Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 T Charlottesville, VA, VA, USA Charlottesville, DOI: 10.1080/13825580701640374 ISSN: 1382-5585/05 print; 1744-4128 online http://www.psypress.com/anc Aging, Neuropsychol -al [email protected] E-mail: State Univers The Pennsylvania 1 D al. Adulthood et Gerstorf Across ExecutiveDenis Dysfunctions the DEXSelf-ReportQuestionnaire Properties andCorrelatesof Adulthood: Measurement Executive DysfunctionsAcross NANC1382-5585/051744-4128Aging,Neuropsychology, Neuropsychology, Cognition, and and CognitionVol. No. 0, 0, sep 2007: pp. 0–0 State College,PA16802, USA and Department of Human Developm IMOTHY ENIS Address correspondence to:DenisGerstorf, Depart validity. Keywords life. everyday as welldirections res for future discuss impli factor.We affect a negative oldergroups,an than reported moreproblems functions are known to decline with todecline known functions are executive that,although found cognition.Wealso and affect, personality, health, were associated withindividual difference characteristics includingage, subjective ad frequentthroughout were moderately withoneunderlyi described simoniously reported executive difficulties. Our results re freque andexploredthe (DEX) Questionnaire st factor the weexamined years), 18–97 obtained twoindependent from Difficulties in executive processes can disturbdaily life functioning. Using data ABSTRACT © G 2008 Psychology Press, animprintTaylor of the &Francis Group, anInformabusiness ERSTORF A.S : Adult lifespan; ; ALTHOUSE 1 , K ogy, and Cognition, AREN 2 L. S ity, 114 Henderson Building, Un ent andFamily Studies,ThePe IEDLECKI 2 Department of Psychology, community-dwelling samples( earch on executive functioning difficulties in functioning difficulties executive earch on i First: 1–22, 2008 advancing adult age, younger agegroups advancing adultage,younger ng factor. Everyday executive dysfunctions executive ng factor.Everyday 2 , E ructure of the Dysexecutive Functioning oftheDysexecutive ructure ulthood. Reports of ulthood. Reportsof executive problems cations for the validity of the instrument thecations forthevalidityof ment of Human Development and Family Studies, Family and Development Human of ment vealed that executive problems are par- LLIOT effect that was partially mediated by effectthatwaspartiallymediated ncies andpotentialself- correlates of Structural equatio M. T M. iversity Park,PA16802,USA. UCKER University ofVirginia, nnsylvania State University, nnsylvania State -D n n modeling; Test 1 ROB =468, =468, 2 , AND n 2 =669,

Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 functioning aspotentia or dysexecutive syndrome areused here. loca anatomical proposed of its terms To avoidthedifficult situation ofde previously been known as“frontal-lobe syndrome” (Stuss&Benson, 1984). general patternofexecutivediffi The include euphoria, apathy, aggression, problems arefrequently ob motivational (cf. Parkin,1998). In ad tasks thatinvolve organization or planningover anextended period oftime distracted, disinhibited, poor atdecision-making, and unable toperform form, forexample, dysexecutive individuals are characterized as being easily Wilson, Evans,Emslie, & Burgess, 1995; Schwartz, 1990; (Baddeley, behavior sequencing and as planning well as ponents asdifficulties inattentionco acteristics includingage,gender,he phases ofadulthood and investigate ava the frequency of executive dysfunctions in everyday lifeacross various invariance across age groups and independent samples. Second, we explore executive difficulties,including the Emslie, &Evans,1996),aninstrument Dysexecutive Questionnaire ties ofthe range.First, theentireadultage across of self-reportedbehavioraldifficu examine two sets of questions about such executivedifficulties. The major ob extent other factorsas negative such a frequent amon more they are whether life, ineveryday experienced are dysfunctions such executive how often Salthouse,in press;Ryff &Singer,19 and old age (Baltes& Baltes, 1990; Lawton, 1983; Rowe&Kahn, 1997; tioning and thus constitute threatsto th or switching among problem-solving strategiescan disturb daily lifefunc- behavioral problems in sustaining atte of executivedifficultie Various forms INTRODUCTION 2 better understand the processes underl (for review, see Malloy &Grace, 2005). Such questionnaires mayhelp us to affective-motivationala changes often designed tosample the rangeofeveryda D Deficits inexecutive processes en Various self-or informant-report ENIS G ERSTORF

ET

AL l correlatesof the DEX. . dition tothesecognitive di lties ineverydayexecutive functioning ntion, inhibitinginappropriate behaviors, alth, affect, pers ntrol, andreasoning, the nature andfunctionalimplications the tion, the terms executivedysfunctions fining asetofcognitiveproblemsin we examine the measurement proper- examinethemeasurement we e qualityoflifethroughoutadulthood designed to assess everyday signs of everyday toassess designed 98).is known,however,about Little compass suchdive underlying factor structure andits ying rather mild forms of executive of mild forms ying rather (DEX;Wilson, Alderman, Burgess, restlessness, orvariable motivation. ssociated with executive difficulties ffect orhealthmightbeinvolvedin culties closely resembles what has culties closelyresembleswhat g certainggroups, age andwhat to y signsofcognitive,behavioral, and served as well.Theseproblemsmay served s such as experiencingcognitive- s such riety of individual difference char- difference individual of riety jectives of the present study are to measures have been specifically 1998).Initsclinicallysignificant fficulties, affective and onality, andcognitive rse cognitivecom- Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 decline in relevantcognitive abilit dysfunctions ineverydaylifeandho abstract problemsolving; seealsoChan, 2001). inhibition, intention, 2006: social regulation, and McFarland, & Walmsley, clinical populationsbefo canalso thatat evidence suggests istics. Initial with their relation executive problemsor directly examining question ple, demonstrating factorialinvariance ac or whether sucha factor structure differs across theadultage range. Forexam- in non-clinicalexecutive dysfunctions Sala, 2003). isknown,however,about Less the of factor self-reported structure tive affect, and negativeaffect:Burgesset (inhibition, five factors have identified 1998; seealsoSt tion (Wilsonetal., that the DEX encompasses three factors, relatives of neurological patientsin mi shown thatthe DEXencompasses several rela in(often studies analytic factor executive problems(Bur ment fortapping be a has beenshownto which (DEX), (Burgess, Alderman, Evans, Emslie, & Wilson, 1998; Chan, 2001). problems executive report and monitor non-clinic found in under-reports of executive dysfunctions using these questionnairestypical have,forexample,indicatedthe that errors in goal-directed behavior (Chan, problems ineverydaylifeincludinglaps formance or in typicalpsychometric that executivedysfunctionsacknowledged ma with performance onexecut (1998) reportedthattheDEX (initsin Inlinewith characteristics. difference individual certain to relate also problems executive more whether known encing executivedysfunctionsless fre be abletoavoidthese better or ations 2006) suggest that themay hand elderly 1998;Roecke, &Kolarz, 1993;Mroczek Kleban, &Dean, 2000; Lawton, ulation with age(Carsten increasing instances morefrequently.At the same such report elderly the that suggest may 2005) Schaie, 2004; Salthouse, It is also largely anopenquestion It isalso One commonlyused ratingscaleis al samples suggestingthatco s about age-related differencesin the frequencies of ive tasks. However, it ive tasks.However,it been also has repeatedly E XECUTIVE uss & Benson, 1984, 1986),uss &Benson,1984, whereas others d-adulthood, someauthorshave reported und in non-clinical studies (Mooney, studies innon-clinical und tively small) clinical populations have tively small)clinical samples of commu samplesof sen, Pasupathi, Mayr, Pasupathi, & sen, Nesselroade, intentionality,executive memory, posi- w this may differ byage.Age-graded maydiffer w this neurological tests of cognitive abilities neurological tests least some of the factors identified in 2001; Reason, 1993). Previous studies ies (Lindenberger situations tosome its conceptual rationale, Burgess etal. how oftenpeople experienceexecutive sensitive and ecologicallyvalidinstru- sensitive formant-rated version)correlated well namely cognition, behavior, andemo- ross ageconstitutesakeysteptowards al., 1998; seealsoAmevia,Phillips,& le suchemotionally challenging situ- amongneurologicalpatientsarenot time, findings of better emotion reg- quently. In asimilar vein,littleis other individual difference character- difference individual other gess et al.,1998;Chan,2001). Initial in everyday life more accurately lifemore ineveryday D distinct factors.Using the reports of es of intention, es of theDysexecutiveQuestionnaire YSFUNCTIONS y notnecessarilyrelatetolow per- mmunity-dwelling individuals A CROSS nity-dwelling adults nity-dwelling extent, thus experi- slips ofaction,or & Baltes, 1997; & Baltes, A DULTHOOD 3 Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 personality characteristics(e.g.,neurotic Charlottesville, in the years2004(St in Charlottesville, standardized cognitivemeasures (Digit healthy (4.0,onaverage,scale),5-pointa on and their average scoreson two were highly educated (>15 years, on average), they rated themselves as years), middle-aged(40–59 years), and ol are presented in Table 1,separatelyforthethreeage groups: young (18–39 excluded dueDEX. tomissing dataonthe years; 66% women) included in Study 2 alsodid not differ from those (18–94 demographic (age, gender) and health These persons did not differ from those excluded due to missing data on with validdataontheDEXwe women) Siedlecki, and Krueger (2006). In St descriptions oftheprocedures an at theCognitiveAgingLaboratory Participants andProcedure METHOD health,personality affect, to typical individualexecutive problems suchwhetherfrequenciesgroup. also explore differbyage relations of We dwelling adultsexperienceexecutive the DEXestablished,weexaminein advertisements, studyflyers, and Participants norms. the age-adjusted pendent samples ( years), and older adults (60+ years)and across two moderately largeinde- ture found acrossage groups ofyoung (18–39 years),middle-aged (40–59 motivational aspects.Wethendetermin reflectin various distinguishablefactors clinical andnon-clinicalstudie from In line withthe proposed nature of Questionnaire usingsel a first step,weinvestigate the f In gained about executive dysfunctions by addressing two setsof questions. contributenatu tobetterunderstand the ence characteristicssuch as reports of empirically demonstratingassociations (Chan, 2001; Shallice& Burgess, 1991; 4 D The current project used data collecte The presentstudy attempts toexte ENIS G ERSTORF

n ET =468 and

AL . f-report datafromcommun , and cognitive functioning. n =669). Withthemeasurementproperties of =669). referrals from other participants. fromother referrals dysexecutive behaviors aswellreports d variables arereportedinSalthouse, d variables re of reports ofreports dysexecutivebehaviors. re of were primarily recruited by newspaper negative affect,poorhealth,orcertain udy 1, 468 adults (18–97 years; 62% of theDEXwithotherindividualdiffer- s, we expect the expect s, we udy 1) and 2005 (Study2).Detailed 1) udy a second stephowoftencommunity- a second actor structure of the Dysexecutive the of actor structure ism; Gold&Arbuckle, 1990) may also Symbol andVocabu Symbol g cognitive,g behavioral,and affective- seealsoRabbitt,1997). Inaddition, variables. Similarly, the669 adults e the invariance of the factor struc- the of e theinvariance difference correlates such as gender, problems intheirdailylivesand re included in the present analyses. re includedinthepresent der adults (60+ years). Participants d in twoseparate studies carried out Characteristics of the twosamples Characteristics of at theUniversityofVirginia, nd and qualify previous insights ity-dwelling individuals. DEX toencompass lary) were above lary) were Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008

TABLE 1. Participant characteristics: Means, standard deviations, and age correlations for the DEX Questionnaire and individual difference variables, separately for the two samples

Study 1 Study 2

Variable 18–39 40–59 60–97 rAge 18–39 40–59 60–97 rAge

N 125 181 162 – 200 249 220 –

DEX (0–4) 1.2 (0.6) 1.1 (0.7) 0.9 (0.6) – .19* 1.2 (0.6) 0.9 (0.6) 0.8 (0.6) – .22* E Age 28.1 (5.9) 50.3 (5.4) 70.9 (8.2) – 25.0 (5.8) 50.5 (5.5) 71.9 (8.1) – XECUTIVE % Women636757–587662– Education 15.2 (2.1) 15.9 (2.6) 15.8 (3.0) .11 14.8 (2.2) 15.3 (2.7) 16.1 (3.2) .19*

Mini-Mental State (0–30) 29.2 (1.2) 28.8 (1.4) 28.5 (2.1) – .19* 28.9 (1.5) 28.6 (1.8) 28.2 (2.0) – .18* D

Trait anxiety (1–4) 1.9 (0.5) 1.9 (0.5) 1.6 (0.4) – .26* 2.0 (0.5) 1.9 (0.5) 1.7 (0.5) – .24* YSFUNCTIONS Subjective health (1–5) 4.2 (0.8) 4.0 (0.9) 3.7 (0.9) – .23* 4.2 (0.8) 3.9 (0.8) 3.8 (0.8) – .20* Depression (0–60) 11.7 (7.4) 11.9 (8.3) 8.1 (5.6) – .18* 13.8 (8.4) 12.4 (9.1) 9.4 (8.2) – .18* Positive affect (1–5) 2.9 (0.7) 3.1 (0.8) 3.3 (0.7) .21* 2.8 (0.7) 3.0 (0.8) 3.2 (0.7) .21* Negative affect (1–5) 1.3 (0.4) 1.3 (0.5) 1.2 (0.3) – .15* 1.4 (0.5) 1.4 (0.6) 1.2 (0.4) – .15*

Neuroticism (1–5) 2.9 (0.7) 2.9 (0.7) 2.9 (0.9) .01 2.9 (0.5) 2.8 (0.6) 2.6 (0.6) – .17* A Digit Symbol (10–27) 85.6 (14.0) 74.3 (14.6) 60.3 (16.0) – .59* 84.3 (15.9) 72.8 (15.6) 56.9 (16.4) – .60* CROSS Vocabulary (6–66) 50.6 (9.3) 51.8 (9.8) 52.4 (10.5) .03 50.3 (11.2) 50.2 (12.3) 52.4 (9.2) .07 Note. M (SD). Study 1, N=468; Study 2, N=669. *p < .01. A DULTHOOD 5 Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 Correlates alphas werehighinthetwostudies( a 5-point Likertscale ranging from 0(never) to 4(very often). Cronbach’s difficulty thinkingor ahead first thingto mind thatcomes about things emotion emotional and personality changes (e.g., “ areas offunctioning portto assessfour was usedinitsself-reportversion and 1996) al., et Wilson (BADS: Syndrome Dysexecutive the of Assessment Dysexecutive Questionnaire Measures 6 Sociodemographic information Sociodemographic health, personality, aff sociodemogra ence characteristics, (Wechsler, 1997). test Vocabulary te Symbol and the as Digit asthe well 1975) &McHugh, Folstein, Folstein, (MMSE; nation functioning cognitive on a scalefrom 1 (very slightlyornot extent towhichtheycurrentlyfelt wh (Watson, Clark,&Tellegen,1988), of indicator As an general. in certain emotions felt they strong to reporthow pants (Spielberger, Gorsuch,Lushene, Vagg iety as measuredbythe20-item from 1(veryinaccurate)to5accurate).Wealso assessed traitanx- a scale on items rate 10self-description asks participantsto tory, which neuroticismasmeasuredbyGo used of or sadfeelings.Asafacet toms suchasrestlesssleep symp- feltdepressive they have thelastweek ticipants howoften over wasused,whic (CES-D; Radloff,1977) Epidem Center for depression, the so that higher scores indicatebett analyses, scoresfor In our (poor). participants to rate their current heal tive anddepression.Subjectiv health years of education. To examine aspects of D To examineassociationsbetween The DEX is a20-itemquestionnaire ENIS ”), motivational changes(e.g., “ G ERSTORF ”), behavioralchanges (e.g., “ affect

ET , weusedthe Positive andNegativeAffectSchedule

AL wasassessedusingtheMini-Mental StateExami- . ect, and cognition were obtained in both samples. inboth wereobtained ect, andcognition planning forthe future included chronologicalage,gender,and included ”), andcognitivechanges(e.g.,“ 10 positive and 10negative emotions positiveand 10 α Trait Anxiety subscale oftheSTAI subjective health werereversecoded subjective er healthratings.Asameasureof the currentstudies.The20itemspur- phic information andmeasuresof phic

associated with executivedifficulties: th on a scalefrom1(excellent)to5 ≥ iological Studies-Depression iological Studies-Depression scale st, both WAIS III taken from the ldberg’s (1999) Personality Inven- Personality (1999) ldberg’s e healthwasexamined by asking , & Jacobs, 1983) thatasks , &Jacobs,1983) partici- .90). I seem lethargic and unenthusiastic and lethargic I seem at all) to5(extremely).Finally, h involves 20 items that askpar- itemsthat 20 h involves ich asks participants to rate the to ich asksparticipants the DEXandindi that supplements the the Behavioral supplements that I act without thinking,I actwithout doingthe health I havedifficulty showing ”). Each isscoredon item , we considered subjec- , we personality vidual differ- I have , we Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 executive memory,positive affect,and see Mooneyetal., model (inhibition,intention, socialre tively better.Incontrast,losses in rela- 1 inStudy data the described model three-factor the that suggesting fit for the one-factor model (cognition, behavior, and affect; see Wilson etal.,1998), the loss in model fit (i.e., three theone-factormodelin Stu and affect), were not necessarilynested among one another. comparison. All other models were nest most parsimonious modelandthus serv items ofth questionnaire using the20 son, separatelyfor Study 1and Study 2. from a 1998). Table2reportsresults M using by data to our above reviewed studies confirmatory a manner andfitted series Questionnaire oftheDysexecutive Structure Factor tion ofTypeIerror,th health, affect, personality, difference charac related toindividual inthe DEX were differences whether Wealso explore adults. older and middle-aged, ofyoung, groups age various life across ineveryday functions In a second step, we examine the frequency of experiencing executive dys- the factormodel found across severaladult age groupstwostudies.and the the measurement properties ofthe DEX Inafirststep,we report analyses of Results arepresentedintwosections. RESULTS samples. participant characteristicsand age corre and negativeaffect,alsowithhigh trait an Digit Symbol), tioning (MMSE, literature, increasedagewasassociated Data Preparation for thesamples from thetwostudies. variables difference individual about Relative to alessparsimonioustw Relative ina ofthe DEX, weproceeded thefactor To determine structure Tabledescriptivestatistics 1shows χ 2 units per one df). As compared onedf).As unitsper 2006) andthefive-factormode e alphalevelwasset to and cognitivefunctioning.To guardagainst infla- was substantial (i.e., 59 was substantial (i.e., E XECUTIVE model fit whencomparing thefour-factor gulation, andabstractproblem solving; e DEX asseparateindicatorswasthe and their age correlations,separately hierarchically nestedmodelcompari- teristics including gender, subjective teristics includinggender, dy 1resultedonlyin marginalloss of Generally consistent erlevels ofpositiveaffect.Overall, and also determine the invarianceof the and alsodetermine with lower levels of cognitivefunc- with lowerlevels As can be seen, a one-factor model As beseen, a one-factor can xiety, subjective health,depression, xiety, subjective ed within theone-factormodel,but of factor models derived from the lations weresimilaracrossthetwo o-factor(cognition-behavior model negative affect; se negative affect; D for the DEX aswellinformation for the ed asthereference in this model YSFUNCTIONS p <.01. withthethree-factormodel l (inhibition, intentionality,l (inhibition, plus A (Muthén & Muthén, χ 2 CROSS units per three df) unitsperthree e Burgess et al., withtheextant A DULTHOOD 7 Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 8 similar results in that the largest loss largest that the in results similar in the data(highest CFI, lowest RMSEA). Analyses of Study 2 data revealed as well AIC andBIC)as (lowest account the DEX,relativeto theother mode model fitindices shown in Table2also Other pronounced. less were respectively, model, one-factor the with 1998) orthogonal oroblique solution, wefoundthat the eigenvaluefactor onefor we carriedoutseparatelyfor thetwo tation is alsoinlinewith resultsfrom DEX.Thisinterpre- the underlying structure one-factor aparsimonious gests results questionsthedistinctiveness of aspectsofthe DEX showed aperfect of 40 factor intercorrelations wereabove be very high in all models, as indicated considered poor statistical fit. Second ically, a Comparative Fit Index (CFI)cl five models considered provide poor fitto modelandthe the one-factor Study 2 model,not butnested necessarily among oneanother. Note Root Mean Square Error of Approximation. Information Bayesian BIC, Information Criterion; 2 1 T Study 1 Model factor models,separately for Study 1and2 Study For model identification, thetwoin identification, model For model. withtheone-factor As compared ABLE r n atr8410–3,7 641.2 .079 .826 36,441 36,171 26/1 – 169 170 848 874 148/3 167 726 modelWilson (three factors) 35/6 Two factors 59/3 factor One 164 167 494 factors) Burgess model(five 470 Mooney model (four factors) modelWilson (three factors) onymdl(orfcos 5 6 122/6 164 752 factors) Burgess model(five Mooney model (four factors) n atr5910–2,9 556.8 .067 .882 25,546 25,298 3/1 – 169 170 526 529 Two factors factor One =.89.Inthethree-factor model, D . Study 1, However,would likewe tohighlight two points ofcaution.all First, ENIS 2. Comparison of the one-factor one-factor Comparison ofthe G ERSTORF N =468; Study 2, Study =468;

ET

AL . 2 2 N =669. Notethatallothermodels =669. 6 6 113/9 161 761 20/9 161 509 dicators fixed ofwere equal. tobe negativeaffect AIC, Akaike’s χ 2 three-factor Wilsonmodel. model of the Dysexecutive Ques Dysexecutive the model of df in model fit was observed for comparing observed for was in modelfit , factor intercorrela , factor for example, behavioral andaffective for example,behavioral a series analyses a series of exploratory factor studies. Independent of specifying an r ᭝ Criterion; CFI, Comparative Fit Index; RMSEA, FitIndex; Comparative CFI, Criterion; thesefactors,anditessentiallysug- ls, providesthemostparsimonious in Table 3.That is, 30out of possible indicate that a three-factor modelof indicatethatathree-factor =.85 with amedianintercorrelation ose toorlower than .90 is generally χ intercorrelation. Such a pattern of intercorrelation. Sucha 2 the best descriptionthe ofthe structure d I I F RMSEA CFI BIC AIC /df the data in absolute terms.Specif- thedata in Goodness of of fit indices Goodness 1 1 1 1 1 1 1 1 6173,2 82.077 .832 .068 36,422 .066 36,147 .886 .062 .892 .067 25,582 .901 25,549 25,296 .883 25,506 25,275 25,550 25,245 25,297 6073,8 81.075 .073 .851 .071 .854 36,388 .862 36,358 36,077 36,313 36,061 36,029 are are nested withintheone-factor tionnaire to several multiple tions werefound to Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 and distractability; and P3 = temporalse = and P3 and distractability; problems, response-suppression restlessness, apathy, problems, planning decision-making,tion, poor noconcern and dissocia- knowing-doing euphoria, impulsivity, reasoning, abstract impaired = P1 were: The threeparcels model). in thethree-factor (asindicated tive difficulties equally representative ofthecognitive,be data by combiningthe20 DEX items to cons celing (e.g.,Kishton&Widaman,1994)a not distinctfrom one another). Todoso the three-factormodelprovidi torial representationoftheDEXbycombin 1 extracted, were but theireigenvalues was consistently above 7, whereas four or five other factorscould have been We also explored whether second-order factor mode was not the case (e.g., three- case (e.g., the not was T fet– 1.00 (1.00) – – 0.89 (0.85) 0.88 (0.79) Model (0.93) 0.98 – Affect Behavior Cognition – Affect Cognition-behavior Factors separately for Study 1andStudy 2 eaieafc – (0.81) 0.81 – 0.81 (0.81) 0.98 (0.98) 0.85(0.85) 0.89(0.89) – – 0.93 (0.93) 0.89 (0.92) (0.82) 0.91 – – (0.86) 0.93 (0.9 0.95 0.88(0.93) Note – Negative affect – Positive affect (0.81) 0.88 Executive memory Intentionality (0.82) 0.91 Inhibition – solving Problem Social regulation Intention Inhibition ABLE . Intercorrelation in Stud in . Intercorrelation In thenextstep,weattemptedtofi 3. Intercorrelations thefactorsid among Intercorrelations onto eairAffect Behavior Cognition Inhibition Intention Social re Social Intention Inhibition niiinItninlt xctv eoyPstv fetNegative affect affect Positive Executive memory Intentionality Inhibition onto-eairAffect Cognition-behavior factormodel1: inStudy y 1 (Study 2). Study 1, 1, 2).Study y 1(Study Two factors ng thebestrelative model fit,but thesefactors are Three factors E )09 09)09 09)0.83(0.83) 0.99(0.99) (0.99) 0.99 5) XECUTIVE entified in various invarious factor models, entified Four factors Four onlymarginallylargerthan1. , we followed classical work on item par- item on , wefollowedclassicalwork nd anappropriateandparsimoniousfac- N havioral, and affectiv ls would provide better model fit to our data. This toourdata. modelfit better provide ls would χ =468; Study 2, 2, Study =468; ing theabovetwoline 2 nd reduced the dimensionality of the nd reducedthedimensionality quencing problems, D =613, df=186, CFI=.860, RMSEA=.070). CFI=.860, df=186, =613, titute threeseparatewere parcels that for social rules; P2 = , = rules; P2 for social Five factors uainProblem solving gulation YSFUNCTIONS N =669. All correlations, Allcorrelations, =669. A CROSS e aspectsof execu- lack of insight, lack of A s ofresults(i.e., DULTHOOD 1 p <.01. 9 Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 measurement modeloftheDEX(and measurement to those above70 age years[ sizes werefound in follow-up analyses th 60s but generalize to particip findings suggesting thatthese respectively, and above age 80years[ differences amountto 0.50 based on the between-person and 7.6 in Study 2, in the number of problems reported was 5.8 in Study 1, in 5.8 was in thenumberofproblemsreported elderly participants. Theaverage difference between theyoungold andthe ingly, youngerparticipants reporteddidthan more problems dysexecutive daily life(e.g their culties in age groupsreported, all three 80, items varyingbetween0and 4 withthesumacrossall from 0to items ranged adults separatelyforthe DEX items) reported by the three age shows the number of dysexecutive probl across functioning ineveryday life tive intheDEX Differences Age Functioning Problems Frequency andIndividual Differen factor load fit whenconstraining in model andth thethreeagegroups was foundacross (i.e., all factor factor load in CFIcloseto1.00),results 1 (e.g., Study one-factormeasurement ous model of the DE details of the models, see f Table 4 resultsofinvariance provides characteristics tobereportedinasubse veration, andno concern for socialrule shallow affect, aggression, disinhibition, 10 2 Follow-up analyses indicated that analyses indicated Follow-up of dysexecutive behaviors in the Wilson Model (1998): toolderadults compared scores as single findingof a underlying factor. For exampl the for the total score (youngadults: the totalscore for (i.e.,endorsed; counting allitems f 0–20), rangewe F adults: (1, 705)=45.80, 705)=45.80, (1, D To examine the frequency of behavioral frequency of To examinethe M ENIS =9.86, G ERSTORF SE p < .01. In addition, when we used a po used a we when addition, .01.In < =0.28; =0.28; F

ET F (1, 418) = 44.0, = (1, 418) (2, 1870)=33.15, (2, 1870)=33.15,

AL ings were above .80), and evidence for metricinvariance evidence ings wereabove.80),and n ootnote of Table 4). As can be obtained, the parsimoni- ootnote ofTable4).Ascan obtained,the be . two studies. Given that th that Given studies. two = 69,intotal: 0.43 = SD M on the sum ofon thesum six itemspurported to this pattern was not restricted to wasnotrestricted this pattern n ., 18–39 year olds in Study 1: =13.10, =13.10, standard deviation oftheyoung participants, these on average, that theyind = 213, in total: 0.60 = 213,in ants intheir70sand80s. in Study 1 and 0.68 SE p < .01). =0.27; middle-aged adults: =0.27; groups ofyoung, middle-aged, andolder analyses across age group and study(for ce Correlates of Everyday Executive ofEverydayExecutive ce Correlates p quent step)ispresentedinFigure1,and variousphasesofadulthood, Figure2 < .01. When expressed as effect sizes aseffect <.01.Whenexpressed ound asubstantively similar ings to be equalacrossageandstudy). ings to noconcernforothe ems (asindexed by the sum across all s. Agraphicalrepresentation of this at restricted the groupoftheelderly at restricted highly reliable indicators of the latent highly reliableindicatorsofthe e, younger adultswerefoundreport to higher examination ofindividualdifference examination were not due to participants in their e two studies (i.e.,nosignificantloss e twostudies X providesX excellent fit tothedataof sitive symptom count across the 20 items DEX difficulties associated with execu- difficulties M SD =7.70, SD , SD F e response format for the for e responseformat , (1, 392) = 10.1, = (1, 392) particular types of items despite ofitems types particular eed experience suchdiffi- eed in Study 2. Similareffect F F SE reflect rather cognitive aspects cognitive rather reflect (1, 536) = 44.2, = (1, 536) (1, 285) = 15.6, = (1, 285) 2 =0.24 vs. M M =11.02, =11.02, rs’ feelings,perse- = 23.2). Interest- 23.2). = pattern tothatreported M =5.41, SE =0.26; older =0.26; p p <.01], p SE < .01] <.01, =0.23, Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008

FIGURE 1. Measurement model for the Dysexecutive Functioning Questionnaire (DEX) and the examination of individual difference characteristics (Z1, Z2, …). In the separate prediction analyses, the DEX was regressed on each individual difference characteristic (Z1) separately. In all other prediction analyses, the DEX was regressed on one or more individual difference characteristic (Z1, Z2, …) simultaneously allowing for intercorrelations among these characteristics. E XECUTIVE D YSFUNCTIONS A CROSS A DULTHOOD 11 Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 test as well as subjective healthand a woman,yearsofeducation, perfo problemsdysexecutive reported werenega considered tion analyses th were relatedtoalmost allof the vari 12 Individual Difference Correlatesof theDEX Z all predictorsthatallowe 5showsresults Table from separatean unique associations ofthese predictors correcting formeasuremen lyses using asimple aggregate score fo Figure 1).Althoughprocedure is such a similartoaseries ofregression ana- and regress thelatentconstructofth well fittingstructuralmodelofth the the one-factormodeltopooldata theabov we used difference variables, 1 ings fixed to 1 for model identification to1formodelidentification fixed Fit Index; RMSEA, Root Mean Square Error of Approximation. * parameters to be estimated (2 factor loading, 1 variance variance 1 loading, factor estimated (2 tobe parameters invariance T unique variance σ groups, leaving sixparameters to bees the Note Study invariance Age groupinvariance Model items acrossthree adultagegroups in Studyacrossand1 Study 1andStudy 2 N estimated (2 fa estimated (2 factor loading for parcel1wasfixed to1 for model , 2 ABLE =200; 40–59years, =200; Z u erc1 / ,0 ,3 97.038 .053 .997 .039 .996 .064 5,131 .997 5,145 5,106 .994 2,131 5,110 2,154 0/2 2,106 2,113 – 7 2/4 – 5 13 12 13 8 15 Metric Configural 13 Metric Configural ). AIC, Akaike’s Information Criterion; BIC, Bayesian Information Criterion; CFI, Comparative age group metric invariance metric group age 2 D . Study 1:18–39 years, × As indicated in column 2 of Table 5, individual differences in the DEX inthe differences individual 5, Table 2of incolumn indicated As To explore associations between th between To exploreassociations , etc.). 4. ENIS 2 study groups, 1variance Examination of factorial inva factorial of Examination model, all factor loadings were estimated loadings were allfactor model, G ctor loadings ctor ERSTORF σ 2 u ). In the the In ). χ N 2 =249; 60+years, =249;

ET ×

N AL study configural invariance 3 age groups, 1 variance =125; 40–59 years, =125; df d forintercorrelationsamon . model, all factor loadings were were loadings model,allfactor σ purposes, leaving sevenparameters ese variables on their own. Specifically,ese variables ontheirown. levels of 2 t error inthe DEX. To DEX timated (2 factor loading, 1 variance 1variance loading, timated (2factor riance of a one-factor model using three parcels of DEX ofDEX parcels three using model a one-factor of riance ᭝ × N

2 study groups, 1unique variance χ =220. In the =220. 2 d I I F RMSEA CFI BIC AIC /df rmance on the MMSE and a vocabulary MMSE and rmance onthe e DEX onto each predictor (labeled ontoeach DEX e positive affect.Positive associations of Goodnessfit of indices ables examinedwhen e DEX (as indicated bythreeparcels), e DEX (as identification purposes, leav purposes, identification N d simultaneous predictionanalyses of d across age groups and studies, apply andstudies, agegroups across r the DEX, it offers the advantage of itofferstheadvantage r theDEX, =181; 60+ years, =181; e findings of factorial invarianceof e findingsof as well as potential agedifferences, as well σ e DEX and a numbere DEXand ofindividual a to be equalacross study groups, leaving five 2 DEX age group configural invariance model, loading thefactor for parcel 1 was tively associated withage,being associated tively σ 2

× DEX 3 age groups, 1 unique variance × 2 study groups, 1 unique variance 1unique groups, 2 study p estimated to be equal estimated tobeequal across age < .01. < N g them (seeFigure 1for to be estimated (2 factor load- (2 factor estimated be to determineshared and =162. Study 2:18–39 years, =162. σ σ ing 12 parameters to be 2 2 u DEX ). In the ). In separate predic- separate × 3 age groups, 1 study metric model,the σ 2 u ). In Z in Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008

FIGURE 2. Age group differences in the number of dysexecutive problems, separately for Study 1 and Study 2. In both studies, younger participants were found to report more problems as compared with elderly participants. E XECUTIVE D YSFUNCTIONS A CROSS A DULTHOOD 13 Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 14 these age-partialed analysessugg as an age wasused significant when of Table5 denotes thatall of thes MMSE. Column3 the for and1% for traitanxiety 30% between ranged and neuroticism. Theamount of with le the DEXwerefound younger participants. younger compared with as elderly the among with thesevariables associations analyses sugges affect. Follow-up a givenvariable andage,effects of in column 4ofTable5reports analyses, problems onceagewastaken into account dysexecutive of thenumber to related negatively test wasalso Symbol years of education,th years can beseen,statisticallysignificant taneous analysis,wethusutilized all of the uniqueassociations interested in negative affect: anxiety andlap (e.g., T ertcs 2*.0 0 0 – – – .03 .05 – .02 .02 – – .01 – .09 – .10* – .17* –.05 –.12* .00 .07 – – .03 .03 – .30* .08* .11* – .08* –.13* –.08 .06 .18* – .20* .15* – * –.07 .03 – .09* indicate givenvariable and a between age – .36* –.11* of term interaction and onan onage, separately, .14* – .49* andonage.Step variableseparately on each –.05 .50* .01 .02 –.20* .22* se measureoneachvariable Regression oftheDEX Note .52* –.17* .38* Vocabulary .52* –.24* – –.24* .16* – Symbol Digit –.12* Neuroticism –.12* .55* Negative affect –.19* affect Positive .16* – .22* – .12* – Depression Subjective health Trait anxiety MMSE Education Gender Age Variable construct analysesof individual difference variablesDEXtheand Questionnaire p ABLE < .01. . D Given that some of the individualdi of the Given thatsome N 5. ENIS =1,137. MMSE, Mini-Mental StateExaminatio Mini-Mental MMSE, =1,137. Standardized regression co regression Standardized G ERSTORF zero-order Step 1:

ET ββββ ββ

AL e MMSE,traitanxiety, . Separate analyses Simultaneous Simultaneous analyses analyses Separate velstrait anxiety, of depression, negative affect, efficients from separate and simultaneous latent andsimultaneous separate from efficients age-partialed Step 2: Step stronger associations intheelderly. 3=Regression of the DEX measure on measure each variable theDEX of 3=Regression ested that performance on the Digit that performanceon ested teraction termswith variance accounted for intheDEX variance accounted ted that the DEXshowedstronger that ted 12 individual difference characteristics 12 individualdifference e associations remained statistically interactions withagewerefoundfor Watson & Clark, 1992), we werealso Watson &Clark,1992), the variables the with the variables DEX. In asimul- analyses when in addition to the main to analyses wheninaddition parately. Step 2=Regression of the DEX measure DEX the of Step2=Regression parately. the variable with age. Significant interactions Significant age. thevariablewith fference variables additional predictor. In addition, additional age n. For gender, men=0, women =1. Step1= n. For gender, men=0, Step 3: Step 3: . Inafinalstepoftheseparate × aibeVral Age Variable variable depression, andnegative depression, age were added.As age were conceptually over- × variable Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 ciation oftheDEX waslesspronounced( found toremainstatistica as aswell affect negative and sion, Columns 5 and 6 ofTable 5indicate that the zero-ordermodel( tively to unpleasant affect ( affect tively tounpleasant andtraitanxiety.It PANAS, depression, unpleasantand affect,asindexed by parameter estimates), whichincludedag provides a graphical representationof Data from bothstudieswere medi partially factor affect unpleasant an whether exploring model amediation employed we finally variables, si the reporting executiveproblemsin plus thefivestatisticallysignificant 3 n items: cantly more dysexecutive problems(i that thecognitively less fit elderly (MMSE Following-up onthe interaction betw reporttoalso tended more dysexecuti b found to show the strongest unique re thatthe underlying factorstruct from twomoderatelylarg life across adulthood and old age.Ou of The majorobjectives DISCUSSION executiv of inreports seen ences functional implications ofself-report suggesting thatunpleasant affectvari tive prediction effectfordifferencesintheDEX( tive same time,directthe effect of Note that information for the MMSE was missing for was theMMSE for information Note that interaction terms in the prediction terms intheprediction interaction con a as usingtheMMSE resultswhen of pattern statisticalpower (assu inreasonable results cut-off assumesimplicitly discontinuity of individualdiff thanthoseusedinclinicalres ishigher MMSE =243; =.30, Informedthe by above findingspronounced ofless ageassociations of M p M <.01). Thatis, individuals who reportedmore unpleasant affect =20.48, =20.48, =15.20, =15.20, SE SE =1.71) than the cognitivelyfitelderly(MMSE>27; =1.71) =0.68), b =– .22, =– e samples of community-dwelling adults, indicated the currentstudywereto lly significant. Specifically of the DEX among 60+ year olds. year 60+ DEXamong of the b pooled together for this of pooled forthis set analyses. Figure together 3 = age on the DEX is reduced to ageontheDEXisreduced F E − (1, 324)=11.84, (1, 324)=11.84, e dysfunctions (m dysfunctions e XECUTIVE .24, p < .01), and negative affect variables were variables affect negative and <.01), ure oftheDysexecutiveQuestionnaire the ageinteractionwiththe MMSE were p ed executivedysfunctionsineveryday interactions aspred tinuous variable and included the MMSE byvariable theMMSE tinuous andincluded variable erences in cognitive functio earch and practice, and alsothatsuchaprocedure and practice, earch ables largely mediated the age differ- red bygroupcorroborated sizes), andwe the general lations to the DEX (e.g., traitanxiety: lationsDEX tothe themodel applied < .01),strongposi- which a itselfhad een MMSE and age, resultsrevealed MMSEandage, een ated the age associations oftheDEX. associations theage ated multaneous analyses of all predictor multaneous analysesof ndexed by allDEX the sumacross r results,on based analyses of data D ve problems in their everyday intheireveryday life. ve problems the negative affect subscale ofthe subscale affect negative the n e and latent constructs oftheDEX latent e and can be seen that age related nega- thatagerelated can be seen =54. We acknowledge that a cut-off of 27 on the =54. b age, gender, trait depres- trait anxiety, age,gender, YSFUNCTIONS =– .11, ≤ 27; p ediated effect: ediated <.01. p examine thenatureand < .01) as compared with compared <.01)as b n , the negative ageasso- , the negative A =.58, =85) reportedsignifi- =85) CROSS 3 ictors oftheDEX. ning. However, using this However, ning. (with standardized b p A = <.01).Atthe − DULTHOOD .08( b = − .14). p < .01) 15 Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 16

FIGURE 3. Standardized parameter estimates from a mediation model of age, an unpleasant affect measure, and the Dysexecutive Functioning Questionnaire (DEX). The latent construct of unpleasant affect was indexed by the negative affect subscale of the PANAS, depression, and trait anxiety. *p < .01 . R2=.36. χ2=52.2, df=14, D CFI=.989, RMSEA=.050. ENIS G ERSTORF

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AL . Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 discussion attemptstoin variables partiallymediatedthenegativ functioning.tive found Wealso eviden teristics includinggender, education, dysexecutivewere relatedto behaviors culties thanolderagegroups.Inadditio declineadvancing with adult age,younger agegroups reported more diffi- problems in their everyday lives. Although executive functions areknown to also indicatedthatcommunity-dwelling found invariant across the adult age range aswell asacrossstudies. Findings coulddescri parsimoniously(DEX) be lems, this findingallowedlems, for adirect the natureandfunctionalexamine imp further To model. structural same the with bedescribed could adults older ofreports executive functioning defi DEX caneffectivelybe summarized us ous aspectsof self-reported everyday gests that wehave found convergent evidence acrosstwo samples that vari- sug- This groups. age various and studies independent across set invariant terms. future researchon self-repo considers implicationsforthe validity parsimonious factorsoluti factors wa three these reflected equally that parcels from constructed model one-factor a Instead, factors. these factor intercorrelations lead us to (1998) providedthe relativelybestmo as components andaffective behavioral, ies, ourresultsindicatethatindeed stud- previous from derived models factor of several comparison empirical range. Proceeding in aconfirmatory manner and using a thorough direct pendent samplesofcommunity-dwelling present study, wehaveused self-report or theagera self- orinformant-reports, in sa differences to due maybe cies a four-orfive-factorstructureto be al., 1998). However, thesereportsdi et (Amevia et al., 2003; Burgess etal., 1998; Mooney etal., 2006; Wilson and non-clinical sampleshasrevealedev Questionnaire oftheDysexecutive Structure Factor A majornewfindingofourthat study the is one-factor model could be Previous research on the factorst onthe research Previous tegrate our findingsinto tegrate on, but also resultedin g rted executivedysfunctioning. E XECUTIVE question the validity and uniqueness of mpling characteristics aswell using athree-factorsolutionofcognitive, st describe thedata.Suchinconsisten- executive problems asassessedby the cits among young,cits middle-aged,and health, affect, personality, and cogni- health, affect,personality, empirical examinationofage-related empirical del fit. However,extraordinarily high lications of reporting executiveprob- of the DEX instrument as well as for wellas as instrument the DEX of ffer inwhethertheysuggest a three-, data from two moderatelylargeinde- n, individual differencesinreportsof s found to provide not only the most the only not provide to s found various individual difference charac- difference individual various idence for multiple idence for bed by a one-factorbed bythat model was nge ofthesampleconsidered.In D ructure oftheDEXbothinclinical e age associations of theDEX.Our e ageassociations reported by Wilson and colleagues by Wilsonand reported ing oneoverallscore.Inaddition, adults indeed experience executive ce thatnegative ce suggesting affect YSFUNCTIONS adults across the entire adult age entire the across adults ood modelfit inabsolute the extantliteratureand A CROSS underlying factors A DULTHOOD 17 Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 Following Chan (2001), such difficulties Following Chan(2001), lems appear tobeof si jective impressions of poor decision-makin this studyprovide evidence that execu large cross-sectional samples thatspan the entire adult age range. Findings from functioning executive difficulties reported To thebest of our knowledge, thisproj often peopleexperience instances ofex (Burgess etal.,1998; Wilsonetal.,19 Functioning Problems Frequency andIndividual Differen relation withindividual differences in the frequen 18 populations to directly capture executive dysfunctions. questionsleave unansweredregarding (Chan, 2001; Shallice &Burgess,1991; and psychometrictests of betw associations MMSE). Suchweak (i.e., compromised cognitiv w few uniqueassociations tive dysfunctionsappeartobewellcap This suggeststhataffec ative affect. towards geared assessing measures with associated primarily were behaviors of dysexecutive reports analyses, neous adulthood.during later Whenconsider whichoverlapspeakunderlyingofmay toalarger sources offunctioning of the DEX-correlate associationswe addition, menwerefound subjective health,fewerpositive affe such as characteristics to desirable less these correlatesseparately with anumber of the individual diffe ing absentmindednessorsomepersona ties maynothavethepotentialto ties Weacknowledgeth scores=.66). period that was available for a subset of participants( a subset period thatwasavailablefor underscored bythemoderately daily lifer be observedin aged Chinesesample(Chan, 2001)andhi in linewith results are range. Our age D Given theprimaryfocus on clinical Reports ofexecutive dysfunctionseverydayin werelife also associated ENIS G ERSTORF

ET

AL zeable frequencyineveryday difference characteristicsinsubsequent steps. outine and tasks. over-learnt isalso This interpretation . cognitive abilities are in lin in cognitiveabilitiesare , more executive difficultie cies of reported dysexecutive behaviors and their ith measuresofcognitiv to report moredifficultiesthan women, and some e fitness among the elderl e fitnessamong high stabilityofsu at, incontrasttoclinicalgroups, thesedifficul- disrupt one’s everydaylifecompletely. tive experiences associated withexecu- associated tive experiences evidence from a relatively small middle- arelatively evidence from 98), itwaslargelyanopenquestionhow re more pronounced among theelderly, ce Correlates of Everyday Executive ofEverydayExecutive ce Correlates tive functioning difficultiessuchassub- tive rence variables examined. Considering examined. variables rence lity facet(seeal ct or lowercognitiveperformance.In depression, anxiety, neuroticism, less depression, anxiety,neuroticism, een reports of executive dysfunctions of executive reports een ecutive dysfunctions ineveryday life. see alsoRabbitt,1997),but ofcourse tured bytheDEX.However, only a ghlight thatexecutive dysfunction can ect thefirst represents study of self- various aspects of unpleasantofvarious orneg- aspects ing unique associations in simulta- in ing uniqueassociations the validityofDEXin normal may thusbereferre in everyday life based onmoderately life in everyday g, distractability, or planningg, distractability, or prob- samples samples in theextant literature e functioningwerefound ch reports over a 1-year ch reportsover life throughout theadult s wereprimarilyrelated so Reason,1984). e with previous reports previous e with y, asindexedbythe n =89, d to as represent- d toas r T1,T2 of sum of Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 troubles experienced by older adults. older by experienced troubles result norms) may have age-adjusted our sample(e.g.,average scoreson Hultsch, 2000). Alternatively, it mayal curacy (orunder-reports)maybemore of howwelltheyperformincognitively not acknowledge thatparticipantsmay did notcorrelate withself-reports (2005) reportedmeasuresthat on divi subpopulations (Burgess etal.,1998). ties amongcommunity-dwellingadults,as day life, we cannot rule ofen frequencies found sizeable have ence ofeverydayexecutive functioning problems. Inaddition, althoughwe unpleasant of aspects rather indexes if theinstrumentdoesnottapdirec DEX questionnaire in thecontextof tioning problems. negative age correlations) so doesth negative agecorrelations) affectdecreases affect, andasnegative expe they part, because problems, in executive more reported adults young other words, In utive problems. unpleas that finding our with in line avoid such to or becausetheymanage emot because theyhandle parts either experience negative emotions less fre adults Thatis,older Roecke, 2006). 1998; &Kolarz, et al., Mroczek 1993; ings of better emotion regulation with age (Carstensen et al., 2000; Lawton fewer reported executive however, At time, the same 2003). &Berish, Atkinson, (Salthouse, tioning typically showlower performanceon m Wilson etal., 1998).This finding wassurprising giventhat older adults tive, behavioral, or affective-motivational aspects only (as suggested by cogni- reflecting of items subsets we considered when unchanged virtually remained differences group age these that note also We participants. young of differences between-person on as effectsizesbased expressed when in theyamounted that 1988) (Cohen, co participants, andthesedifferences elderly did than average on problems dysexecutive more reported pants experiencing everyday executive functioning problems. Youngerpartici- factor involved in there involved factor Taken together, thesefindingsraise Taken Of particular interest were age-related differences in thefrequency of duction with age in thefrequencyofreportedexec- with age duction out the possibility ofunder-reportingsuchdifficul- functioning problems in the elderly parallel find- E XECUTIVE community-dwelling ad tly tapintoexecutiv of dividedattentionability.Wethus ded attention tasks performedin thelab ded attentiontasks affect affect that mayaccompany the experi- e number of reported executive func- executive of reported e number For example, Salthouse andSiedlecki Salthouse example, For cognitive measures were above were the above cognitivemeasures ed inunderestimating theamountof dorsing executive problems in in every- problems executive dorsing always be accurateintheirjudgments always ant affect variables were the prime the were ant affectvariables ionally challenging situations better ionally challenging counter- thantheiryounger quently D situations. Such an interpretation is situations. Suchaninterpretation pronounced in old age (Hertzog & age (Hertzog pronouncedinold rrespond to a mediumeffectsize rrespond to demanding situations andsuchinac- to about half a standard deviation a standard about half to rienced higher levels of negative of higher levels rienced withage(seealso Table 1 forthe so be thatthe po easures relevant toexecutive easures relevant func- YSFUNCTIONS questions aboutthe validityof the has beenreportedinclinical A CROSS e functioning, but sitive selection of A ults. It seems as ults. It DULTHOOD 19 Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 ACKNOWLEDGEMENTS number ofinterestingquestions remain. potentialimplications ofeveryday and study hasofferedinitialinsightsinto of leadingindicator area tive problems experience to people prompts affect tions.For example,such a line ofinqu bring about such difficulties andther instructive tobette may be context.Specificall in aneveryday fromexamin benefit may also research precursors andconsequencesof exec potential well as as changes a direct examination ofage-related allow not tion ratherthanmoreconventiona therebyexaminelargelythe whether reflects DEX aspects ofemotion regula- in re and affectivecomponentsinvolved study. Thiswould also allow for more functionto index executive considered future researchs lenges ofeveryday living.Beforeconclu who areatriskfordeveloping impairment independently, butlivingment toidentifycommunity-dwelling who are elderly thus beusef could well bethattheDEX dysexecutive more stantially problems th DEX-cognition associations wasthat cogn edge severallimitations ofthisstudy. adult age range,th asmeasured by of self-reported executivefunctioning pr Limitations andOutlook 20 Parts of thisarticle were prep and checkingdata, the withspecialthanks to their assi all 2004 and2005for of ing thesummers AG02427042Salthouse. andR01AG19627awarded toTimothyA. the National Institute on Aging(NIA). Data tion (DFG). Elliot M. Tucker-Drob is supp University ofVirginia onaResearch Fellow D One furtherlimitation isthatthecros The presentstudy hasshed light on thenature and functional implications We would like tothankthe members ofth ENIS G ERSTORF hould closely examineassociationshould ofthe DEXwithmeasures

ET

AL ared while Denis Gerstorf was ared whileDenisGerstorf . r understand the characteri l aspects ofexecutivefunctioning. e DEXinstrument.However, weacknowl- y, time-sampling assessment procedures assessment y, time-sampling orted as a trainee by grant T32 AG020500from bygrant as atrainee orted ship awarded by the German ResearchFounda- ship awardedbythe Cris Rabaglia for her help in theprocess. Cris Rabagliaforherhelp collection was supported by NIA GrantsR37 was supportedby collection executive problems or whether execu- thoroughlydecomposingthecognitive eby providepossibilities for interven- ing dysexecutive functioning problems functioning dysexecutive ing utive difficulties in daily life.Future utive indaily difficulties iry may informiry may uswhether unpleasant ul as asupplementary screeningul instru- To beginwith,ouronlyevidence for ing, which were not availableinour sive statementscan bemade,however, unpleasant affect.Insum,thecurrent factorsunderlying,thefrequency, executive functioning deficits,but a e Salthouse Cognitive Aging laboratory dur- s in theircapacitytomanagethechal- s in an thecognitively fit elderly. Itmay oblems in everyday life across the ports of executive difficulties, and of executive ports itively less fit elderly reported sub- reported lessfitelderly itively stance in testingpart stance s-sectional nature of our data did data our of nature s-sectional Original manuscript received March 16, 2007 16, March manuscriptreceived Original Revised manuscript acceptedAugust 7, 2007 First publishedonline month day, year at the Department of Psychology, stics ofsituationsthat icipants andentering Downloaded By: [Pennsylvania State University] At: 03:09 8 April 2008 Goldberg, L. R. (1999). Abroa Gold, D.P.,&Arbuckle,T.Y.(1990).Intera Lawton, M.P.(1983). Environment and other Hertzog, C. & Hultsch, D.F.(2000). Metacogni Burgess, P.W.,Alderm Folstein, M.F.,S. Cohen, J. (1988). Carstensen, L. L.,Pasupathi, Chan, R.C. K. (2001). Dysexecutive symptoms Lawton,P., M. Kleban,(1993).Dean,J.H.,M. & Affect andage: Cross-sectional compari- K. Kishton, J.M.,&Widaman, Baddeley, A. D.(1990). 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