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The 9/11 attacks inside and outside the US:Testing four models of flashbulb memoryformation across groups and the specific effectsof social identityOlivier Luminet a & Antonietta Curci ba Université catholique de Louvain (UCL) and Belgian National Fund for ScientificResearch (FNRS-FRS) , Belgiumb University of Bari , ItalyPublished online: 18 Sep 2009.

To cite this article: Olivier Luminet & Antonietta Curci (2009) The 9/11 attacks inside and outside the US: Testingfour models of flashbulb memory formation across groups and the specific effects of social identity, Memory, 17:7,742-759, DOI: 10.1080/09658210903081827

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The 9/11 attacks inside and outside the US: Testingfour models of flashbulb memory formation acrossgroups and the specific effects of social identity

Olivier Luminet

Universite catholique de Louvain (UCL) and Belgian National Fund for Scientific Research

(FNRS-FRS), Belgium

Antonietta Curci

University of Bari, Italy

Flashbulb memories (FBMs) are consistent recollections of specific details of the reception context ofevents. Four theoretical models accounting for FBM formation (Brown & Kulik, 1977; Conway et al.,1994; Er, 2003; Finkenauer et al., 1998) were tested on average 21 and 524 days after the 9/11 attacks inthe US in 2001 in two groups of participants (US, N�112; non-US, N�727). Structural equationmodelling revealed that (1) a revision of Finkenauer et al.’s (1998) model provided the best fit indices inboth the US and non-US groups, (2) several relations among latent variables that were predicted by thethree other models (Brown & Kulik, 1977; Conway et al., 1994; Er, 2003) were not significant, (3) withrespect to Finkenauer et al’s model, the ‘‘direct path’’ (from novelty/surprise to FBMs) was found to besignificant only for the US group, while the ‘‘indirect path’’ (from emotional states, rehearsal and event-memory to FBMs) was only significant for the non-US group. It is suggested that the specific activation ofsocial identity in the US group can explain these differences.

Keywords: Flashbulb memories; Consistency of memory; Emotion and cognition; Social identity; 9/11 attacks.

Flashbulb memories (FBMs) are detailed mem-

ories of the reception context (Brown & Kulik,

1977). In some circumstances people remember

the specifics of the context in which they first

heard a piece of news, such as the exact time it

happened, their detailed location, or the activities

# 2009 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

Address correspondence to: Olivier Luminet, Universite catholique de Louvain, Research Institute for Psychological Sciences, 10

Place du Cardinal Mercier, B-1348 Louvain-la-Neuve, Belgium. E-mail: Olivier.Luminet@uclouvain.be

The present study was supported by grants 1.5.078.06 and 1.5.158.08 from the Belgian National Fund for Scientific Research. The

authors gratefully acknowledge the help of Elizabeth J. Marsh (now at Duke University, USA), Ineke Wessel (now at the University

of Groningen, The Netherlands), Ticu Constantin (University of Iasi, Romania), Masao Yogo (Doshisha University, Kyoto, Japan),

and Albina Shayevich (previously at University of Cambridge, UK) for their enormous help in collecting and encoding the data at

test and retest, and Tiziana Lanciano (University of Bari) for the data cleaning.

The authors would also like to thank members of the FNRS-research group on collective memory (Olivier Klein, Laurent Licata,

Valerie Rosoux, Laurence van Ypersele, and Susann Wolff) for their useful comments at various stages of the work progress.

The authors would also thank the following people for their contribution to various aspects of the study: Guglielmo Bellelli,

Liesbeth van Breda, Giovanna D’Onchia, Dario Galati, Jenny van den Heuvel, Giannangela Mastrorilli, Prisca Niel, Annarita

Pugliese, Mario Refice, Maud Slaats, Catherine Demaret, Jurgen Engerisser, Sylvie Grumiau, Veronique Pellegrin, Sophie Wautier,

James Pennebaker, Allen Omoto, Martin Conway, Catrin Finkenauer, Mark Snyder, Carolin Showers, Martial van der Linden,

Marie-Claire Gay, Emmanuelle Zech, Anna Tcherkassof, Kate Niederhoffer, Ambroise Neve, Paula Niedenthal, Gwenola Herbette,

Debra Golden, Gerard Duveen, and Annette Lafontaine. Many thanks also to Mike Friedman for his careful check of the

manuscript.

MEMORY, 2009, 17 (7), 742�759

http://www.psypress.com/memory DOI:10.1080/09658210903081827

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they were doing at the time. Numerous studies

describe these memories, often insisting on their

initial vividness (e.g., Conway & Bekerian, 1987;

Rubin & Kozin, 1984). It is crucial to note that in

the present paper we restrict the definition of

FBMs to memories for reception contexts that

were consistent through time.The present paper focuses on two key aims.

First we investigate the conditions that lead to the

formation of FBMs, comparing four models that

have been provided in previous literature. Sec-

ond, we examine whether variations in social

identity can modify the paths leading to the

formation of FBMs. Regarding the first aim, we

consider four models (Brown & Kulik, 1977;

Conway et al., 1994; Er, 2003; Finkenauer et al.,

1998). Although they all include cognitive, emo-

tional, and social determinants of FBMs, the focus

on these three dimensions differed somewhat,

and the way these variables affected FBMs

formation in a direct or an indirect way also

varied. In order to compare models we used the

structural equation modelling (SEM) approach.1

This approach allows testing of directional hy-

potheses, although conclusions about the ‘‘real’’

structure of the phenomenon remain only tenta-

tive. Regarding the second aim, only a few studies

have examined the effects of group membership

in relation to the formation of FBMs (see

Berntsen, 2009, for a review), although these

variations*being related to citizenship, gender,

or ethnic background*seem to affect to a large

extent the mechanisms of FBM formation (e.g.,

Brown & Kulik, 1977; Conway et al., 1994; Curci,

Luminet, Finkenauer, & Gisle, 2001; Gaskell &

Wright, 1997; Otani et al., 2005). Social identity,

defined as the part of the self-concept that derives

from group membership (Hogg, 1995), could

represent a relevant theoretical framework to

understand the differences observed among

groups. The claim we make by assessing models

of FBM formation in groups differing in social

identity is that the structure of relationships

among predictors is modified, while the relevant

predictors included in the model are the same.

In the remaining part of this introduction wewill first review the models to be compared,together with the hypotheses regarding thedeterminants of FBMs. Then we will suggesthow the models might differ in regard to groupmembership and activation of social identity.

FOUR MODELS OF FBM FORMATION

We examined four models that have been pro-posed in the literature to account for FBMformation. The main criterion for selecting themodels was that they were derived from theore-tically grounded assumptions.

Brown and Kulik (1977), Conway et al. (1994),Er (2003), and Finkenauer et al. (1998) all refer totheoretical assumptions about the relationshipbetween memory formation on the one hand,and cognitive, emotional, and social factors on theother. For instance, appraisal theories predictspecific associations between some initial cogni-tive evaluations and specific emotional states thatfollow, like the novelty�surprise association (e.g.,Frijda, 1986; Lazarus, 1982; Leventhal, 1984;Scherer, 1984). Also, socio-emotional theoriessuggest a strong link between the intensity ofemotional reactions and the amount of rehearsal(e.g., Luminet, Bouts, Delie, Manstead, & Rime,2000; Rime, Philippot, Boca, & Mesquita, 1992).These models also have the advantage that theyrefer to specific predictions of the relationshipsbetween predictors.

Brown and Kulik (1977) are the first authorswho proposed a model of FBM formation. This isquite paradoxical as they never tested any modelsthemselves, but rather suggested different stagesthat could account for the formation of FBMs. Wewill still present their proposals as a modelbecause many researchers who later tested mod-els using statistical indexes referred to theassumptions of Brown and Kulik’s model.

The assumptions of Brown and Kulik (1977)closely followed the neurophysiological Now-Print! theory (Livingston, 1967). In their view,to initialise FBM formation the original eventmust be new or unexpected, thus eliciting sur-prise. Given a sufficient level of surprise, theevent is then evaluated in terms of consequenti-ality or personal importance which, in Brown andKulik’s perspective, is equated with emotionalarousal. Surprise, importance/consequentiality,and emotional arousal are direct predictors ofFBM formation. Brown and Kulik also suggested

1 Structural equation modelling (SEM) adopts a

confirmatory approach to test hypotheses of relationships

among observed indicators of latent variables. It encompasses

measurement and structural modelling. The former is

accomplished primarily through confirmatory factor analysis,

the latter through path analysis with latent variables (Bollen,

1989).

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that emotional arousal will then trigger rehearsal,

which will also predict FBMs. Finally, higher

consequentiality is assumed to evoke more fre-

quent rehearsal (see Figures 1 and 2). It is worth

noting that these authors considered a single

measure of FBM rather than the consistency

approach. Another limitation of their theory is

that they assumed high ratings on variables such

as novelty and surprise without measuring them.

Conway et al. (1994) developed a model forFBM formation using the SEM approach. Theirstudy was based on the unexpected resignation ofthe British prime minister Margaret Thatcher,using a large sample of UK and non-UK citizens.In their model FBMs had two direct predictors,emotionality and rehearsal. Knowledge/interestand importance/consequences were two indirectpredictors. Emotionality and rehearsal werefound to be unrelated (see Figures 5 and 6).Conway et al.’s model was innovative in severalaspects. First, they were the first to combine atest�retest definition of FBM together with theSEM approach. Second, their model differen-tiated between the direct effects of the predictorson FBM (affective reactions) and their indirecteffects (e.g., importance, through rehearsal, af-fects FBM). Third, it was the first paper toconsider personal characteristics of respondentsby including prior knowledge. Prior knowledgewas assumed to be a key predictor affectingemotionality, importance/consequentiality, andrehearsal. Fourth, this was the first study (exceptBohannon, 1988) that used a large sample ofparticipants and that performed group compar-isons. This is important as it allows one to testwhether different models are necessary toaccount for group differences or if the samestructure (but with different strengths in the pathsbetween predictors) can account for group differ-ences.

Although this model represents a significantimprovement in understanding the processes ofFBM formation, it is not without limitations. First,the authors did not define or operationalise theappraisal of novelty and did not distinguishbetween emotional appraisals and emotionalresponses. Also, intensity of emotional feelingsand surprise were considered together, whileemotion models insist these components aredistinct and separate from one another (e.g.,Frijda, 1986; Lazarus, 1982; Leventhal, 1984;Scherer, 1984). The event itself did not elicithigh ratings in the UK group for some of the keydeterminants such as emotional feeling states andrehearsal. Finally, the sample was mainly com-posed of first-year psychology students, whichprecludes generalisability to other populations.

The third model was proposed by Finkenaueret al. (1998). It was tested on a large group ofFrench-speaking Belgians of various age groupsand backgrounds. Seven to eight months after theunexpected death of the Belgian king in 1993,participants recalled the circumstances in which

Figure 2. Brown and Kulik model in the Europe group

(N�727). Continuous arrows refer to paths predicted by

Brown and Kulik (1977) and that were found to be significant.

Dotted arrows refer to paths predicted by Brown and Kulik

(1977) but that were non-significant in these data. Double-

headed arrows indicate that the two variables were considered

as a single one by Brown and Kulik (1977). *pB.05.

Figure 1. Brown and Kulik model in the US group (N�112).

Continuous arrows refer to paths predicted by Brown and

Kulik (1977) and that were found to be significant. Dotted

arrows refer to paths predicted by Brown and Kulik (1977) but

that were non-significant in these data. Double-headed arrows

indicate that the two variables were considered as a single one

by Brown and Kulik (1977). *pB.05.

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they first heard the news, and answered questionsconcerning their discovery of the news, such astime, ongoing activity, informant, and location(FBM). They were also asked to rememberspecific details about the following predictors ofFBMs: (1) personal consequentiality and impor-tance, (2) novelty, (3) surprise, (4) emotionalfeelings, (5) overt rehearsal (i.e., frequency oftalking about the event and following it in themedia), (6) personal attitude, which was assessedthrough the degree to which the person reportedhaving a favourable attitude towards the RoyalFamily in general, and (7) memory for the event.According to this third model, the process offormation and maintenance of FBMs developsthrough two pathways (Finkenauer et al., 1998).The first connects the cognitive appraisal ofnovelty to FBMs, through the effect of thespecific emotional feeling of surprise. This path-way is representative of the direct effect ofemotion. The second pathway represents theindirect effect of emotion. The experience oflearning a relevant piece of news induces highlevels of cognitive appraisal of personal impor-tance and consequentiality, which in turn leads tointense negative feeling states. Then emotionalfeelings trigger rehearsal, which strengthens thememory trace of the original event. This even-tually enhances FBMs. In this process an impor-tant role is also played by affective attitudes,

which are hypothesised to influence importance/

consequentiality, emotional reactions, and rehear-

sal (Finkenauer et al., 1998) (see Figures 3 and 4).

The authors compared their model with the ones

developed by Brown and Kulik (1977) and by

Conway et al. (1994) using the SEM approach.

Results showed that Finkenauer et al.’s model

evidenced the best fit indices and was often the

only model that had indices above standard

thresholds. In addition, all but two predicted

causal paths linking factors were significant, while

Figure 3. Finkenauer et al. model in the US group (N�112).

Continuous arrows refer to paths predicted by Finkenauer

et al. (1998) and that were found to be significant. Dotted

arrows refer to paths predicted by Finkenauer et al. (1998) but

that were non-significant in these data. Arrows with a single

dot refer to paths assumed by Finkenauer et al. (1998) but that

were not measured. Arrows with two dots refer to new paths

that were not predicted by Finkenauer et al. (1998) but were

significant. *pB.05.

Figure 4. Finkenauer et al. model in the Europe group

(N�727). Continuous arrows refer to paths predicted by

Finkenauer et al. (1998) and that were found to be significant.

Dotted arrows refer to paths predicted by Finkenauer et al.

(1998) but that were non-significant in these data. Arrows with

two dots refer to new paths that were not predicted by

Finkenauer et al. (1998) but were significant. *pB.05.

Figure 5. Conway model in the US group (N�112). Con-

tinuous arrows refer to paths predicted by Conway et al.

(1994) and that were found to be significant. Dotted arrows

refer to paths predicted by Conway et al. (1994) but that were

non-significant in these data. *pB.05.

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some crucial paths suggested by the other modelswere not significant.

One main advantage of this model over thetwo previous ones was a more refined analysis ofthe emotional process. First, it included a distinc-tion between cognitive appraisals and feelingstates (e.g., Frijda, 1986; Lazarus, 1982; Leventhal,1984; Scherer, 1984). Second, a distinction wasmade between surprise and other emotionalfeelings. This allowed the closer linkage of certainappraisals (like novelty) with specific emotionalfeelings that are triggered (such as surprise;for a more detailed account of the ‘‘novelty-encoding’’ hypothesis; see Tulving & Kroll, 1995).Finkenauer et al. (1998) also provided a detailedanalysis of the relationship between immediateemotional responses and rehearsal. At the struc-tural level, these data were the first to support atwo-path model, in which a distinction is madebetween direct and indirect determinants ofFBMs. These results were thus in contrast withthe ‘‘Now Print!’’ mechanism postulated byBrown and Kulik (1977), in which the informationis permanently encoded in memory. Finkenaueret al. (1998) were also the first to consider arelationship between event memory and FBM.Finally, from a statistical viewpoint, this was thefirst attempt to compare different models of FBMformation.

However, there were two major limitationsrelated to the study that tested the model. First,FBMs were operationalised by a single measureof memory for the reception context and notunder the test�retest procedure that permits the

measurement of consistency. Second, only onegroup (Belgian citizens) was considered, while itwould have been interesting and informative toinclude comparison groups of people with lowerinvolvement with the news.

In the fourth model, Er (2003) investigated theformation of FBMs for individuals who had adirect experience with a severe earthquake thathappened in Turkey in 1999 (high involvement orvictim group) and for people who only heardabout it on the news (low involvement or non-victim group). The author suggested that the highinvolvement group’s recollection would be sodifferent from those who had no direct experi-ence that two structurally different models wouldbe necessary to account for the data. For thevictim group, the model was quite different fromthe previous ones (see Figure 7). A first majordifference was that level of personal conse-quences/importance was directly related to thedegree of elaboration of FBMs. Another majordifference was that no distinction was madebetween event memory and FBMs with therationale that if the person directly experiencesa major event, he/she cannot differentiatebetween the memory for the event itself and thememory for recollections of specific details of thereception context. For the low involvement group,the model was very close to the one suggested byFinkenauer et al., except that surprise and noveltywere considered as a single dimension and that adirect link between emotional reactions andFBMs was predicted (see Figure 8). For eachgroup considered, a comparison was madebetween the new model (labelled ‘‘importance-driven emotional reactions’’) and the previousones (Brown & Kulik, Conway et al., Finkenaueret al.). Results showed that for the low involve-ment group the fit indices and the structure ofrelationships among predictors were very close toFinkenauer et al.’s model. Both models had goodfit indices, while these indices were much lowerfor Conway et al. and Brown and Kulik’s models.For the high involvement group, the new modelevidenced better fit indices as compared to thethree other models.

Er’s (2003) study provided a first proposal formodels of FBM formation for events in whichpeople differed in their level of involvement withthe event (direct vs indirect). The better fit thatwas found as compared to the three other modelssuggests that, when assessing victim groups, itwould be appropriate to consider this model.However, for non-victim groups, the benefit of

Figure 6. Conway model in the Europe group (N�727).

Continuous arrows refer to paths predicted by Conway et al.

(1994) and that were found to be significant. Dotted arrows

refer to paths predicted by Conway et al. (1994) but that were

non-significant in these data. *pB.05.

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using Er’s model as compared to Finkenaueret al.’s model is unclear. It is important to notethat in the present study our sample of highinvolvement individuals were not directly ex-posed to the event (i.e., they were far from theWTC). We consider 9/11 as a particularly excep-tional event for the US population, in whichpeople had a very strong sense of belonging andshowing extreme empathic reactions towards thevictims and their families. We thus considered itappropriate to apply the victim model to theseindividuals. The main goal in applying Er’s victimmodel to the US group was to test whetherextremely high concern and involvement couldmodify the process of FBM formation, makingthe ‘‘importance’’ path central as a direct pre-dictor of FBM.

Three strengths are worth mentioning in Er’s(2003) study. First, the event selected had highratings on personal importance and consequenti-ality, affective reactions, and surprise, which arekey variables for the formation of FBMs. Second,a large comparison group was recruited, whichallows testing separate models for people who aremore (vs less) involved. Third, the author used aquestionnaire that was closely modelled after theone used by Finkenauer et al. (1998), whichallows for more direct comparisons across studies.Some important limitations must also be men-tioned. The initial data collection took place 6months after the event. This means that the‘‘original’’ memory that was investigated at thattime was already reconstructed through media

exposure and social communication. Also, FBMswere operationalised in the model testing as thedegree of vividness rather than consistencybetween test and retest. The appraisal of noveltyand the emotional feeling state of surprise that

follow were not distinguished conceptually.Finally, there was a confound in the measure ofsurprise, which was assessed by items moreconceptually related to emotional feelings.

Overall, the four models agree that the follow-ing variables need to be included in models ofFBM formation: (1) the reaction of surprise whenlearning about the original event, (2) the apprai-sal of importance or consequentiality of theoriginal event, (3) the intensity of emotional

feeling state, and (4) rehearsal. All models alsoagree that FBMs are initialised by new (or

unexpected) situations and that this mechanismhas evolutionarily adaptive value (e.g., Brown &Kulik, 1977; Conway, 1995). In addition, rehearsalaffects FBM in all models, although in Finkenauer

et al. (1998), the effect is mediated by memory forthe event.

Other aspects are shared by the majority ofmodels. Three models (all but Er’s) predict thatrehearsal is associated with the importance of theevent. Also for three models (all but Brown &Kulik’s) pre-existing personal characteristics(attitudes and/or knowledge) are thought tofacilitate the assimilation of new informationinto long-term memory. Finally, the link betweenaffect and rehearsal was always assumed, exceptin Conway’s model. The role of affect for the

Figure 8. Er model in the Europe group (N�727). Contin-

uous arrows refer to paths predicted by Er (2003) and that

were found to be significant. Dotted arrows refer to paths

predicted by Er (2003) but that were non-significant in these

data. *pB.05.

Figure 7. Er model in the US group (N�112). Continuous

arrows refer to paths predicted by Er (2003) and that were

found to be significant. Dotted arrows refer to paths predicted

by Er (2003) but that were non-significant in these data.

*pB.05.

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prediction of FBM is thus quite complex, withsome models assuming a direct effect, whileothers predict indirect effects. The present paperattempts to clarify these relationships.

EFFECT OF SOCIAL IDENTITY ONFBM FORMATION

Another purpose of this paper is to test the fourmodels as a function of participants’ socialmembership. More specifically, we would like toemphasise the critical role of social identity in theformation of FBMs. Depending on thecircumstances, the individual’s personal identity(self-definition derived from close personal rela-tionships and idiosyncratic personality attributes)or social identity (self-definition in terms of theproperties of a specific group and the strength ofan individual’s identification with this group) willbe more highly activated. Broadly defined, asocial identity is a categorisation of the self intomore inclusive social units (Brewer, 1991; Tajfel& Turner, 1986; Turner, Hogg, Oakes, Reicher, &Wetherell, 1987). Most studies examining socialidentity have focused on attitude biases that leadone to evaluate one’s own group more favourably.Only a few have been dedicated to memoryissues. All of these studies, however, have focusedon the memory of the ingroup as a perpetrator ofviolence against others (e.g., Doosje, Spears, deRedelijkheid, & van Onna, 2007). Because suchviolence created guilty feelings, people scoringhigh on social identity had more inaccessibleschemata when attempting to recall the historyof their group. In the present study, however, theingroup (i.e., the US group) was a victim ofviolence by other people. This can lead ingroupmembers to have more accessible schemata, asremembering is a way to maintain social bondswithin the group. As recently suggested by Sahdraand Ross (2007), social identity influences indivi-dual-level memory processes by affecting theschemata that individuals possess about theiringroups.

The activation of social identity may enhancememory through various pathways, such asenhancing the intensity of initial feelings and/orenhancing the rehearsal processes that follow(Berntsen, 2009). To illustrate, in relation to the9/11 attacks Curci and Luminet (2006) showedthat, despite similar levels of FBM consistencyfor US and non-US groups, the US group (basedon a citizenship criterion) had much higher

ratings on event-memory accuracy, backgroundknowledge, emotional feelings, and rehearsal.One might suggest that it was more relevant forthe social identity of US citizens to rehearse thenews for both emotional (reassurance, socialcomparison) and cognitive (clarity, understand-ing) reasons. The high threat to participants’personal safety was also likely to enhance emo-tional reactions. Finally, better performance onevent-memory and background knowledge canbe explained from a social identity perspective bya higher need for US residents to know, forexample, the exact location of the attack on thetowers in case one’s relatives or close others weretrapped in them.

The first evidence of the importance of socialidentity for the formation of FBM was suggested,for instance, by Neisser (1986) who showed that hisFBM for the Pearl Harbor attack was distorted infavour of the self. Interestingly, recent findingsalso demonstrated that systematic biases in mem-ory are enhanced when they are congruent withone’s social identity (Berntsen & Thomsen, 2005).These authors showed that Danes recalled theweather as worse than it actually was during theinvasion of Denmark by the Germans in 1940,while they remembered the weather as beingbetter than it actually was for the liberation in1945.

As examining the effect of social identity onmemory was one main interest of the study, weused a between-groups design. In some otherstudies on FBMs the emphasis has been more onexamining the potential non-ordinary nature ofFBMs. In these cases the designs involved thecomparison of memory across events, and requireda within-group design.

OVERVIEW

The goals of the current research were (1) to testand compare four theoretical models of FBMformation using a test�retest design (consistencyscores) and the SEM approach (Bollen, 1989),and (2) to consider the respondents’ country ofprovenance in order to examine whether theprocess of FBM formation is affected by varia-tions in social identity. Based on their citizenship(US vs non-US), participants were categorisedinto high vs low activation of American socialidentity. We predicted differences in the structureof FBM formation across groups, based on thisdifference. Testing four models across two

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groups not only sheds light on which models aremost appropriate, but it also gives importantinformation on specific elements of the eventand/or of the group involved that could weakenor deactivate some of the links between thepredictors and FBMs.

METHOD

Participants

A total of 839 participants from five countriesparticipated in both phases of the data collec-tion. Participants were divided into the USgroup (i.e., US citizens) (n�112) and the non-US group (n�727). Although smaller than thenon-US sample, the group of US respondentswas large enough to enable a valid assessment ofa SEM model for FBM formation. The non-USgroup was composed of respondents with Eur-opean citizenship, from Belgium (n�136), Italy(n�40), Romania (n�421), and The Nether-lands (n�130). Participants completed question-naires on average 21 (SD�10.0) and 524(SD�10.2) days after the events (for full detailsof the sample, see Curci & Luminet, 2006;Luminet et al., 2004).

Measures

The questionnaire used in this study is described indetail in Luminet et al. (2004) and in Curci andLuminet (2006). It involves the seven dimensionsthat have been identified in the literature as centralelements for predicting FBM formation. For alldimensions, sum scores were computed.

FBMs. Five canonical variables were consid-ered when examining the recall people had of thecircumstances in which they first learned aboutthe terrorist attacks: (a) time of the day, (b)location of the respondents (e.g., country, city,room, or other kind of location such as a car), (c)informant (family, friends, colleagues, media), (d)other people present, and (e) ongoing activity. Foreach item, responses at the first data collectionand retest were compared. A score of 2 wasattributed if exactly the same answer was pro-vided at the two data collections (i.e., for theongoing activity question: ‘‘I was cleaning thehouse’’), thus reflecting perfect consistency. Ascore of 1 was given if answers were basically but

not entirely identical; that is, when a gain/loss ofinformation occurred (i.e., ‘‘cleaning the house’’

at test, ‘‘vacuuming the house’’ at retest). A scoreof 0 was given if answers were missing in bothphases of data collection, or when they were

totally different (i.e., ‘‘cleaning’’ at test, ‘‘watch-ing TV’’ at retest). The items were summed inorder to get an index of consistency in FBMs

ranging from 0 to 10. This coding slightly differsfrom Conway et al. (1994), in which a score of2 was given if participants provided the same or

more specific responses at the retest than at theinitial test. We consider that our coding system iscloser to the definition of consistency (i.e., con-formity with previous attitudes, behaviours, or

practices) which only allows people who gave anidentical answer to obtain the highest score.Indeed, giving a more specific response results

in an equally large deviation from the originalanswer as does giving a less-specific response.

Event memory. Five variables were consideredon people’s memory of the terrorist attacks. They

were selected from the sample of questionsreported in Luminet et al. (2004) as beingrepresentative of different important aspects

that occurred that day: (a) number of hijackedplanes, (b) names of the airline companiesinvolved, (c) number of people aboard the planes,

(d) time lag between the impact and the collapseof the South Tower, and (e) time lag between theimpact and the collapse of the North Tower. For

each item, responses at the first data collectionand retest were compared. Scores were computedfor each question by comparing responses at the

test and retest. A score of 2 was assigned ifrespondents provided exactly the same answers atboth phases of data collection, and the two

answers were either completely or basicallycorrect (i.e., for the question on the names ofthe airline companies: American Airlines and

United Airlines). A score of 1 was assignedwhen an initially accurate answer was followedby a minor gain/loss of information at retest (i.e.,

American Airlines and United Airlines at test,United Airlines at retest). Finally, 0 was assignedwhen answers were completely inconsistent (i.e.,

American Airlines at test, Continental Airlines atretest), when the answers were missing at bothphases of data collection, or when completely

irrelevant answers were provided at both test andretest. The items were summed in order to get anindex of event memory ranging from 0 to 10.

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The next measures were only considered at thefirst data collection, as all the models tested insiston the impact of the predictors at encoding. It isthus more reliable to consider retrospectivemeasures taken days or weeks after the eventrather than after approximately one and a halfyears as assessments of reactions at encoding.

Appraisal of novelty. Participants rated how (a)common, (b) unusual, (c) special, and (d) ordin-ary the event was. The items ranged from 1 ‘‘notat all’’ to 7 ‘‘very much’’. Scores on items (a) and(d) were reversed.

Emotional feeling of surprise. Participants ratedhow expected the event was. The scale rangedfrom 1 ‘‘not at all’’ to 7 ‘‘very much’’. Scores onthis item were reversed to assess surprise.

Appraisal of importance. Respondents ratedthe extent to which the event was important (a)for themselves, (b) for their family and friends, (c)for their country, and (d) at the internationallevel, on four 7-point scales (1�‘‘not at all’’, 7�‘‘very much’’). Additionally, they rated the extentto which (e) the original event had consequencesfor them on a 7-point scale (1�‘‘no consequencesat all’’, 7�‘‘many consequences’’).

Intensity of emotional feeling states. Participantsrated the extent to which they felt (a) upset, (b)moved, and (c) shocked by the news on 7-pointscales ranging from 1 ‘‘not at all’’ to 7 ‘‘very much’’.

Rehearsal. Participants rated (a) the frequencywith which they had thoughts, memories, orimages related to the event. Then, respondentsdescribed (b) how many times they had discussedthe events. Finally, participants rated (c) howoften they had followed the news via the news-papers. The three items were rated on 5-pointscales (1�‘‘never’’; 5�‘‘more than 15 times’’),and referred to the 3 days immediately precedingthe questionnaire administration. We used thelast 3 days as a reference point in order to avoidceiling effects.

Attitudes. Only non-US respondents rated ontwo 7-point scales (1 ‘‘not at all’’, 7 ‘‘very much’’)to what extent they liked (a) the United States asa country, and (b) United States citizens.2 Thenthey rated the extent to which they had knowl-edge about the US, on a 7-point scale rangingfrom 1 ‘‘almost nothing’’ to 7 ‘‘more than anycountry’’. These three measures were consideredat the first data collection and were only relevantfor Finkenauer’s and Er’s models.

Prior knowledge. For Conway’s model, respon-dents reported (a) the number of floors of theWTC towers, (b) the year in which a previousattack against the WTC occurred, (c) the name ofthe administration located at the Pentagon, (d)the number of people working in the WTC, (e) thenumber of terrorist attacks that occurred in theUS from 1998 to 2001, (f) the names of Islamicterrorist groups. For the last two questions weadded 1 point for each correct answer. All theother questions were scored as 2 if the answer wascompletely right, 1 if it was basically but notentirely correct, or 0 when no answer was given orwhen the answer was completely wrong. Toillustrate, consider answers to when the WTChad previously been attacked: a 2 was given to ananswer of 1993, a 1 to answers of 1991, 1992, 1994,or 1995, and 0 to all other years or if no year wasprovided. Details about percentage of correctanswers can be found in Luminet et al. (2004).The selection of questions was made in order tohave different levels of difficulty and to avoidfloor and ceiling effect.

Procedure

Questionnaires were distributed among universitystudents, university faculty and staff, and experi-menters’ acquaintances. At the test, studentscompleted the questionnaires in groups (i.e.,during class), whereas other participants weretested individually. Participants in the test phasecompleted a paper-and-pencil version of thequestionnaire, except for 111 Americans whoanswered an online version (see Luminet et al.,2004). Questionnaires were anonymous. How-ever, at the test participants who had agreed toparticipate in subsequent phases of data collec-tion were invited to provide their name, postaladdress, and/or e-mail address. People who had

2 One could argue that attitudes should also have been

assessed within the US sample. However, there were several

reasons for not including them. First, we made the assumption

that we would obtain ceiling effects on these variables within

this group. People from one country usually exhibit highly

favourable attitudes towards themselves, especially at times of

high threat for their nation, which was the case after the 9/11

attacks. Second, we think that even US residents who hold less

positive attitudes were not likely to express them

spontaneously through explicit measures immediately after

the 9/11 attacks. Only implicit measures would have been

appropriate, thus making their assessment through a web

questionnaire prohibitively long and difficult.

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provided their postal address received the retestversion of the questionnaire by post, as well as aletter with the web address for the on-lineversion, and an ID number to match the testand retest questionnaires. People who had pro-vided their e-mail address only received the letterwith the web address and ID number.

Statistical analyses

Structural equation modelling. To test the fourmodels (Brown & Kulik, 1977; Conway et al., 1994;Er, 2003; Finkenauer et al., 1998) on the data of thepresent study, the SEM approach (Bollen, 1989)was applied, through the Lisrel software package(Joreskog & Sorbom, 1996). More specifically, thehypothesised pattern of relationships among thevariables was estimated through a path analysismodel. In such a model, explanatory and depen-dent variables are all observed, and constructs areconsidered to be directly measured, not assessedthrough a specific measurement model. As aconsequence, no measurement errors are esti-mated by the procedure, since all theoreticalconstructs are supposed to be fully captured bythe corresponding observed indicators. Relation-ships among variables in the model can be direc-tional or non-directional. Directional relationshipsare estimated through regression coefficients.Non-directional relationships correspond to cov-ariances among exogenous variables. For eachendogenous variable, the procedure gives anestimate of the proportion of variance not ex-plained by the structural relationships (Bollen,1989; Joreskog & Sorbom, 1996). Finally, allcomputed coefficients are associated with a sig-nificance test, which allows the researcher to drawinferences about the generalisation of the resultsto the population.

The procedure gives general indices of fit for themodel. For the purposes of the present paper, thechi-square, GFI, AGFI, RMSEA, SRMR, NNFI,and chi-square fit index divided by its degrees offreedom are considered. These are standard in-dices in the SEM literature (Kline, 1998). The chi-square (and its corresponding DF) is a measure ofoverall fit of the model to the data. It measures thedistance between the sample covariance matrixand the estimated covariance matrix. A small non-significant chi-square corresponds to good fit, anda large significant chi-square to bad fit (Bollen,1989). The Goodness of Fit Index (GFI) measuresthe amount of variance and covariance in thesample matrix that is predicted by the estimated

covariance matrix. The Adjusted Goodness of FitIndex (AGFI) adjusts for the degrees of freedomin the model. Both indices range from 0 to 1 andcan be considered as satisfactory if they exceed.90 (Bentler & Bonnett, 1980). The Root MeanSquare Error of Approximation (RMSEA) is ameasure of the approximation between the modeland the population covariance matrix. A perfect fitwill yield an RMSEA of zero. Values equal to orlower than .05 are considered good. Values ex-ceeding .10 are indicative of a poor fit (Browne &Cudeck, 1993). The Standardised Root MeanSquare Residual (SRMR) corresponds to theaverage difference between the predicted andobserved variances and covariances in the model,based on standardised residuals. The smaller thestandardised RMR, the better the model fit.The Non-Normed Fit Index (NNFI) is also calledthe Bentler-Bonett Non-Normed Fit Index. Itreflects the proportion by which the model fitimproves as compared with the null model (ran-dom variables). It penalises for model complexity,and it is less affected by sample size. It is notguaranteed to vary from 0 to 1, and a negativeNNFI indicates that the chi-square/DF ratio forthe null model is less than the ratio for the givenmodel. Higher values are indicative of better fit.Finally, we report the chi-square fit index dividedby its degrees of freedom. This procedure isvaluable because it makes the statistics less depen-dent on sample size. Carmines and McIver (1981)recommended that relative chi-square should be inthe 2:1 or 3:1 range for an acceptable model. Kline(1998) maintained that 3 or less is acceptable.

RESULTS

The statistical analyses comprised three steps: (1)descriptive statistics, (2) Pearson correlations toinvestigate the relations between observed vari-ables, and (3) SEM. In each step the results areexamined separately for the US and the non-USgroups.

Descriptive statistics and Pearsoncorrelations among variables

Descriptive statistics (M, SD, range) and Pearsoncorrelations among variables are described inTable 1 (US group) and Table 2 (non-US group).Descriptive statistics will only be commented onbriefly here, as they were already described in

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detail in Curci and Luminet (2006) and inLuminet et al. (2004). Overall, the mean levelswere medium to high for all variables for bothgroups, except for event memory and impor-tance/consequentiality, which reached higher le-vels in the US group. The highest correlations(r�.30) were found in both groups between

FBM and event memory, between importance/consequentiality on the one hand and emotionalfeeling states and rehearsal on the other hand,and between emotional feeling states and re-hearsal. The highest correlations involving FBMswere found with event memory, surprise, andrehearsal in the US group. However, in the non-US group the correlation between surprise andFBMs was low.

Although the average values of the surpriseratings are similar for the US and non-USgroups, the inclusion of the variable surprise inthe model is justified with respect to the firstclassical hypothesis of invariance, applicable to

SEM path analyses (Bollen, 1989; Kline, 1998).Indeed, as a careful inspection of the two inputmatrices reveals, the correlation coefficients ofthe variable surprise with the other variables inthe model for the US sample are generally highand significantly different from zero, while forthe non-US sample all correlations are close tozero. Given these different patterns of correla-tions, we are enabled to run SEM analyses on thetwo subsamples separately, since no invariance isfound across the two covariance matrices. Inother words, although the distribution of thesurprise ratings are generally skewed in thewhole sample, different pattern associationsemerged among surprise and the other variablesin the model for each of the two groups ofrespondents. This difference in the patterns ofassociations was thus investigated through theapplication of a SEM model aiming to testprecise hypotheses of relationships among theFBM variables.

TABLE 1

Correlation matrix: US subsample

1 2 3 4 5 6 7

1. Flashbulb memory 1.000

2. Event memory .275 1.000

3. Novelty .046 .181 1.000

4. Surprise .266 .115 .294 1.000

5. Importance/consequentiality .003 .063 .090 �.028 1.000

6. Emotional feeling states �.041 .141 .291 .001 .432 1.000

7. Rehearsal .147 .148 .104 .024 .408 .303 1.000

Mean 8.25 5.83 25.65 6.61 30.01 16.82 9.08

SD 1.81 2.22 3.01 1.17 4.02 4.02 2.05

Range 3�10 1�10 16�28 1�7 19�35 5�21 5�15

Correlation matrix of the variables included in the structural model of formation and maintenance of flashbulb memory: US

subsample.

TABLE 2

Correlation matrix: non-US subsample

1 2 3 4 5 6 7 8

1. Flashbulb memory 1.000

2. Event memory .246 1.000

3. Novelty .058 .115 1.000

4. Surprise .063 �.055 .069 1.000

5. Importance/consequentiality �.003 .023 .136 �.058 1.000

6. Emotional feeling states �.001 .023 .300 �.023 .465 1.000

7. Rehearsal .153 .249 .111 �.043 .323 .311 1.000

8. Attitudes �.052 �.005 .120 .028 .295 .267 .160 1.000

Mean 6.58 2.99 24.71 6.55 25.30 16.51 8.57 10.86

SD 2.00 2.06 3.49 1.12 4.93 3.89 2.20 3.15

Range 0�10 0�10 4�28 1�7 13�35 3�21 4�15 3�19

Correlation matrix of the variables included in the structural model of formation and maintenance of flashbulb memory: non-US

subsample.

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SEM: Comparison of fit indices acrossmodels

For the prediction in the US group, Table 3 shows

that Finkenauer et al.’s (1998) model provided the

best indices, which were always above the stan-

dard thresholds (see Method). The Brown and

Kulik model had also satisfactory indices, except

for the AGFI, which was just below the .90

threshold. The two other models, however, had

several indices that reflect a poor fit. For Conway

et al.’s (1994) model, the chi-square was signifi-

cant, the AGFI and RMSEA were below the

thresholds, as was the chi-square by DF index.

Er’s (2003) model evidenced an even poorer fit

with a largely significant chi-square, very low

AGFI, very high RMSEA, low NNFI and a chi-

square by DF index above 4.Regarding the prediction for the non-US

group, it was again Finkenauer et al.’s model

that had the best indices. This time, however, the

chi-square by DF index was above the usual 3:1

threshold (3.71) but still lower than for the other

models. RMSEA was also above the .05 value for

good fit, but was still lower than the .10 threshold

indicating poor fit. For the non-US group, Er’s

model had more acceptable fit indices which were

very close to those for Finkenauer et al.’s (1998)

model, with the exception of a higher chi-square

by DF ratio. Conway’s model was third with an

unacceptably large RMSEA and a chi-square

by DF ratio that was far above the threshold.

Finally, Brown and Kulik’s model was the poorest

with a chi-square by DF ratio even higher than

Conway’s model and the AGFI below the .90threshold.

SEM: Examination of the paths linkingthe latent variables

The next step was to examine the extent to whichthe paths that were predicted in the four modelswere found to be significant in the present data.

If we first examine Brown and Kulik’s model inthe US group (Figure 1), five predicted pathswere found to be non-significant. First, threedirect predictors of FBMs (importance, emotionalfeeling states, and rehearsal) were not found to besignificantly associated with FBM. Second, tworelationships among predictors (from surpriseto importance and from emotional feeling statesto rehearsal) were non-significant.

When looking at Brown and Kulik’s model inthe non-US group (Figure 2), again five predictedpaths were non-significant. Replicating resultsfrom the US group, importance and emotionalfeeling states were not direct predictors of FBMs.Rehearsal was significantly related to FBMs but,contrary to the US model, surprise was not asignificant predictor. Regarding the relationshipsamong predictors, the non-significant link fromsurprise to importance was again found. How-ever, while the link from emotional feeling statesto rehearsal was found to be significant, the pathfrom novelty to surprise was no longer significant.

Turning to the Finkenauer model, we will firstexamine the results in the US group (Figure 3).This model provided strong support for the direct

TABLE 3

Comparison of fit indices across models and groups

Brown & Kulik, 1977 Conway et al., 1994 Er, 2003 Finkenauer et al., 1998

US Non-US US Non-US US Non-US US Non-US

x2 (6)�10.83,

p�.10

(6)�70.10,

pB.001

(3)�8.54,

p�.04

(3)�32.62,

pB.001

(4)�18.10,

p�.001

(11)�47.52,

pB.001

(14)�18.52,

p �.18, ns

(16)�59.29,

pB.001

GFI .97 .97 .97 .98 .94 .98 .95 .98

AGFI .89 .89 .85 .91 .77 .95 .91 .96

RMSEA .09 .12 .13 .12 .18 .07 .05 .06

SRMR .07 .08 .07 .05 .10 .04 .07 .04

NNFI .80 .53 .66 .73 .28 .86 .89 .86

Chi-square/DF 1.81 11.68 2.85 10.87 4.53 4.32 1.32 3.71

Comparison of fit indices across models (Brown & Kulik, 1977; Conway et al., 1994; Er, 2003; Finkenauer et al., 1998) and across

groups (US vs non-US).

The thresholds were: for GFI and AGFI,�.90; for RMSEA, close orBto .05; and for Chi-square/DF in the 3:1 range. Thresholds

are only relative for SRMR and NNFI. For SRMR, smallest values are indicative of good fit and for NNFI, largest values are

indicative of good fit.

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link from novelty to surprise and from surprise toFBMs. However, the indirect path was not foundto be significant, as the relationship betweenrehearsal and event memory was non-significantfor this group of respondents. The path fromsurprise to emotional feeling state was also notfound.

We also tested some additional links. First weexamined the direct links from emotionality andfrom rehearsal to FBMs as they were suggested inConway et al. (1994), but these paths were foundto be non-significant. Second, one additional pathwas estimated in a second step between noveltyand emotional feeling states. The rationale forexamining this path was that while novelty is thedirect antecedent of the specific emotional stateof surprise, it should also affect the entire emo-tional reaction to the news. This assumption wasconfirmed by a significant relationship betweenthese variables.

In the non-US group a rather different patternof relationships was found (Figure 4). First, allrelationships among variables from the indirectpaths appeared to be activated. Contrasting withresults for the US group, a significant relationshipbetween rehearsal and event memory was found.Second, the direct path was disconfirmed, withnon-significant relationships between novelty andsurprise, and between surprise and FBM. We alsoexamined three additional paths as we did for theUS group. Perfectly replicating these results, wedid not find a significant relationship betweenemotional feeling states and FBM, nor onebetween rehearsal and FBM. However, in asimilar manner to the findings for the US group,the path between novelty and emotional feelingstates was significant. Finally, a significant linkwas also found between novelty and eventmemory.

In Conway’s model, examined for the USgroup, the effects of the two direct predictors ofFBM (emotional feeling states and rehearsal)were found to be non-significant. Also, priorknowledge did not predict emotional feelingstates and importance (Figure 5). In the non-USgroup, emotional feeling state was again a non-significant predictor of FBMs, but this timerehearsal was significant. The predicted pathbetween prior knowledge and importance wasalso non-significant (Figure 6).

The examination of Er’s model for the USgroup revealed that three out of the fourdirect predictors of FBMs had non-significanteffects (importance, emotional feeling state, and

rehearsal). Only the variable combining noveltyand surprise had a direct impact on FBMs (seeFigure 7). In the non-US group most of therelationships that were predicted were actuallyfound, except that among the three direct pre-dictors of FBMs, only event memory was sig-nificant (see Figure 8).

DISCUSSION

The discussion will be divided into four mainsections. We will first summarise results regardingfit indices for the models tested. We will alsoexamine whether the pattern of relationshipsbetween the predictors and FBMs were found asexpected in the different models. We will thenexamine the link between novelty/surprise andFBMs and discuss our rationale that socialidentity is a key factor for the activation of thispath. In the next section we will discuss the linksbetween emotional feeling states and FBMs. Wewill conclude with a review of the limits of thestudy and the future perspectives that need to beconsidered.

Summary of the results

In the prediction of FBMs for the US group,Finkenauer’s model evidenced the best fit forall of the indices considered. For the non-USsample, Finkenauer’s model again had the bestindices. In this sample, however, some indiceswere below the required thresholds. This meansthat, although it was the best available model,some improvements are still warranted.

The data showed that a large number ofpredicted paths were non-significant in Brownand Kulik’s model. In both the US and the non-US groups, the paths from surprise to importanceand from importance to FBMs were non-signifi-cant. The first result can be explained by confu-sion in this model between appraisals andemotional feeling states. Cognitive theories ofemotion (e.g., Frijda, 1986; Lazarus, 1982;Leventhal, 1984; Scherer, 1984) suggest thatemotions result from an initial appraisal ofstimulus conditions in terms of their relevancefor the organism and its behavioural adaptation.While these theories suggest that appraisals pre-cede feeling states, Brown and Kulik’s modelerroneously predicts that an initial feeling statethen elicits an appraisal. The second result

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suggests that although importance is a centralvariable in accounting for FBM formation, itseffect is only indirect.

In Conway’s model one key prediction is thatemotional feeling states will directly influence theamount of FBMs. This assertion was not sup-ported in either of the samples. Prior knowledgewas also assumed to be a key predictor in thismodel. The present data show that, contrary tothis assumption, prior knowledge did not predictimportance in any sample. Additionally, priorknowledge failed to predict emotional feelingstates in the US sample. These results suggest aless central role for prior knowledge than wasoriginally proposed by Conway’s model. Anotherimportant limitation in the ability of this model toaccount for the present data was that, in the USsample, neither of the direct predictors of FBMs(emotional feeling states and rehearsal) wasfound to be significant.

Turning to Er’s model, a clear distinction ismade for the US and the non-US data. Er’s modelwas able to confirm most of the assumptionsmade for a non-involved group (i.e., the non-USone in this case). In contrast to the support shownfor the model in the non-US data, the modelsuggested for the involved group (i.e., the USgroup) was not supported. One key assumptionthat failed to receive support is the direct effect ofimportance/consequences on FBMs. The pathwayhad a coefficient close to 0 in the present data.The two other direct predictors were, as inConway’s model, emotional feeling states andrehearsal. These relationships were again non-significant. It is important to remember, however,that US participants who were involved in ourstudy were not direct victims of the event as wasthe case for the involved group in Er’s study (seethe last section below).

When we estimated Finkenauer’s model usingthe present data, we replicated most of the pathsobtained in the initial study (Finkenauer et al.,1998). However, some paths were not found, suchas the one linking surprise to emotional feelingstates. This path was not found in either sample.This suggests that the different emotionalfactors investigated were more independent thanpreviously found. While surprise is related to aspecific state corresponding to an orientationresponse, the variable ‘‘Emotional feeling states’’is related to the global intensity of affect.

It is important to note that in both groups ofrespondents FBMs were formed (see Curci &Luminet, 2006), suggesting that the activation of

only the direct or the indirect path is sufficientfor the elicitation of FBMs. This representsan important advancement over the study byFinkenauer et al. (1998), in which only a highlyinvolved group was considered. It is also re-markable that although the data published byFinkenauer et al. in 1998 were based on a singlemeasure of FBM, a model of FBM formationvery close to the one found for the present studywas observed, in which a consistency measure ofFBM was considered. This is a strong indicationof the solidity of the model, because the wayFBM was operationalised did not greatly influ-ence its relationships with the key variablesinvolved in FBM formation.

Social identity: A key variable for theprediction of the link between noveltyand FBMs

As explained in the introduction, some events orcircumstances activate more highly an indivi-dual’s personal identity, while others make theirsocial identity more salient. We suggested that inreference to the 9/11 attacks, the US participants’social identity was particularly activated, giventhe country’s reactions in the days and weeksfollowing 9/11. According to Turner (1982),perception of group membership is shaped byfactors such as similarity, common fate, proximity,and shared threat, all characteristics particularlysalient in the US group during that time. Sharedthreat seems to be a particularly importantpredictor for initiating commemoration in agroup. The number of commemorations, in turn,is related to strengthened ingroup identity(Sahdra & Ross, 2007). This was observed amongUS citizens who very rapidly developed frequentcommemorations as a response to the sharedthreat created by the attacks. These commemora-tions were clearly related to the reinforcement ofsocial identity, with for instance constant exhibi-tions of a very symbolic feature of US identity(i.e., the flag) that was displayed on housewindows and jackets, or wrapped around peoplewalking in groups in the street, or carryingcandles. A similar activation of social identity isassumed for the death of the Belgian king, theevent investigated by Finkenauer et al. (1998) tobuild their model. In a country divided by culturaland linguistic conflicts the king was perceived bythe Belgian citizens as the main symbol of unityfor the country. His sudden death was perceived

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as a shared threat for the future of the nation.

Numerous commemorating behaviours occurred

soon after, such as individuals gathering in front

of the king’s palace, holding Belgian flags, or

people putting stickers with the Belgian flag on

the back windows of their cars. The affective

reactions of sadness and grief were shared by the

vast majority of Belgians (Lits, 1993).Interestingly, for these two groups, the test of

FBM model formation showed that the paths

from novelty to surprise and from surprise to

FBMs were significant. Contrasting with these

results, a fairly large amount of studies suggests

that when no social identity is at stake, the path

from surprise to FBMs is no longer significant

(for more details, see Luminet, 2009). First, this

was observed for the non-US group in the present

study. Second, Mahmood, Manier, and Hirst

(2004), in a study with gay men who experienced

multiple deaths among their close relatives, found

no relationship between novelty/distinctiveness

and the elaborateness of the memory for the

reception event.3 We can assume that in that

study the personal identity of participants was

more activated than their social identity (as

member of the gay community). Third, in the

Conway et al. (1994) study, the UK social identity

was probably not activated in the group of UK

citizens in response to Mrs Thatcher’s resignation

as there was no collective threat to the country

based on this event. Another PM was going to

replace her and participants knew that the UK

political system would continue as usual. The

event was of political relevance for people’s daily

activities rather than for the identity of the

country. Another indication of the lack of activa-

tion of social identity was the absence of public

demonstrations related to UK identity (such as

the exhibition of flags) that followed the news.

Furthermore, the event was experienced in dif-

ferent ways (as being negative, positive, or

neutral) among UK citizens, depending on

their political orientation, while the activation of

social identity involves high intra-group homo-

geneity in affective reactions and attitudes.

Once again, no effect of surprise on FBM was

observed.

Taken together, these results suggest that theinitial activation of social identity is a necessarycondition for the novelty-surprise-FBM path tobe triggered. This would mean that a salient andsurprising event could make consistent memoriesfor the reception context only if it has relevancefor a social community. As noted by Berntsen(2009), p. 198) in the context of the invasion ofDenmark during WWII, ‘‘many memory reportsillustrated that apparent trivial situations could beremembered for decades, if the situation inquestion had addressed dilemmas of group com-mitment (e.g., showing the appropriate Danishattitude) versus kindness to all fellow humanbeings (including German soldiers)’’. One alsoneeds to consider that the relationship works theother way around, such that the appraisal ofnovelty is also influenced by initial higher groupcommitment. In other words, one would alsoappraise an event as particularly novel or salientbecause it is highly relevant for one’s socialidentity. But whatever variable comes first, theseresults suggest that social identity would be animportant factor to consider when predicting theformation of FBMs.

It will be important in the future to givegreater consideration to the social functions ofFBMs, Consistent FBMs for a socially relevantevent within a community is suggested to providetemporal continuity and cultural coherencewithin the group (Bar-Tal, 2003; Frijda, 1997;Staal, 1990). The group then has a shared historycommon to all ingroup members, which makesthem different from other groups.

Emotional feeling states and FBMs

One critical link that is assumed by three models(Brown & Kulik, 1977; Conway et al., 1994; Er,2003) is the one between overall intensity ofemotional responses and FBMs. The present dataclearly disconfirm this assumption. When lookingat other available studies examining predictors ofFBM formation, a similar conclusion can bedrawn. For instance, in a recent review of theliterature, Luminet (2009) found that among 14data sets that examined this relationship, it wassignificant in only three cases. Together with thepresent results, this is a strong indication that thedirect link between intensity of emotional feelingsand FBMs is not sustained. However, as notedbefore, the link between the specific emotionalstate of surprise and FBMs was found for the US

3 Mahmood et al. (2004) used a single measure of memory

for the reception event. They thus adopted the vividness

perspective of FBMs rather than the consistency one. One

would therefore need to be careful about the implications for

the present study based on the consistency of FBMs.

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group. These results highlight the importance ofdifferentiating between these two different com-ponents of emotional reaction when modellingFBM formation. Although the direct linkbetween intensity of affect and FBMs was notfound, there are stronger indications for anindirect link through rehearsal and event-memory. In the review by Luminet (2009), thelink between emotion and rehearsal was found ineight out of nine available data sets and the linkbetween rehearsal and event-memory in four outof five data sets.

Further studies would also need to clarify hownovelty/surprise has an impact on the formationof FBMs. It is quite likely that this effect isactually mediated by increased attention. Indeed,novelty and surprise have been shown to have adirect effect on the enhancement of attention(e.g., Lee, Youn, Gallagher, & Holland, 2006;Nyberg, 2005).

Limitations of the present study andfuture perspectives

In this last section we would like to raise someissues that limit the present findings and that needto be considered in future studies on FBM modelformation.

A first aspect to consider is related to the level ofspecificity of the event we examined (9/11) ascompared to other public events considered in theFBM literature. The 9/11 attacks were initiallyselected as an event that encompassed the maincharacteristics necessary for the formation ofFBMs (high surprise, importance, emotionality).It is possible, however, that the event was toospecific and included characteristics that wererarely encountered together in other studies. Thesewere the number of victims, the severity in the USpopulation of the psychological trauma that re-sulted, and the scale of national and internationaloutcomes (new safety regulations, new laws to limitterrorist acts, diplomatic and military reaction ofthe US, strong tensions in the Middle East). Theexceptional aspect of 9/11 was also emphasised bythe frequency with which people spontaneouslyreported a sense of historical awareness (as theevent occurs, the immediate feeling that it wasgoing to be a major historical event at the worldlevel). Also, many people reported easy access toother historical events as comparisons (e.g., thePearl Harbor attack) (Lardellier, 2006). Thus,although the results mainly support the Finkenauer

model of FBM formation, some specificities foundin the present data, particularly for the US sample,might be attributed to the characteristics of theevent.

The effect of novelty needs to be examinedmore systematically. While the initial modeldeveloped by Finkenauer et al. (1998) onlyshowed a relationship between novelty and sur-prise, the present data also showed a relationshipto emotional feeling states in both groups. Thissuggests that novelty has a more general impacton the emotional response than originallyassumed. In addition, novelty was directly relatedto event memory, although only in the non-USgroup. This suggests a purely cognitive effect asnovelty is related to an initial orientation reactionthat will then redirect attention and favour theencoding of information. Future studies shouldreplicate this result and determine why it was onlyfound for the less-involved group.

One important predictor of FBM includes priorknowledge or attitudes. Previous models consid-ered either attitudes (Er, 2003; Finkenauer et al.,1998) or prior knowledge (Conway et al., 1994). Asimultaneous investigation of attitudes and knowl-edge could be relevant as attitudes involve moreaffective components, while knowledge is morerelated to cognitive ones. It is very difficult,however, to get an accurate rating of prior knowl-edge because of the rapid contamination of themeasure by media coverage. Therefore this mea-sure, which was only suggested by Conway, shouldbe avoided in the future not for theoretical reasonsbut for practical ones due to the unavoidable delayin data collection. Although attitudes can also bemodified by media coverage, the effect is likely totake more time. Attitudes change progressivelyafter being exposed to a variety of opinions, whileknowledge can be increased (or decreased) afteronly one exposure to the media. Attitudes were notinvestigated for the US group in the present studybecause we assumed that the items would all haveevidenced ceiling effects. This, however, precludedmaking a complete assessment of the modelsthat included this variable. We also need to becautious in the real interpretation of event memorybecause the information reported was rehearsed inmany ways and for a long time. This suggests thatthis variable involves a partially co-constructedmemory.

Some improvement in the measure of socialidentity is also needed. In the present study, socialidentity was based on the citizenship of respon-dents. This involves high homogeneity within the

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group. This is likely to be the case for the USgroup, for which the 9/11 attacks created a strongincrease in social identity. For the Europeangroups, however, the variability was probablylarger. It could thus be useful in future studies toinclude a continuous measure of social identityand to examine whether using social identity as acovariate would make any difference in therelationships between predictors of FBMs.

In conclusion, the present paper providesstrong support for one model explaining theformation of FBM by the combination of cogni-tive, emotional, and social factors. It suggests thatsocial identity could determine the type of path(direct vs indirect) that is activated and that onlyone path is sufficient to produce FBM.

Manuscript received 5 March 2008

Manuscript accepted 31 May 2009

First published online 26 August 2009

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