Individual Differences in Anger and Sadness

40 Pages·2006·0.21 MB·English

Individual Differences in Anger and Sadness:
In Pursuit of Active Situational Features and
Psychological Processes
Kristof Vansteelandt and Iven Van Mechelen
Katholieke Universiteit Leuven
ABSTRACT Inthecognitive–affective personalitysystem (CAPS) the-
oryofMischelandShoda(1995,1998),personalityisconceivedasasys-
tem of cognitions and affects that mediates between active situational
features and behavior. Two major tasks for this approach to personality
are the search for active situational features and for mediating psycho-
logical processes within a behavioral domain of interest. We report two
studies to address these tasks for the domain of anger and sadness. To
designthesestudiesandtoanalyzetheobtaineddata,novelextensionsof
our previous developed Triple Typology Model (TTM; Vansteelandt &
VanMechelen,1998)areproposed.Theseextensionsallowtheresearcher
to test hypotheses concerning potentially relevant active situational fea-
turesinasystematicandconfirmatorywayandtoexaminepsychological
processes as they occur in concrete situations.
In the Cognitive–Affective Personality System (CAPS) theory of Mi-
schel and Shoda (1995, 1998), personality is conceived as a system of
cognitionsandaffectsthatmediatesbetweensituationsandbehavioral
responses. According to this theory, features of a situation activate
several cognitions and affects—including encodings, expectancies,
TheresearchreportedinthisarticlewassupportedinpartbygrantGOA/2000/02of
K.U.Leuven.
All correspondence concerning this article should be sent to Iven Van Mechelen,
Department of Psychology, Tiensestraat 102, B-3000 Leuven, Belgium. E-mail:
[email protected].
JournalofPersonality74:3,June2006
r2006,CopyrighttheAuthors
Journalcompilationr2006,BlackwellPublishing,Inc.
DOI:10.1111/j.1467-6494.2006.00395.x
872 Vansteelandt & Van Mechelen
values, and/or competencies. Subsequently, these cognitions and af-
fects activate or inhibit other cognitions and affects, and, finally, the
totalactivationofthecognitive–affectivepersonalitysystemresultsin
the displaying(or not displaying) of certainbehaviors.Individual dif-
ferences in behavior are assumed to be the result of individual differ-
ences in the way information from the situation is processed and
transformed by the CAPS (Mischel & Shoda, 1995, 1998).
AfirstimportanttaskforCAPStheoryistodiscoverwhichactive
situational features are relevant for a behavioral domain of interest
(Shoda, Mischel, & Wright, 1994), active features being those fea-
tures of the situation that render a meaning to it (Higgins, 1990) or
that have an impact on behavior (Shoda et al., 1994). A second im-
portant task for CAPS theory is to uncover the psychological proc-
essesunderlyingindividualdifferencesinsituation–behaviorprofiles;
the latter comes down to revealing the mediating mechanisms in the
CAPS or, in Mischel and Shoda’s terms (1995, 1998), to finding the
cognitive–affective domain map of a particular behavioral domain.
The twofold aim of CAPS theory implies a considerable methodo-
logical challenge. In this article, we want to tackle both problems
for the domain of anger and sadness. To accomplish this task, we
will present a new methodology that builds further on earlier work
(Vansteelandt & Van Mechelen, 1998) in which a Triple Typology
Model (TTM) was proposed. Starting from empirical data that indi-
cate which persons display which responses in which situations,
the TTM methodology allows the researcher to group persons, situa-
tions,andresponsesintoalimitednumberof(hierarchicallyorganized
andmutuallyexclusive)person, situation, andresponseclasses;subse-
quently,eachpersonclass(ortype)ischaracterizedbyasetof‘‘if(sit-
uation class)–then (response class) rules’’ that define its behavioral
signature.
This TTM is a categorical and deterministic model, the different
classes of which are monothetic categories. The latter means, for ex-
ample, that all persons who belong to the same person class are as-
sumedtodisplayexactlythesamesetofbehaviorsineachsituation.A
similar statement holds for boththe situation classes and the behavior
classes. The if (situation class)–then (behavior class) rules are also as-
sumed to be deterministic in nature. In the analysis of real data, how-
ever, parsimonious models with a less than perfect fit to the data are
preferred over complex, perfectly fitting models. For the TTM, a less
than perfect fit implies that each class is turned into a fuzzy category
ActiveSituational Features and Processes 873
withmembersthatvaryinprototypicality(Rosch,Mervis,Gray,John-
son, & Boyes-Braem, 1976); it also results in probabilistic rather than
deterministicif–thenrules,withtheprobabilityforapersontoperform
a behavior in a situation being higher for more prototypical persons,
situations, and behaviors (see also Wright & Mischel, 1987).
In its original form, the TTM methodology suffers from two ba-
sic limitations: First, the methodology is limited to exploratory re-
search in which the researcher wants to induce active psychological
featuresfromthedata;assuch,theoriginalTTMisnotsuitedtotest
a priori hypotheses about active situational features that are de-
rivedfromtheoreticalinsightsorfromearlierempiricalresearch.Sec-
ond, with respect to the underlying psychological processes, the
TTM in its original form only leaves room for dispositional, con-
text-free, process variables; however, psychological processes always
occur in a concrete, situational context, and it may be desirable to
examine them assuch. Inaddition, for a behavioral domain of inter-
est, the CAPS may comprise both universal and person type-specific
processes;tofullyunderstandthesystem,weneedamethodologythat
allows the researcher to discover both kinds of processes. In the
present article, we will propose novel extensions of the TTM meth-
odologytoremedytheseshortcomings.Althoughthemethodologyis
generallyapplicable,wewillapplyitheretothedomainofangerand
sadness.
The structure of the remainder of this article is as follows: In the
first section, an overview of potentially relevant active situational
features in the domain of anger and sadness is proposed, and indi-
vidualdifferencesintheprocessingofthesefeaturesarederivedfrom
literature. In the next two sections, two empirical studies are pre-
sented: In the first study, individual differences in the behavioral
signatures for the domain of anger and sadness are investigated; in
the second, the process basis of these individual differences is exam-
ined. In Section 4, we conclude with a general discussion.
ACTIVE SITUATIONAL FEATURES IN THE DOMAIN OFANGER
AND SADNESS AND INDIVIDUAL DIFFERENCES IN REACTION
TO THEM
Like all negative emotions (Smith & Lazarus, 1993), anger and sad-
ness often start with the occurrence of a negative event (Abramson,
874 Vansteelandt & Van Mechelen
Metalsky, & Alloy, 1989; Blaney, 2000), which may be considered a
first active situational feature. Such negative events may vary in in-
tensity(Abramsonetal.,1989)aswellasinquality.Thelattertypes
ofvariability canbe linked todifferences inhow negativeevents are
being appraised, as represented in cognitive theories of emotions
(Frijda,Kuipers,&terSchure,1989;Ortony,Clore,&Collins,1988;
Roseman, 1984; Roseman, Spindel, & Jose, 1990; Scherer, 1984;
Smith&Ellsworth,1985;Smith&Lazarus,1993).Inthesetheories,
a large number of potentially relevant appraisal dimensions have
been proposed, assuming that particular kinds of appraisals are as-
sociatedwithparticulartypesofemotions(includingangerandsad-
ness). In the theory of Smith and Lazarus (1993), the two major
appraisals(or core relation themes)for, respectively, anger and sad-
ness are other-blame and loss. In other research on anger (Averill,
1983; Ben-Zur & Breznitz, 1991; Levine, 1996; Smith & Lazarus,
1993; Weiner, Graham, & Chandler, 1982), other-blame is found to
be a crucial feature: People appear to be especially angry when they
haveanegativeexperiencethattheyattributetoanotherpersonwho
had control over what happened, that is, someone who acted inten-
tionally and who had the potential to prevent the occurrence of the
negative event. With respect to sadness, several clinical theorists of
depression argue that some person types (dependent persons) are
especially vulnerable tonegative events that are characterized by re-
jectionandinterpersonalloss(Arieti&Bemporad,1980;Beck,1983;
Blaney, 2000, Blatt, 1974; Robins, 1995; Robins & Block, 1988;
Zuroff & Mongrain, 1987). Summarizing, one could say that both
anger and sadness can be elicited by a negative event that is caused
by another person.
In previous appraisal research, however, it has been argued that
there is no simple one-to-one relationship between appraisals and
emotions and that individual differences in this relationship may
occur(Frijda&Zeelenberg,2001;Kuppens,VanMechelen,Smits,&
De Boeck, 2003; Kuppens, Van Mechelen, Smits, De Boeck, &
Ceulemans, 2005; Parkinson, 1997, 2001; Reisenzein, 2000; Russell,
2003;Scherer,2001;Schweder,1993;Vansteelandt&VanMechelen,
2005). As such, the relationship between anger and sadness on the
one hand and the appraisal of a negative event caused by another
person on the other hand is not that clear-cut. For example, anger
may also be caused by an impersonal agent (e.g., the hard disk of
yourcomputercrashes). Withregardtosadness,clinical theoristsof
ActiveSituational Features and Processes 875
depression suggest that person types (autonomous persons) exist
who are vulnerable to achievement failure or, more generally, to
negativeeventsthatareinconflictwiththeirself-definition(Arieti&
Bemporad, 1980; Beck, 1983; Blaney, 2000; Blatt, 1974; Robins,
1995; Robins & Block, 1988; Zuroff & Mongrain, 1987).
Taking all this into account, we decided to include in our study a
situationalfeaturethatindicateswhetheranegativeeventisascribed
to another person, to the actor him- or herself, or to an impersonal
agent.Inaddition,whenanegativeeventisascribedtoaperson,we
included a feature indicating whether this person had control over
the event or not.
Individual differences in the processing of these possibly relevant
active situational features may occur for several reasons. For exam-
ple, there is abundant evidence for individual differences in the
number of situational cues people take into account when making
behavioral decisions. Dodge (1993), for example, found that chron-
ically aggressive boys attend to fewer active situational features in
comparison to nonaggressive boys. Individual differences may also
occur because some persons process active situation features in a
biased way. At this point, the distinction between dependent and
autonomous persons may again be relevant: Dependent persons are
assumed to have chronic fears of being abandoned and to seek to
gain approval and acceptance of others in order to maintain self-
esteem; as such, they may be biased easily to interpret interpersonal
conflicts in terms of rejection or interpersonal loss (Blatt & Zuroff,
1992). Autonomous persons, on the other hand, are assumed to be
characterized by self-criticism and feelings of unworthiness and in-
feriority; they have high achievement strivings, and, as a conse-
quence, they may be easily biased to attribute the causes of failure
situations to their own shortcomings.
Furthermore,individualdifferencesinangerandsadnessrespons-
es may also occur because individuals display different reactions to
similarly experienced situations, the so-called individual response
stereotypy(Fahrenberg,1986).Forexample,dependentpersonsmay
respond to experiences of rejection and interpersonal loss with an-
aclitic reactions; also, when they fear losing another person, they
may easily suppress anger responses. In contrast, autonomous per-
sons are likely to be characterized by introjective responses; more-
over, because of their intense competitiveness, they may be very
critical and may attack others as well as themselves (Arieti &
876 Vansteelandt & Van Mechelen
Bemporad, 1980; Beck, 1983; Blatt & Zuroff, 1992). Because there
may be substantial individual differences in the kind of sadness
(analclitic, introjective) and anger responses (anger-in, anger-out)
individuals display, multiple responses will be included in the study.
STUDY 1
In this first study, we will examine potentially active situational fea-
tures and responses in the domain of anger and sadness in a sys-
tematic and confirmatory way. For this purpose, we will propose a
new extension of the TTM; in this extension, nomothetic concepts,
whicharemanipulatedbytheresearcher,arefilledwithidiosyncratic
contentsthatareprovidedbytheparticipants.Thelatterapproachis
in line with Pervin’s plea (1996) to combine in the study of person-
alitygeneral (nomothetic)principlesoffunctioningwith idiographic
contents.
The TTM extension starts by constructing formal situations on
the basis of a facet-theoretical mapping sentence (Guttman, 1958,
1959; Ben-Zur & Breznitz, 1991), the facets being the active situa-
tional features under study. In Study 1, the following mapping sen-
tenceisconstructed:Youareinasituationinwhichanegativeevent
occurs that affects you [weakly, strongly] and in which there is [no
other person, one familiar other person] involved; the cause of the
negativeeventis[thefamiliarotherperson,yourself,noperson]and
the person who is the cause of the negative event [has not, has] con-
trol over thenegative event. Thefacets ofthis mapping sentenceare
mentioned between squared brackets. By taking all possible mean-
ingful combinations of facets, sixteen formal situations were ob-
tained.
Atthispoint,wewanttodrawattentiontoarecurrentissueinthe
study of process models of personality, that is, the question ‘‘Where
does the situation stop and when does the person begin?’’ Although
active situational features and CAPS variables can be rather easily
distinguished on a conceptual level, many situation characteristics
verysoonimplysomekindofprocessingbytheperson.Inthisstudy,
we take a pragmatic point of view with regard to this issue: In ap-
plying the TTM methodology, it does not matter at exactly which
pointonestartsinthechainsituation-CAPSbehavior,aslongasall
participantsstartatthesamepoint.Assuch,thesituationalfeatures,
ActiveSituational Features and Processes 877
as mentioned above, refer to the common start of all participants.
Admittedly,somesituationalfeaturesaremore‘‘objective’’innature
(e.g., the presence of other persons in the situation), whereas others
have more ‘‘subject-related’’ qualities (e.g., a negative event).
Given the formal situations, the participants are asked, for each
formal situation, to write down a concrete situation they have ex-
perienced themselves. For example, ‘‘My grandmother died from
cancer’’ may be a concrete situation for the formal situation ‘‘You
are in a situation in which a negative event occurs that affects you
stronglyandinwhichthereisonefamiliarotherpersoninvolved;the
cause of the negative event is the familiar other person and the per-
son who is the cause of the negative event has no control over the
negative event.’’ The advantage of this approach is twofold: On the
one hand, it allows the researcher to examine nomothetic relations
between active situational features and responses (and individual
differences in these relations); on the other hand, it allows partici-
pants to report on concrete situations they experienced themselves
rather than on hypothetical situations. Otherwise, as has been ar-
guedbyEpstein(1980,1997),thefactthatparticipantscanreporton
daily events they have experienced themselves may contribute to a
larger ego involvement, which may, in turn, yield more robust find-
ings.
Next, participants are required to rate each concrete situation
with regard to a set of multiple responses selected by the researcher.
In this study, we selected (a) an anaclitic and an anger-in response
and (b) an introjective and an anger-out response since these re-
sponses are hypothesized to be typical for dependent and autono-
mous person types, respectively.
Finally, the person(cid:1)situation(cid:1)response data were subjected to
a series of TTM analyses. As a result of such analyses, situations
(persons and responses) were assigned to a limited number of situ-
ation (person, response) classes that were linked in terms of if–then
rules. Relevant active situational features may be derived from the
output of such analyses by inspecting the situation typology. Given
the way the situations were constructed, the obvious thing to check
thenistowhichextentthesituationtypologybearsasimplerelation
tothefeaturesinvolvedinthefacet-theoreticalmappingsentence.In
exploratory TTM analyses, however, the interpretation of the situ-
ation typology may be blurred because of a limited number of
‘‘wrongly classified’’ situations. To check then whether a purer
878 Vansteelandt & Van Mechelen
interpretation is justified, the exploratory analyses will be supple-
mented by another extension of the TTM methodology that implies
analyses in which the structure of the situations is user imposed.
When the goodness of fit of a confirmatory TTM analysis is only
slightlyworsethanthegoodnessoffitofitsexploratorycounterpart,
one can conclude that the confirmatory interpretation of the situa-
tion structure is justified.
Method
Participants
The participants in this study were 249 first-year psychology students of
the University of Leuven. Their participation was in partial fulfillment
of a requirement to participate in research. The group consisted of 42
(16.9%)menand207(83.1%)women(whichreflectsthesexproportion
of first-year psychology students in Belgium). The average age of the
participants was 18.6 (SD5.87, minimum517; maximum524).
Materials
Anexperimentalsituation–responsequestionnairewasdevelopedbyfully
crossing16situationsand6responses.Thesituationswereconstructedon
the basis of the facet-theoretical mapping sentence as discussed above.
Furthermore,thefollowingresponseswereincludedinthequestionnaire:
‘‘Ifeelsad,’’‘‘Ifeelabandoned(anaclitic),’’‘‘Iamdissatisfiedwithmyself
(introjective),’’‘‘Ifeelangry,Ishowmyanger(anger-out),andIambot-
tling up my anger (anger-in).’’
Procedure
Participants received extended written instructions in which they were
told that we were interested in personal reactions to a variety of situa-
tions. To ensure that these situations would coincide with their own ex-
periences, we explained that the situations would first be described in
terms of abstract features. These abstract situations then had to be ex-
panded on and made specific by their describing a concrete situation for
each abstract situation they had experienced in their daily life. The way
thiscouldbedonewasillustratedwithabriefexample.Next,thevarious
abstract features of the mapping sentence were defined and illustrated.
After these instructions, the 16 facet-theoretical situations were pre-
sentedinrandomorder.Foreachfacet-theoreticalsituation,participants
first had to describe in writing a concrete situation they had experienced
themselves.Next,theyhadtojudgeona3-pointscalethedegreetowhich
ActiveSituational Features and Processes 879
theydisplayedthesixresponsesineachsituationatthetimetheywerein
that situation (05not; 15to a limited extent; 25to a strong extent).
Visual inspection of the generated situations indicated that these sit-
uationshadhighecologicalvalidity.Examplesofobtainedsituationsare:
‘‘Mygrandmotherdiedfrom cancer,’’ ‘‘Afrienddidnotinvitemetoher
birthday party,’’ ‘‘I missed my train; as a consequence, I arrived late at
home and my mother was very worried,’’ ‘‘I failed my statistics exam,’’
and so forth.1
Analysis
The person(cid:1)situation(cid:1)response data were analyzed by means of the
individualdifferenceshierarchicalclassesanalysis(INDCLAS)algorithm
(Leenen, Van Mechelen, De Boeck & Rosenberg, 1999; Vansteelandt &
Van Mechelen, 1998). This algorithm operates on a three-way, three-
modedichotomizeddatamatrixinordertofindthebestfittingTTM.The
algorithm generates a series of models of increasing complexity or rank,
withrankreferringtothemaximumnumberofclassesallowedatthebase
of the person, situation, and response hierarchies. The optimal rank
(comparabletothenumberoffactorsextractedinfactoranalysis)canbe
determinedbymeansofascreetest onagoodness-of-fit(cid:1)rankplot.To
calculatethegoodness-of-fitstatistic,eachperson(cid:1)situation(cid:1)response
data entry in theoriginaldatamatrixiscomparedwiththe dataentry in
thedatamatrixthatisconstructedonthebasisoftheselectedmodelwith
a concordance indicating that a zero (one) is predicted by the model,
whereas the original data-matrix also contains a zero (one); then, the
goodness-of-fit index equals the proportion of concordances.
The INDCLAS algorithm allows for confirmatory, in addition to ex-
ploratory, analyses. In the confirmatory case, the user has to impose the
solution for one (or two) of the three modes (e.g., situations), and then
the INDCLAS algorithm searches the best fitting hierarchical structure
fortheremainingmode(s).Goodnessoffitoftheresultsofconfirmatory
and exploratory analyses should be compared; if the confirmatory result
isonlyslightlyworsethanitsexploratorycounterpart,itcanberetained.
1. Totestthecorrespondencebetweenthesituationsasgeneratedbythepartic-
ipantsandtheformalfacetsasmentionedinthegenerationinstructions,ablind
raterreadarandomsampleof100generatedsituationsandindicatedwhichfacets
werepresentinthem.Theratingswerehamperedbythelackofclarityofmany
situation descriptions, yet the overall correspondenceappeared tobe reasonable
(the mean proportion of correct classifications, averaged across facets, was
73.7%)(seealsoGeneralDiscussion).
880 Vansteelandt & Van Mechelen
In our study, the person(cid:1)situation(cid:1)response data were first dicho-
tomized (zero vs. 1 or 2) and then subjected to exploratory INDCLAS
analyses in ranks 1 to 5. After selection of the optimal rank model, in-
terpretations of the situation structure of this model in terms of active
situationalfeatureswerederived.Theseinterpretationswerefurthertest-
edinconfirmatoryanalyses.Fortheselectionofthefinalmodel,resultsof
exploratoryandconfirmatoryanalyseswerecompared.Tocheckthesta-
bilityofthefinalsolution,anodd-evensplitofthesampleofpersonswas
performed;reliabilitywasthenexaminedbycomparingthesituationand
behaviorstructuresofexploratoryINDCLASanalysesofthedataofthe
two samples.
Results
An exploratoryTTM ofRank 3 was chosen; the global goodnessof
fitofthissolutionwas0.734,implyingthat73%oftheentriesinthe
original data matrix could be correctly predicted from the chosen
TTM.INDCLASsolutionsinthechosenrankappearedtobestable
acrosstwosubsamplesofpersonsasobtainedfromanodd-evensplit
(with Jaccard congruence coefficients taking values of 0.80 and 0.83
for the situation and response structures, respectively).
In the selected TTM, all persons, all situations, and all responses
are classified into 8 nonempty, mutual exclusive person classes, 6
nonemptysituationclasses,and4nonemptyresponseclasses.Aswill
be discussed later, each person type is characterized by a person-
type-specific set of if (situation class)–then (response class) rules, as
can be seen in Table 1. Further, it may be noted that, to avoid an
overloaded presentation, we opted for not displaying the proto-
typicality of the persons, situations, and responses and for not dis-
playing the probabilities of the if–then rules (see discussion of the
TTM earlier). The reader should bear in mind that although class
membership and the if-then rules are stated in an absolute manner,
membership, in fact, is a matter of degree, and if–then rules are
associatedwithaconditionalprobabilitythatapersonoftheperson
typeunderconsiderationwilldisplayabehaviorofthebehaviorclass
in a situation of the situation class.
The hierarchy of the situation classes of this TTM is shown in
Figure 1. Note that for clarity’s sake, we attached to each of the
lower-hierarchyclasses(i.e.,SituationClasses2,3,and4)thefeature
that applied to that class as well as all hierarchically higher classes.
To facilitate the interpretation, we recall that two situations belong