, confirmed the two stage model prediction
of priming. Furthermore, there were no main or interaction
effects of order (first vs. second task), indicating that the prime
was equally effective even on the out-of-context task.
42
FIGURE 10. Strategy Changes as a Function of PrimingManipulations
0.4-
StrategyChanges(Z-Score
Means)
0.2-
0.0-
-0.2 -
-0.4-
-0.6-+.-- _
Effort Ability Strategy
Attributional Priming Manipulation
The second measure of interest was change in performance
quality. For both tasks, this was measured by dividing the
difference in performance between the late and early trials by the
sum of the late and early trial performances. Positive scores
therefore indicated improvement whereas negative scores indicated
declines in performance.
43
Predictions for the TV Commercial task were straightforward,
based on similar previous work. Strategy subjects were expected
to show the most improvement on this task. Because subjects
typically work very hard at this task, and because the task is
strategy dependent, it was expected that effort subjects would not
show unusually high improvement. Ability subjects also were
expected to show relatively little improvement.
The basketball task is somewhat different, though.
Performance certainly is both strategy and effort dependent. But
the best strategy may be obvious to most subjects -- pick a
distance which allows one to make many shots but not one so
close that the point value is to low. Thus, shifts in strategy may
not help performance much. Effort level is important in the
sense that the faster one recovers the ball the more shots can be
taken. In addition, the more attention one pays to the task, the
quicker one learns to adjust to shooting errors. Thus, effort
subjects were expected to show lots of improvement relative to
the ability subjects. Strategy subjects were expected to show
intermediate levels of improvement.
Note that the two stage model merely predicts that the
priming manipulation would have some reliable effects on
performance. Specific predictions, as outlined above, depend on
the adequacy of the effects models being used. Figure 11
presents the results of the performance improvement measures.
As expected, the strategy subjects showed the most improvement
in the TV Commercial task, whereas the effort subjects showed
the most improvement in the basketball task. These effects were
44
both significant, as were the task by attributional prime
interaction. However, as expected the task order variable did not
interact with the prime and the task variables, suggesting that the
priming effects were essentially the same on both the first and
second task.
FIGURE 11. Performance Changes as a Function of PrimingManipulations.
0.8-
0.6-
Improvementin 0.4-Performance
0.2-
0.0-
TV Commercial Ba ketball
%M Effort_ Ability2m Strategy
One final feature concerning these data also are of interest.
Note that strategy and effort are located in essentially the same
multidimensional causal space (internal, unstable, controllable).
Thus, according to a dimensional approach they should yield the
45
same effects. That they did not do so on either the strategy
change or the performance quality measures suggests that the
specific attributions themselves carry important information (see
also Sujan, 1986). Obviously, one can create more dimensions to
account for such failures of the dimensional approach, but it is
not clear to me how valuable it would be to do so.
Priming Congruent versus Conflicting Causal Candidates. The
fifth and final prediction I want to discuss concerns attributional
style and the interpersonally debilitated. Numerous researchers
have demonstrated that people with various problems in living
such as depression, loneliness, and shyness have different
attributional styles than do their non-debilitated counterparts. In
addition, attributional style differences are particularly pronounced
when assessed for interpersonal failures (e.g., Anderson &
Arnoult, 1985b; Anderson, Horowitz, & French, 1983; Anderson,
Jennings, & Arnoult, 1988). Specifically, people suffering from
these problems in living are relatively more likely to attribute
interpersonal failures to uncontrollable causes such as their lack
of ability or their personality traits, and are relatively less likely
to attribute such failures to controllable causes such as insufficient
effort and use of an ineffective strategy. Indeed, one of the
problems of past motivational models of attribution has been their
inability to account for self-deprecating patterns of attributions
displayed by such clinically troubled groups. A typical
motivational explanation has been to posit a different set of
hidden needs for these people. The two stage model (as well as
research in self-schema theory) suggests that the self-deprecating
46
pattern arises from stage one processing. That is, the knowledge
sets used by depressed people (for instance) are different than
those used by nondepressed.
There are two likely sources of difference at stage one. One
possibility is that the debilitated people have a different and
maladaptive causal structure for the problem situations. The
other possibility is that the causal structures are essentially the
same, but that the self-relevant information (e.g., beliefs, prior
probabilities, recall of past experiences) brought to bear on the
problem is different. Of course, it is also possible that both
are different.
Let us assume, for the moment, that the difference is the
causal structure perceptions. What does the two stage model
have to say about performance and interventions designed to
influence performance in interpersonal settings? Briefly, it
suggests that attributional priming manipulations should have
significant and specific effects on variables such as success
expectancies, motivation, and performance. People with
maladaptive attributional styles for interpersonal failure should be
more adversely affected by initial failures than people with
adaptive attributional styles. Priming adaptive cases should
improve the failure response of people with a maladaptive
attributional style, but should have little impact on people with an
adaptive style. Conversely, priming maladaptive causes should
hurt the performance of people with an adaptive style, but should
have little impact on people with a maladaptive style. This is
because the priming manipulations would affect the knowledge
47
structures and causal candidates lists of subjects only when the
prime "contradicts" the attributional style.
At the moment there are no data on possible differences in
causal structure between people with adaptive versus maladaptive
attributional styles. I do have one relevant priming study, though
(Anderson, 1983). Subjects were preselected for having either a
maladaptive or an adaptive attributional style for interpersonal
failures, and performed an interpersonal persuasion task. Prior to
the task they were assigned to one of three attributional priming
conditions. Some subjects received no prime; these were expected
to perform as a function of their attributional style. Maladaptive
style subjects were expected to have lower success expectancies,
lower motivation, and poorer quality performances than were
adaptive style subjects. Other subjects received adaptive primes.
Specifically, they heard mention of strategy and effort causes as
potential explanations for performance. The remaining subjects
received maladaptive primes, hearing mention of ability and trait
causes. The priming manipulations were embedded in the
experimental instructions, presented quite some time before
task performance.
The task was to persuade people on the telephone to donate
blood to the local blood bank. This is a difficult interpersonal
persuasion task, guaranteeing much failure. Subjects examined
relevant blood bank information and made a (rigged) failure call
in the laboratory. Subsequently, they called from their homes for
a one week period, and then returned to the lab. The three
48
primary dependent measures were success expectancies, motivation,
and performance quality.
On all three measures the predicted results (outlined above)
were obtained. A z-score composite index of these results is
present in Figure 12. Attributional style had a dramatic impact
on performance in the absence of causal primes. It had no
impact in the priming manipulation conditions. In those
conditions, subjects' performances depended upon the causal
primes. Thus, it appears that part of the problem of people
with maladaptive attributional styles lies in their causal
structure of the problem situations. Further work is needed on
this point, however.
Conclusions
To summarize, the two stage model views the attribution
process as a variant of Kruglanski's epistemic problem solving
process. Specifically, the first stage consists of problem
formulation; the second stage consists of problem resolution.
Problem formulation is influenced by a variety of factors,
including the salience or accessibility of relevant guiding
knowledge structures. In stage one a variety of knowledge
structures are brought to bear on the problem, including
information about one's past performance in the domain, one's
expectancies and intentions, and other information from the
present situation. Motivational manipulations and motive levels
have their impact at this stage, by influencing the selection of
relevant knowledge structures. Problem resolution is the actual
49
FIGURE 12. Performance Quality (Z-Score) as a Function ofAttributional Style and Priming Manipulation
StrategyChanges(Z-Score
Means)
0.4
0.3
0.2
0.1
0.0-
-0.1 -
-0.2 -
-0.3 -
-0.4 -
oManipulation
AbilityTrait
StrategyEffort
Attributional Manipulation
mm\ Controllable_ Uncontrollable
attribution process. People do use the various attributional
process proposed by Kelley and others, but do so imperfectly.
For example, people do something like a covariation assessment,
but do so through use of various judgmental heuristics (see the
edited volume by Kahneman, Slovic, & Tversky, 1982).
The main advances of this model are: (a) It takes into
account the knowledge held by the perceiver concerning the past,
the target of the attribution analysis (self or other), situations,
and causes; (b) It relies on demonstrated information processing
effects at the attributional stage, rather than normative principles;
(c) It accounts for motivational variables in testable, process
50
terms; (d) It suggests that people's knowledge about causes goes
beyond dimensional thinking, and thus accounts better for our
intuitions and for our data; (e) It suggests a fairly detailed
account of attributional style problems; and (f) It suggests
practical ways of modifying maladaptive thought processes and
subsequent self-defeating behaviors by modifying the underlying
social cognitions.
Future work will be directed at testing some of the
presently untested predictions, and further specification of the
admittedly vague premises in the present version. Those of you
who have ideas or data relevant to any of this are invited to
share them with me. I would certainly appreciate any assistance
or insight offered.
51
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The Measurement of AttributionProcess: Trait and SituationalApproaches}
Daniel W. RussellCollege of MedicineUniversity of Iowa
Measuring Causal Attribution Processes:
Trait and Situational Approaches
In recent years, increasing attention has been paid to
measurement issues in the context of attribution research.
Comparative analyses of different methods for assessing causal
attributions (e.g., Elig & Frieze, 1979; Russell, McAuley, &
Tarico, 1987) as well as the publication of scales to assess
attribution processes, including attributions for specific events
(Russell, 1982) as well as dispositional tendencies to make certain
types of causal attributions (e.g., Peterson, Semmel, von Baeyer,
Abramson, Metalsky, & Seligman, 1982; Lefcourt, 1981), have
served to improve research methodology in this area.
The development of these new measurement procedures does,
however, pose a conceptual problem for research on causal
attribution process. Fundamentally, researchers have been
lPaper presented at the conference entitled, "New Models - NewExtensions of Attribution Theory to Clinical Uses," Held at the California Schoolof Professional Psychology, Los Angeles, CA, January 30 and February 6, 1988.
56
focusing their attention on two different facets of the attribution.
Some assessment procedures are designed to measure casual
explanations for specific events that have occurred (i.e., the
situational approach), whereas other procedures assess cross
situational tendencies to explain events in a particular way
(i.e., the trait approach). Although both of these approaches
to measurement are clearly relevant to a complete understanding
of the causal attribution process, the relations among the
constructs being assessed in not understood, either theoretically
or empirically.
The purpose of this paper is to examine these two
approaches that have been taken to assessing attribution
processes. Problems that are apparent with each assessment
strategy will be noted, and relations among the trait and
situational measures of attribution processes are examined.
Implications of these findings for models of the attribution process
are discussed, along with recommendations for future research in
this area.
Methods of Assessing Attribution Processes
Three basic methods of assessing causal attribution processes
can be identified from the literature. Two of these methods
involve the assessment of causal attributions for specific events,
and therefore represent a situational approach to measurement.
The third method involves the assessment of dispositional
tendencies to make certain types of causal attributions across
situations, and therefore represents a trait approach.
57
Historically, the first and still most prevalent method of
measurement involves the assessment of specific causal attributions
for events (i.e., ability, effort). A number of different procedures
have been used to assess these causal explanations, including
coding of free response attributional statements, percentage ratings
of the extent to which different causes contributed to the outcome
(that sum to 100%), and independent likert scale rating of the
importance of different causes as determinants of an event. Elig
and Frieze (1979) examined the reliability and validity of these
different methods of assessing causal attributions, and concluded
that independent importance ratings appeared to provide the most
reliable and valid methods of assessment.
A second method of assessing attributions for a specific event
has been developed more recently. Rather than focusing on the
causal attribution the individual has made for an event, this
approach attempts to assess directly how the individual perceives
the cause or causes of an event in terms of the causal dimensions
hypothesized by Weiner (1979, 1985, 1986) to underlie causal
attributions. Russell (1982) has developed the Causal Dimension
Scale as a multi-item measure to assess the causal dimensions
described by Weiner. Other investigators have also attempted to
directly assess causal dimensions, by relying on single item
measures of the causal dimensions.
Both the causal attribution and causal dimension approaches
are situation-specific, being focused on the individual's explanation
for an event that has occurred. The trait approach to assessing
attribution processes attempts to measure cross-situational
58
tendencies to make certain types of attributions for events.
One well-known example of this type of measure is the
Attributional Style Questionnaire developed by Seligman and his
colleagues (Peterson et aI., 1982) as an aspect of their learned
helplessness model of depression. Other dispositional measures of
attribution processes have been developed by Anderson, Horowitz,
and French (1983) and Lefcourt (1981).
These three methods of attribution measurement appear to
highlight different facets of the causal attribution process. Both
the causal attribution and causal dimension approaches focus on
cognitions surrounding a particular event, such as an achievement
outcome. Thus, these two methods of assessment are situation
specific. The attribution and dimension approaches differ,
however, in the level of cognitive processing that is measured.
The causal attribution approach attempts to identify the factor of
factors that the person believes were responsible for the event.
By contrast, the causal dimension approach moves to a higher
level of abstraction, in attempting to assess the dimensional
properties of the cause or causes as perceived by the attributor.
The trait approach to attribution measurement focuses on the
individual's general tendencies to explain events in a particular
manner. As such, it would appear that this approach to assessing
attribution processes is focusing on a construct or constructs that
are antecedent to the person's explanation for a particular event.
One might predict that dispositional tendencies to make certain
types of causal attributions would combine with characteristics of
the situation (e.g., consensus or consistency information, the
59
achievement outcome; see Weiner, 1986) to determine causal
attributions for a specific event. Thus, this approach to
measurement appears to be assessing a distinct aspect of the
attribution process from the causal attribution or causal
dimension approaches.
In the next section, I will discuss the situational approach to
measuring attributions, focusing particular attention on the relation
between causal attribution and causal dimension approaches to
measurement. Following that, the trait approach to measurement
will be discussed, with particular attention paid to the relation
between dispositional tendencies to make certain types of casual
attributions and how the individual explains specific events.
Assessing Causal Attributions for Specific Events
An issue that arises concerning the assessment of causal
attributions for specific events involves the importance of the
cause or causes cited by the attributor versus the dimensional
properties of the cause or causes. Theoretical models of the
attribution process emphasize the dimensional properties of causal
attributions, and not the specific cause arrived at by the
individual in explaining why the event occurred. For example, in
Weiner's (1979, 1985, 1986) attribution model, it is the
dimensional properties of attributions that are viewed as
determining such consequences of the attribution process as
affective reactions and future expectations of success. Similarly,
in research of actor-observer differences in causal attributions, the
focus is on whether the causal explanation is to a facet of the
60
situation or to the person, and not on the specific causal
explanation offered by the actor or observer.
As a consequence of this theoretical focus on causal
dimensions, researchers have attempted to "dimensionalize" the
causal attributions that have been offered by subjects in their
studies. On the basis of the theorized dimensional properties of
specific causal explanations, researchers have classified attributions
into categories (e.g., internal vs. external), and then tested
predictions from models such as Weiner's on the basis of this
categorization of the cause. For example, if an individual cited
"ability" as a cause of his or her success, that attribution would
be categorized by the researcher as representing an internal,
stable, and uncontrollable cause in Weiner's model and, in turn,
certain relationships between that attribution and the individual's
affective reaction to the outcome and expectations of future
success would be predicted.
Two problems with this approach to assessing causal
dimensions can be identified. One difficulty is conceptual. In
Wiener's attribution model, an implicit assumption is that
individuals dimensionalize the causal explanation they have arrived
at, and that this dimensional representation serves in turn to
influence the person's affect and expectations. Weiner's model
suggests that an abstraction process occurs, wherein the individual
develops a representation of the cause in terms of dimensional
properties. Support for this inferred dimensionalization process
comes from multidimensional scaling studies of causal explanations
(Michela, Peplau, & Weeks, 1982; Passer, 1977; Passer, Kelley, &
61
Michela, 1978; Stern, 1983), where dimensions similar to those
hypothesized by Weiner (1979, 1985, 1986) have been found to
underlie how individuals perceive causes. Thus, it appears
that the causal dimensions are not merely in the minds of
attributions researchers, but are also used by subjects to
evaluate causal attributions.
The measurement problem posed by this theoretical
perspective is that the individual's perceptions of causal
attributions may not agree with our theoretical view of the
dimensional properties of specific causes (Russell, 1982; Russell,
tvlcAuley, & Tarico, 1987; Weiner, 1979, 1983). To illustrate this
point, consider the data presented in Figures 1, 2, and 3. These
data come from a study of causal attributions for performance on
a midterm examination (Russell et aL, 1987), where students were
asked to state a causal explanation for their performance and
then indicate how they perceived that attribution in terms of the
locus of causality, stability, and controllability dimensions
described by Weiner (1979, 1985, 1986). The free response
attributional statements were then coded according to which of
eight different causes the statement represented. Dimensional
ratings by students of three of the causes (Le., ability, unstable
effort, and task difficulty) that were cited by at least 10 of the
students in explaining their exam performance are presented in
the figures.
As can be seen in Figure 1, the ratings of the locus of
causality of these causal attributions agree with theoretical
expectations. Ability and effort were both viewed by students as
62
FIGURE 1. Ratings of Causal Attribution on the Locus ofCausality Dimension
27Internal
Locus ofCausality
External3
FIGURE 2. Ratings of Causal Attributions on the StabilityDimension
27Stable
Stability
Unstable3
Ability UnstableEffort
63
FIGURE 3. Ratings of Causal Attributions on the ControllabilityDimension
27Controllable
Controllability 15
Uncontrollable3
Ability UnstableEffort
TaskDifficulty
~l$%mw1'WwJ[o}w!r~!~~I~oow>%mW!!'mfWWWm;tl%?~'Wlf~=~:mm'~aj'\maim~
internal causes, whereas task difficulty was rated as an external
cause. Also consistent with theoretical expectations, ability was
perceived as a stable cause, whereas effort was perceived as an
unstable cause (Figure 2). However, in contrast to theoretical
expectations, task difficulty was viewed by students as unstable.
Finally, as shown in Figure 3 all three causal explanations were
perceived by students as being controllable, including ability and
task difficulty, which are theorized to be uncontrollable causes.
The second difficulty with the traditional approach to
assessing causal attributions concerns the psychometric properties
of the measurement procedures. In a recent paper, Russell et a1.
(1987) examined the reliability and validity of three different
methods of assessing causal dimensions. Two of these methods
involved the assessment of casual attributions cited by the
individual in explaining the event, and then coding these
64
attributions into dimensions based on theorized properties of the
causes. The third approach involved the direct assessment of how
the individual perceived the cause or causes he or she had cited
in explaining the event, using the Causal Dimensions Scale
(Russell, 1982).
One interesting set of findings from this investigation
concerned the reliability of these different methods of assessing
causal dimensions. The free response coding of attributions into
categories was found to be reasonably reliable (Kappa =.76).
Reliabilities of the casual dimension measures based on the
importance ratings of different causal attributions and the Causal
Dimension Scale are presented in Table 1. As can be seen, the
reliability of scores based on the importance ratings of causes was
very low. This was due to the method of calculating these scores.
For example, in computing a locus of causality score, one sums
together the importance ratings of the internal causes and the
ratings of external causes, and subtracts these two values from
each other. These values therefore represent difference scores,
and the equation for computing the reliability of difference scores
given by Lord and Novick (1968) was employed in calculating the
reliability of these measures. The low reliabilities shown in Table
1 resulted from the positive intercorrelation of scores representing
the opposite ends of the causal dimensions, Ranging from .24 to
.41. So, for example, individuals tended to rate both internal
and external causes as being important in determining their
performance, rather than seeing the two types of causes as
65
mutually exclusive. Therefore, it appears that this method of
calculating causal dimension scores is particularly problematic.
Table 1 Reliability of Different Methods of Assessing CausalDimensions
ImKor~ance CausalCausal Dimension atmgs Dimension Scale
Locus of Causality .389 .787
Stability .043 .855
Controllability .079 .511
The reliability data shown in Table 1 for the Causal
Dimension Scale indicates that the locus of causality and stability
subscales are reasonably reliable. For the controllability subscale,
however, the alpha coefficient was quite low, suggesting the need
to improve this subscale. We recently have added four additional
items to the scale that are designed to assess controllability. This
version of the Causal Dimension Scale was administered in a
recent study of causal attributions for midterm exam performance
(to be described in more detail below). where the reliability of
the controllability subscale was found to be much higher
(coefficient alpha = .72).
66
Russell et al. (1987) also conducted a multitrait-multimethod
analysis of the causal dimension measures, comparable to the
analyses reported by Elig and Frieze (1979) for causal attribution
measures. An interesting result from that analysis concerned the
relation between the locus of causality and controllability
dimensions, as estimated in a confirmatory factor analysis across
the three methods of assessment. That correlation, !:. = .928, was
sufficiently high to raise questions regarding the discriminant
validity of measures designed to assess these two causal
dimensions. Table 2 presents results using the Causal Dimension
Scale to assess the locus of causality and controllability
dimensions in three different settings. These studies involved
causal attributions for exam performance (Russell et aL, 1987),
student performance on a mathematics test (Russell et al., 1985),
and feelings of loneliness (Russell, Cutrona, Rose, & Yurko,
1984). As can be seen in Table 2, the relationships among these
causal dimensions vary greatly, ranging from essentially no
relationship in the context of attributions for performance of
another to a relatively strong relationship when explaining
personal performance on a midterm examination. These relations
appear to vary depending on the nature of the causal attributions
made for the event. For example, our coding of attributions for
exam performance indicated that most of the causal attributions
were to effort (e.g., not studying hard enough for the exam) or
task difficulty (e.g., the test was very easy; see Russell et al.,
1987, Table 2). Since students tended to make either internal
and controllable attributions or external and uncontrollable
67
attributions, it is not surprising that these dimensions were
strongly and positively correlated in that study. In conclusion, it
appears from these data across studies that the measures of the
locus of causality and controllability dimensions from the Causal
Dimension Scale are assessing distinct constructs.
Other analyses reported by Russell et aI., (1987) examined
the construct validity of the three methods of assessing causal
dimensions, on the basis of predictions from Weiner's (1979, 1985,
1986) attribution model. Specifically, the impact of the
achievement outcome and expectations of success on the causal
dimensions was tested, as well as the relation between the causal
dimensions and affective reactions to exam performance. Although
none of the methods of assessment provided support for every
prediction from Weiner's model, the general pattern of results
clearly indicated that the direct assessment of the individual's
perception of the dimensions as operationalized by the Causal
TABLE 2 Correlations Between Locus of Causality andControllability
Event
Exam Performance
Student. Performance
Loneliness
Correlation
.lS2C*
QThese data are from Russell, McAuley, and Tarico (1987).df= 128.
bThese data are from Russell et al. (1985). df=77.cThese data are from Russell, Cutrona, Rose, and Yurko (1984).
df=471.*I! < .001.
68
Dimension Scale provided the most valid assessment of the
causal dimensions.
The available evidence therefore suggests the utility of
directly assessing how the individual perceives the causal
attribution for an event in terms of the causal dimensions. As
noted previously, Weiner's attribution model hypothesizes that the
dimensional properties of causal attributions determine the
consequences of the attribution process (i.e., affective reactions
and expectations for future success). Two implications of this
model need to be examined in future studies. First, this model
implies that the causal attribution made by the individual is input
into a dimensionalization process, where the person extracts
certain properties of the cause. Alternatively, the causal
attribution may actually represent an epiphenomenon in the
context of this dimensionalization process. That is, various
determinants of the attribution process (e.g., consensus or
consistency information, dis positional characteris tics; see We iner,
1985, 1986) may directly lead the person to view the cause of an
event as having certain dimensional properties (e.g., reflecting an
aspect of them selves; being stable over time). This information
may be turned to for a possible causal attribution when prompted
by a why question. However, in the absence of such an external
stimulus, a specific causal attribution may not be identified by the
person. Careful information processing investigations are required
to determine the process by which the individual arrives at both a
causal attribution and a dimensional representation of the cause.
69
A second point concerns the impact of causal attributions and
causal dimensions on such consequences of the attribution process
as affective reactions to success and failure and expectations of
future success. Weiner (1979, 1985, 1986) proposes a mediation
model, wherein the causal dimensions are hypothesized to mediate
the effects of the causal attributions on these consequences. To
date, few attempts to test directly this hypothesis have been
reported. Russell and McAuley (1986) found there was some
evidence of direct relations between causal attributions for success
and failure and affective reactions, that was not mediated by the
causal dimensions. An example of these results is presented in
Table 3. Both the specific causal attribution for the outcome and
the dimensional properties of that causal explanation appear to
influence the individual's affective reaction to success and failure.
These findings suggest that either (a) there are direct relations
between specific attributions and the consequences of the
attribution process. or (b) other characteristics or dimensions
underlying causal attributions for success and failure are also
relevant to affective reactions, which need to be assessed. Future
studies need to further examine this mediation question, in order
for us to develop a better understanding of the relation between
causal attributions, causal dimensions, and consequences of the
attribution process.
70
cr~~mmryN$~?~%-:fu~~~m~mE~~m~4:~&w~em~itmgMM&8g~~
TABLE 3 Variation in Affective Reactions to Success and FailureAccounted for by Causal Attributions and Causal Dimensions
Causal Causal JointAffect Attributions Dimensions Effects
Competent .085* .050* .479
Gratitude .101 * .006 .097
Positive Affect .021 * .067* .218
Anger .056* .021 * .137
Guilt .030* .019* .119
Surprise .129* .007 .123
Negative Affect .052* .002 .018
*1! < .05.
Trait Measures of Attribution Processes
The first measure of dispositional tendencies to make certain
types of causal attributions was the locus of control scale
developed by Rotter (1966). This tradition of research can be
traced to the more recent development of domain-specific
measures of locus of control, such as scales to assess health locus
of control (Lau & Ware, 1981; Walls ton & Walls ton, 1980) and
the Multidimensional-Multiattributional Causality Scale (Lefcourt,
1981 ) that is designed to yield locus of control scores for
achievement and affiliative situations.
A second tradition of research on dispositional attribution
tendencies has been inspired by the learned helplessness model of
depression developed by Seligman and his colleagues (Abramson,
71
Seligman, & Teasdale, 1978). These investigators developed the
Attributional Style Questionnaire (ASQ) to assess dispositional
tendencies to perceive the causes of events in a depressive
fashion (Peterson et aI., 1982). Similar instruments have also
been developed by other researchers (e.g., Anderson et aI., 1983).
These attempts to develop dispositional measures of
attribution assume that individuals are consistent across situations
in their explanations of events. This assumption appears
questionable given the general thrust of attribution research within
social psychology. Although some studies have found relations
between personality characteristics (e.g., achievement motivation,
self-esteem) and causal attributions for success and failure
outcomes, a substantial body of literature suggests that situational
characteristics (e.g., achievement outcome, consensus and
consistency information) can greatly influence the causal
attributions made by the individual (see Weiner, 1985, 1986).
Thus, one can question the assumption that individuals will be
consistent across situations in their explanations for events.
Research employing the Attributional Style Questionnaire also
raises questions regarding this assumption of cross-situational
consistency in causal attributions. Cutrona, Russell, and Jones
(1985) conducted a confirmatory factor analysis of responses to
the ASQ, finding only weak evidence of tendencies to make
certain types of attributions across situations. In addition to
factors reflecting the three causal dimensions employed by
Seligman and his colleagues in assessing attribution tendencies
(i.e., locus of causality, stability, and globality), factors reflecting
72
each of the specific situations on the ASQ were found. These
results are shown in Figure 4. These findings are even more
striking given the hypothetical nature of the situations on the
ASQ. Thus, there appears to be evidence of situational specificity
in attributions even for events that have not actually occurred.
In a second study, Cutrona et al. (1985) examined whether
attributional style scores would be predictive of attributions for
negative events. Relations between the attributional style measure
and causal explanations for actual events were very weak,
averaging from .125 for locus of causality to .245 for globality.
These findings have been replicated in a more recent study by
Follette and Jacobson (1987). They examined the relations
between ASQ scores and attributions for failure on a midterm
examination. They found a small but statistically significant
relationship, I (41) .38, 12 < .05.
We have recently completed a study examining trait and
situational determinants of causal attributions, where we examined
the impact of dispositional attribution tendencies on causal
attributions for performance on a midterm examination. Several
weeks prior to their midterm examinations in an introductory
psychology course at the University of Iowa, a sample of 254
students completed a number of different measures, which
included the Multidimensional-Multiattributional Causality Scale
(MMCS) developed by Lefcourt (1981) and the Attributional Style
Questionnaire developed by Peterson et al. (1982). These two
scales were selected since they employ different methods of
assessing dispositional tendencies to make certain types
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74
of attributions. The MMCS instrument assesses the individual's
use of certain causal attributions (i.e., ability, effort, and luck) in
achievement and affiliative situations, whereas the Attributional
Style Questionnaire has individuals rate the causes they cite for
hypothetical events on the causal dimensions of locus of causality,
stability, and globality, Thus, we anticipated that scores of the
first measure of trait attribution would be predictive of causal
attributions made for exam performance, whereas scores on the
ASQ would be predictive of how the individual perceived the
causal attribution in terms of the causal dimensions.
After receiving their grade on the midterm examination,
students were asked to indicate how successful they were on the
examination and to make causal attributions for their performance.
In terms of causal attribution measures, students rated the
importance of eight different causes of their exam performance
and completed the revised Causal Dimension Scale (Russell, 1982)
described earlier. Finally, students reported their affective
reactions to their outcome on the examination on a series of
rating scales and indicated how well they expected to perform on
the final examination in the course.
Table 4 presents the results of analyses examining the
relation between the trait attribution measures and causal
attributions for exam performance. Scores on the dispositional
measures were derived in the following manner. First, for both
instruments we restricted the analyses to items assessing
perceptions of the causes of achievement outcomes. Separate
scores were developed for success and failure outcomes, and a
75
total trait score across success and failure outcomes was also
computed. For the measures of attributions for exam
performance, students were divided into success and failure groups
on the basis of performance ratings, and a total attribution score
across outcome was also computed.
;?t1;~~1m.3~~.J~~~jW~~~~~~g®;~@?tlW&11f.~~~~~mm~tJm}m@~§f:J~:q:~~~Ji
TABLE 4 Correlations Between Trait and Situational Measures ofAttribution
Attribution Failureo Successb Overall'
Ability .192 .069 .114*
Effort -.034 -.059 .047
Luck .446*** .381*** .360***
Causal Dimension
Locus of Causality .116 .083 .092
Stability .312** -.034 -.006
°df=63. bdf= 161. cdf=252.*I!. < .05. **I!. < .01. ***I!. < .001.
The results in Table 4 generally indicated little relation
between the trait measures of attribution tendencies and causal
attributions for exam performance. Considering the relation
between scores on the MMCS and the importance ratings of
different causal attributions, only luck attributions were found to
be related to the trait measure. Individuals who generally tend to
attribute achievement outcomes to luck were also found to rate
that cause as an important determinant of their exam
performance. For the Attributional Style Questionnaire, only one
76
of the correlations with scores on the Causal Dimension Scale was
found to be statistically significant. Individuals who performed
poorly on the midterm examination and who tended to make
stable attributions for failure in response to the hypothetical
situations on the ASQ also perceived the cause of their exam
performance as being stable.
To summarize, these findings in conjunction with the results
of previous studies (Cutrona et aI., 1985; Follette & Jacobson,
1987) suggest that trait measures of attribution tendencies have
little effect on the causal explanations arrived at by the individual
for actual events. The results of these studies pose an interesting
dilemma for attributional models of motivation, such as Weiner's
model of achievement motivation or the learned helplessness
model of depression developed by Seligman and his colleagues.
An assumption made in both of these models is that trait
measures of attributional tendencies should influence motivation
through their effects on the individual's causal explanations for
actual events. Thus, one would predict that (a) trait measures of
attribution would be related to explanations for actual events that
occur, and (b) that causal attributions for these events would
mediate the effects of trait attributions on motivation (e.g.,
affective reactions and expectations of future success). Given that
these trait measures are not predictive of causal attributions for
actual events, we would expect from both of these models to find
that these trait measures are not predictive of motivational
variables. However, these measures do appear to be predictive of
77
such outcomes as depression (Cutrona, 1983) and reactions to
stressful experiences (Lefcourt, 1983).
To illustrate this point, consider the results presented in
Table 5. These data are drawn from our recent study of
attributions for exam performance. For students who indicated
that their performance on the examination was unsuccessful, we
examined the impact of trait and situational measures of
attribution on feelings of depression. A hierarchical multiple
regression analysis was conducted, in which the first set of
variables to enter the equation were the three subscale scores
from the Causal Dimension Scale. After these variables were
entered into the regression equation, the total score from the
Attributional Style Questionnaire was entered into the equation,
which reflects the student's tendency to make internal, stable, and
global attributions for failure.
lr@·~~Jlw.!gm'2:H*:mw,,,*!f%l:Willlffilli$!.W.!\§f&.'iK'm~.@W>W.~1%&%WN'Y~jW'~it,~~PMlmWl~Il:*,1W"~@
TABLE 5 Impact of Trait and Situational Attributions onDepression
Predictor
Locus of Causality
Stability
Controllability
Attributional Style
aJl < .10.*p. < .05.
Beta
.253*
.173
-.009
.214*.044*
78
In combination, the three causal dimension scores from the
Causal Dimension Scale accounted for approximately 11 % of the
variation in depression following failure, E (3, 60) = 2.41, Q. =
.07. As shown in Table 5, only the locus causality subscale was
a statistically significant predictor. The direction of this
relationship indicated that students who made internal attributions
for failure also reported greater depression. After these three
predictor variables entered the equation, the attributional style
score was entered. An additional 4% of the variation in
depression was explained by this variable. As can be seen in
Table 5, individuals who tended to make internal, stable, and
global attributions for failure on the ASQ also reported greater
depression in reaction to failing on their midterm examination.
Thus, these results indicate that the trait measures of attribution
tendencies influenced the level of depression reported by
students over and above the influence of the situational
attribution measure.
To summarize, it appears that trait measures of attributional
tendencies are predictive of such important motivational variables
as affective reactions to events, despite the lack of relationship to
the individual's causal explanations for events. These results pose
an interesting dilemma for attribution-based models of motivation,
since cognitions about the causes of specific events do not appear
to account for the effects of these trait attribution measures.
79
Conclusion
In conclusion, the results of the investigations reviewed in
this paper indicated a need to examine carefully the relations
among trait and situational measures of attribution processes, in
order to develop a more complete understanding of how
attributions influence motivation. Concerning the relation between
causal attributions and causal dimensions, research needs to
evaluate the cognitive processes linking these two sets of
variables. We need to understand how the individual goes from
an explanation for an event to a dimensional representation of
that cause. In addition, the relative influences of causal
attributions and causal dimensions on such motivational
consequences as affect and expectations needs to be better
understood. Do the causal dimensions mediate these relations, or
are there direct relations between causal attributions and the
consequences of the attributions process?
Understanding the process by which trait measures of
attribution processes, such as the Attributional Style Questionnaire
and the Multidimensional-Multiattributional Causality Scale
developed by Lefcourt (1981), influence motivational variables such
as affect and expectations is also an important topic for future
research. In contrast to existing attribution-based models of
motivation, the available evidence indicates that these trait
variables affect motivation through processes that are not
80
attributional in nature. One possibility is that other cognitive
processes, such as self-efficacy cognitions, may be affected by
these trait variables. Clearly, it is an important task for future
research to understand better the role of these trait variables in
motivation, and to attempt to better integrate these factors in
attribution-based models of motivation.
81
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Anderson, C.A., Horowitz, L.M., & French, R. deS. (1983).Attributional style of lonely and depressed people. Journalof personality and Social Psychology, 45, 127-136.
Cutrona, C.E. (1983). Causal attributions and perinataldepression. Journal of Abnormal Psychology, 92, 161-172.
Cutrona, C.E., Russell, D., & Jones, R.D. (1985). Crosssituational consistency in causal attributions: Doesattributional style exist? Journal of Personality and SocialPsychology, 47, 1043-1058.
Elig, T.W. & Frieze, I.H. (1979). Measuring causal attributionsfor success and failure. Journal of Personality and SocialPsychology, 37, 621-634.
Follette, V.M., & Jacobson, N.S. (1987). Importance ofattributions as a predictor of how people cope with failure.Journal of Personality and Social Psychology, 52, 1205-1211.
Lau, R.R., & Ware, J.E. (1981). Refinements in the measurementof health-specific locus of control beliefs. Medical Care, 19,1147-1157.
Lefcourt, H.M. (1981). The construction and development of theMultidimensional-Multiattributional Causality Scales. In H.M.Lefcourt (Ed.), Research with the locus of control construct(VoU, pp. 245-277). New York: Academic Press.
Lefcourt, H.M. (1983). The locus of control as a moderatorvariable: Stress. In H.M. Lefcourt (Ed.), Research with thelocus of control construct: Vol. 2: bevelopments and socialproblems (pp. 253-268). New York: Academic Press.
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Passer, M.W., Kelley, H.H., & Michela, J.L. (1978).Multidimensional scaling of the causes of negativeinterpersonal behavior. Journal of Personality and SocialPsychology, 36, 951-962.
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Stern, P. (1983). A multimethod analysis of student perceptionsof the causal dimensions. Unpublished doctoral dissertation,University of California, Los Angeles.
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Weiner, B. (1983). Some methodological pitfalls in attributionresearch. Journal of Educational Psychology, 75, 530-543.
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Weiner, B. (1986). An attributional theory of motivation andemotion. New York: Springer-Verlag.
Existential Versus CausalAttributions: The Social Perceiveras Philosopher}
Paul T.~ WongTrent University and University of Toronto
During my sabbatical leave at UCLA, Bernie Weiner and I
collaborated on a number of studies on spontaneous attributions.
The paradigm we employed was rather straightforward. Inasmuch
as attributions are answers to "why" questions, we simply asked
subjects to write down the questions or thoughts that came to
their minds in various achievement situations. We wanted to
find out when people ask why questions. We were also interested
in the temporal process and the heuristics of attributional search.
This series of studies was later published (Wong & Weiner, 1981).
The main finding is that given an unexpected or a negative
outcome, individuals tend to ask the following three types
of questions:
(1) Attributional - The subjects ask themselves what causes
the outcome. They entertain various hypotheses in their causal
search, such as Did I study enough? Do I have the ability to do
well? Is the exam too difficult? Is the instructor a hard marker?
IPreparation of this chapter was partially supported by a grant from theSocial Sciences Council of Canada to the author.
85
(2) Coping Appraisal - In the case of an undesirable
outcome, individuals also assess their coping resources and
consider possible courses of action. They ask such question as
What can I do to improve my grade? Should I talk to the instructor?
Who will give me some help on this subject?
(3) Re-evaluation - for wanting of a better label, the term
re-evaluation was used to classify questions which re-examine the
value or purpose of pursuing university education. This type of
questions includes What am I doing here? What is the value of a
university degree? Is it worth my while to spend a few years of my
l~fe in university?
Since then, our findings of spontaneous causal search have
been replicated and extended (Weiner, 1985a; Wong, Delerga, &
Wilson, 1988). However, I am somewhat disappointed that people
have not paid enough attention to the heuristics of attributional
search. This line of research should further our understanding of
the hypothesis-testing strategies.
Our finding on appraisal is probably the first piece of
evidence of spontaneously generated coping appraisal. This
finding supports Lazarus' contention that individuals consider what
can be done when they are confronted with a threat or a
challenge, and such assessment is referred to as secondary
appraisal (Lazarus & Folkman, 1984).
It is rather surprising that very few people have investigated
the relationships between causal attribution and coping appraisal,
because the two processes are closely related. For example,
appraisal of personal coping resources (Is there anything I can do
86
about this problem?) should be linked to internal and controllable
attributions (I am responsible for what has happened. I could have
avoided this problem.)
One of the main assumptions of attribution theory is that
people are motivated to seek causal understanding in order to
predict and control. Knowing what causes a problem would
facilitate the choice of appropriate coping actions. Unfortunately,
the conceptual distinctions between causal attributions and
secondary appraisal have not been articulated and the interactions
between these two variables remain an uncharted territory that
awaits further research.
The third type of spontaneously generated cognitions which
we labeled re-evaluation -- has probably received the least
attention from researchers, but I hope that this situation will
change in the near future. When we first discovered this type of
cognitions, we found it interesting and intuitive, but never gave it
much thought. However, in the past few years a number of
observations have made me realize the tremendous importance of
re-evaluation, which may be more appropriately labeled as
existential attribution. In this chapter, I present some evidence
concerning the role of existential attribution in the achievement
domain and stressful encounters, compare these two kinds of
attributions conceptually and empirically, and propose a model of
existential search.
87
Observations in the achievement domain
Kwong, a visa student from Hong Kong, was very bright and
studious. He maintained a straight A record. Unexpectedly a
mid-night telephone call came from home. He was devastate by
the news that his father had just died of a heart attack. As he
grieved over the untimely death of his father, life lost its
meaning, and education lost its appeal. His grades deteriorated
steadily. Before the end of the school year, he withdrew from
the university and returned to Hong Kong.
Lisa was an intelligent and energetic student. She excelled in
all subjects during her first two years of university. However,
starting in her third year, her performance took a nose dive.
During the mid-year review, which we do at Trent every year with
our students, I asked her why she did so poorly. The answer was
simple: she had just discovered that there was more to life than
getting good grades and she failed to find any meaning in the
"rat race" for high marks. She wanted to spend a couple of years
in Europe traveling before deciding what to do with her life.
There are many such under-achievers and college drop-outs.
In some cases, it is due to a personal trauma, such as breakup of
a romantic relationship or death of a family member. In other
cases, it is simply a matter of realizing that university education
is no longer a meaningful experience for them. If you ask them
about the cause of their poor performance, they can clearly tell
you that it is due to a lack of efforts on their part. But if you
tell them that they should improve their grades by working
harder, they would retort by asking yo:" What for? To what end?
88
Their under-achievement does not seem to have anything to do
with causal attribution, but has everything to do with existential
attribution. They no longer achieve, because they can not find
any good reason for studying hard.
The same kind of existential analysis can also be applied to
over-achievement. Recently, there is considerable interest in the
high levels of academic achievement attained by Asian immigrants.
In the cover story of a recent issue of Time magazine on Asian
Whiz Kids (Brand, 1987), we learn that educators are wondering:
Why do these oriental kids, many of whom are first generation
immigrants with a language handicap, out-perform their North
American counterparts? What enables them to win a
disproportionately large number of prizes and awards? Some
researchers, like Dr. Arthur Jenson and Dr. Philip Ruston, would
argue that Asians are more endowed intellectually. But the most
common explanation is that the oriental students are more
motivated because of their cultural values (Bond, 1986; Leung &
Foster, 1985; Ross, 1977; Sue & Sue, 1973). For example,
Chinese parents place a special premium on education and push
their children for scholastic success (Chenug, 1986; Yeh, 1985).
The impact of Confucius' teaching on filial piety is still evident in
that many Chinese students consider respect for the parents and
family honor as most important (Mak, 1988; Yang, 1986). There
is some empirical evidence that Chinese-Canadian adolescents have
internalized their family value and feel that they would shame
their family if they fail to live up to parental expectations (Mak,
1984). Another source of motivation for the Chinese students is
89
that they perceive a good university education as a necessary
stepping stone towards financial security in a foreign country
(Wong, 1979). In short, Chinese students seem to be under more
external pressure to achieve academically than their majority
peers. These differences in cultural values and individual
ascriptions for the meaning of education seem to be a more
compelling interpretation of the superior Chinese achievement than
differences in causal attribution.
Research on cultural differences in causal attributions has
shown that Chinese students are more likely to make self-effacing
attributions, such as attributing success to luck (Wan & Bond,
1982). This reflects their concern to maintain harmonious
interpersonal relationships (Leung & Bond, 1984; Yu, 1980).
Recently, Mak (1988) has obtained data indicating that both Hong
Kong Chinese students and Canadian Chinese attribute self-failure
to lack of effort, while their Euro-Canadian peers attribute it to
high task-difficulty. Bond (1983) has pointed out that cross
cultural comparisons have been limited by the fact that
attributional categories derived from an individualist culture may
not be relevant to oriental cultures that emphasize interpersonal
harmony. In any event, available findings on cultural differences
in causal attributions between Chinese and Caucasians are neither
robust nor consistent. Research is needed to determine the
relative contributions of causal and existential attributions to
academic achievement.
To illustrate further the relevance of existential attribution in
the achievement domain, we will try to explain the phenomenal
90
economic success achieved by Japan. Experts have been trying to
understand what makes Japan such a formidable competitor in the
world market (e.g., Morishima, 1982; Vogel, 1979). A hypothesis
that has gained considerable currency is that Japanese productivity
is importantly related to their management style, which emphasizes
consensus and the involvement of workers in quality control and
decision making (e.g., Ouchi, 1981; Vogel, 1979). The adversary
model of management vs, labour, which is so prevalent in North
America, is rare in Japan. Big Japanese corporations model after
the traditional family, with management functioning as caring
parents, and workers faithfully carrying out their "filial" duties.
It is a common practice for the Japanese workers to put in extra
hours and sleep in the factory in order to get the job done.
Some experts have advocated that if we adopt the Japanese
management style, productivity should improve. The results of
such experiments have been mixed. For example, in some
Japanese auto plants in America, where the Japanese management
philosophy is implemented, tension between management and
workers has been on the increase. Many workers protest that
they are made to work too hard. Others have reported that
without the protection of a union, workers who complain about
the management are liable to get fired. Therefore, instead of
harmony and high morale, hostility and dissatisfaction creep in.
What has gone wrong? Why is it that the Japanese management
style does not work well in these auto plants in the
American context?
91
The answer has to do with cultural differences in values and
existential attributions. If you were to ask a Japanese worker:
Why do you work so hard? He would probably answer: I want to
do my very best for my company, and for my country. He might
even explain to you that the survival of Japan, and the survival of
his company importantly depend on the quality and productivity of
his work. He believes that what is good for the country and the
company is good for him. If he is assured of anonymity, he may
also mention the external pressure to conform to group norm and
company expectation. The Japanese worker knows the
consequences of putting self-interest above company interests! In
short, his existential attributions would reveal that collective
interests and loyalty to the company are the primary sources of
motivation. Thus, it is not possible to understand Japanese
individual achievement and productivity apart from their collective
orientations (Maehr, 1974; Maehr & Nicholls, 1980).
If you were to pose the same questions to a typical American
worker, his answer would be very different. He would tell you
that he is in it for the money. He has to work hard simply
because of the demand imposed by the boss. He would tell you
that he is more concerned about his own benefit package than the
profit margin of the company. As for his country, sure he is
patriotic, but he believes that what is good for him is good for
the country, and not the other way around. His beginning point
is self-interests. His self-centeredness is further reinforced by the
fact that the objective of most unions is to bargain for maximum
benefits with a minimum of work. These differences in values
92
between Japanese and American workers (e.g., Engel, 1988) are
perhaps the main reason why the Japanese workers are more
productive. Some of these differences have recently been
confirmed empirically. For example, Engel (1988) reports that
American workers place more value on individualism, independence
and self-sufficiency, while Japanese workers place a higher value
on group involvement, loyalty to employer and country.
The above observations suggest that existential attributions,
which are based on cultural and personal values, play an
important role in academic achievement as well as in economic
productivity. Therefore, a viable theory of achievement motivation
should take into account ascriptions of personal meaning for
schooling or work.
One way to contrast causal and existential attribution is in
terms of levels of attributional process. At the surface level, the
social perceiver is concerned with causal attribution, which is
equivalent to Aristotle's sufficient cause (Rychlak, 1976; Taylor,
1967). For example, hard work is the cause of Johnny's school
success, while laziness is the cause of Bobby's school failure.
However, if one wants to pursue why questions even further by
asking: Why does Johnny study hard, while Bobby does not? What
accounts for the difference in motivation? sooner or later one
would resort to existential attribution. Thus, Johnny has a serious
purpose for his studies because he wants to be a medical doctor.
Bobby does not know what he wants to do and cannot find any good
reason for staying in school. At a deeper level, the social
perceiver is concerned with existential or teleological attribution,
93
which is similar to Aristotle's final cause. It serves to explain
the purpose behind the immediate, sufficient cause.
Similarly, the social perceiver may not always go beyond the
level of causal analysis in self attribution. However, when one
becomes disillusioned with education or work, and when causal
analysis fails to provide a compelling reason for further pursuit,
then existential attribution becomes necessary. Further research is
needed to identify the antecedents for existential search in the
achievement domain.
Observations in the domain of stress and coping
A woman in her late fifties is dying of cancer. When she
first learned about this fatal disease, she was troubled by the
thoughts that she might be punished for being a bad person in
the past. Such self-blame is simply a part of the attribution
process aimed not so much at finding the cause of her illness as
searching for the meaning and purpose of her suffering. Initially,
she regarded her illness as a retribution for her past sins. As a
result, her physical pain was compounded by feelings of guilt and
regrets. Eventually, she is able to find relief only when she
comes to accept it as coming from God, who knows what she is
going through, and who will work out His perfect will in her life.
In another case, a professor lost his son, who, on his way
home from school, was brutally murdered by a teen gang. The
parents know the cause of their son's untimely death -- he is one
of the many innocent victims of senseless violence. Yet for years,
they were tormented by obsessive thoughts that the tragedy could
94
have been prevented, had they sent their son to a different
college to study, or had their son come home earlier that fatal
evening. As well, they struggled to find some meaning and
purpose in this tragic loss. They still cannot talk about it
without experiencing the pain. However, he eventually managed
to gain a certain measure of serenity, when he came to accept
the suffering and death are an inevitable part of life, and that to
make something out of life, one must endure pain. He concedes
that one may gain a glimpse of insight, but will never find a
definite answer to the mystery of suffering. After all the struggle
for meaning is an on-going process which will not cease until life
comes to an end. This existential view somehow makes his pain
more bearable and grants him some sense of personal control.
What kinds of existential attribution we arrive at may have
important implications for health and psychological well-being.
For example, in a recent TV interview, the longest surviving AIDS
patient Mr. Turner stated that one of the reasons why he has
survived so long is because that he has a purpose in life; and
that in the struggle against this deadly disease he has found
something worth surviving for.
In the past five years, in my research on successful aging, I
have repeatedly found that those who maintain a relatively high
level of health and happiness are more likely to demonstrate
existential acceptance and affirmation of meaning in coping with
stressful life events (Wong & Reker, 1984; Wong, 1989).
There is now a growing literature which demonstrates that
following a personal crisis, individuals try to make sense of what
95
has happened to them (see Silver & Wortman, 1980 for a review.)
For example, Bulman and Wortman (1977) reported that most of
the spinal-cord injured patients they interviewed asked the
question "why me" and came to some kinds of ascriptions of
meaning. They reported that the only patient who was not able
to answer the question was judged by the staff as coping least
well. They concluded that self-blame was adaptive and that the
patients attributions reflected a need to find some meaning for
their injury. To state that something good had resulted from
their injury was described by Bulman and Wortman as
"reevaluation of the victimization as positive". Although their
conclusion regarding the adaptive benefits of self-blame has been
challenged (Heinemann, Bulka, & Smetak, 1988; Nielson &
MacDonald, 1988), their observations of ascriptions of meaning for
undesirable events have been supported (e.g., Heinemann, et aI.,
1988; Silver, Boon, & Stones, 1983). In a similar vein, Taylor
(1983) has recognized that the search for meaning is a major
cognitive theme in adapting to threatening events. These findings,
together with my own observations, have made me realize that the
quest for meaning is a common reaction to undesirable events,
and that the reevaluation questions triggered by school failure
(Wong & Weiner, 1981) are simply examples of this existential
search. When a tragedy has shattered one's beliefs and sense of
control, a frantic search for meaning is inevitable.
It appears that people's attributional response to undesirable
life events occur at two levels. At one level, people are engaged
in causal search, which will help them to find the cause of their
96
problem and take appropriate actions. At a deeper level, people
are engaged in existential search, which will help them to restore
a sense of meaning and coherence in a time of personal crisis.
In the past few years, an increasing number of studies have
examined whether attributing the cause to one's own behavior
yields adaptive benefits in coping with personal disasters (e.g.,
Affleck, Tennen, Croog & Levine, 1987; Janoff-Bulman & Frieze,
1983; Nielson & MacDonald, 1988; Taylor, Lichtman, & Wood,
1984). I believe that this issue cannot be resolved without
differentiating between causal and existential attributions. It
seems reasonable to assume that self-blame would be adaptive if
the accident were avoidable, and that self-blame would be harmful
if the accident were beyond anyone's control. However, one's
existential answer to the question "why me" may have a great
adaptive significance. The affirmation that the undesirable
serves a higher purpose may yield adaptive benefits regardless
of one's causal attributions. Thus, it is important for the
researcher to examine possible interactions between causal and
existential attributions.
One of the reasons for this neglect is that the conceptual
distinctions between the two types of attributions have not been
fully recognized. For example, Rychlak (1976) has pointed out
that modern attribution theory has been almost exclusively
concerned with sufficient cause. Buss (1978) has criticized that
attribution research has failed to distinguish between cause and
reason and argued that both causes and reasons are required for
an adequate explanation of human behavior. Some of the cases
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involving reason explanations including evaluating and justifying
one's action or stating the goal or purpose of one's action.
Kruglanski (1979) considers that teleological (reason-type)
explanation belongs within the broader attributional domain, and is
one among a vast number of possible explanatory types.
Debate has continued for some time over whether
explanations are always causal, and whether there are more than
one kind of Why questions (Buss, 1979; Harvey & Tucker, 1979;
Fincham & Jaspars, 1980; Jaspars, Fincham, & Hewstone, 1983).
I have just demonstrated that certain observations demand at least
two types of explanation. In the causal type, the social perceiver
is concerned with cause-and-effect analysis, whereas in the reason
type, the social perceiver is concerned with the meaning, purpose
and personal significance of the event.
Fisk and Taylor (1984) have pointed out that the view of the
social perceiver as a naive scientist has overly narrowed the
domain of research. They also propose that future social
cognition research should consider other views of people, "as
fantasizers, ignoring objective reality; as hermits, isolated from the
social environment; as archivists, forever looking backward..."
(p. 417). While these different views of people are indeed valid
and worth pursuing, it may be more fruitful to focus on models
that are applicable to most individuals, such as people as
philosophers, seeking the abstract truth of meaning and purpose;
or people as moralists, striving to decide between right and
wrong. After all, people live not only in a social environment,
they also live in a phenomenological world in which the meaning
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and value of events are measured by subjective experiences.
Furthermore, they inhibit a moral universe, where actions are
evaluated as being ethically right or wrong (Kohlberg, 1984). For
example an individual is concerned not just what can be done
about a problem, but also with "determining what course of action
would best fulfil a moral ideal, what ought to be done in the
situation". (Rest, 1979, p. 561). By entertaining these alternative
models, researchers can gain a better understanding of the
different cognitive processes in the social perceiver.
Existential vs. causal attributions
In this section, I will elaborate on the conceptual distinctions
between existential and causal attributions. Existential attribution
is a subjective, intuitive understanding of the meaning and
significance of events, while causal attribution is a common-sense
explanation of sufficient causes. Examples of existential search
include: Why me? What for? What is the purpose? What good
does it do? What is the use? Why should he die of AIDS at such a
young age? What is the meaning of this tragedy? Examples of
causal search include: What caused it? How did it happen? Who
was responsible for this? What was the cause of death for this young
man? Was this brought about by his own negligence?
Naive scientist vs. lay philosopher. The above two sets of
questions are clearly concerned with different issues. In causal
attribution, people function as a naive scientist. They attempt to
understand their own behavior and that of others in much the
99
same way as a scientist. They test hypotheses, and try to
establish causal relationships. They are concerned with prediction
and control, even though they may not be conscious of such a
motive. As a naive scientist, they intuitively know that without
causal knowledge, it is difficult, if not impossible to predict and
control. The cognitive process involved is a logical, rational
analysis of the cause and effect relationships. This process entails
the use of hypothesis testing. For example, the hypothesis that
one's failure outcome is due to a lack of ability can be tested
empirically. This hypothesis is rejected if one can demonstrate
that one has succeeded many times on a similar task. There are
generally accepted principles and rules which allow one to
determine whether a particular causal explanation is acceptable.
In contrast, the basic assumption of existential attribution is
that within each individual resides a philosopher. This creature
may lie dormant for long periods of time, but always makes his
presence known in time of personal crisis or major transition
points. For those who are prone to self-reflection, philosophical
musings may occur more frequently. But, even for those who are
only interested in sampling small pleasures from day to day, the
philosopher inside them will not simply go away.
The cognitive process involved in existential attribution is
very different from that in causal analysis. Consider the example
of the woman dying of cancer. She can not refer to general
causal rules in her quest for meaning. Nor can she answer the
question "why me" through rational thoughts. It is in the spiritual
realm of faith an prayer and in the philosophical arena of
100
acceptance and reconciliation that she finds her answer. Her
cognitive tools are reflection, review, and even mystical visions.
Her search is guided not by logical analysis, but by personal
values. Indeed, there is no objectively right or wrong answer.
The only criterion is what feels right. The only proof she needs
is whether her ascription of meaning restores a sense of serenity.
And feeling play a much more important role than facts and
logics. It appears that her right brain is more involved than her
left brain in her quest for personal meaning.
The lay philosopher also favours the wholistic approach,
because the meaning of specific events is often derived from
reviewing life as a whole. Events are located in a larger picture,
such as one's past, future or religious beliefs. Only rarely does
meaning reside in an isolated event. At the very least, the lay
philosopher will review the way one's life has been unfolding in
order to reach a sense of coherence.
Perhaps, the two types of attributions can best be contrasted
in the achievement domain. Within the framework of the
"expectancy x value" model of achievement motivation, causal
analysis tells us what to expect. If the cause is stable, then we
have confidence that the same outcome will happen again.
Furthermore, we can predict what will happen, given certain
antecedent conditions. Suppose you know that you have the
ability for a particular task that requires skill and concentration,
then you can expect that the more effort you put in, the greater
the likelihood of success. Similarly, if you know that a particular
outcome is due to chance, and you also know the odds involved,
101
then you are in a good position to predict how likely it will
occur. Thus, causal attribution mediates expectancy.
In the realm of value, causal analysis becomes inadequate.
For example, according to Weiner, value can be reconceptualized
in terms of attribution-specific as well as dimension-related
affective reactions, such as pride or shame. gratitude or guilt
(Weiner, 1985b). It seems reasonable that these feelings should
have some effect on both the quality and the magnitude of
incentive value. For example, a good grade obtained through
cheating would have less subjective value than one obtained
through hard work, because the former evokes feelings of shame.
Although Weiner's analysis of the complex achievement-related
emotions is a significant contribution, it only represents a limited
aspect of the value component of achievement motivation. Surely
value is more than affective reactions. For example, food has
survival value no matter how we feel about it. Some enjoy
eating, some hate eating, but all must eat to survive. Similarly,
the survival value of food is quite independent of one's causal
attribution. Furthermore, value is more than incentive value. We
often assign values on the basis of our needs, beliefs, future plans
and a host of other factors, even before we have the opportunity
to experience the outcome.
In short, Weiner's causal analysis fails to capture the richness
and complexity of the value component in the Expectancy-Value
theory of achievement. Parsons & Goff (1980) have pointed out
that "The most serious problem, in our estimation, with the
traditional achievement model is the omission of incentive value.
102
The question of underlying values, either personal of those
inherent in the task, was not handled in Atkinson's original need
achievement model. Viewed from within the traditional
achievement model, the failure of a highly able individual to
aspire to a high level occupation is incomprehensible." (p.357).
The same criticism can also be applied to Weiner's attribution
theory. Without incorporating the various types of values into
Expectancy-Value formulations (Feather, 1975, 1986, 1988; Parsons,
1982; Parsons & Goff, 1980), we would have difficulties explaining
a wide range of achievement-related phenomena, such as cross
cultural differences, individual differences in choosing a school or
a major, sustained under-achievement and over-achievement.
Existential attribution, as an ascription of meaning, value and
purpose of achievement behavior, appears to be a more powerful
construct than causal attribution in encompassing the different
sources of the value component of the equation. Existential
attribution is inherently value-laden, because any existential
ascription must be derived from some combinations of cultural
values, an individual's global values, as well as the intrinsic values
specific to that activity. In fact, existential attribution in the
achievement context can be regarded as personal values for
education. While causal attribution reflects an individual's
domain-specific knowledge regarding causal relationships, existential
attribution always reflects one's value orientation.
The above conceptual distinctions between causal and
existential attributions are summarized in Table 1.
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Table 1. Differences Between Existential and Causal Attribution
Existential attribution
Social perceiver as alay philosopher
Mainly a reason explanation
A deeper level of processing
Concerned with purpose andmeaning
Reflects cultural andindividual values
Subjective reflections
Focus on the larger picture
Causal attribution
Social perceiver as anaive scientist
Mainly a causal explanation
A surface level of processing
Concerned with prediction andcontrol
Reflects domain-specificknowledge
Ra tional and obj ective analysis
Focus on specific events
Focus on feelings of fulfillment Focus on problem-solving
Primarily future-oriented
Examples
Why me?
To what end?
God took her "home".
Work is the reason(purpose)for my existence.
There is no good reason forcontinuing my study.
Primarily past-oriented
Examples
Who was responsible?
What was the cause?
She died of cancer.
Hard work is responsiblefor my career success.
Lack of motivation is thecause of my failure.
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An empirical investigation of existential and causal attributions in
achievement
These two types of attribution can also be operationally
differentiated and empirically tested. I now turn to a preliminary
empirical study that attempts to provide separate measurements of
causal and existential attributions and assess their role in
academic achievement.
We first identified the major reasons and purposes for
attending university and the values of university education by
soliciting open-ended answers from university students. Their
responses were then summarized and classified into four factors,
resulting in a 14-item Academic Attitude Scale (AAS), which is
shown in Table 2. (This scale has been revised. A copy of the
revised scale is available on request.)
I would not elaborate on the psychometric properties of the
scale at this point, except to state that the scale seems to capture
the major sources of values associated with university education.
Factor A is labeled "Intrinsic Value", because the accent is on the
challenge and the inherent interest of learning. The value is
derived from the activity or the process itself. Like a canoe trip,
the reward is the journey rather than the destination.
Factor B is labeled "Instrumental or Extrinsic Value". This is
similar to the traditional conception of incentive object or utility
value. The reward is what you anticipate at the end of the road.
University education is valued for the benefits and opportunities it
provides in the future. It is a stepping stone to other life goals.
For example, a student is motivated simply because a high grade
105
Table 2. Factors of Existential Attributions for Education
Intrinsic Value
1
1) I find my studies intrinsically interesting.2) The pursuit of knowled~e has value in itself.3) I find university educatIOn challenging.4) What I learn from lecture is mostly trivial. *
Instrument or Extrinsic Value(1) University education is necessary to prepare me for the
competitive working world.(2) The knowledge and skills acquired in university will enable
me to make a useful contribution to society.(3) University education does not contribute to the attainment of
my life goals. *(4) University education has little value to me in real life.*
Personal Growth(I) University education contributes to my personal development.(2) University education helps develop my ability to think
critically and creatively.(3) The discipline and rigor of academic pursuit will make me a
better person.(4) University education does not contribute to the fulfillment of
my potential. *
External Pressure(1) I want to please my parents by doing well academically.(2) I value university education, when I think of how much it
costs me (or my parents).
(* stated in the negative)
point average can open the door of graduate or professional
schools. The instrumental value of university education thus
depends on the totality of future incentives and opportunities that
are contingent on successful completion of undergraduate training.
Factor C is labeled "Personal Growth". Here, the focus is on
personal development -- the stretching of the mind and the
106
building of character. The reward is the process of "becoming".
The benefits that accrue reside in the learner; therefore, they are
less dependent on external circumstances than instrumental values.
Factor D is labeled "External Pressure", because the driving
force comes from outside sources, such as parents. Reward is in
the form of approval from significant others. Negative
reinforcement is also involved here, because achieving good grades
is used as a way of avoiding nagging and other unpleasant
treatments from parents.
Needless to say, these four kinds of existential attributions
serve different functions and reflect different values. For
example, intrinsic value is related to the difficulty value (or
challenge) and inherent appeal of the task. Satisfaction is derived
from "being" and "doing". Maehr & Kleiber (1980) have suggested
that as people grow older, intrinsically satisfying activities may
increase in importance. Thus, intrinsic value may be the primary
motive for a retired person to enroll in university. Personal
growth, although also an internally oriented value, is primarily
concerned with the prospect of achieving desirable changes in
personal attributes through education. The satisfaction comes
from the process of "becoming". Mastery and self-actualization
(Maslow, 1987) would be the primary motive for those who have
moved beyond the concerns for career succes'S. Instrumental value
is related to the number of opportunities of obtaining an incentive
object (Atkinson & Raynor, 1978; Raynor, 1980). This is probably
most relevant to young people. The majority of them would be
107
concerned about getting into the right career and achieving
financial security.
A great deal of research is needed to investigate how these
four types of ascriptions are related to culture, age, sex, and a
wide array of variables, and how these four values differentially
affect achievement-related behaviors, such as persistence, choice,
vigor and affective reactions. It is also important to study the
interactions between causal attributions and these existential
attributions. However, since the effects of these four education
values on academic motivation are all assumed to be positive, it
is predicted that the greater the total score of the Academic
Attitude Scale (AAS), the greater the scholastic achievement.
In this study, the AAS was administered to 75 second year
university students after the midterm examinations, along with Dan
Russell's (1982) Causal Dimension Attribution Scale. They were
asked to explain their mid-term results by using the Causal
Dimension Scale. They were also asked to indicate their expected
final grades. Five months later, we were able to obtain their
actual final grades. The question we are interested in is how
well do existential and causal attributions predict the expected
and the final grades.
Stepwise regressions were performed on the data. The
results indicate that existential attributions are a better predictor
of both expected and actual grades than anyone of the causal
dimensions. In the case of expected grades, the controllability
dimension is the second best predictor. In the case of actual
final grades, the stability dimension is the second best predictor.
108
Surprisingly, internality dimension is not a significant predictor for
both expected and actual final grades.
What this study shows is that both existential and causal
attributions contribute to achievement behavior. Both types of
attributions are needed to gain a better understanding of
achievement motivation. It may be hypothesized that causal
attributions are a getter predictor of affective reactions and
performance shortly following an outcome, while existential
attributions are a better predictor of performance over the long
haul. It is a person's values and purposes that sustain him/her
through changing fortunes and emotional swings. Thus, existential
attributions should be a better predictor of steady state
performance and eventual achievement than causal attributions of
a specific outcome.
Existential attributions can also shed some light on
racial/cultural differences in academic achievement. Several
attempts have been made to explain the discrepancy between
black and white students. Studies have been done both on
student attributions (Graham & Long, 1986) and teacher
attributions (Wong, Delerga, & Wilson, 1988). Most of these
studies fail to show consistent differences in causal attributions.
Perhaps, the lower black performance may be due to
environmental deprivation and the lack of personal meaning for
schooling. Suppose you were brought up in a deprived
environment, where very few people in the neighborhood are
interested in academic pursuit, and very few books can be' found
in your home. Let us further assume that your primary concern
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is how to survive on a day-to-day basis in the concrete jungle.
With this kind of background, you probably would have difficulty
seeing how education can playa meaningful role in your life.
Consequently, you would not be interested in scholastic success.
The perspective of existential attribution also promises new
avenues of intervention. One can devise ways of enhancing
achievement motivation through any combination of these four
types of existential attributions. For example, if a student does
not have a clear goal, and is not at all concerned about what
his/her parents think, then the best strategy is to emphasize
intrinsic interests and personal growth.
The main contribution of the present study is that it not only
operationally defines existential attributions for education, but also
demonstrates that causal and existential attributions can be
measured separately. A great deal of research needs to be
conducted to determine the differences and interactions of these
two types of attributions in various life domains. Possibilities for
attribution therapy are greatly enhanced by taking into account
existential attribution.
A model of existential attribution
The following model is one way to illustrate the complex
process of existential attribution. It is assumed that existential
attributional search is more likely to take place under conditions
of discontent, disaster or disconfirmation, as appraised by each
individual. One can be dissatisfied with life in general, without
being able to pinpoint any specific reason. There are also
110
individuals who have everything, yet have nothing; they discover
that life is more than success, possessions and pleasures, yet they
don't know what is missing. In other cases, discontent may occur
in a specific domain, such as marriage or work. For example,
recently an engineer complained to me that "Everyday, I'm so
tired from working long hours, that I begin to wonder what life is
all about."
Disasters are an especially fertile ground for philosophical
musings. Accidents, major illness, death of a loved one are some
of the common personal disasters. We typically react to trauma
as an noxious foreign object intruding into our own body.
Disasters are as undesirable as they are unexpected, because
we all like to see life go on merrily. When something bad
happens to us or to our loved ones, we would protest vehemently:
Who me? What have I done to deserve that? We would try
desperately to find something positive, something meaningful from
a bad experience.
When our fundamental beliefs are violated, we will also
engage in existential search. Here are come of the examples of
disconfirmation -- believe in a friend, but betrayed by him;
believe in the reward of hard work, but fired by a company that
you have served faithfully; believe in a loving God, but lost your
spouse through a tragic accident... In each of these cases, some
fundamental beliefs that endow our lives with a sense of
coherence are shattered, thus creating an existential crisis.
Once the existential search is initiated, it will continue until
some sort of ascription, whether positive or negative, is reached.
111
This search process is accompanied by heightened tension and
uncertainty. The individual is no longer sure what to believe in,
or what to do. In this state of existential vacuum, anxiety level
should be high and motivational level low.
Existential search is characterized by two parallel but related
processes: the search for meaning and the re-assessing of
priorities. The former involves attempts to find something
positive and purposeful from a bad experience. The main
objective is to find some reassurance that one's suffering is not in
vain, and that something good has resulted from it. For example,
it is not uncommon for parents to take comfort from the thoughts
that the death of their children because of an incurable disease
may contribute to a cure for other children in the future (e.g.,
Chodoff, Friedman, & Hamburg, 1964). It is also common for the
bereaved to seek solace from the belief that God has taken the
child home and it is far better for a child to be in heaven than
to grow up in this terrible world. In this particular example, the
contrast between causal and existential attributions becomes
abundantly clear. The idea that God has taken the child to
heaven is not a causal attribution, because the child's death is
caused by an incurable disease; rather, it represents an attempt to
find a positive ascription for a tragic, untimely death.
It does not matter whether the ascription is based on reality
or a leap of faith, as long as it helps remove troubling thoughts,
resolve cognitive conflicts and restore certain measures of
coherence. Since questions of personal meaning are basically
philosophical (Battista & Almond, 1973; Hocking, 1957) or
112
spiritual (Bianchi, 1982; Soderstrom & Wright, 1977), one often
has to venture into the province of philosophy or religion to find
a satisfactory answer.
The process of re-assessment is inevitable when an individual
has lost something valuable, or when some highly cherished object
has lost its appeal. In either case, there is a vacuum of value
and life purpose. The individual must now find some sort of
replacement. He/she must now glean from all that is available
and see if there is something to fill the void. It is more than an
attempt to clarify one's own value structure. It in fact involves
an active search for some worthwhile goal or purpose that can
rekindle the passion for life.
In the course of re-evaluation, the individual often surveys
the entire landscape, from past achievements, present needs to
distant horizons. The individual would consider various
alternatives, deciding which one is most promising and most
consistent with one's own aspirations.
The above two processes are complementary to each other.
Success in finding a positive ascription of a terrible loss would
lessen its pain, and facilitate the search for a replacement.
Similarly, the process of re-assessment would lessen the urgency
for a positive ascription, if the loss is dev~lued or replaced by an
alternative incentive object. Which of these two processes become
predominant would depend on the antecedents. For example, in
the case of achievement failure, re-assessment may be the major
concern (Wong & Weiner, 1981), whereas in the case of personal
disaster, the search for a positive meaning may be most urgent
113
(Bulman & Wortman, 1977). The complex interplay between these
two processes of existential search offers many possibilities for
empirical investigations.
Existential search is successfully completed, only when an
individual finds a positive explanation for a bad event as well as
worthy goal for living. Here are some examples of affirma tive
ascriptions: "There is a higher purpose in what has happened to me."
"Suffering has made me a much better person." "God has saved me
from the path of self destruction through this tragic event." "Without
the crucible of pain, [ would not have gained this precious insight."
"My life has been completely turned around as a result of this painful
experience." "Now, [ have found a new purpose in my life, and a
new song in my heart." "Out of the ashes of death, [ have become a
new person." "I'm glad that many other people will benefit from the
painful lesson [ have learned." "[ believe that everything will work out
for good for those who love God."
All the above expressions are affirmations of the values of
suffering. Systematic research is needed to identify the main
factors or dimensions of affirmative ascriptions. On the basis of
what is already known from the literature, these factors are likely
to include philosophical "acceptance" of what cannot be changed,
"altruism", "personal growth", "optimism", and "belief in a
benevolent God".
The journey from self-doubts to affirmation is often a long
and agonizing one. But the benefits of positive ascriptions can be
substantial. These include the healing of inner wounds, a sense
114
of coherency and comforts, attainment of ego integrity, zest for
life, and the pursuit and achievement of major life goals.
However, for a variety of reasons, existential search may not
be successful. Following an arduous struggle, the individual may
come to the position of Existentialist thinkers, such as Camus and
Satre. "Nothing makes sense." "Life is absurd." "Life is a bowl of
b,s. " "Life is nothing more than blind fate, even though we like to
think that we have control." "I was born under the wrong star, alld
everything is stacked against me." "I have lost everything, and I don't
see any good reason for living." "It really does not make any
difference whether I live or die."
The above negative ascriptions can also be grouped into
several factors or dimensions. In the absence of systematic
research, I would like to suggest that these factors might include
"indifference", "fatalism", "pessimism", and "helplessness". These
negations are likely to be persistent, resulting in major
dysfunctioning and health problems.
If we feel that we are all like Sisyphus, the Greek hero
condemned by the gods to spend his life rolling a rock up hill
only to find it slipping back, and that all our strivings are futile,
we should be overwhelmed by a sense of despair. "Does life have
any meaning?" Camus once asked; "and, if not, why go on
living?" Thus, against the backdrop of nothingness even death
seems to be an attractive alternative.
The above model of existential attribution, as shown in
Figure 1, can be illustrated by writer Gladys Taber's (1963)
touching account of her inner struggle following the death of Jill,
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Figure 1. An Illustrative Model of Existential Attribution
Antecedents The processes The products Consequences
* Disaster
* Disconfirmation
* Discontent
Searching formeaning andpurpose
Re-assessingprioritiesand life goals
Affirmativeascriptions
Negativeascriptions
* Coherence* Ego integrity* Zest for life
* Confusion* Despair* Depression
her friend and companion of many years. At first life seemed
tohave lost its meaning, and just to maintain the basic functions
of day-to-day living was a struggle, The why questions she
grappled with were existential rather than causal. She was not so
much concerned with the cause of Jill's death as with the meaning
of personal loss. After a long "journey through the night", she
was able to move from questioning to acceptance, from negation
to affirmation. The following is quoted from her book entitled
A flolher Palh.
'''My son and his young wife were only taking a plane tothe place his next job was. Why? Why?'
I do not think anybody can understand why death selectsthis one and passes that one by..... I think trying to explainaway death is futile. At least it did not help me at all. Ihad to begin rather, to find a larger solution. I began withthe universe. I had lived all my life without forming anyopinion as to the nature of God, the meaning of life, thedestiny of mankind. Now I found that I believed in anordered universe. If I believed in an ordered universe, itfollowed there was purpose. And purpose implies God. Heis, because He must be.
My finite mind could never encompass this, but my heartcould understand. Even in the first stage of grief, my heartwas eased when I prayed .....
I do not know, nor ever will, why the pattern of my lifewas shaped as it has been, I do not know why I was
116
destined to walk alone for so long. I no longer ask. Iaccept this as I accept rain and wind and weather. I reachout to live with an open hand .....
I think of all the happy reople in the world and of thesorrowing ones. I am a smal humble part of mankind, nomore important than the smallest fragile shell on the greatbeach. The tide of eternity sweeps in, and life and deathare two halves of one whole. One day we shall understandthe mystery, but not yet. Now we journey with faith,remembering that God said, Let there be light, and there waslight."
Conclusions
What began as a minor finding -- that people question the
value of education after failure - has evolved into an important
construct. I have shown that there are actually two basic types
of attributions - causal and existential, and they complement each
other. In every trying situation, the naive scientist would say,
"What causes this problem? What can I do about it? Let me
tryout a few things. There's got to be a logical solution to this
problem." At the same time, the lay philosopher raises a
different voice: "Why me? What is the meaning of it all? To
what end? What is its significance for me? Is life worth living?
There has got to be a purpose."
We do not always go beyond the level of causal analysis, but
we are more likely to pursue existential questions in personal
crisis. Both the scientist and the philosopher come to our aid as
we face the trials and tribulations of life. The scientist isolates
and analyzes the cause(s) of the problem, while the philosopher
places it against the cosmic backdrop, and reflects on its personal
117
significance. One seeks to solve the problem, while the other
attempts to make the pain more bearable. One tries to increase
the sense of mastery in the individual, while the other tries to
affirm the individual's sense of self-worth and coherence. TheJ
two partners work together side by side to provide a balance
between the left and the right brain, between logic and feelings,
and between reality and vision.
I have also shown that the construct of existential attribution
is useful in integrating findings from several domains, such as
stress research, psychotherapy, and achievement motivation. In
all these situations, the outcome depends importantly on whether
we reach an affirmative or a negative ascription in our
existential search.
The model of the social perceiver as philosopher will
undoubtedly broaden the domain of attribution research and
enlarge our understanding of motivational and cognitive processes.
I have already demonstrated that existential attribution for
education is a better predictor of both expected and actual grades
than causal attribution dimensions. Similar lines of research need
to be conducted in the domain of health, such as cancer patients
and disaster victims. Numerous new questions can be raised
about the complex interactions between existential and causal
a ttributions in various life si tua tions.
There is now growing interest in personal meaning as a
dimension of health (e.g., Adler, 1958; Antonovsky, 1979, 1987;
Chamberlain & Zika, 1988; Erickson, 1964, 1976; Frankl, 1967,
1969; Klinger, 1977; Maddi, 1971; May, 1969; Maslow, 1987; Reker
118
& Wong, 1988; Wong, 1989; Yalom, 1980). The present model of
existential attribution provides a promising approach to the study
of meaning. As a conceptual frame work, it will guide future
research on the complex process of quest for personal meaning
that encompasses antecedents, existential search, ascriptions and
consequences. At present, not much is known about any of these
variables either in isolation or in interaction with each other.
Research on existential attribution promises a fruitful marriage
between humanistic psychology and social cognition.
Some philosophers have argued that the answer to the
question whether life has meaning comes through the
disappearance of the question. Others have suggested that the
fundamental question regarding the meaning of life becomes
irrelevant, when one finds meaning in life through activities
(Hocking, 1957). Regardless of which philosophical position one
takes, the question of meaning will surface whenever discontent or
self-doubt creeps in. Some may try to ignore this question by
becoming totally absorbed in work or pleasure seeking, but the
question will not simply go away. In a civilization which has lost
faith in its own values, the cries for meaning become more
frequent and more urgent (Barrett, 1972). When the excesses of
self-indulgence fail to fill the inner void, when the American
dream turns into a nightmare, people begin 'to wonder what life is
all about. All of a sudden, work becomes a treadmill and life a
burden. In the face of death, all activities seem meaningless.
"How could I find meaning in life? Can anyone give me
something to believe in and something to live for?" they cry
119
in silence. As psychologists do we have an answer to their
existential crisis? Do we dare to venture out of the narrow
confines of familiar paradigms to investigate the most fundamental
question in life?
120
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Chinese collective orientation and need forInternational Journal of Social Psychiatry, 26,
Perceptions of Success in WorkEnvironments
Irene Hanson Frieze, Mira Moss, andJosephine E. OlsonUniversity of Pittsburgh
Before it is possible to make an attribution for the cause of
a particular success or failure event, it is first necessary to define
the event as one that was successfully accomplished or not. This
chapter examines this definitional issue as it occurs within work
settings. Using empirical data from our own research as well as
theoretical work within the domain of social cognition and
organizational behavior, we examine the ways people describe the
successes they encounter at work and the steps they feel they
must take to become successful. The chapter concludes with
suggestions for expanding attributional process models to consider
organizational success perceptions and how the interact with
individual conceptions.
Definitions of Success and the Attribution Process
Since the publication in the early 1970's of the work of
Weiner and his colleagues (Weiner, Frieze, Kukla, Reed, Rest &
Rosenbaum, 1971), it has been widely accepted that people do
react to success and failure experiences in cognitive as well as
emotional ways (Weiner, 1985a). Research has shown that people
127
use information about the situation in which they have
participated to form an explanation for the outcome they have
experienced. This explanation is the causal attribution for the
particular success or failure. Once this attribution is made, it has
certain predictable emotional and behavioral consequences
(Weiner, 1985b).
Much of the large body of work supporting this theory of
attributions for success and failure has been done in the
laboratory, although there are increasing numbers of applications
in real world settings (Antaki & Brewin, 1982; Frieze, Bar-Tal, &
Carroll, 1979). The laboratory studies of attributions often rely
on manipulations of success and failure. Three common
techniques are used to do this: (1) simply telling subjects that
they had succeeded or failed after working on a task; (2) giving
subjects (fictitious) norms about the performance levels of other
students that allowed them to label their performance as high or
low on the basis of social comparison: or (3) arranging a task so
that the objective performance was either very good or very bad.
After doing a number of studies involving manipulation of
success and failure, Frieze and her students became concerned
about the validity of such procedures. One of Frieze's studies
(Elig & Frieze, 1979) demonstrates the problems. In this study,
students were randomly assigned to a "success" group or a
"failure" group on the basis of the anagrams they were asked to
do (procedure 3 from the above list). Some of these subjects
received problems that had previously been found to be easy
while others were given apparently similar, but actually
128
insolvable problems. Thus, by giving subjects very hard or very
easy problems that did not appear on superficial scanning to vary
on difficulty level, we were causing them to do well or poorly on
the task. We intensified the manipulation with the addition of
social comparison information (procedure 2). After working on
the anagrams for a timed period, subjects were given norms about
how well other college students did on the task they had just
done. The norms were rigged so that the "success" group
performed better than 75% of other college students. The
"failure" group was clearly lower than 75% of other students on
the basis of their performance. Subjects were expected to use
this normative information in addition to their own performance
levels to evaluate their own level of performance as a success or
failure. In spite of the strong manipulations used, we found that
not all of our subjects placed them selves in the assigned group
in our manipulation check question. Of the original 250 students
in the study, about 20% did not rate themselves "correctly" as
succeeding or failing when asked how successful they had been on
the anagram task.
Another of Frieze's studies demonstrates this same lack of
correspondence between the objective event and the subjective
labeling of the event. As part of a larger study of the
attribution process as it actually functions in the classroom.
Frieze, Snyder & Fontaine, 1978) asked fifth graders to evaluate
their performance on either a social studies or a mathematics
exam. The correlation between the subjective success ratings and
the actual score was .74. Although this is a rela tively large
129
correlation, it is sufficiently below 1.00 to suggest that subjective
success ratings are influenced by a variety of factors in addition
to objective performance. Other analyses indicated that students
who actually performed at a high level (high objective score) saw
themselves as exerting much effort, whereas those who perceived
themselves as most successful (regardless of their objective scores)
rated their ability relatively high.
A plausible explanation for this lack of correspondence
between objective and subjective appraisals of success is that
people have many ways of defining success. For the student who
is pleased with a "C" grade, even being close to 75% of other
students may have been seen as success. For the superior
student, being just above 75% of other students may have been
defined as a failure. Students may reject the experimenter's
outcome label for other reasons as well. Social comparison is
only one of many criteria used to determine whether one has
been successful. Comparison with one's past level of performance
or comparison with one's expected performance level may be more
important than comparison with everyone in a large group.
Others may feel successful if they managed to perform adequately
in spite of barriers such as being sick (Frieze et aI., 1983).
Along with variations in the criteria used to decide whether a
performance is a success or not, there are also differences in the
activities one associates with success. Meece and Frieze (1982)
surveyed 80 fifth and sixth graders and 111 undergraduate
psychology students, asking them to complete the sentence "I was
very successful when " (elementary school students) or
130
"Describe a time when you felt successful." Answers to these
open-ended questions were coded for the type of activity
described and the criteria used to determine success. Academic
activities made up less than half of the success experiences
described. An equally large group chose to describe winning a
game or participating in some other sporting event as providing
them with success experience. Other success activities included
social activities and work-related events. Looking at how success
was defined across domains, ability-related standards and others'
evaluations were most common, along with objective outcome.
These studies strongly suggest that if one wants to understand
how people think about success and failure, one has to move
outside the laboratory and outside of the educational system. For
adults, one of the major success domains is the workplace. After
a discussion of other theoretical work on ways of conceptualizing
success, the remainder of this paper focus on success perceptions
in work setting l.
Individual Differences in Conceptualizing Success
Although one generally thinks of the labeling of an outcome
as a success or failure as the first step in the attribution process,
there is evidence that the attribution made for the event affects
the labeling of the event. For example, Maehr (1974) suggested
that a person does not feel successful in doing a task unless
1Another major focus of Frieze's work has been on reactions tovictimization -- the failure side of the theoretical applications.
131
there is a sense that the outcome of the task resulted from
factors under the control of the person doing it. Frieze and her
colleagues (Frieze et a1., 1983) replicated this observation, in
which, college students rated themselves as most successful if their
outcome was attributed to effort. "Success" attributed to cheating
or to luck received much lower ratings as subjectively success.
Many other factors have been shown to relate to a success
judgment. As reviewed by Frieze et a1. (1983), achievement
researchers have always had to deal with the question, "what is
success?", and they have often arrived at different answers.
Perhaps the most influential of all of these definitions was offered
by McClelland who defined "success" as meeting or exceeding a
personal standard of excellence (McClelland, 1961). Other success
standards proposed by researchers include doing better than
expected, doing better than one's peers, doing better than one's
own past performance, and doing what is defined by the culture
as important (Frieze et a1., 1983).
A number of generalizations can be drawn from the extensive
work on varying conceptualizations of success. First, although
there are generally accepted ideas about what types of
performances would be defined as successful, such definitions are
particular to a cultural group. There are wide cross-cultural
variations in concepts of success (Maehr & Nicholls, 1980). There
are also individual differences within a culture in how success is
defined. Finally, success may be thought of differently within
different domains. While the exertion of effort may be seen as a
necessary condition for one to feel success in school, at least in
132
the United States, quite different associations may exist in the
workplace or on the playing fields.
Defining Success in Work Settings.
In order to answer the question of how people think about
success in their lives, it seems natural to focus on work settings.
Much of our daily achievement activity occurs at work, especially
for cOllege-educated professionals. In these important, real-life
activities, do we find the same variation in the ways people define
success? Or, can we measure work success in more standardized
ways -- with money and position?
Success Experiences at Work. Our first assessment of how
people think about success at work was an exploratory study done
with a sample of nurses and business students. Frost, Frieze and
Perloff (1987) asked professional nurses to "Describe [a] successful
nursing experience in which you were involved" and why they gave
this example of work success. Staff nurses as well as
administrative and teaching nurses were in the sample.
Data were coded into categories similar to those used by
Meece and Frieze. In general, there was little difference among
the three groups of nurses; all types of nurses looked back to a
patient experience as a time when they felt successful. Patient
improvement was often cited as the success criterion, along with
praise from patients or coworkers. Sample responses are in
Table l.
We next asked business students similar questions to see
how success experiences differed between a male and a
133
TABLE 1 Perceptions of Successful Work Experiences
- Describe this successful nursing experience in which you wereinvolved.
*
*
*
*
Published an article in a nationally known nursing journal.[Was successful because of] receiving recognition by peers andmentors. Self-fulfillment. [28 year old female nursingeducator].
I participated in organization and instruction of a series ofgroup sessions for out-patients on hypertension. [Wassuccessful because of] positive feedback from patients.Personal satisfaction of accomplishing things I was afraid todo. [35 year old female primary care nurse].
Made rounds with a doctor who abruptly told patient that hemight have surgery in near future, then left the room. Thepatient became quite anxious. I spent time with him andthen with he and his wife later. I listened to him, answeredsome of his questions and was able to have him reach aconstructive solution ... [37 year old female nurse educator].
I ascertained that one of my patients was changing... anddocumented this and collected appropriate drug screens/labwork even though everyone else thought I was crazy. Thepatient arrested abut 4 hours later and through the lab workI had sent off it was discovered that he was toxic and hewas saved. [Was successful because] I had maintained myprofessional judgment despite peer pressure from manyfriends/co-workers ... [25 year old female staff nurse].
- Describe this successful business experience in which you wereinvolved.
*
*
Development and implementation of accounting systems for anew remote plant site using existing equipment. [Wassuccessful because of] job well done resulting in continuingpositive responses from users. [32 year old male MBAstudent].
Having audit report accepted by client despite strongrecommendations. [Was successful because j it showed that Icould be convincing (and that I had presented byrecommendations appropriately) ... [28 year old female MBAstudent].
(Continued on next page)
*
*
134
(Continued from previous page)
I helped design a walkthru of a new Inventory RecordingComputer System so that people who are going to use thesystem have some idea of how it will work. [Was successfulbecause] other people felt that they had benefited from itand I felt that I had done something WORTHWHILE. [22year old female MBA student].
Being promoted from a technical to a supervisory position.[Was successful because] showed the fruit of hard work andinvolvement. [28 year old male MBA student].
Data collected and analyzed by Frost, Frieze, & Perloff (1987).
female-dominated field. We were surprised at the similarities.
Doing one's work well and feedback from others were often the
basis of success for the business students as well as for
the nurses.
Perceptions of Professionals in Business and Librarians.
Based on the results of this first exploratory study, we decided to
do a more formal study with a more clearly defined sample.
First, Olson and Frieze (1987) surveyed over 2000 graduates of
the Master of Business Administrations Program at the University
of Pittsburgh. A final sample of over 1400 of 1973 to 1982
graduates was obtained. Questions on the surveys asked about
work histories, income, and a variety of attitudes about work and
family issues. We also collected similar data (in collaboration
with Detlefsen) in 1986 using a survey of graduates of the Master
of Library Science (MLS) program at the University of Pittsburgh.
This survey yielded about 960 responses and also included
masters' level professionals who had been working in their
135
careers for many years. Multiple mailings of the surveys allowed
us to receive responses from about 70% of both of the original
survey sam pIes.
The question of most importance for assessing perceptions of
work success was "how do you personally define success in your
company?". The first two open-ended responses to this question
were coded into about fifty categories by a coder naive to the
hypotheses of the study. Coding reliability was established
through a minimum percentage agreement of responses across
coders of at least 80 percent. Since the large number of
categories made it difficult to make comparisons across gender
and professions, the personal success criteria were recoded into
six aggregate categories. These success categories and the
frequencies of the first responses by sex are shown in Table 2 for
all MBAs and MLSs working full time at the time at the time of
the survey.
Looking first at the data for the MBAs, the results in Table
2 show that even for supposedly financially-oriented business
people, economic definitions (such as money) and job level or
position were not the most important single criterion for their
personal success. For both men and women MBAs, "Doing good
work and getting results" was the most frequently cited indicator
of success. Economic criteria were, nevertheless, important. Over
half of the MBA sample listed the traditional success criteria of
economic factors, job level, power, and promotions as their first
success criterion. However, the remainder of the MBAs (nearly
half) listed aspects of success that are not strongly economic
136
TABLE 2 Definitions of Success for Two Professions
Percent Within Each GroupMBA MLS
Men Women Men Women
Doing Good Work. Getting Results. 27.7 21.3
Other 17.6 21.7
How do you personally definesuccess in your company?
Economic Definitions
Job Level or Position
Power or Responsibility
Promotions
Number Responding
What would your life need to be like10 years from now in order for youto consider yourself a success?
Work Related
Marriage/Children
Material Possessions/Money
Personal Growth/Other
Number Responding
11.4 7.3
10.0 10.8
17.7 18.5
15.6 20.4
823 314
49.4 51.2
20.2 26.7
20.7 12.9
9.7 9.2
796 303
10.7 5.1
4.9 3.3
3.9 4.5
3.9 2.7
41. 7 35.9
35.0 48.5
103 334
63.6 62.5
10.3 18.6
15.0 11.4
11.2 7.5
107 387
For MBA group.
For MLS group.
Sex difference in success definitions significant(p<.03)Sex difference in long-term goals significant(p<.Ol)Cell sizes to small to test for sex differences insuccessSex differences in long-term goals borderline(p< .13)
(con tin ued on next page)
137
(Continued from previous page)
For Males. Field difference in success definitions significant(p<.OOI)Field difference in long-term goals significant (p< .02)
For Females. Field difference in success definitions significant(p<.OOI)Field difference in long-term goals significant (p< .02)
~~m;w./*:·r$r@[r~&.~A~tal{M~~~~~i®m~~&~~~mmgm~m11~ffi~~m~E.WI:~~~
in nature. In addition to doing good work, these included "Other"
responses such as being recognized by others, meeting personal
goals, and interpersonal definitions. Although the results
indicate there are significant sex differences in the responses of
the MBAs, the differences do not lie along the dimension of
economic versus noneconomic criteria for this sample of male and
female managers.
How does the MBA data compare with success perceptions of
librarians? We anticipated that the female-dominated profession
of librarianship would yield less traditional success definitions.
Looking again at Table 2, it can be seen that "doing good work"
and "other" criteria were even more important to the MLS
graduates than to the MBAs. And, as one might expect given the
notoriously low salaries of librarians, the first four categories,
which are the mostly economically oriented, account for only 28
percent of the men's responses and 15 percent of the women's,
for less than for the MBAs. Because of several small cells, a
test of significance by sex could not be done for the MLS
graduates. However, a test across the two professions indicated
significant differences by field for men and for women.
Other data from the MBA and MLS surveys allowed us to
assess success perceptions in another way. The question we asked
138
was "What would your life need to be like 10 years from now in
order for your to consider yourself a success?" One of the codes
used for this question was the domain mentioned by the person.
The most common domains mentioned were work, family/marriage,
material possessions/money, and personal growth and development.
Frequencies for these responses are shown in at the bottom of
Table 2.
At least half of all four groups defined work as the domain
of their future success, with the librarians being even more work
oriented than their counterparts in business. In addition, another
substantial percentage thought of future success in the traditional
terms of material possessions or money. This response was most
typical of the male MBAs. Nevertheless, about a third of the
MBAs and a quarter of the MLSs considered family or personal
development as the domain in which they sought to be successful.
Here again, there were some statistically significant sex differences
within the occupational groups, but the occupation differences
tended to be larger.
Both of these sets of data would suggest that those in
different professions have different views of success and that
occupation effects are more important than sex differences. This
is consistent with other research. The "female" professions (such
as librarianship, social work, nursing, and teaching) are often seen
as allowing more opportunity to work with and help other people
(Eccles, 1987). Other research has shown that men and women in
the same occupation tend to share many of the same values
regardless of sex (Bailyn, 1987; Golding, Resnick & Crosby, 1983).
139
Given that there appear to be differences in the ways people
in different occupations define success, one might ask "why?".
There are at least two answers. Does the field itself structure
what is possible? The focus on promotion, position and power as
indicators of success by MBAs, as opposed to the MLSs' focus on
doing work well, could reflect the nature of the tasks in the two
work environments. Performance in many business management
positions can be measured by tangible factors such as net income,
profit margins, or total sales. In addition, there is usually a well
established hierarchial ladder to climb. For librarians, however,
the only measure of a job well done may be the actual
performance on the specific task (Frieze et aI., 1988).
Another possibility is that people who share basic values and
ideas about success differentially select themselves into certain
occupations. A recent study of college students choosing male as
compared to female-dominated occupations indicated that there
were more similarities in motives and ideas about success within
the occupational groups than differences and that occupational
choice was a better predictor of motives and beliefs than sex or
race (Murrell & Frieze, 1990). This would support the idea that
there is some selection that goes on before people enter different
occupations. But, undoubtedly, the structure of the occupation
has a reciprocal influence and also affects ideas about success.
Success Scripts in the Organization
Related to, and in many ways inseparable from the definition
of success, is the question of the steps people believe are needed
140
to achieve success. Within the traditional attributional model, this
question becomes the causal attribution. The attribution answers
the question of "why?" after the event has happened. But, people
have prior conceptions before doing a task about what they will
need to do. Such beliefs are another form of attribution. They
may be specific to a particular, short-term task or they may take
the form of very long-term plans for major life goals. Our work
has also attempted to understand this form of attributional
beliefs better.
Steps Needed for Work Success. Our first attempt to explore
the beliefs that people have about how to be successful in work
was incorporated into our study of the MBA graduates. We also
included this in the MLS comparison survey. In addition to the
question of "What would your life need to be like 10 years from
now in order for you to consider yourself a success?", we asked
"What steps do you feel you need to take to become successful in
these terms?" Coding for this second question was complex
because there were so many different types of responses. Some
people made traditional causal attributions (effort, ability, luck,
etc.). Others mentioned some level of performance, either a high
level or a comfortable level. For others, the performance-related
response was attaining some goal (such as getting a job) or doing
better than one was doing now. A category of nontraditional
success definitions was also added to the coding system.
Data for both questions were coded using a total of 32
categories. These were grouped into four major categories: level
141
of performance, causal attributions, nontraditional success criteria,
and other.
Looking next at the success criteria for those whose domain
was business, Table 3 shows that high levels of performance were
most important of the MBAs while a variety of performance
standards were cited by the MLSs. MBAs more often cited
autonomy while MLSs were more concerned with happiness os a
success criteria. Overall, though, differences were small, There
were even fewer differences when the respondents were asked
about the necessary steps to become successful in the work
domain. Again, only those citing the work domain were included
in this analysis. Here, effort was the single most often cited
factor for both groups.
These data suggest that although people may differ greatly
across occupations in how they define success for themselves,
there is less disagreement on how to attain work success. We
intend to explore this issue in future research.
Success Scripts. Another way of conceptualizing beliefs about
how to become successful is as a "script". Abelson (1981) defines
a script as a "coherent sequence of events expected by the
person". Cognitive psychologists have studied individuals' scripted
knowledge for short-term or daily activities such as "eating at a
restaurant" or "going to the doctor" (Bower, Black & Turner,
1979). Clinicians have written about long-term scripts that may
guide behavior over a lifetime (Carlson, 1981).
Recently, social psychologists have again become interested in
how knowledge structures that embed numerous causal assumptions
142
TABLE 3 Success Criteria Used for Long-Term Success in Work
Percent With Each GroupMBA MLS
What would your life need to be like10 years from now for you toconsider yourself a success?
Level of Performance
High level of performanceImprovement over presentReaching specified goalOther performance criteria
Causal Attributions
Nontraditional Success Criteria
37.2% 16.8%13.3% 8.1%8.9% 17.9%5.8% 14.8%
4.2% 5.3%
Happiness or SatisfactionIndependence or AutonomyOther nontraditional criteria
Other
Number Responding
What steps do you feel you need to taketo become successful in these terms?
Level of Performance
Continue same level of performanceImprovement over presentReaching specified goalOther performance criteria
Causal Attributions
Effort and hard workLearning new skills (Ability)Other attributions
Nontraditional Success Criteria
Other
Number Responding
7.7%11.5%
4.5%
7.0%
573
13.0%9.2%7.5%7.5%
20.6%9.9%
11'.9%
5.5%
14.8%
545
11.8%5.6%5.9%
13.7%
357
7.7%7.3%
12.8%5.4%
21.4%9.3%9.6%
4.5%
22.0%
313
143
act as guides for behavior and affect decision making and future
expectations (Anderson, 1983; Cantor, Norem, Niedenthal,
Langston & Brower, 1987; Pennington & Hastie, 1986; Vallacher
& Wegner, 1987; Wong, 1988). For example, Pennington and
Hastie (1986) suggest that jurors use evidence presented in a trial
to formulate a story about what really happened in the alleged
criminal event. Built into this story are causal assumptions about
why the defendant acted as he or she did. Wong (1988) has also
investigated the reasons for achievement-oriented behavior. These
"existential attributions" are more predictive of long-term behavior
than attributions about any particular event.
Organization theorists such as Gioia and Poole (1984) and
Martin (1982) believe that scripts can be used by individuals to
guide behavior in daily work situations. Specifically, they suggest
that organizational scripts are mental representations of events
that individuals use to guide their behavior in specific contexts
such as staff meetings and performance evaluations. As repeated
activities become learned, they are often given a label that is
understood within the group. For example, strategy meetings that
take a brainstorming form may be identified as "think tank
sessions" as a shorthand for the established script (Gioia, 1986).
Organizational scripts may also take the form of concrete stories
about how a particular individual was successful (Martin, 1982).
Both these types of scripts refer to relatively short sequences of
behaviors. Gioia and Poole further argue that there are scripts
for long-term goal-oriented behavior. These longer term scripts
may contain less sequencing and more interpersonal content (Lord
144
& Kernan, 1987). However, there has been little empirical work
on such scripts (Moss & Frieze, 1987).
In a study designed to test for sex differences in scripted
knowledge about success, Moss and Frieze (1987) asked 127
currently enrolled MBA students to write about how a "fast-track"
male or female manager became successful. As with other
research already described, the scripts were coded for specific
types of behaviors by naive coders. In doing this coding, we
noted that, consistent with theorizing by Gioia (1986), many of
our subjects first referred to the label "fast-track manager" as an
organizing term, and then they proceeded to describe the events
associated with this label.
Using procedures developed by Bower et al. (1979) to
combine the individual script elements, a prototypical management
success script was derived from the open-ended responses
CTable 4). This consensual script contained 10 script elements
mentioned by at least 25% of the sample. The most common
element in all the scripts was hard work. Gaining experience and
skill, having the right personality, and networking with others were
other commonly mentioned aspects of the script. Thus,
traditionally studied attributions were clearly present and were
spontaneously mentioned by large numbers of the study
participants (Weiner, 1985a).
Following a number of popular and scholarly books which
have suggested that one reason that women are not as successful
as men in managerial careers is that they lack knowledge of how
to be successful and how to "play the game" (e.g., Kanter, 1977;
145
TABLE 4 Success Scripts of MBAs for Fast-Track Manager
Have good technical skills 2,4
Have good interpersonal skills 4
Gain experience and develop skills 3
Have the right personality 3,5
Get a job with a growing company 4
WORK HARD 5
Network with others 2,5
Get help from upper management 2
Do one's work well
Be in the right place at the right time.
1.
2.3.4.5.
Item in ALL CAPITAL LETTERS mentioned by 55% or moresubjectsUnderline items (mentioned by 40-54%)All small letters (mentioned by 25-39%)More common for male than female targetsMore common for female than male targetsMentioned more by male subjectsMentioned more by female subjects
Harragan, 1977), we expected to find sex differences in the
success scripts. Contrary to our predictions, there were no
differences in the degree of detail in the scripts between the male
and female respondents. There were, however, some minor sex
differences in the content of the scripts. More males mentioned
ability-related attributes. We also found that regardless of sex,
those who had had more actual work experience were more likely
146
to mention luck (being fortunate or being in the right time and
place) as important to career success. Some difference were also
found in the scripts written about fast-track men as compared to
those about fast-track women. There was more mention of
gaining skills and experience in the women's scripts. Other
hypothesized difference were not found.
While there were relatively few group differences in the
scripts generated by our subjects, there were large variations
across individuals. Some emphasized interpersonal aspects of
management success while others were focused on work imagery.
Once again, further work is needed to understand better the basis
of such differences. Recent work by Kunda (1987) indicates that
people build casual models to explain future events and that these
models emphasize the positive nature of one's own characteristics
in bringing about good outcomes. Perhaps our MBA students
build models emphasizing what they feel that they can do best.
This study was an initial attempt to gain understanding about
the long-term success scripts of individuals before they enter an
organization. Moss and Frieze are now analyzing data on
managerial scripts of undergraduate students to see if these
less-knowledgeable individuals have different types of success
scripts. We also hope to study how success scripts evolve over
time and how they are affected by the particular organizations in
which one works.
147
Shared Success Conceptions and Corporate Culture
Broadening the Attributional Model. Up to this point in this
chapter, we have been concerned with personal conceptions of and
definitions of success. But, once one becomes interested in
success conceptions in real world settings such as the workplace,
it is clear that there is an organizational context to consider as
well. The process of determining what is successful and how to
obtain that success involves a complicated interaction between the
perceptions of the individual and those of the larger group in
which the individual functions.
This interaction, is described in Figure 1 suggests a
broadening of the attributional process that not only includes the
individual and organizational perspectives, but also the degree of
similarity or matching between them. This matching can occur at
the level of what is considered a success (the focus of much of
this chapter), whether a particular event is a success or not, what
information is used to explain the event, and the attribution made
for the event. Presumably, objective indicators of the success of
the individual within the organization would be affected by all of
these forms of matching.
To discuss some ideas about success matching, we first review
research and theory relating to organizational beliefs or
"corporate culture".
Corporate Culture. The culture of an organization is a set
of shared norms, beliefs, and values about how things are done in
that organization (Deal & Kennedy, 1982; Schein, 1986). An
important component of these beliefs is the determination of what
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149
is worth striving for and what will be rewarded by the
organization (Maehr, 1987). There are also standards for what
behaviors and practices will lead to success (Martin, 1982;
Shrivastra & Schneider, 1984). As people enter an organization,
they must learn these unwritten rules of the organization about
"how things are done here". One important form for
comm unicating such rules is through stories of particularly
noteworthy employee behavior (Martin, 1982). Martin's work has
demonstrated that concrete stories are more effective in
communicating company policy and are more remembered than
abstract policy statements. Some common types of stories whose
themes are shared by a large number of organizations are:
1. "No mass layoffs" script about an organization's refusal tofire employees when economic times get tough.
2. "Horatio Alger" script about the employee who starts atthe bottom and climbs to the top.
3. "Great man is human" script, where the founder orpresident of a company makes a personal gesture towarda lower-level employee, for example, buying a present fora new baby.
4. "We appreciate and/or tolerate deviance"script, where atop executive goes out of his way to respond well to acomplaint or challenge from a subordinate. (Martin,1983, p. 285).
Over time, it is assumed that individuals within the
organization will share more and more of the same values and
beliefs. Research has demonstrated that newcomers to a group
develop new conceptions of the organization as they enter the
group (Louis, 1980). New quantitative techniques are being
developed to measure such changes using structural equation
procedures (Schaubroeck & Green, 1989).
150
It is further argued in these largely theoretical papers that
shared values or norms enhance group functioning and make the
organization more efficient (Barney, 1986; Enz & Schwenk, 1989;
Feldman, 1984; Schein, 1985). Organizational culture theorists
also assume that shared values within the organization should
predict higher levels of job satisfaction for the individual members
of the group (e.g., Granrose & Portwood, 1987; Wanous, 1980).
Value similarity between employees and top management is
assumed to be especially important (Barney, 1986).
In one of the few studies directly testing the importance of
shared values in the organization, Posner and Schmidt (1984) sent
questionnaires to 6000 managers and executives asking questions
about their values. Nearly three-fourths of those surveyed
reported that pressure to conform to organizational standards was
strong. Other work has shown that those managers who perceived
that they shared the values of the organization felt more personal
success (Posner, Kouzes, & Schmidt, 1985).
Recent work has begun to question some of the assumptions
about the role of culture and shared beliefs. Enz and Schwenk
(1989) studied actual and perceived sharing of values within a
transportation organization. Although they did find that unit
managers who actually shared the values of top management had
higher performances within their units, there was no effect for
actual similarity within a unit to relate to that unit's performance.
In addition, perceived similarity did not relate to the overall
performance of the organization. In another non-confirming study,
Mayberry (1985) found that shared values within the group had no
151
relationship to organizational satisfaction or commitment.
Meglino, Ravlin, and Adkins (1989) did find a positive relationship
between job satisfaction and value similarity for production
workers and their supervisors, but the effects were modest.
These studies, and others that have failed to confirm
matching predictions (e.g., Vandenberg & Scarpello, 1990),
suggest that more attention needs to be given to the effects
associated with particular types of matching. Of most interest for
us here is the matching of ideas about how to be successful in
the organization.
Effects of Matched Success Definitions. Much of the work
done thus far on the matching of values has not looked at
specific types of values. Instead, more generalized matching of
job rewards and preferences for particular types of rewards (e.g.,
Vandenberg & Scarpello, 1990; Wanous, 1980) or matching of
individual and organizational career plans (Granrose & Portwood,
1987), or even more general types of matching have been done.
There is reason to believe that definitions of success should
be especially important components of organizational culture.
Matched success definitions within the organization should lead to
higher performance levels and to more recognition in the form of
higher salaries for those who do match. There should also be
higher job satisfaction for those who fit in well in terms of
matching. However, as we have seen, the empirical support for
such ideas is still weak. In addition, most of the work has taken
an organizational approach, and has not looked at the effects of
matching on the individual. Are those who see themselves as
152
most similar to others in the group the most successful? Are
they the most satisfied with their work?
The above questions were addressed in a paper by Russell,
Frieze, & Olson (1987). We argued that an organizational
member who can "listen" and incorporate the appropriate
behaviors and values is more likely to succeed than those who do
not "fit" as well. At the same time, those with shared values
were also expected to be more satisfied with their jobs. Using
the same sample of University of Pittsburgh MBAs described
earlier, we tested these ideas regarding matching. The questions
used were the one about how they defined success in their work
and a question about how they felt that their co-workers defined
success. In this case the original 50 categories of success criteria
were used and the first personal success response was compared
to first response for the co-worker's success criterion. If the
same code was used for one's own success definition and for the
success definition of co-workers, the person was considered to be
matched in success values. Overall, 46% of the group was
matched. This was a much higher proportion of matching than
we had anticipated, especially given the exact matching requires.
One demographic variable was related to matching. There
was a trend for women more often to be matched than men
(x2J =2.7, p<.08). Over 50% of the women had matched success
definitions as compared to 44% of the men. Higher levels of
matching for women is consistent with other research. For
example, in their survey of 6000 managers and executives, Posner,
Kouzes and Schmidt (1985) found that women reported more
153
pressure to conform than men. In a review of other research,
Colwill (1982) has noted the women tend to be more likely to
echo traditional male definitions of success, particularly "the
acquisition of money, advancement and recognition in the world of
employment" (p. 89). It seems reasonable to hypothesize that
women who are successful managers are the most accepting of
traditional male definitions of success that dominate the
managerial work environment.
Going back to the more general question of the impact of
matching on salary, a series of regressions were performed. In
order to test our first hypothesis that those whose success values
matched those of their co-workers would have higher salaries, a
multiple regression equation was estimated using a dummy variable
equal to one if success values matched and three other variables
which our previous studies (e.g., Olson, Frieze and Good, 1987)
had found were significant determinants of MBA salaries. These
three variables were years of full-time employment before
receiving the MBA, years of full-time employment after receiving
the MBA, and a dummy variable for sex (l=female). The
criterion variable was the MBA's 1983 full-time annual salary.
The overall F for this regression was highly significant (F41014 =
115, P < .01). All the individual coefficients in the equation
were significant at the .01 level of confidence and the percentage
of variance in salary accounted for by the equation was 31 %.
The resulting equation was:
Salary = 24.7 + 1.3 Years Work Before MBA
+ 2.3 Years Work After MBA - 2.9 Sex + 2.2 Matched.
154
As expected, those whose success values matched their perception
of those of their coworkers earned significantly more than
those managers whose values did not match. The difference
translates into an average of $2200 in additional annual salary
for those managers whose values matched. The regression
results also replicated earlier studies which showed that women
earned less than men and the salary tended to increase with years
of experience.
A similar analysis was done to assess the effects of matching
on job satisfaction. Respondents were asked to rank their overall
job satisfaction on a five-point scale (1 = very dissatisfied and
5 = very satisfied). In this regression equation, job satisfaction
was used as the criterion variable; the same variables as in the
salary regression were used as predictors along with the addition
of salary. Results were less significant. The overall F was
highest with only salary level and matching; both coefficients were
significant at the .05 level. The F declined with the addition of
years of full time work and years of previous employment and
sex. In the full equation, the overall F 51013 = 7.02 (p < .01).
The resulting equation was:
Satisfaction = 3.3 + .01 Salary
- .03 Years Previous EmploymeDt + .08 Matched
+ .02 Years Full Time Employment + .06 Sex
Although matching was related to job satisfaction in the predicted
direction, the coefficient for matching was not statistically
significant; neither were the coefficients for sex or years of
155
full time employment. Those with more years of previous
employment were less satisfied with their current positions when
we controlled for salary. The strongest predictor of satisfaction
was salary level.
The results of this work indicated, as expected, that
organization members whose personal definitions of success in
their company matched their perceptions of their coworkers'
definitions of success tended to earn higher salaries and to have
somewhat higher levels of job satisfaction. Since salaries are
determined by many factors (e.g., Olson & Frieze, 1987), the
strength of these findings suggest that matching is indeed
important to organizational success.
Conclusions and Questions for Future Research
As this paper has suggested, the question of how people
define success is complex. There is evidence that ideas about
success are individualized and that many people use definitions
that have not been widely acknowledged by achievement
researchers. Even MBAs define success in other than financial
terms. Librarians rarely think of success economically. They are
much more likely to see success in terms of doing their work
well. But, at the same time that we find these wide individual
differences in perceptions of success, there are also similarities
within professional groups. Gender may also differentiate people.
These studies have shown that men and women often tend to
think of success differently, even today when so many women are
entering the work force. We hope to continue to study individual
156
differences in success definitions and the implications of such
definitions for upward mObility and for satisfaction in one's work.
As reported earlier, many people may not routinely experience
success in their work. What are the conditions that maximize
such success feelings? Clearly, this is an important theoretical
and practical question.
Moving beyond the individual, there are also important
questions about the interaction of individual success perceptions
and organizational values and ideas about how to be successful.
Is "fitting in" especially necessary in terms of how one defines
success within the organization as we argue here? Another
question for future research is to identify what types of people
are the most likely to match their success values to the
organization. Posner and Schmidt (1984) asked managers whether
they faced conflict between the organization's goals and their own
values. It is interesting to note that upper level managers had
the least problem with this, while supervisory level managers were
highest in conflict. It follows that those who subscribe to the
organization values and goals are the ones who will stay and grow
in that environment. Those who have conflicts are more likely to
be passed over for promotions or to leave the organization in
order to relieve the conflict caused by this dissonance. At the
same time, the highest level managers may see themselves as
unique and may be less likely to define personal success in the
same way that they feel their coworkers do. Once again, further
research is needed on this issue.
157
Finally, we acknowledge that most of our work has
concentrated on questions raised by the left hand portion of
Figure 1. As attribution researchers move into the workplace,
other attributional questions will be raised. We suspect that the
answers such studies give us will add to and contribute to the
continued development of Weiner's very important work.
158
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Understanding CloseRelationships: An AttributionalPerspective J
Frank D. FinchamUniversity of Illinois at Urbana-Champaign
Social psychologists became concerned with the study of
cognition shortly after the first social psychological experiment
conducted by Triplett in 1897 and this cognitive emphasis was
reaffirmed and expanded in the founding of modern social
psychology (d. Lewin, 1951; Heider, 1958). Although the interest
in cognition has remained constant, the dominant conceptual
framework has changed regularly. For example, attribution theory
replaced cognitive dissonance theory in the late 1960s and it is
apparent that the information processing approach has now
replaced attribution theory as the guiding theoretical framework in
social psychology. Such changes are natural and healthy
developments. However, in their enthusiasm to embrace new
conceptual frameworks, social psychologists tend to overlook the
untapped potential of the conceptual framework that is replaces.
This is certainly the case for attribution theory, a theoretical
framework that is still proving fruitful in the study of close
relationships, particularly marriage.
lThe author thanks Susan Gano and John Grych for their helpfulcomments on an earlier draft of this manuscript.
164
To illustrate the value of an attributional approach for the
study of close relationships, this chapter is divided into three
sections. First, a rationale for studying attributions specifically in
the context of close relationships is presented. Second, a brief
summary of attributional research on marriage is provided. Third,
a rough cartography for future avenues of inquiry is offered so
that the potential of an attributional approach to marriage might
be realized more fully. The chapter concludes with a summary of
its major themes.
Why study attributions in close relationships?
Heider's (1958) analysis of "naive" or common sense
psychology provided the single most important foundation for
contemporary attribution theory and research. According to
Heider, causal explanation or attribution is fundamental to
common sense because "Attribution in terms of impersonal and
personal causes, and with the latter, in terms of intent, are
everyday occurrences that determine much of our understanding of
and reaction to our surroundings" (Heider, 1958, p. 16). Not
surprisingly, Kelley and Michela (1980) uncovered over 900 papers
on attribution for the ten year period prior to their review, and
attribution research, particularly on applied topics, has since
continued to thrive.
Given this wealth of information on attribution, why
investigate attributions in marriage? Surely, the findings of basic
attribution research is social psychology apply to marriage?
Although not explicitly stated, a positive response to the last
165
question was assumed by clinical psychologists as they became
increasingly aware of the importance of attributions in marital
therapy. For example, Jacobson and Margolin (1979, p. 108)
noted that spouses" "Typically view therapy as a way to
demonstrate to the partner and to themselves that they are
blameless, and that the other is at fault." They also noted that
"theories of ... causal attribution figure prominently in the
derivation of treatment strategies" (Jacobson & Margolin, 1979,
p. 31). At the time of this observation there were no published
studies on attributions in marriage and to the extent that
attribution theory informed marital therapy, this application rested
on the unarticulated assumption that the application of basic
attribution research to marriage was straightforward.
This assumption deserves closer scrutiny, however, because the
generalization of basic attribution research to close relationships is
contraindicated by several findings. For example, it has been
shown that attributions vary as a function of (a) expected
interaction with the attribution target (Knight & Vallacher, 1981),
(b) the nature of the attributor's relationship (e.g., friend,
acquaintance, spouse) to the attribution target (Taylor &
Kouivumaki, 1976), and (c) the affect experienced towards the
attribution target (Regan, Straus & Fazio, 1974). These findings,
combine with the observation that most basic research investigated
attributions made in regard to hypothetical others or strangers,
suggest that the results of attribution research in social psychology
may not apply to attributions in marriage. Despite the
voluminous attribution literature available in social psychology,
166
research on attributions in marriage therefore began to appear in
the 1980s and has developed relatively independently of basic
attribution research in social psychology. As will become
apparent later in the chapter, marital research has enriched the
study of attributions and has resulted in the identification of new
attributional phenomena. However, it will be argued that recent
attribution research in social psychology also has the potential to
advance the study of attributions in marriage.
Overview of attribution research on marriage
There has been an explosion of research on marital
attributions in the last few years. Currently, there are at least 30
published studies on attributions in marriage, only five of which
appeared prior to 1985. Because it has been suggested that this
research shows "little cohesion" (Baucom, Epstein Sayers & Sher,
1989), a framework for reviewing and evaluating marital
attribution research is offered in this section. The following
overview is not intended to be exhaustive as a comprehensive
review of this domain already exists (see Bradbury & Fincham,
1990). Rather, the goal is to provide a brief introduction to this
research domain by identifying the major themes that underlie the
bulk of research on marital attributions.
Interest in marital attributions was motivated by applied
concerns and has therefore focused on marital satisfaction, the
final common pathway that leads couples to seek therapy. More
specifically, it has been widely assumed in clinical writings that
(a) attributions explain variance in marital satisfaction and (b)
167
attributions may help us understand the patterns of behavior
exchange found in distressed and nondistressed couples. Each of
these assumptions is examined in turn.
Attributions and marital satisfaction
The assumption that attributions account for variance in
marital satisfaction can be broken down into two propositions:
1. Attributions maintain current levels of satisfaction. This
assumption requires as a minimum the demonstration of an
association between attributions and marital satisfaction.
2. Attributions can precipitate changes in marital satisfaction.
The implied causal relation between attributions and marital
satisfaction in the previous assumption is quite explicit in the
present one. This assumption therefore calls for evidence to show
that attributions influence marital satisfaction.
The typical marital attribution study asks distressed and
nondistressed spouses to generate causes for marital events (most
often hypothetical partner behavior, marital difficulties or, less
frequently, actual partner behaviors) and to rate these causes
along causal dimensions such as the locus of the cause (for an
exception, see Epstein, Pretzer & Fleming, 1987). The rationale
for focusing on causal dimensions, rather than the content of
attributions, is that the same cause (e.g., "My husband didn't do
his chores because he was preoccupied with this work") can be
viewed differently (e.g., the husband's preoccupation may be
viewed as a response to temporary circumstances, an external and
unstable causal attribution, or as a trait, an internal and stable
168
attribution) and it is the underlying dimensions that are most
relevant for understanding the consequences of attributions (cf.
Weiner, 1986). Because couples presenting for therapy often
express feelings of helplessness and because of the salience in the
clinical literature of the attributional reformulation of learned
helplessness (Abramson, Seligman & Teasdale, 1978), research has
focused on the causal dimensions of locus, the stable versus
unstable nature of the cause, and the extent to which it was seen
as global versus specific.
Although clinicians typically discussed attributions in terms
of responsibility or blame (see earlier quotation from Jacobson &
Margolin, 1979), they did not initially investigate these
constructs and unwittingly followed the practice in basic
attribution research where data on causal judgments serve as the
basis for statements about responsibility and blame. This practice
is intriguing because there is a body of attribution research in
social psychology that clearly documents differences in responses
to questions regarding cause, responsibility, and blame (see
Fincham & Jaspars, 1980; Schultz & Schleifer, 1983; Shaver, 1985)
and shows that lawful relationships exist between these different
judgments (e.g., Fincham & Roberts, 1985; Fincham & Schultz,
1981).2 Briefly stated, causal judgments deal with who or what
7he distinctions between cause, responsibility, and blame have beendiscussed in detail elsewhere (e.g., Bradbury & Fincham, 1990; Schultz &Schleifer, 1983; Shaver, 1985). Although a distinction can be drawn betweenresponsibility and blame, it is quite subtle because the criteria underlying the twojudgments are the same. Whether this distinction is important for understandingmarriage is an empirical question. However, clinical experience suggests that thedistinction is unlikely to reflect psychological functioning in marriage. In this
169
caused an event (i.e., they are primarily descriptive) whereas
responsibility and blame deal with accountability for the event and
with sanctions (Le., with evaluation) once the cause of the event
is known.
Recognition of the distinctions between various attributional
judgments, not only places the study of attribution on a firmer
empirical foundation, but also has important conceptual
implications. This can be illustrated in relation to the perceived
intent of a behavior. Intent is not a property of causes but of
Qeople, and inferred intent is critical to understanding a
perceiver's affective and behavioral response to an observed action
(Heider, 1958). Because intent is acknowledged to be a problem
for theories of causal attribution, it is accorded a minor role in
such theories (cL Weiner, 1986).3 However, when cause is
distinguished from responsibility and blame, intent assumes a
central role because a freely chosen, intentional behavior is the
quintessential act for which one can be held responsible
(Hart, 1968).
Noting these discrepancies in clinical and social psychological
writings, an attempt was made to expand the attributions studied
in marital research (Fincham, 1983, 1985a). Spouses were
therefore also asked to rate responsibility criteria such as partner
chapter, responsibility and blame are therefore used interchangeably. This usageis consistent with marital attribution research where judgments of blame havebeen used to assess responsibility.
~his is again curious because, as Heider (1958) notes, inferred intent isfundamental to the perception of personal causality (see beginning of section,"Why study attribution in marriage?").
170
motivation, intent and blameworthiness. Table 1 shows the
distribution of studies relevant to examining the association
between attributions and marital satisfaction and the possible
causal nature of this association.
The skewed distribution of studies shows markedly uneven
development of research on a possible concurrent and causal
relation between attributions and marital satisfaction. Because a
comprehensive review of the studies investigating a concurrent
relation between attributions and satisfaction is available elsewhere
(Bradbury & Fincham, 1990), only a summary of the findings for
negative marital events is given. The findings for negative
maritalevents are highlighted as negative events are more likely to
give rise to attributions (Holtzworth-Mumoe & Jacobson, 1985;
Weiner, 1985).
TABLE 1. Distribution of Studies Investigating a Concurrent andCausal Relationship Between Attributions and (a) MaritalSatisfaction and (b) Marital Behavior.
Association
Concurrent
Causal
MaritalSatisfaction
18
3
MaritalBehavior
4
1
Table 2 shows that consistent support has been found for an
association between attributions and negative marital events. Over
60% of the studies show that compared to happy spouses,
171
dissatisfied spouses are more likely to see the cause of negative
marital events as stable, global, and located in the partner, and
to see the partner's behavior as intentional, selfishly motivated,
and blameworthy. That is , relative to their nondistressed
counterparts, distressed spouses make attributions that are likely
to maximize the impact of negative behavior. No study has shown
a pattern of attributions opposite to that described.
This compelling evidence may make the absence of research
on a possible causal relation between attributions and satisfaction
TABLE 2. Summary of Studies Showing an Association BetweenAttribution Dimensions for Negative Marital Events and MaritalSa tisfaction
Number of Full/Partial NoAttribution Dimension Studies Support Support
Locus 13 69% 31%
Stability 11 63% 36%
Globality 10 100% 0%
Blame 8 63% 38%
Intent 6 67% 33%
Motivation 3 100% 0%
Note. Support was assigned to a study if the results wereentirely consistent with the hypothesis under consideration, or ifthey were consistent for either sex, for any of the groups studiesor any operational definition of the dimension uses.
This table summarizes the findings reviewed by Bradburyand Fincham (in press; see also Fincham & Bradbury in press-b).
172
appear surprising. However, experimental research that will allow
causal inference is on both ethical and practical grounds very
difficult to conduct in this area of inquiry. Introducing a
temporal factor to this research provides slightly stronger grounds
for causal inference. Thus, a pattern of findings in which
attributions predicted later marital satisfaction and in which
marital satisfaction did not predict later attributions would be
consistent with a causal relation in which attributions influenced
satisfaction. This is precisely the pattern of findings obtained in
the three longitudinal studies that have investigated attributions
in marriage.
In the first study, Fincham and Bradbury (1987a) assessed
marriages at two points separated by a 12-month interval and
found that initial causal and responsibility attributions predicted
wives', but not husbands', later marital satisfaction. This
relationship did not simply reflect a general association over time
between cognitive variables and satisfaction because unrealistic
relationship beliefs did not predict later satisfaction. In the
second study, Bradbury (1989) also found that attributions
predicted marital satisfaction over a 12-month period for husbands
but not wives. In a third study, Fincham and Bradbury (1990)
showed that causal attribution dimensions predicted marital
satisfaction for husbands and wives with spouses' level of
depression statistically controlled. These effects are particularly
noteworthy because they were found (a) even when initial
happiness/satisfaction was removed from the longitudinal
associations reported, (b) in established marriages where one
173
might expect relative stability in attributions and satisfaction, and
(c) for an arbitrarily chosen lag (12 months) that may not reflect
the causal lag between attributions and satisfaction. However, the
reason for the inconsistent sex difference found across the studies
is unclear. On the one hand, it suggests that the influence of
attributions on satisfaction may be unreliable, On the other hand,
it is encouraging in that it shows that a causal relation may exist
for both wives and husbands.
Attributions and marital behavior
As mentioned earlier, the second major assumption underlying
marital attribution research is that attributions may help us
understand the patterns of behavior exchange found in distressed
and nondistressed couples. That is, a specific spouse behavior
(e.g., wife arrives home late from work) is thought to result in an
attribution (e.g., "she's late because she cares more about her
work than about me" versus "she had extra work to do") that then
mediates the partner's response to the behavior (e.g., upon
spouse's arrival, "I've just had enough of the way you treat me"
and storms off versus "It's been a long day for you. Can I get
you a drink?"). The pattern of attributions associated with
mari tal dissatisfaction (see last section) is consis ten t with this
assumption and with the greater rates and reciprocity of negative
behavior in distressed marriages (see Weiss & Heyman, in press).
Demonstrating a causal relation between attributions and
behavior is quite difficult (see section, "Investigating the causal
role of attributions") and hence most research has examined
174
whether attributions and behavior are associated. However, in the
absence of such an association, the need to investigate a possible
causal relation is moot. Table 1 shows the distribution of studies
that examine the concurrent and causal relation between
attributions and marital behavior. Following the precedent of
basic attribution research where behavior is equated with
behavioral intention (a judgment), two initial studies investigated
the association between attributions and behavioral intentions
(Fincham, Beach & Nelson, 1987; Fincham & O'Leary, 1983). In
both studies little evidence was obtained to support an association
between causal attribution dimensions and behavioral intentions.
However, when responsibility attributions were examined (Fincham,
Beach & Nelson, 1987), a strong association was found with
intended behavior. That is, the more negative partner behavior
was seen as negatively intended, selfishly motivated, and
blameworthy, the more punishing was the intended response;
attributions accounted for approximately half of the variance in
behavioral intentions. This finding was obtained even when
marital satisfaction was statistically controlled.
Although encouraging, such data on intended behavior cannot
replace the investigation of overt behavior. Two further studies
have examined attributions and observed behavior. Fincham and
Bradbury (1988a) showed that causal attributions (summed ratings
of partner locus, causal stability, and globality) and responsibility
attributions (summed ratings for intent, selfishness, and
blameworthiness) correlated positively with negative behaviors for
both husbands and wives and negatively with wives' positive
175
behaviors during a discussion in which the couple attempted to
resolve a marital difficulty. Bradbury (1989) also found that
attributions were related to specific affects exhibited in a
problem-solving discussion. A similar causal attribution measure
correlated positively with husbands' whining and wives' anger and
negatively with wives' sadness. In contrast, the responsibility
attribution measure correlated negatively with wives' interest and
positively with wives' anger and contempt. Most importantly, the
associations reported between attributions and behavior are not
due to shared variance with marital satisfaction because this
variable was partialled out of the correlations in both studies.
Such evidence, however, does not address directly the
assumption that attributions mediate behavior exchanges. More
direct evidence for this assumption requires the documentation of
an association between attributions and sequences of behavior.
That is, attributions should be associated with the likelihood that
a spouse will respond negatively to an immediately preceding
negative partner behavior and respond positively to an
immediately preceding positive, partner behavior. Table 3 shows
the correlations between responsibility attributions and the
likelihood of a spouse reciprocating partner behavior (Bradbury &
Fincham, 1988a). It can be seen for both husbands and wives
that two thirds of the correlations were significant and that
spouses' attributions correlated with their response to partner
behavior in the expected manner. For example, the positive
correlation between husbands' intent attributions and the
reciprocation of negative behavior shows that husbands who
176
tended to see negative wife behavior as intentional responded
negatively to such behavior. In sum, available data suggest that
attributions are related to marital behavior and attributions may
indeed mediate spouse behaviors.
TABLE 3. Correlations Between Responsibility Attributions andLikelihood of Behavior Sequences in roblem Solving Discussion.
Behavioral SelfishSequence Intent Motivation Blame
Husbands
W+ --- > H+ -.36 -.26 -.25
W- ._-> H- .31 ns ns
Wives
H+ ... > w+ -.45 -.26 ns
H- --- > w- ns .36 .36
Note: ns - nonsignificant correlations (~ > .05).Higher attribution scores reflect more negative intent, more
selfish motivation, and greater blame.
With an association between attributions and behavior
established, Fincham and Bradbury (1988b) manipulated
attributions for a negative partner behavior in the laboratory to
investigate the impact on subsequent behavior towards the partner.
They recruited one spouse as a confederate. The confederate was
asked to assist the experimenter by writing a negative description
of his or her partner. The experimenter provided an outline of
177
the description and the confederate's task was to choose from a
list of items that could be inserted into the description so that
his or her spouse would find it credible. Once this was done, the
confederate copied the complete description onto a sheet of
paper. The experimental manipulation consisted of the
instructions that appeared on the top of the page onto which the
description was copied. In one condition, the instructions simply
asked for "an honest account of your partner's qualities". In a
second condition, the instructions provided a plausible external
cause for the negative description, thus allowing the subject
spouse to discount the causal role of the confederate spouse.
The instructions in this condition asked for a description of "your
spouse's negative qualities and his/her personal weaknesses".
Fincham and Bradbury (1988b) found that the behavior of
distressed spouses was affected by the manipulation: spouses who
located the cause of the negative behavior in the confederate
were more negative towards their partner in a subsequent
discussion than those who attributed the negative behavior to the
circumstances. However, they also exhibited more positive
behavior towards the partner. To account for this unexpected
finding it was argued that an internal attribution for the negative
partner behavior led to greater arousal in distressed spouses and
that the valence of the behavior resulting from this arousal was
influenced by the constraints of the laboratory situation (i.e.,
public behavior recorded on Videotape) leading spouses to present
themselves in a balanced way to the experimenters. In any event,
178
there is preliminary evidence consistent with the view that
attributions influence behavior.
Unfortunately, data relating to attributions and behavior
reflect several important limitations. First, the correlational
studies described earlier relate observed behavior to general
attributions regarding a marital difficulty rather than to
attributions for specific spouse behaviors to which the spouse then
responds. Ultimately, a more microanalytic approach is needed to
address the mediational assumption under consideration. For
example, a study currently underway asks spouses to indicate the
perceived intent of each partner communication in an interaction
so that the relation between this attribution and the spouse's
response to the communication can be examined. Second, no
attempt has been made to determine whether attributions meet
the criteria of a mediating variable. At the very least, a
significant correlation between a spouse behavior and a partner
response should disappear when the partner's attribution for the
behavior is statistically controlled (see Baron & Kenny, 1986).
Third, the single experimental study on attributions and
behavior yielded weak results and a replication of this study is
therefore underway. As a consequence of these limitations,
existing data only suggest a possible causal relation between
attributions and behavior and cannot be used to draw strong
conclusions about the attribution-behavior relation.
The relation of attributions to marital satisfaction and to
marital behavior do not exhaust the issues investigated in marital
attribution research. Attention has been devoted to several
179
additional issues, including the relation between attributions for
partner behavior and for own behavior (Fichten, 1984; Fincham &
Beach, 1988; Fincham, Beach & Baucom, 1987; Lavin, 1987), the
measurement of attributions (e.g., relating to causal dimensions,
Fincham, 1985b; Bradbury & Fincham, 1989b; spontaneous
attributions, Bradbury & Fincham, 1988b; Holtzworth-Munroe &
Jacobson, 1988; Stratton, Heard, Hanks, Munton, Brewin &
Davidson, 1986), responsibility for contribution to marital activities
(e.g., Fincham & Bradbury, 1989a), attributions for turning points
in the relationship (Lloyd & Cate, 1985; Surra, Arizzi &
Asmussen, 1988), attributional style (Baucom, Sayers & Duhe,
1989), individual difference variables (e.g., Bradbury & Fincham,
1988c; Fincham & Bradbury, 1989b), and the role of attributions
in jealousy (Buunk, 1984), relationship termination (e.g., Fletcher,
1983; Harvey, Weber, Galvin, Huszti, & Garnick, 1986), sexual
dysfunction (Fichten, Spector & Libman, 1988), and marital
violence (for a review see Holtzworth-Munroe, 1988).
However, the two assumptions identified, that attributions
account for variance in marital satisfaction and mediate behavior
exchanges in marriage, are central to this field of research.
Indeed, they constitute the raison d'etre for contemporary marital
attribution research. The preceding review shows that
considerable progress has been made in providing an empirical
foundation for these assumptions. It is also apparent, however,
that the task of providing evidence for these assumptions is far
from complete. Moreover, once fully documented, the associations
raise the more important question of why they exist. Our
180
exploration of attributions in marriage has therefore only just
begun and the remainder of this chapter is devoted to the
question, "where to?"
Quo vadis?
The goal of this section is to highlight directions for future
research suggested by the earlier review of the marital attribution
literature. Particular emphasis will be placed on avenues of
inquiry that will facilitate a more complete empirical foundation
for the assumptions made in marital attribution research and
increase our understanding of the role of attributions in marriage.
Four issues are addressed: (a) increasing confidence in basic
findings; (b) investigating the causal role of attributions; (c) the
need for conceptual integration; and, (d) strengthening ties with
the social psychological literature on attribution.
Increasing confidence in basic findings
The preceding review shows that the association between
attributions and marital satisfaction is a reliable phenomenon, but,
as Huston and Robins (1982, p. 919) note, "It is rare for research
on close relationships to approach, in a systematic fashion, the
problem of ruling out plausible alternative explanations of the
obtained effects." There are several alternative explanations for
this association.
Methodological artifact. The most obvious alternative
explanation is that the attribution findings in marital research
are a methodological artifact. This concern is manifest in two
181
forms. The first involves possible overlap in the content of
measures used to assess attributions and satisfaction. The second
arises from the observation that spouses may only make
attributions when asked to do so by psychologists. Each is
considered in turn.
Inspection of the items used in standard measures of marital
satisfaction arises the possibility that attributions and satisfaction
may be associated due to overlapping item content. For example,
standard satisfaction inventories typically include questions
regarding the degree to which spouses agree versus disagree about
various marital issues (e.g., finances, in-laws). Because marital
dissatisfaction thereby is defined, in part, as the tendency to
report disagreement across several martial domains, scores on
these inventories are likely to be related to a tendency to see
causes of events as operating across many areas of the marriage.
That is, both assessments entail the degree to which negative
events occur across many areas of the relationship.
One means of addressing this problem is to use only overall,
evaluative judgments of the marriage to assess marital satisfaction
(see Fincham & Bradbury, 1987b). Unfortunately, no published
studies have examined this issue. However, Baucom, Bell and
Duhe (1982) found the usual association between a daily
satisfaction rating and the global causal dimension. In a more
complete investigation of this issue, we found essentially the same
results for causal and responsibility attribution dimensions using
different measures of satisfaction. Table 4 shows the correlations
obtained between the attribution dimensions and a standard
182
measure of marital satisfaction (Marital Adjustment Test, Locke &
Wallace, 1959), two measure of satisfaction that consist solely of
evaluative items (Marital Quality Index, Norton, 1983; Kansas
Marital Satisfaction Scale, Schumm, Paff-Bergen, Hatch, Obiorah,
Copeland, Meens & Bugaighis, 1986), and a measure of
satisfaction comprising three semantic differential items (good-bad,
pleasant-unpleasant, satisfied-dissatisfied). It can be seen that the
correlations obtained between attributions and these various
measures of marital quality are very similar. It therefore appears
that the association between attributions and marital satisfaction i&
not due to overlap in the measures of these constructs.
The second concern, that attributions may not occur
spontaneously, takes two forms. First, it might be argued that
spouses seldom make attributions spontaneously and that findings
are relevant only to the reactive methods used to assess
attributions (i.e., explicit questions about causes). Second, the
hypothetical partner behaviors used as stimuli in most studies may
not be relevant to everyday life.
Some existing studies provide data that address these issues.
For example, Holtzworth-Munroe and Jacobson (1985) found that
attributions coded from open-ended responses to partner behavior
were not only related to marital satisfaction but also to spouses'
ratings of the attributions on underlying causal dimensions.
Similar findings have been obtained for dating couples (Grigg,
Fletcher & Fitness, 1989). As regards hypothetical stimulus
behaviors, Fincham and Beach (1988) showed that while
attribution ratings of hypothetical behaviors and real behaviors
183
TABLE 4. Correlations Between Attribution Dimensions andMeasures of Marital Satisfaction.
AttributionDimension
Husbands (n= 105)
Locus
Stability
Globality
Intent
Motivation
Blame
Wives (n= 110)
Locus
Stability
Globality
Intent
Motivation
Blame
MAT
-26*
-42
-42
-42
-41
-38
-34
-43
-39
-39
-33
MQI
-25*
-33
-39
-44
-43
-36
-34
-32
-34
-31
KSS
-34
-43
-49
-43
-40
-29*
-40
-39
-46
-35
SD
-31
-38
-41
-42
-39
-26*
-37
-39
-38
-31
Note: MAT = Marital Adjustment Test, KSS = KansasSatisfaction Scale, MQI = Marital Quality Index, SD = SemanticDifferential.
Nonsignificant correlations (l! > .01; and decimal pointshave been omitted.
* denotes significance at l! < .01 all other correlationsare significant at 2 < .001.
~mW%'~~~~Wlr,m~t$"~
184
differed in absolute values, the pattern of differences found in
prior research distinguished distressed from nondistressed spouses
for both types of events.
These results are encouraging but leave unaddressed the
question of whether attributions occur spontaneously (without any
prompting) in marital interaction and, if so, the conditions under
which they occur. Attempts to code attributions in marital and
family interactions have been undertaken but are highly
problematic (for a detailed discussion see Bradbury &
Fincham, 1988b). In any event, unlike attributions that remain
private, public or communicated attributions are likely to be
affected by the social environment in which the occur and the
rules of discourse.
Different factors may therefore influence private and
communicated attributions. Thus it is questionable whether
communicated attributions can be used as a criterion for the
occurrence of private attributions. It appears that "unsolicited
attribution" produced, for example, by a request to think out loud
may be the most appropriate criterion for evaluating the
occurrence of private attributions. Judged by this standard, there
is some evidence for the occurrence of attributions (e.g.,
Holtzworth-Munroe & Jacobson, 1985). To in~rease confidence in
the relevance of attributions, replication of this basic finding is
needed together with further delineation of the events most likely
to engage attributional processing.
Spouse attributions as reports of marital events. A second
rival hypothesis for the association between attributions and
185
satisfaction is that attributions are simply accurate reports of
the events distressed and nondistressed spouses experience in
their marriages. That is, compared to happy spouses, distressed
spouses are likely to encounter higher rates of negative behavior,
and it may be accurate to infer that the causes of such behaviors
are located in the spouse, are stable, and influence many areas of
their marriage, and that their partners are responsible for these
repeated negative experiences.
There is a hidden assumption in this viewpoint, namely, that
there is some objective criterion against which the accuracy of
attributions can be evaluated. If such a criterion exists for
marital attributions, it has not been articulated, and any attempt
to erect such a criterion should take into account the fate of
earlier attempts in social psychology to determine the accuracy of
social judgments (cf. Cronbach, 1955). Nonetheless, the issue of
accuracy in social judgments has recently been resurrected and
therefore requires further consideration.
Funder (1987) offers two pragmatic criteria for determining
the accuracy of social judgments. The first, interobserver
agreement, is difficult to apply to marital attributions. For a
given partner behavior, a spouse and another observer may make
different attributions as a function of their prior experiences with
the partner, the relevance of the behavior to them, and its
implications for future interaction. As indicated earlier, these
variables are known to influence attributions. Despite a lack of
agreement, the two attributions are equally valid and it would be
inappropriate to label either of them as inaccurate. The second
186
standard is that a social judgment is accurate if it allows
prediction of behavior. To the extent that the issue of
accuracy remains applicable to marital attributions, our review
showed that attributions do predict the attributor's behavior in
marital interaction.
However, the accuracy position is weakened further by the
fact that (a) satisfied and dissatisfied spouses are found to make
different attributions when responding to identical, hypothetical
stimuli and (b) attributions made for hypothetical stimuli and
stimuli unique to each marriage predict marital satisfaction equally
well (Fincham & Beach, 1988). Although it could be maintained
that spouses transform the hypothetical stimuli in a way that
makes them unique to their marriage, this implies nonetheless that
a psychological process is in fact at work and that attributions do
not simply mirror an external "reality".
It is not clear that attributions in marriage can be classified
as accurate or inaccurate. In any event, no research has
examined the issue of accuracy, an issue that must be addressed
if a plausible standard for evaluating the accuracy of attributions
can be found.
The role of depression. It is also possible that the
attribution patterns found in the marital literature do not reflect
a marital phenomenon but instead occur because attributions and
satisfaction covary with depression (see Gotlib & McCabe, in
press; Robins, 1988). An attempt has been made to address
this question. Fincham, Beach and Bradbury (1989) found that
responsibility attributions made for hypothetical, negative partner
187
behaviors accounted for variance in marital satisfaction with levels
of self-reported depression held statistically constant in a sample
of community wives. They also showed that maritally distressed
wives diagnosed as clinically depressed following a structured
diagnostic interview and nondepressed wives who were maritally
distressed did not differ in the responsibility attributions they
offered for hypothetical, negative partner behaviors. However,
both groups differed in the usual manner from happily married
wives. Fincham and Grych (in press) showed also that both
husbands' and wives' self-reported depression does not account for
the association between satisfaction and attributions for partner or
child behaviors.
Although there is as yet no evidence to suggest that the
attribution-satisfaction association is an artifact of depression, our
understanding of the relation between attributions, depression and
marital satisfaction is very incomplete. For example, the
attributional reformulation of learned helplessness predicts that
depressed spouses should locate the cause of negative marital
events in themselves. In contrast, the marital attribution
literature suggests that depressed (distressed) spouses should
locate the causes of such events in the partner. These
contradictory predictions need to be evaluated empirically.
Research is also needed to investigate the possible causal
relations among attributions, depression, and marital satisfaction to
increase confidence that the marital attribution findings reflect a
phenomenon associated with marriage rather than depression.
188
Spouse attributions are not unique to marriage. A related
rival hypothesis is that spouse attributions for marital events are
not unique to the marriage but reflect a manner of making
attributions that is used across various interpersonal relationships.
At first glance, this hypothesis appears to be inconsistent with
earlier cited research that attributions ratings vary across
relationships (e.g., Taylor & Kouivumaki, 1976). However, this is
not the case because the pattern of findings across happy and
distressed spouses may remain the same. That is, it is possible
that happy spouses, compared to dissatisfied spouses, make more
benign judgments regarding the behaviors of spouses, other family
members, friends and so on even though the magnitude of ratings
varies across relationships.
There is some evidence to support this view. Fincham and
Grych (in press) found the same pattern of causal attributional
differences between distressed and nondistressed spouses when
they rated the causes of marital difficulties and child behaviors.
Indeed, the ratings of causal locus, stability, and globality
correlated significantly. These findings provide limited evidence
because the majority of variance in these judgments was not
shared (common variance ranged from 9% to 11%). Thus the
evidence to support the view that spouses view attributions
consistently across relationships is quite weak. Greater attention
needs to be paid to this issue to increase our confidence that the
patterns of attribution found in the marital literature indeed
reflect a marital phenomenon.
189
Investigating the causal role of attributions
The earlier review shows that insufficient attention has been
given to establishing the potential influence of attributions on
marital satisfaction and marital behavior. Although the difficulty
of this task makes this neglect understandable, it does not
diminish the importance of evaluating the consequences of
attributions in marriage. Testing the impact of attributions In
marriage not only poses practical and ethical difficulties but also
conceptual ones. How might researchers tackle this critical issue?
Recognition of the clinical roots of marital attribution
research suggests a natural context in which the impact of
attributions can be tested, namely, marital therapy outcome
research. The goal of therapy is to improve marital satisfaction
and hence it lends itself to experimental manipulation of variables
such as attributions. Although four outcome studies have
attempted to change attributions in therapy (Baucom & Lester,
1986; Emmelkamp et al., 1988; Epstein, Pretzer & Fleming, 1987;
Margolin & Weiss, 1978) they do not provide data to assess the
impact of attributions. For example, none of them include
measures of attributions following therapy and thus do not
examine (a) whether the intervention actually altered attributions
or (b) whether the rationale provided to clients for alternative
interventions affects attributions. It is therefore difficult to
interpret the results of these studies in regard to attributions, a
difficulty compounded by the fact that none of the studies
investigate specifically the effect of attribution change
because they use multifaceted cognitive interventions. Thus, In
190
clinical outcome research there remains "no direct evidence that
the modification of attributional processes leads to behavior
change" (Berley & Jacobson, 1984, p. 32).4 This is indeed an
unfortunate state of affairs given the status accorded attributions
in clinical writings.
The current status of outcome research should not blind us
to its potential for increasing our understanding of the impact of
attributions. This potential is briefly illustrated by describing an
outcome study that would address the causal status of attributions.
Before turning to this task, it is necessary to outline an important
conceptual problem. Setting aside the radical behaviorist view
that unobservable variables (e.g., cognitions) are not the proper
domain of psychological inquiry, it must be recognized that it is
not possible to demonstrate the influence of attributions on
satisfaction or behavior. As a hypothetical construct, an
attribution can only be inferred from behavior (e.g., response
ratings) and can never be measured directly. Thus in
experimental research we can only demonstrate that the
manipulation of stimulus conditions hypothesized to influence
attributions are related to particular outcomes. This observation
is critical because it has important methodological implications as
illustrated below.
4Despite at least a dozen studies on attribution retraining in research onlearned helplessness (see Forsterling, 1988), there has been no demonstrationthat this training (repeatedly telling children that they failed on an academic taskbecause they did not try hard enough) changes attribution style or that changesin attribution actually produce changes in behavior. It is quite possible, forexample, that this clinically naive intervention induces guilt that is responsible forany behavioral change (for further discussion see Fincham, 1988).
191
Consider an outcome study where there are two treatment
groups and a wait list control group. The treatments consist of a
cognitive intervention designed to change attributions and a
standard behavioral intervention that focuses on communication
and problem solving skills. Assessments are made immediately
prior to treatment, at the end of therapy, six months following
therapy and one year following therapy. The variables assessed
include marital satisfaction, attributions, observed behavior
during a problem solving discussion, and daily reports of behaviors
over a two week period. How can these data address the issue
under consideration?
Most obviously they allow one to examine whether the
treatments were successful in altering marital satisfaction
(treatment versus control) and differed from each other (cognitive
treatment versus behavioral treatment). Positive findings would
suggest that attributions influence satisfaction. However, further
tests are needed to justify such a conclusion. It must be shown
that (a) the cognitive intervention actually changed attributions
(pre cognitive treatment versus post cognitive treatment); (b) that
these changes are correlated with changes in marital satisfaction;
and, (c) statistically controlling attributions reduces significantly
the effects obtained for satisfaction. Similar tests could be
conducted to examine attributions and daily behaviors and
behaviors observed during problem solving discussions. Notice
that an analogous set of analyses can also be conducted to
examine the impact of the behavioral intervention. Thus it is
possible to determine whether changes in satisfaction are produced
192
by attributions, behavior to both of these variables. Finally,
examination of the follow-up data allow one to test whether
further changes in attributions and behavior are associated with or
predict relapse (marital distress).
There are several other issues that would need to be
addressed when the proposed study is considered from a clinical
perspective. For example, the actual implementation of an
attributionally oriented intervention is not straightforward.
However, these need not be outlined in the present context. It is
sufficient to note that more compelling evidence relating to the
causal status of attributions is potentially available and can be
obtained in an ethically acceptable manner. Because considerable
resources are needed to conduct such research, it should also be
noted that appropriate analysis of correlational evidence can
enhance our current understanding of the impact of attributions.
Specifically, correlational data on attributions, satisfaction, and
behavior could be used to examine whether attributions are a
mediating or a moderating variable. For example, do attributions
mediate behavior exchanges? That is: (a) does partner behavior
account for a significant portion of the variance in subsequent
spouse attributions?; (b) is variation in spouse attributions related
to changes in spouse behavior?; and, (c) does a previously
significant relation between partner behavior and spouse behavior
disappear when attributions are held constant statistically?
Failure to meet anyone of these tests would indicate that
attributions are a moderating rather than a mediating variable
(see Baron & Kenny, 1986).
193
Conceptual integration
"We shall not attain a conceptual framework by collecting
more experimental results. Rather, conceptual clarification is a
prerequisite for efficient experimentation" (Heider, 1958, p. 4).
Although applicable to many areas of psychology, Heider's
observations are particularly relevant to the study of marital
attributions. This field has arisen in the relative absence of
theoretical models to guide research and it is perhaps not
surprising that it has been viewed as confused and incoherent
(e.g., Baucom, Epstein, Sayers & Sher, 1989). By making the
tacit assumptions in this research explicit, an attempt was made in
the earlier review to rectify this perception. Nonetheless, the
assumptions identified do not provide the kind of theoretical
guidance needed to advance this field of inquiry.
The need for three steps towards conceptual integration is
particularly salient. First, there is a clear need to offer a
framework that integrates the study of attributions, behavior, and
satisfaction. Attributions have been studied in relation to either
satisfaction or behavior with little attention to how these three
variables might be interrelated. It seems likely that spouse
attributions influence behavior which, in turn, alters partner
behavior and that this process leads ultimately to changes in
spouse satisfaction. An attempt to provide such a framework is
outlined elsewhere (see Bradbury & Fincham, 1990).
Second, the study of attributions in marriage needs to be
integrated with the broader field of research on cognition. When
this is done several omissions in marital attribution research
194
become evident. For example, current research is devoted
exclusively to the study of cognitive content, that is, what
judgments are made. However, the study of cognition shows that
more complete understanding of a cognitive variable such as an
attribution requires attention to the (nonconscious) cognitive
processes and cognitive structures that influence attribution
judgments, that is, how judgments are made. For example, a
spouse who is asked to make an attribution for a recent argument
is likely to recall similar arguments and determine whether the
causes of these arguments aid in understanding the cause of the
present one. In fact, determining the implication of the cause of
the present argument for the future (judging the stability of the
cause), rests on recall of the causes of past arguments and/or
knowledge about the general properties of the cause in question.
Thus factors that affect the retrieval of relationship relevant
material and/or general knowledge from memory require attention
for a complete understanding of attributions in marriage. A more
detailed exploration of the implications of integrating attribution
research with the study of cognition can be found in Fincham,
Bradbury and Scott (in press).
Third, the study of attribution needs to be integrated into a
broader contextual model that includes consideration of
personality, cognitive variables, affective variables, and behavior.
This is particularly relevant in view of the observation that most
theories in the marital domain "either effectively explain a small
segment of the marital interaction, but lack the scope and range
of the many factors involved, or else have the range and broad
195
perspective, but lack detail and intricacy at the practical dyadic
level of analysis" (Newcomb & Bentler, 1981, p. 92). Placing
attributions into a broader contextual model would thus provide a
level of analysis seldom found in the marital literature (for an
attempt to fill this gap, see Bradbury & Fincham, 1989a).
Strengthening ties with the social psychological literature
Although the idea of investigating attributions in marriage was
certainly influenced by the dominance of attribution research in
social psychology (see Fincham & Bradbury, in press), research in
this domain has proceeded relatively independently of basic social
psychological research on attributions. For example, the classic
attribution models (e.g., the ANOVA model, correspondent
inference theory) have had no impact on marital attribution
research. It is arguable whether this has hindered progress
because these models are not easy to apply to marriage and they
have been shown to have serious deficiencies (e.g., inattention to
the role of world knowledge for attributions, see Hewstone, in
press). However, it is disturbing that the relative merits and
demerits of these models for marital research have not been
discussed, an omission that could indicate ignorance of them.
The need to study attributions specifically in the context of
close relationships should not be seen to imply that basic social
psychological research and theory is irrelevant to this enterprise.
On the contrary, there is much to be gained from strengthening
ties with this research literature. Of particular note is Weiner's
(1986) book, An attributional theory of motivation and emotion, a
196
monograph that sets forth what is perhaps the first fully fledged
attribution theory. On an occasion honoring Bernard Weiner
there is a particular poignancy to concluding the present analysis
by noting the value of this work for marital research.
Earlier a limitation of Weiner's theory was noted, pertaining
to the treatment of inferred intent, and it must be acknowledged
at the outset that his theory arises mainly from work on
achievement motivation.5 This is important to acknowledge
because, as Weiner himself notes, he is concerned with
attributions for the outcomes of behavior and not with attribution~
for the behavior per se. In close relationships outcomes are less
clear and much of the commerce of these relationships concerns
attributions for behavior. Notwithstanding these observations,
Weiner's (1986) theory could serve as a rich theoretical framework
for marital research, especially in view of it detailed treatment of
emotion, a factor central to understanding close relationships.
Although this is not the context in which to provide a
detailed review of Weiner's theory, its value for the study of
marriage can be briefly illustrated. According to the theory, each
causal attribution dimension results in specific affects (e.g.,
locating the cause of negative events in the self will effect pride
and self-esteem). Simply incorporating this core feature of the
5Weiner believes his theory applies equally to the relationship domain andindeed provides interesting data relevant to this claim. However, these data arelimited in that they deal with matters such as requests for dates where a clearoutcome can be specified and where there is no extensive history between thepartners. Thus the status of his theoretical claims for close relationships requirefurther empirical evaluation.
197
theory into marital research will provide a finer level of analysis
of attributions as no dimension specific hypothesizes have been
evaluated in marital research. Such research could, in turn,
provide a "real world" evaluation of Weiner's (1986) theory. In a
similar vein, aspects of the theory have already influenced
theorizing on marital conflict. For example, Weiner (1986)
predicts that causal stability influences behavioral expectancies
that, in turn, give rise to the emotions of hopelessness and
hopefulness and that expectancies and emotions mediate the
relation between the stability dimension and behavior. Drawing
on Weiner's (1986) work, a similar sequence of events has been
hypothesized in a recent model of conflict in close relationships
(Fincham, Bradbury & Grych, in press). The latter model,
however, incorporates responsibility attributions in this sequence,
an omission in Weiner's (1986) theory that may limit its ultimate
usefulness in marital research. However, this is an empirical
question that, regardless of outcome, should not detract from the
gold mine of ideas relevant to marital research in Weiner's
attributional theory of motivation and emotion.
Conclusion
The major goal of this chapter was to illustrate the value of
an attributional approach for understanding marriage. To this
end, existing research was organized in terms of the two tacit
assumptions found in the marital attribution literature. This
exercise demonstrated that the literature shows far greater
coherence that previously assumed. However, it also showed that
198
the bulk of research focuses on the concurrent relation between
attributions and marital satisfaction and is therefore quite limited.
This lead naturally to a consideration of the ways in which the
contribution of an attributional approach to understanding
marriage might be more fully realized.
Four avenues of future inquiry were therefore identified.
Two of these, increasing confidence in basic bindings and
investigating the causal role of attributions, entail further research
on the two assumptions identified in the review. Although
important, such efforts are insufficient to advance significantly our
understanding of attributions in marriage. The assumptions
evident in the marital attribution literature have not been related
to each other and do not amount to a coherent conceptual
framework. Consequently, two additional avenues of future inquiry
were discussed, namely, the need for conceptual integration and
development and the strengthening of ties with the social
psychological literature on attribution.
There is little doubt that research on attributions in marriage
has established itself as a legitimate field of inquiry in psychology.
The gains made are impressive and have resulted in a more
complete understanding of close relationships and of attributions.
However, the field may be at a crossroads. It no longer suffices
to document the concurrent associations between attributions and
marital satisfaction/behavior; yet no clear alternative body of
research has emerged. At the present time, the key to advancing
this literature is likely to lie in taking stock of its strengths and
weaknesses and in offering conceptual frameworks to guide future
199
research. In the absence of such efforts, there is the danger that
this field may collapse under the weight of its own (incoherent)
data. Avoiding this eventuality presents a challenge because the
demands of the next generation of research in this domain are
much greater than those of present one. However, the benefits
are also far greater and include not only an increased
understanding of marriage but also the potential to enrich
attribution theory and research in social psychology.
200
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Author Index]Abelson, (1981) 141Abramson, Seligman, & Teasdale, (1978) 70, 168Adler, (1958) 117Alffleck, Tennen, Croog, & Levine, (1987) 96Anderson, 12Anderson & Arnoult, ~198?) 38Anderson & Arnoult, 1985a) 12Anderson & Arnoult, 1985b) 20, 45Anderson & Slusher, (1986) 35, 36Anderson, ~1983) 47, 143Anderson, 1983a) 26Anderson, 1985) 31Anderson, Horowitz, & French, (1983) 26, 45, 58, 71Anderson, Jennings, & Arnoult, (1988) 45Antaki & Brewin, (1982) 127Antonovsky, (1979) 117Antonovsky, (1987) 117Arkin & Baumgardner, (1985) 12Arkin, Cooper, & Kolditz, (1980) 15Atkinson & Raynor, (1978) 106
193
175179, 184179195179
166, 170,
Bailyn, (1987) 138Barney, (1986) 150Baron & Kenny, (1986) 178, 192Barrett, (1972) 118Battista &. Almond, (1973) 111Baucom & Lester, (1986) 189Baucom, Bell, & Duhe, (1982) 181Baucom, Epstein, Sayers, & Sher, (1989)Baucom, Sayers, & Duhe, (1989) 179Berley & Jacobson, (1984) 190Bianchi, (1982) 112Bond, (1983) 89Bond, (1986) 88Bower, Black, & Turner, (1979) 141, 144Bradand & Lerner, (1975) 12Bradbury & Fincham, 1988a)Bradbury & Fincham, 1988b)Bradbury & Fincham, 1988c)Bradbury & Fincham, 1989a)Bradbury & Fincham, 1989b)Bradbury & Fincham, 1990)Bradbury, (1989) 172, 175Bradley, (1978) 15Brand, (1987) 88Bulman & Wortman, (1977) 95, 113
166, 193
IDate is in parentheses after the name of the author. Page numbersfollow next.
208
Buss, (1978~ 96Buss, (1979 97Buunk, (19 4) 179
Cantor, Norem, Niedenthal, Langstom, & Brower, (1987) 143Carlson, (1981) 141Chamberlain & Zika, (1988) 117Chenug, (1986) 88Chodoff, Friedman, & Hamburg, (1964) 111Colwill, (1982) 153Crocker, (1981) 25Crocker, Hannah, & Weber, (1983) 13Cronbach, (1955) 185Cutrona, (1983) 77Cutrona, Russell, & Jones, (1985) 71, 72, 76
Deal & Kennedy, (1982) 147Dyck & Rule, (1978) 12
Eccles, (1987) 138Eisen, (1979) 17Elig & Frieze, (1979) 55, 57, 66, 127Emmelkamp et aI., (1988) 189Engel, (1988) 92Enz & Schwenk, (1989) 150Epstein, Pretzer, & Fleming, (1987) 167, 189Erickson, (1964) 117Erickson, (1976) 117
Feather, 11975) 102Feather, 1983) 20Feather, 1986) 102Feather, 1988) 102Feldman, (1984) 150Fichten, (1984) 179Fichten, Spector, & Libman, (1988) 179Fincham 163Fincham & Beach, (1988) 179, 182, 186Fincham & Bradbury, 1987a) 172Fincham & Bradbury, 1987b) 181Fincham & Bradbury, 1988a) 174Fincham & Bradbury, 1988b) 176, 177Fincham & Bradbury, 1989a) 179Fincham & Bradbury, 1989b) 179Fincham & Bradbury, 1990) 172Fincham & Bradbury, in press 195Fincham & Grych, in press 187, 188Fincham & Jaspars, (1980) 97, 168Fincham & O'Leary, (1983) 174Fincham & Roberts, (1985) 168Fincham & Schultz, (1981) 168Fincham, !1983) 169Fincham, 1985) 17Fincham, 1985a) 169
138
209
Fincham, (1985b) 179Fincham, Beach, & Baucom, (1987) 179Fincham, Beach, & Nelson, (1987) 174Fincham, Beach, & Bradbury, (1989) 186Fincham, Bradbury, & Grych, in press 197Fincham, Bradbury, & Scott, in press 194First, Olson, & Frieze, (1987) 134Fisk & Taylor, (1984) 97Fletcher, (1983) 179Follette & Jacobson, (1987) 72, 76Frankl, (1967) 117Frankl, (1969) 117Frieze 126Frieze et aL, (1983) 129, 131Frieze et aL, (1988) 139Frieze, (1976) 16Frieze, Bar-Tal, & Carroll, (1979) 127Frieze, Snyder, & Fontaine, (1978) 128Frost, Frieze, & Perloff, (1987) 132, 134Funder, (1987) 185
Gioia & Poole, (1984) 143Gioia, (1986) 143, 144Golding, Resnick, & Crosby, (1983)Gotlib & McCabe, in press 186Graham & Long, (1986) 108Gramose & Portwood, (1987) 150, 151Grigg, Fletcher, & Fitness, (1989) 182
Hamilton, (1981) 12Hanagan, (1977) 145Hart, (1968) 169Harvey & Tucker, (1979) 97Harvey, Weber, Galvin, Huszti, & Garnick, (1986) 179Heider, (1958) 163, 164, 169, 193Heinemann, Bulka, & Smetak, (1988) 95Hocking, (1957) 111, 118Holtzworth-Munroe, & Jacobson, (1985) 170, 182, 184Holtzworth-Munroe, & Jacobson, (1988) 179Holtzworth-Munroe, (1988) 179Huston & Robins, (1982) 180
Jacobson & Margolin, (1979) 165, 168Janoff-Bulman & Frieze, (1983) 96Jaspar, Fincham, & Hewstone, (1983) 97Jones & Harris, (1967) 12Jones & McGillis, (1976) 14Jones & Davis, (1965) 14
Kahneman, Slavic, & Tversky, (1982) 49Kanter, (1977) 144Kelley & Michela, (1980) 164Kelley, (1967) 13Kelley, (1973) 13
25
60
151
210
Klinger, (1977) 117Knight & Vallacher, (1981) 165Kohlberg, (1984) 98Kruglanski, (1979) 97Kruglanski, (1980) 22Kunda, (1987) 146
Lane, Anderson, & Kellam, (1985)Lau & Ware, (1981) 70Lavin, (1987) 179Lazarus & Folkman, (1984) 85Lefcourt, (1981) 55, 58, 70, 72, 79Lefcourt, (1983) 77Leung & Bond, (1984) 89Leung & Foster, (1985) 88Lewin, (1951) 163Lloyd & Cate, (1985) 179Locke & Wallace, (1959) 182Lord & Kernan, (1987) 144Lord & Novick, (1968) 64Louis, (1980) 149
Maddi, (1971) 117Maehr & Kleiber, (1980) 106Maehr & Nicholls, (1980) 91, 131Maehr, (1974) 91, 130Maehr, (1987) 149Mak, (1984) 88Mak, (1988) 88, 89Margolin & Weiss, (1978) 189Martin, (1982) 143, 149Martin, (1983) 149Maslow, (1987) 106, 117May, (1969) 117Mayberry, (1985) 150McClelland, (1961) 131McGuire, (1985) 12Meece & Frieze, (1982) 129Meglino, Ravlin, & Adkins, (1989)Meyer & Mulherin, (1980) 12Michela, Peplau, & Weeks, (1982)Miller (1976) 33Miller & Ross, (1975) 32Monson & Snyder, (1977) 17Morishima, (1982) 90Moss 126Moss & Frieze, (1987) 144Murrell & Frieze, (1990) 139
Newcomb & Bentler, (1981) 195Nielson & MacDonald, (1988) 95, 96Nisbett & Ross, (1980) 12Norton, (1983) 182
211
Olson 126Olson & Frieze, (1987) 155Olson, Frieze, & Good, (1987) 153Ouchi, (1981) 90
Parsons & Goff, (1980) 101, 102Parsons, (1982) 102Passer, (1977) 60Passer, Kelley, & Michela, (1978) 61Pennington & Hastie, (1986) 143Peterson, Semmel, von Baeyer, Abramson, Metalsky, &
Seligman, (1982) 55, 58, 71, 72Posner & Schmidt, (1984) 150, 156Posner, Kouzes, & Schmidt, (1985) 150, 152
Raynor, (1980) 106Regan, Straus, & Fazio, (1974) 165Reker & Wong, (1988) 117Rest, (1979) 98Robins, (1988) 186Ross, (1977) 88Ross, Bierbrauer, & Hoffman, (1976) 12Rotter, (1966) 70Russell 55Russell & McAuley, (1986) 69Russell et aI., (1985) 66, 67Russell, (1982) 55, 57, 61, 64, 74, 107Russell, Cutrona, Rose, & Yurko, (1984) 66, 67Russell, Frieze, & Olson, (1987) 152Russell, McAuley, & Tarico, (1987) 55, 61, 63, 65-67Rychlak, (1976) 92, 96
Schaubroeck & Green, (1989) 149Schein, (1985) 150Schein, (1986) 147Schneider, Hastorf, & Ellsworth, (1979) 12Schultz & Schleifer, (1983) 168Schumm, Paff-Bergen, Hatch, Obiorah, Copeland, Meens, &
Bugaigh, (1986) 182Seligman, Abramson, Semmel, & von Baeyer, (1979) 20Shaver, (1985) 168Shrivastra & Schneider, ~1984) 149Silver & Wortman, (1980 95Silver, Boon, & Stones, 1983) 95Soderstrom & Wright, (1977) 112Stern, (1983) 61Stratton, Heard, Hanks, Munton, Brewin, & Davidson, (1986)
179Sue & Sue, (1973) 88Sujan, (1986) 45Surra, Arizzi, & Asmussen, (1988) 179
212
Taber, (1963) 114Taylor &. Kouivumaki, (1976) 165, 188Taylor, (1967) 92Taylor, 1983) 95Taylor, ichtman, & Wood, (1984) 96Tetlock & Levi, (1982) 15Triplett, (1897) 163
Uleman, (1987) 14
Vallacher & Wegner, (1987) 143Vandenberg & Scarpello, (1990) 151Vogel, (1979) 90
70( 1980)89
151
Wallston & Wallston,Wan & Bond, (1982)Wanous, (1980) 150,Weiner 7Weiner, 1979) 57, 59, 61, 67, 69Weiner, 1983) 61Weiner, 1985) 57, 59, 61, 67-69, 71, 170Weiner, 1985a) 85, 126Weiner, 1985b) 101, 127Weiner, 1986) 16, 57, 59, 61, 67-69, 71, 168, 169, 195-197Weiner, rieze, Kukla, Reed, Rest, & Rosenbaum, (1971)
126Weiner, Nierenberg, & Goldstein, (1976) 17Weiner, Russell, & Lerman, (1979) 17Weiss & Heyman, in press 173Wetzel, (1982) 15Wimer & Kelley, (1982) 16Wong 84Wong & Reker, (1984) 94Wong & Weiner, (1981) 16, 84, 95, 112Wong, ~979) 89Wong, 1988) 143Wong, 1989) 94, 117Wong, elerga, & Wilson, (1988) 85, 108
Yalom, (1980) 117Yang, (1986) 88Yeh, (1985) 88Yu, (1980) 89
Zelen 1, 4Zillman, (1978) 12Zuckerman, (1979) 15