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LOflGI T UDIIl AL CAUS.'\LANALYSISOFSUBJ ECTIVE WELL-BE INGAND ITS MAJ OR CORRELATES:AMODIF I ED TOP-DOWNFORMULAT I ON

by

Susan C. Stone

De pa r tm e nt of Psychology

Submi tted in partia l fulfi ll me nt of the re q u i r e ment s forthe degr eeof

Ma s t er of Science

Facul tyof Gra d ua t e Studies Hemor-talUnive r si tyofNeW'! ou nd land

St.John ' s, Ne wf o un d l an d sep t e mbe r , 199 5

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L'AUTEURCONSERVELAPROI)RIETE DUDROIT o'AUTEURQUIPROTEGE SA THESE.NI LATHESE NI DES EXTRAITS SUDSTANTIELSDE.CI:.I.I.I::·

CINEDOIVENT ETREIMPRIMESOU AUTREMENTREPRODUITSSANSSON AUTORISATION.

i i Abstract

Data from afo u r- yea r longitudina l study of 407 adults across theli f e s p a n were used to examine theca u a a I p<lthways between the higher -orderaub'j ect Lv ewell-beingconstructand its. primary lower-orde r correlates, Correlates included six life dome Ln satrsrecctcns , thr ee pers ona l disposit ions, and two me a su r e s of genera l stress.

A sez-Lee of pa r-t.LaI and multiple regressionanalyses wereuse d to assess the pr'e aence and direct ionof ca usal linkages between variables in a"t o p -down " pr opensitymodel of sUbjectivewell-being. Results di d not cons i s t e n tly support"bot t om-u p" or "t o p-d o wn " effects . They did ind i c ate modit Io etIcn of theproposed"t op - d own" formula tionto include d.irectlinks from per-e one L dispo sit ions to lire domainsa t i s f a c t i o n s .

Giventihelack of cons istent findings in the literature and in the present data set, thepos sibleexi s tenceof bi- direct ional links between sub j ec tive wel l-beinganddo ma i n satisfactionswasdiscussed.

iii

Ack.nowledg e ments

I am"happ y" to havethisopportun Itytothank scee very importantpGople.Tomy graduatesupervisor, Dr . Albert Kozma: Thank you foryour advice,expez-k Lse,and und erstand i ng .

To my thesis comm i t t e e, Or.Chri stineAr let t andMr.

M<llcolm Grant: Thankyoufor your con struct iv... fe edback alongthewa y.

Mygratitud ealso exte nds to severalpeoplewho generous lygaveot theirtime inhelpingme be tt e r unde rstandLISREL:Terry Qu i n lan, TonyGoudie , andCharles Lance.

Last ly, I thanKmy parentsfortheir on-goi nglove and supportof this int e r min ab le studentI

Table of Contents

Abstract .... .•• . • . .•... .. . .. . ...•.. . ii Acknowledgeme nts...•... iii Table of Contents.... ... . . . ...• .. iv

List of Tables vi

List of Figures... .. ... .... ... ... ... . viii

List of Appendf ces Ix

Int rod ucti on overview

Stabilityof Subjectivewell-Being 6 Correlates of SUb jectiveWell-Being... . 8

Life Domai nIndicators 9

Demographic Variables 23

Environmental Influences ~8

Individual Dispositions 32

Models... ... ... ... . . . 40 Bottom-Up ...•... ... . . 40

Top-Oown 45

Bi-Oirect ional •.•... ... .. 55 Hypotheses ...•. ... ... ... ... ... 62 Meth od

suefeccs .... ....•...•.. .. ... ... .. . .... 69 xse svc-es ••• • •••••.• •••• •••••••.•••• •••• •• ••70 srccecure •... ... ..•... .... ... . ..74

iv

Ta b l e of Contents

Result s

Des criptive St a tis t i c s ...•... •....•.. 76 Hypothesi s 1 •• ••••• ••• .. ••••••• •••••• • •.• 81 Hypothesis ae•••••••••• •••••••••••••••••• 91 Hypothesis2b ••••••.•••••• ••• ••• • • ••••••• 93 Hypothe s i saa •••• ••.•••.•.••••.• ••.•.•••• 95 Hypothesi s Jb •.••• •• • ••••.•••••• ••••.• • .• 95 lIyp o t h e si s 4 ••••.•••• •• ••.••.• •.••.•• .•• • 106 Hypo t h e s is 5 •• •..•.•• • •••.• •••. .• •.•.•••• 116 Ex Post Facto Analyses .••••••••.•.•• •.• •• 111 Discussion

Concl u s ion Refere nc es

121 128 130 Ap pe ndices ••••.••••••. ••••••.•••.•• .• ••• •• • ••• 155

List of Tables

1.St1\bil ityCoeff icientsfo r vario us

SWB Measures .

2.DescriptiveStatisticsof

studyVariables 77

3.Time1DomainSatisfaction Intercorrelations and Partial Corr e l a tio ns Wi t h SWB Con trolled

•• ••••• . ••• • •• • •••••..••••...••. •••••• • •.••• 83 4. Time 2 Doma inSat i sfac tionIntercorrel.:ltions

and Partial CorrelationsWithSW9 Controlled ....••. • .••• ••••• • .••. . . ••••••.• •• • •. •.. •••. 84 5.Time 3 Domain Satisfactio nInt ercor relati ons

and Par tia l Corr elationswith SWB Controlled

•••••.••• ••.•• • ••.••••.•••••••••••.••••••• •• 85 6. Time 1 Int ercor re la t ionsBetween Lower-order

Var iab lesand Partial Correl a t i on s with SWB Controlled •.. .... .. . ... ... . .... •.. .. ..

7.Time 2 Intercor relat ions BetweenLo we r-o r de r Variablesan d Partial Corre l at ion s WithSWB

Controlled 89

8.TimeJ Int ercorrela tions Between Lower-order Variabl esand Partial Corre lationswit hSWB

Co nt roll e d 90

9a. Ze r o-o r d e r stabilityCoefficients of MUNSH and Part ialCorrela t ions Wi t h Current and Pr i o r Domain Satis factio ns Removed 92 9b. Zero-order StabilityCoefficientsof SWLS

and Partial CorrelationsWithCurrent and PriorDomai n SatisfactionsRemoved 92 10. stab lli t y Coe ff i c i ent s of six Domain

sat Iu r ectIc ne for Thre eTime Frames 94 vi

List of Tables

lla-l l f . Cross- phasecor-z-eLa t.Lo n e BetweenPrior DomainSatisfactionsandLater SWB, using Two Measuresof SWB for rnr e e Waves of Data. Zero-orderCorre la tionsareThen Compar ed WithPartialCorrelationswhich Control for Pr i or SWB•••• •• •••• •••••. ••.•• 96 12a-12c. Cross-phaseCorrelations BetweenPrior

SliBand Later Domain satisfa ctions , Us ing Two Measures of SWB forThreeWaves of Data. Zero-order Co r r ela t i o n s areThen ComparedWith PartialCorrela tions Which con trol for th e correspondingPrior Domain SatisfactionScores (5) ••• •• •• •• •••.•••.•.• 103 13a-13f.MUltiple Regressionof Pre d i c t ors with

six Domain seetera ctac nefor Relevant study Phases..• .•• ••. . • ... • . . .•. •• ••••••••. •• ••• 109

vii

Listof Figures

1. General Top-downModel Relating SWB to its Maj o r Corr e lates .••••• •.•• .•. ... ... • • • • . • . ••• 13 2. GeneralBottom-upModel RelatingS\~Bto its

Maj or Correlates ••.••••.•••...• •.. ..• •..• . ... 14 3. Prop o sedTop-d own St r uc turalModel •• • •• • • •• •. 66 4. Propo s e d Bott om-upStructural Model ••••• •. • •• 68 5. RoformUlilte d Top - d own structural Model ••••.. 126

viii

List ofAp pen d i c e s

A.SUbjectivewell-Bei n g:Questionnaires 155 B. Domain SatisfactionQuestionnaire 157 C. Personal DispositionQuestion nai res ...• 158 D. Envi ronm enta l Influ e ncesQuestionnaires ..•.• 161 E. Intercorrelationsof study Variables

- Time 1 •• • • • • •.• •• ••••••• ••••••••••.•.••• 164 F. 1ntercorrelationsofstudy Variables

- Time 2 •••••••••••• ••••• •••••••••••.•••• • 167 G. In t e r c o r r e l a t i o n sofstudy Variabl es

- Time 3 •• •• • • •• •• • •• • ••••••• ••••••.•••••• 170 ix

Int roduc tion

sinceOiener's (1 9 8 4 )appealformore "theoret i c al structureto guide empirical wor k."in the area of su bjectLv o well -bei ng (SWB), consi dera b lymoreps y ch o l og i c alre s earch ha s be e nconduc ted inth e direct con t ex t of SWBthe ory . Theor ies of SWBareconcernedwiththe attai nmentof happinessand seek to expla in th e me c han i sms by whichpe op l e cometolabelthems elves asha p py.

The o ri e s of eubject.Lve we ll-being ca n be divided rough ly intoprocess and structure models. Wherea s structure models at t e mpt to delineate the rel at i onsh i p s betwe e n the vari ou s co mp o ne n ts ofSWB, pro c ess models areconce r ne d wi t h relat i o nships betweenSWBand othe r var iabl e s . Both appro achestoexp l a nat i o n have be en influencedto a lar g e degree bythoe social in di ca tors mov e me nt ofthe 1950' s and 19 6 0' s inthe Un i te dStates.Two importa n t sets ofucte resulted from ear ly qualityoflife (QoL) re s e arch, wh ich attemp te dtoas ses s th e psy chos oc i alst a t u s ofthearaor Ican public.

Norman Bradburn'swork. on happ Lneaawas responsi b lefor the enduringfinding thatshort-termha pp i ne s s is composed of pos i t i ve and negativeaffect (Bradburn &Cap lovitz , 1965; Brad bur n, 1965') . Besid es the s e two compone nts of happi ness , heals o provided da t aon the relatio ns hipbe tw e e nhap pLnes s and a numberof itssociodemographic corr e l ates.

Bu ild i ng on hi s findings, the Instit utefo r Socia l Res e arc h (ISR) atthe Unive rs ityOfMi c h i gan completeda compre he nsive nat ional proba bi li t y surveyin1971 which wa s de s ig ne d to assess the qualityof American lif e fro m le s s objective means than had previously characte r iz edsocial ind i c a t o r s research (Andrews&Withey, 1976; campbell , Conve rse, &Rodgers ,1976).

Based on this survey, ISRre sea r che r s found evi denc e for a thi r d, cognit ive componentof SWBandeval uat ed a more exhaust i ve li s t oflife satisfact i ondomainswhichwere hypot hesizedto correlate with SWB (e.g., wo r k , fa milylife , hea lth) . Ca mpbell et al. (197 6 ) also initiated an exp lorat ion int o the intr a-ind iv i d ualfa cto r s whichmigh t rel a t e to sUbjectiveevaluat ionsof well-be i ng.They inv e stig ate d (1 ) cogni t iveprocesses involve d inthe det e r min a t i on of life do ma in satisfactio ns in rel a t i on to the objective circumstances of domainlife and (2) personal

re s ourc e s, suchas intelligenceor physical attractiveness , whi c h were thou gh t to influence SWB jUdgements.

Thismass ivebodyof researc hwas be s t summarizedby one of theaut ho rsas merely"s cra t c h ing thesu r fa c e" of the pro bl e m (Bra d burn , 1969). Although th e efforts of earlyQoL researc h er s undo ubtedlyfu r t he red the und e rs ta ndi ng of the structure andproc e ssof SHB, the i r rea l con t r i b ut ion lay in the mult i tud ino us lines ofinquiry whichwere opene dfor SUbsequent re s earc h e r s.Mostcontiampcrar-y theories of SWB contain el e ments derivedfr o m the findi ngsof ISR researchersor NormanBradburn (e. g.,Kozma, Ston e s ,&

Mc Ne il , 1991; Mi c ha l o s , 19 8 6 ) .

Inadditi o ntothe socia l indic ato rsmovemen t , the fieldof socialgeronto logy has figuredprominent lyinthe de v e l op me nt of SWBtheo ry (Ge o r g e , 1981). In fact, the ir.~tia lco nce p t ualizati on ofli fe satisf actio narose from the wor kofap plie d ge r on t ologi s t s inthe1940'swho studied per s onalandsocia l adj ustmentin oldage (Bort ne r &

Hult s ch, 19 7 0 ; Ryff& Essex, 19 91). Altho ugh this re sea rch wa s in i tiall y ap proach e d from the perspecti v e of coping with the successive lo s s that ac c ompan i e sag i ng (Hoyt&Creech, 198 3 ), theco n c ept of "s u c ce s s f ul aging"gra d u a l l y bec ame accepted as a mo reapp r o priate wa y of approachi n g research

on thepr oc e s s of adaptationto aging (Baltes&Baltes, 1990).

Pal mo r e (19B7) has defined successful aging as comprising three factors : longevity,healthand happiness.

Inventories which were originally designed to assess ad j us t men t inthe aged began to be studiedin their own ri g ht as measures of well-being, life satisfaction, or happiness(Harley, 19B4; Hoyt&Creech, 19 B3 ) . Thus, from the twodivergentre s e a r c h perspectives of social ind icators and applied social gerontologyemergedan empirical endeavour on the nature and attainmentof happiness.

Al thoughan integrative theory of SWB will necessarily specify its components, the relationshipbetweencomponents, and how the various componentsrelate to otherva r i a bl e s , researchers have traditionallynarrowed research questions to eitheranexaminationof the components (structure) or correlates (processes) of SWB.

contemporaryprocessmodels of SWBca nbe separated further into micro- and macro-processtheor i es . Whe reas mi c r o-p r oc e s s theoriesdeal wi thintra-individual cogni tive

processes invol ved inthede t e r mi nat i o n of SWB, mac ro- proc e s s theories address there l a t i on s h ip betweenSWBand its majc.r correl a tes. By far the most fundamental issue re ma in i n g unresolvedwith i nthe macro-processapproac h is th e ques tio nof causalit y . Thepur p os eofthisstudy is to illumi natethe ca usal nat ur eof there l a ti on shipbe t wee n SWB and itsmaj o r corre lates.

First, the stdbili tyof SWB will be evaluated, followed by are v i e w ofthe major correlatesof SWB. Macro-process theo r i e s wil l then be conside redwit h par t i c ul arre f ere nce tocau sa li t y. Finall y, hypo the s e s will be ad van ced tote s t therela t ivemeritsof severalofthe main typ es of ce us ci theories currentlyinthe research literature.

Twonot e s arein orderprior to embar ki ngonthis review. Firs t, inrel at i o nto struc ture , cons e nsus has not be en rea chedwit h re gard toanexha us tive SWBcompo ne n t get. Howe ver, enou g hsuppor t has bee nobtai ned fo r pos it i ve affec t, negat iveaffec t , and the cognitivecompone nt lab elled 'sat i s f a cti o n' asfi r st-o r de r factors and global SWB, "h appf.neas ", or'psy c ho l og i c a l we ll-being ' (PWB) as se c ond-or de r fa cto r s thatloos eac c e pta nc e of thisstructur e wil l be made fo rpurposesofthe prese nt review(see Cha mber l a l n , 1988, fo r a review).

Second, and related to the first no t e, the fOllowing terms will be used interchangeablyto denote the second- order,global SWB construct: S~1B;PWBj life satisfaction ; morale; andhappiness.Agreement also has yet to berea ch ed regardingtermi nologyin this research area.Howe ve r , several researchers have cited evidence for the psychometric comparabilityof these constructs andco nc lude d that each shares a commoncore typically referred to asSWB (Diener, 1984i Kozma et eL,, 1991; Larsen, 1978; Lohmann,1980i stones&.Kozma, 198 0, 198 5, 1989).

stability of SUbjectivewell-Be ing

SUbjective well-being, like other psychological constructs, can be analyzed on two different measureme nt levels. The id i og r a phic approachinvolves the analysis of individualreports of SWB. In contrast, the nomothetic approach involves the analysisof SWB levelsacross individuals.

From a nomotheticperspective,the moderate temporal stabilityof SWB has been clearly established.Ta b l e 1 lists 16 longitudinal studiesand their associatedretest reliabi l i ties (where availab le) for a ra nge of SWB measures.

Overall, retest coefficientsrangefrom .38 to .92.Thus,

Ta b l e 1

Sta b i l i ty Coe ff i ci ents for VariousSWB Meas ur es

Study Re t e s tInterv al Re li a b i li t y

We s sma n & Ricks 2 yean .67

196 6

Campb e11" et at , B months .38 to .76

1916

Oeorge " Ma d doK1917 5 yean

. "

Palmo re & Ki vet t 4 yean .40 to.56

(1911)

Xoz;ma" Stones_1,980 6 manths -_{1 veal'}

.'0

Atkinllon,1982 2 vearll .6S

Hus l'Ili'n ,Non :r;ik,

.

Ei Ch o r n (19821

Baur" Okun (1983 3veal" .61

Ko~ma& sec ne n 1,8 mont h s no significant

198 3 a int erv al chang"

Re k lilr"Wo ner198 4 ) 2 yea n

."

McN eil,se o nen ,

.

xoama 19 86 a inte rva1cha nQe

Stones&-Ko zma 1,8 months .vi

19 8 6 ...

Costaeta1. (19 8 1 ) 9yean no significant

interval chancre Headey" Wear ing 2. 4.&6 y ea r s .5 5 to.6 (1989)

Hea d e y'"Wea t"in g 6 years .92, .64and .65

19 91

Le ....insohn.Redner, B months .63 and

. "

&-Se ele v 1991

Cha mb e t"l a in'-Zik a 6 months .S t o.e

(19 92)

the proportionof variancein SHe attr.ibuted to dispositiona l (a nd/ o r stableenvi ronment )rectc r-s ranges from14 to 85 percent, mostof t e nhov e r i ng about 45 %. With re s p e c t to bivariate'd i ff er e nc e ' comparisons, it appears that mean levels ofswa donot change appreciablYina varietyof sample s over periods as long as nineyears.

However,whenindiv i dua l le ve l s of SWS are analyzed ove r time , some chang e isinv ari8blyevi.dent. For example , neecey and wea ring (19 9 1) reported a change ofmore than ann st andarddevia tionin one qua rter of thei rs ampIe, In addi tion, mos t retest correl a ti on s fall below t.he rclla b il i t. i e s fo r each meaa ur-e, indicat i ng acme truechang e in le velsof SWS.

Corre la t e !=:of SUbject~-being

The aimof researchwhich examinestheco r r ela t e s of SWB is to acc ountfor the var Lance in ratingsof SWB.Whydo senepeoplera t e the ms e lve s as happy whileothersrate themselvesas unhappy?What factors influencethe s e ind i v i dua l differenc es?

One mainimpetus for ear lyQoLresearchwas the growing rea lizationthat typi cal 'ha r d' social indic a t ors of

objective li f e circumstances (e.g., unemployment, crowding, crime) didnot alwayscorrespond to the eubjeot Ive exp e r i e nc e of individuals (Campbell&Converse, 1972).

Today, researchers continue to examine sUbjective satisfactionin variousdomains of life withrespect to its Objective counterpart since thiscan provide valuable information ontheps yc ho l og i c a l processes involvedinth e determination of SWB.

Accordingly,the fOllowing review of correlatesor SWI3 will evaluatethe re l at i ons h i p betweenobjective and SUbjective life domainindicators of SWB. The remaining correlates to be revt cwec are: demographic vartnmes, environmenta l influences, and individual di s posi t i on s . When data areava i l a bl e, commentwill alsobe made onthe temporal stability of these correlatesand their relationship to SWD.This is not meant to be an exhaustive review of all possible correlates of SWB but will cover some of tho maintypes of correlatesthat areused to test currentmacr-o-process models of SWB.

LifeDomai n Indicators

Ear l yresearch on the relations hipbetween SWB and various objective and SUbjective life domain assessments

10 conta i ne d a number of sh o r t co mi n g s. Of t e n studiesdidnot adequately disting uishbetween objectiveand subject.Lve measures in their evaluation of effects. certaindomains, suc h as income or housing, lendthe ms e l ve s to this distinctionmorereadily thanothers (e.g., he a l t h ) because obj e c tive meas u r e s ofthese li f e dtl~:'.lnsare readily available. For ex am ple, peoplecanreadily state their obj ec tiveannual in co me , but their Objectiv ehea l t h status is difficult to ver if ybec au s ehealth isat leastpartially a SUbjective st.ot.e.

In addit i on tothe lac k of distinct ionbetween objectiv e and SUbj ec tive lif e domain measures,multivariate techniques, ....hich can control fo r the intercorrelations betweencorrelatesof SWB, werenot always utilized.

Never t he l e s s,resu ltshave beenre l a t i ve l Y consistent across all domainsin sh o wi ng ast r o nge r correlationbetween SWB and sUb j ec tiveass essment of li f e domain sascompa r e d with the more obj ect ivecor r e spo nding asses s ment. (Andrews &:

Wit hey, ~976;Ca mpb e ll et a1., ~97 6; Diener, 196 4 ; Emmons &

Die ner, 198 5; renqrer &:Je ns e n , 1981).

For example, in the healthdomain, reviewsof the early work found cons istentresults showing simple zero-order correlations between SWB and primarily objectivehe a l t h

11

indicators in th e ra n ge of .2 to .5. (Larsen, 1978; okun, st o c k, Haring, &Witter, 19 84; Ge o rge &Land e rma n, 1984;

Zautra &Hempel, 198 4 ).Ho we ve r inall cases cited , thi s relationsh ipstrengthenedasone progre s s ed frommore Objectiv eto lessobjective as s es smentofhealth.

In reviewingthe relevantresea r ch forolder adults , Kozma at a1. (19 91) reportedthefo llowi ngdi s c repan cies between th e perc en t ages of vari an c eaccountedfor in SWB by SUbjectiveand objec tive life domain ass e s sm e nts: 10 %to20\

for SUbjective health versus4%to7\ for obj ecti vehCil l t h;

3% toJO% for subj ect i vehous ing ver susH to4\for obj ec t ive housing, 1% to 30%for subjectIvc fin ance s versu s 1%to 4%for income; 1%to 13%foreubject Ive ma rriage versus 1%to 4% for obje ct i ve ma ri t a l status ; andJ%to 25 % for SUbjectiveemployment vers us 0\to1%for Object ive employment.

Gen era lly, thesefig uresar econs i s te nt with re s ea rch on mor e diverse age samples (And r ew (, Wi they , 1976; Ar g y l e , 1987 ;campbell et al., 1976 ) . One exception noted inthe literature is a studybyMullis (1992) inwhi c h va rious meaaurea ofob j ec t i v efin a nc i a l statuswer e compared in their ability topredict SWB.Although a stro nge r relationshipwithSWBwas found thaninstud ies using the

12 typical 'currentincome' measures, the authorswere surprised that their newly developed ' life-timeincome' measure of economic well-beinqaccountedfor only 7%

variance inSWB.

In certain respectsthese discrepanciesare not surprising. One mightexpect that it isn't what you have but how happy you are withwhat you haveth a t is going to be related to how happy you are ingeneral (Le.,happiness comesfr o m wit hin ). Conve r s e l y , an equally credible assertion wou l d beth a t objectivecondi tions,such as poverty or illness, would ha ve a significant effect on one's happiness (presumablybyLower-Lnq domainsatisfactions)•

These two pointsof viewcanbe conce ptualizedIn te r ms of the causal linkages between satisfaction in various life domainsandoverall SWB. Diener (1984) la bel l e dth e competing theoreticalapproaches"t op-down" (TO)to deno te the higher~orderhappiness construct affec tingone's satisfact ion invarious lower-orderlif edomainsand

"b o ttom-u p" (BU)torepresent the causal pat hway from the sumof li fe doma in satisfactions "up" to levelsof overa l l 5\.,.8 (see Figures1 and 2).

13 Figure 1

GeneralTo p-d own Model Relat ingSu b j e c ti v e we ll-be ingtoi ts Major Correlates

OVERALL SUBJI:CTIVEWElL·13I;ING

LIF E DOMAIN LifEDOMAIN LIFE DOMA IN Uf EDOMAIN

SATISf AC TION1 SA T ISFAC T IQ N2 SATISFAC TIONJ SI\Tl$FAC TlON4

Fig u re2:

General Bottom- u pModelRel a ting Subjec tivewell~beingto its Maior- Correl ates

OVERALL SUBJECTIVE WEll·BEIN G

~/7~

ureDOMAIN LIFEDO MAI N LIFE DOMAIN LIFE DOMAlN SATISfflCT lONl SI\TISfAC TION2 SATISFACTION3 SATISFA CTlON 4

15 An o t herco nsis t ent cha r acte r i stic of lif e domain as s es sme nt s is the factthat intercorrelationsbetween domai n sa tis f a ct i ons are usually quite high (Diener, 1984; He a dey, Hol mstrom , & Hearing,1985;Lance, Lautenschlager, Sloan , &verce, 1989; Lewl nsohn, Redner, "Seeley , 1991; Rodger s. He r zog , "An dre ws, 1988). Fo r examp le,Lcwinsoh nat a L,(19 9 1 )foundsat isfactionwith the followi ngar-ee s of li f e to behighlyLrrt.erco.r-reteuocsself. fri e n d s, spouse and family life , work or school,neighbourhoodandcommunity, andsports and recreatio nalfacilities. When subjected to a pr incipal component anal y s is,al l sat is fac t ionitems ha d highlo a di ngs enthe first princi pal compone nt,account i ng

for<Isubsta n t ialportionof thevaria ncein SWB. The

authors concludedtha t all of the life set.Isr act Lon items we r e essentiallymeasures of the sameunde r l y i ngdIeensLon, whi chth ey cal l edli fesatisfactio n.

Despite suc h high inte r cor r e l at i on s , thepred ictive ability of domainra tings docs increase....hen r-el at.Lc nshLpn ar eassessed in a mu ltivariate fashion. Apredictorur r a y consis t ingof hous ing satisfaction,act iv ityI perceived heal th, marital status, l if e events, and fina ncial eat .issa ct fonwas repo rted to ac c o unt fo r 36%ofthe variance inSWB rating s of an elde rlysample (Kozma & stones, 19 8 3a).

16 In two other elder lyseap t es, between 40 \ and 50\ of the variance inSWB was explained.Self-ratings ofhealth , educat i on, activJty, and income accountedfor 40\and sotof the varia nceinSWBrat ings for women and me n, respecti vely (Karki d es &Maz.-tin, 1979).Mich al o s (1986)explained 45 \ of th e va ria nce in life satisfactio n from th e follow i n g 6 do ma insa t i sfa c t i on s: he alth (b e ta.. O.29)ispo use (be ta- 0. 2 2 ) ; fi n a ncia l security . self-e ste em (self) and housing

(eac h beta.. 0. 1 5) an d fr ie nd s hips (beta " 0.13) . 'f h e inclusi on of satisfact i onwith sel f (self-est e em) mayha ve inflatedthe mUl tiplecorr e lation sin c e, st ri c t l y spea k ing , it is moreofte nconceptualize das an Intr llpsychic me diat ing vari a b lethanas a doma i n of life (Ar g y l e , 19 8 7;Waltz, 19 8 6 ).

Usi ng a la r g e probabili tysample, Bharadwaj &Wilkening (1977) regre s s e d self-rating s of satisfactio n in14 life do mai ns on general SWB for the tot alsamp lean dfor subsamplesdivided by age, sex, andincome. Th eir res u l t s indi cated that between 20tand 40\ at' the exp la i n e d var ianc e inSWBrati ng s was pre d i ctedby th e 14 lif e satis fa ct io n domain s.

17 To summarize, thetota l va r i an c e accounte d fo r inSWB by satisfa ctionin variousli f edo main s ranges from20 to 50 percent. Impressive as these re sul t s appear, there ramain substantial portions of 81-.'Bvariance unaccounted for by the combinationof satisfactionsinsome of the most importa nt doma ins of life.

Little doubt exists that certainlife domai n satisfactions are better predictors of SWB than others.Tile gen e r a l finding isth a t the less pub lLc (Le., re l ate d to the largersociety) and moreprivate, or personal, the doma in, the stronger the relationshipwithSWB(An d r e ws Eo wi t h e y , 197 6 j Bharadwaj &Wilke ni ng, 1977; Bradburn, 19 6 9 ; Campbe l l at a! . . 1976; Glatz e r, 19 9 1 ; Leelakulthanlt&Day, 19 92 )•

It isal so apparen t that the rel a t i ve importanceof doma ins inaccount i ng forSWB var i an c e is depend e n t onth e speci f icsampleor subsam p leassessed (Ar g yl e , 1987;

Bal a t s k y &-Diener , 1993; Bharadwaj&Wilke ning, 1977; Kozma

&Sto nes , 19 8 3 a; Markides&Martin, 1979; Near& necn ner,

19 9 3; Quirouette&Gold; Stull, 1988;). For example, health appearstobe more important in aged samples (Bhara dwaj &- Wilkening, 1977; Kozmaeta1., 19 9 1 ; Lars e n, 1978; Michalos, 198 6 ) whe reasfriendshi pand lei sur e figure promin e ntl y in

rs

domains of most importance tothe 5WBofna t ionall y re p r e s enta ti v e samples (Andrews&Withey , 1976; Campbell et aL,, 1976; Headeyet al., 1985; Headey, Veenhoven, '"

we ar i ng, 19 9 1 ). Even within the same sample, changesin the relati veimportanceor lifedomainsatisfactionsin predicti ngSWBhave beennot e d ove r time (Kozma&Sto ne s , 19 8 3 .1)•

Researchaddress i ng temporal cha nge inobject ive and sUbjective doma i n indicatorsofSWBha s beenqu i t e scarce.

Ap pa r e nt l y few re s e arc he r shav e beenintereste d in the qu est ionof what accounts fo r changesinthemea nlevelsof satisfactio n in life domai ns. The pre s umpt i o n has be en that cha nge in objective circumstancesis primarily re spon s i bl e for cha ngein SUbjectiveassessme nts howeve r thede gree of th is correspondence is unknown.

Acco r dinej to McNeil, sto nes, andKozma (198 6a )no lo ngi t udina l studies on thest abi lityof life domain sat is f ac t i o nhadbeen done up to thatpoint.Overan18- mont h peri od , they found no sig nificant change inmean level of sceIsrecercn rati ngsfo r housing, rel i gion, and fi na nces. unf ortun a t e l y, noObjectivemeasure s of thesedoma ins were

19

obtained. Objectiveand sUbjective measures of healthshowed change but in oppositedirectio ns.McNeil, stones, and Kozma suggested that an increasein the use of medicationsle a d to an increase in healthsatisfaction despitea deterioration in the objectivehealth ofthe i r elderly sample. Costa et al. (1987) foundsUbjectiveratings of health to remain stable over a nino year period. They assumed some deteriorationin objectivehealth with aqe during the s omc time period for their largesamp l eof SUbjects aged 25-711.

Landua (1992) used a modified Markov model to evaluate the individual stabilityof objective and SUbjectivehe a l th assessments over four waves of German panel data from 1984- 1987. For analysis, he divided the samp le into eubject e who ha d healthcomplaintsat anytime during the four surveys (i ll) versus thosewho did not (healthy). SUbjects were then divided into groups which changed ("movers") or did no t change (lIstayers^lt) intheir subjective evaluation of health.

Re~ults indicated tha t 26%ofth e ill groupwere stayers t'lhile13%ofthe healthy group were. Th e ill group were assumed to be in a permanent state of bad health while the so-calledhealthy group were believed to sur r er less severe but no ne- t h e-l e s s substantialenoug h he al th symptoms to cause 87% ofthis sample to change. Proportional diffe rences be t we e n groups were not tested for significa nce, nor-we r e

20 the estimations of changebased on the xarxcv mod el.Thus, studieswh i ch ha v e focusedon the domainof hea l t h ha v e showninconsistentf:i.ndinqs.

Similarly, inconsistentresultshave been obta inedon the stability of satisfaction inthe job domain.Job satisfactionhas been found to remai n rela t i v ely sta b leover periods as long as 5 years, evenwith changesin occupations or employers (Gerhart, 19 8 7; Schneider& Dachler, 1978; Staw

&Ross, 1985). However, Farkas&TetricK (I989) found that

the job satisfactionof U.S. Navy employees changed significant lyover a period of 19 months.

Using2-year lon g i tud i n al da t a from the Australian PerceivedQuality of Life surveys, He a d ey , Glowacki, Ho l ms t r om and wearing (1985)evaluatedsatisfactio nchange infour lifedomains:health, standardof living, job, and marriage/sex.Alt h oug h the amount ofabs o l u te domain satis fact ionchangewas not reported, the au t ho rsdid find strong associations between li f e event changeand satisfactionincorrespon dingdomains.

The use ofLI SREL structural equation modeling (SEM) provided the followinggammas linki ngrespectivedomain

21 eventsand domain satisfaction change: 0.54 for health; 0.40 for standard ofliv i n g; 0.36 for job; and 0.25for marriage/sex. Some spillovereffects were also noted.

Standardofli vin g events werefound to effectchange in marriage/sex satisfaction (Gamma= 0.20) andjo b even ts predicte.dboth health and standard of liv i ng satisfaction cha ng e (Ga mma s= 0.12and 0.1 7 , respectively).

Atkinson (1982) separatedhis sample intothose who had exp e r i e n c e dli f e change in thetwo-year interval between assessmentsand those who did not. In addition to overall SWB, satisfactionin five life domains was evaluated. For four out of fivedomains, resultsindicated that retest correlationswere significclotlylowe r inthe group reporting change thaninthe no changegroup. Unfort una te ly , chanqe was not differentiatedwith respectto specific life domains so the domain-specificreactivity of life domain satisfaction couldnot be evaluated.

Inte re s t ing l y,Atki nson (1982) found th atfor the total sample, li f e domainsatisfact ionwas as stable, if nat more stable than evaluations of life in generaL He alsoreported data fr o m campbe llet a1.'s (1976) a-month longitudinal survey whichindicated equa l or greater stability of domain satisfaction incompa ri s o n to the stability of overall SWB.

22

Wheth e r th e s e findings reflect me asu remen t artifacts or th e act ual re l at i ve stabilit yof sat isfactio n inlif e domains re mai ns to be seen.

When Atki nson(1962) separated groups accordi ng to the experience oflif e change,scores on only one of the four overall SWB measuresweresignificant lydifferentbetween groups.!low life satisfact iondomainmeasures can simultaneously be more stable ove r time than genera l SWB measures and morere a c t i veto life changeis worthfurther investigation.

The re l a t i v e stabilityofdomain satis faction s over timeapp e a r sto be at le a st equalto that of overallSWB but furth e r work is ne e d edto confi r mtheseprel imi nary findi ngs. Results from thesestudies are equivocal wi t h re s pe c t to how reactive domain satisfactions areto changes in objective domain conditions.Likeoverall SWB, it seems that mean le ve l s of domain satisfactionremain moderat e ly stab lealthoug hchangedoes occurin indi v i d u a l le vel s over time.

Summary .Although inmost cases, a positivecorrelati on betweenobjectiveand sUbjectiveassessmentsof life domains exists , it is not strongand sometimes does notreach

signif icance (Andrews&Withey, 1976; Gutek, Allen, Ty ler , Lau, &Majchrzak, 1983; Kozma et aL,, 1991 ; Lan d ua, 199 2 ; Larsen, 1978; Levkoff, crearv ,&Wetl e, 1987). Ove r50\ of the variance insubjeccIve domainassessmentscannot be accountedfor by va ria nce inthe objective conditio n.

Fur thermo r e, the corre lat i o nbetweenautrject. Lveassessment of lifedoma i ns and happi nessis stronger thanthatbe t we en object ivelifedomain conditions and happiness.

It appearsthat factors otherthan the actual condi tionsof life, or the sum of one's satisfactionwith the s e discrete life domains, ar e at playinthe processof arrivi ng at one's self-perceptionof ha ppine s s . The directionof causality is anot hermatter, requ i r ing lo ngitudi na l desig ns , and will be addressedmore thoro ug hly in a subsequentsect ion. However, itis wor t hment ioni ng thatsince th e aimof ear l ysocial l.lJ.di.£'lt.2..I.:.s.re s e arch wa s to seehow the environmentaffectedpeople'swell-bei ng, its influe nceonsubsequent SWBre se arch may have inadver tent l y biasedresearchers' expectancieswith respect to the direc t i on of influence of domainsatisfactionsand SWB.

Demogra ph icVariables

24 The a.mount of swa varia nc e ac c o u nte d for by housin g , inc ome, maritalstatus, and empl oyme nthasbeen note dabo v e in direct comparisonto the sUbjectiveas s e s s ment of the s e demograph icvadables (p.12). The range of vari ance explainedby eachof the s e objectivelife domain variab l es wa s repo rted tobe be t we e n zeroand 4% (Kozma et 1'101. , 19 91). Ear l yst u di es ha ve shown age, sex , education,and eth n ici ty to correlatewithswa (Andrews&Withey, 1976; Campbell et 1'101. , 1976).

Demogra ph icvaria bles, takentogether, ha ve acco un t ed for up to10%ofSWBvariance (Michalos, 1986). Andrews and Wi t h e y (19 7 6 ) explained 11%of SWB varianc e from the fo ll o wi ng variables:age, sex, education, race, family income, andstage of family life-cycle. In the i r Ba ng ko k sample, LeelakulthanitandDay (1992) found sex, marita l status, race, emp loyment status,educ a tion , Inccma,;:nt;1 ag e toexp l a in 12% of SWBvariance. Somewhat hi gh e r figures (15 %: )hav e been repor t e d whenmoreso ciode mog ra p hic var iables (e .g .•polit i c al conse rvat ism) ha v ebeen used (Gri chti ng. 198 3).

Wh en life do main eatIs reot Ions'lor e include d in predictor arrays for regressionanalyses, de mog r a p hic variab l es do notofte ncontribu teanyfurther ex plained

25 var iance(e.g.,Michalos, 19 8 6). indicating thatthe effe ct of many demograph icvariablesonSWBis indirect (Diener.

198 4 ;Ko zma et a L,, 1991 ). Demographic variables such as age (George,Okun, &Landerman, 1985), and sex (Markidesr.

Martin , 19 7 9; Oku net al., 1984) have been shown to moderate the impa c t of other corre l a tesofSWB. Simila r l y , the relationship betwee nSWBandotherdemog ra ph ic variab l es, such aseducat i onor mar italstatus , is believed to beof a spurious nature (Ar gyle , 1987 ; Koz ma eta1. , 1991). Thus, few of these variableshave shownany di r ectrelationship with SWB. Using path analysis, neit h e r Liang andWarfel

(19 8 3) norHe a d e y (19 93) found a dire ctrela tionsh ipbetween educationand SWB. In addition, Head ey (1993) coul d not confirmany directeffects for eithersex, age, or social statuson SWB.

Althoughdemographicvariablestypicall y do no t account forany uniqueSWB variance abo ve thatex pla ined by life domain satisfa cti on s, some consistent findi ng s have be en found in terms of sampl edescript ion. The majority of re s e a rchha s notshown any sex differenc e s inmeanlevels of SWB when relevantvariables are controlled (Diener, 198 4 ; Larsen, 1978 ; Le wi ns o h net aL,, 1991; Palmore&f<ivett, 1977; ve e nncv e n , 198 4 ) . with rega rdto marita lstatus, a numberof revi ewshav e con c l ude d that on average , married

26 people are happier than th o s e who are unmarried,divorced, or widowed (Argyle , 1987;Diener, 19 84 ; Kozma et al., 19 91 ) .

Within count ries, highe r mean inc ome level ste nd tobe as sociated withhi gh erme a n levels of SHB (Argyle ,1987;

Campbe llet a L., 1976; Diener,19 8 4 ; Dou t h i t t,Mac Donald, &

MUllis, 19 9 2 ; Leelakulthani t &Day, 1992 ; Mullis, 1992). Much debate has foc us e d on the relationshipbetween income and SHe in cross-country co mpa ri s o ns. Diener, Sandvik, Se i d li tz,and Diener (1993) have recentl ycriticized previous research on methodological gr o und s . Using a more diverse sample ofcount r i e s and longitud ina l data, they concluded that SHe showsa curvilinear increasewith income withinthe U.S.A.anda moderately strong line a r re lationshipbetween SWBand GNP across countr ie s.

Like the Inc c s e-swarelation s h i p in cross-cou nt ry comparisons, agreemen t has been difficulttore a ch on the relationshipbetween age andSWB. Pr e vi o us inconsistent re e u j.t;s can beattributed tothr e e main sources: (a ) the use of cross-s ec tionalage cohort comparisonsversusanalysisof maturatio nal change inSWB withaging, (b) thefindingthat the sac Ls r act.Ion component of SWBtends to increasewithage but affective intensitydecreases, and (c) inadequate st a t i s t i c a l co nt r ol of confoundingvariables (Argy le, 1987;

27 Campb e llat al., 1976; Di e n e r , 19 84 ; Diene r ,sand vi k , &

La r s en , 19 8 5;Doyle&Forehand, 1984;He r z o g&Rodg ers, 1961; Larsen,1978).

Longi tud i na l studieshave shown rather consistent resu lts th a t ind ica t e nomaturatio na l che ne cinme a n levels of SWB(Bau r& Okun, 19 8 3 : Co staetal.,19 8 7;George&

Ma d d ox , 1977;Ko z ma &Ston es, 19 8 3 ilj Mussen, lIonzi k, &

Ei c h o r n , 1982; Palmore" Kivett, 1977; Reker&Wo n g , 1984).

However ,asonemig ht expec t, many studies have fo u nd a moder a t ing effect of ageon related variables.

Research on races, particularly blacks and Whites, is another area in which res e a r c he r s exper-Ience a greatdna1of confusio n and equivocal findings (Krause, 199 3 ).The cnr v longitud i na l ex a mina t i onto dateha s found tha t raceis not a si g nif icant pre d i c tor of avowed happinessove r a s-yea r pe r i od in a samp l eofel derl ymen (Burto n, Rus hi ng, Ri t te r,

&Rakocy, 1993). In their25%:blacksample, ra c ewa s found

toha ve an ind i rec t effecton happiness thro ug heducation andsoci al ro l e s. usingan elder lysubsampl e of a nat i o nal probabil i tysamp l e, Krause (199 3) came to a sim ilar conclusi o n afte r analyz inga complex saciaeconomir.:

conceptualmodel th r ough SEM.

2B Michalos (1982) accoun tedfor 53% ofth e variance in SWBin terms of satisfaction in12 domains and 7 demogra phic variables. However, the contribu tionof the demographic variables was of a moderating nature, by influenc ingthe relative importanceof the domain satisfactionsfor different demographicgroups.

~. Many demographic variablesreduceto noneLqnLf Lca nce when they are examined in a mUltiple regressionformat which includes other relevantvariables.

Whenthey do retainan indep e nde nt contributionto SWB variance,i tis usuall y ofli mited ord e r and inthe fo r m of a moderating effect.

Environmental in fly e nc e s: Life events hassles andup li f t s

As previouslynoted, objective measuresof life domains have not been foundto explainmuch variance in SWB. Fr om a Ilbottom-up " intuitive perspective, theseresu ltshave been regardedas surprising. This finding le dSWBre s ea r c he r s to evaluate alternate conceptualizationsand measuresof objective life circumstances.consultingthe existing literat urere ve al ed a la r ge body of researchon the stress- illnessre l a t i o ns h i p .

Thisresearchconcerne d thenegat i ve effectsof life changes on the development of bot h phys i c a l illnessand psychological distress(Holmes&Rahe, 1967; ncbrenwe nd&

Doh renwen d , 1974 ; selye, 1956). Given thewell-being /ill- bei ng rel a t i o ns hi p, there'las obv i o us reason to believethat theli f e eventsconce ptualizationof environme ntal influencesmaypr e d i c t SWB.

Life events. Many examples of life eventsinvolve social role and life demand changes which accompanytypical lif e-sp a n development (e . g., deathof a spouse , ill ness, loss of employme nt, marriage, bir t h of a child).Ov erall , re sul t s ha ve bee nconsistentinobtaining modera te zero- order correlatio ns be t we e n certain life events andSWB (Bre tt, Brief , Burke, George &Webster, 1990; Cohe n, 1988; Cchler&Boxer, 1984; Filipp&Kl a ue r, 1991; Stones&Koz ma, 198 4; zaut ra&Reic h, 198 3).

Hasslesand UPlif ts. Ha s s l e s and up li ft s were devised to addressa repo r t e d req uirementof balance in the valence and durationof lifeeve nt s incl ude d in typical lifeevent lists (Ka nne r , Coyne, Schaefer, &Lazarus, 1981;Zautra &

Re i c h , 1983). Incomparisonto majorlife events, the s e measuresfocus on the assessmentof more minor, daI ly events in life that may prod ucenegative stres s (ha s s l e s) or

30 po s i t i.. ecue coees (uplifts) . Examplesoftypical hassles ....oul d include lIlisp laci n g keys orhavi ng transportation pr-oblems.Typica l uplif t s inclu dema ki ng new friendsor be i ng complimented.

Chambe r lai nand z Lke (19 9 2 ) conducted a3-6 mont h long it ud ina l studytoasses s the relat ionshipbe t wee n vari o u s meas u resof wel l-be.ingand two predic to r vari a bles. 'I'heHassles Scale (Kann e r et a L,,19B1)wa sus ed to as se s s

minor stres sor- swhichrepresentedone of the pred ictorsin thestudy.The autho r s report thatwhen priorwell-b eingwas part.La Lfedout, the additional vari a n c e in curre ntwell- being ac c oun tedfor by current hassl e s was limited(1 -9') butprior has sl e shad no such unique eff e c t.current hassles were still foundto predict current ....ell - bei ng afte!"

va riance dueto both pr ior IoIell-b e i nqand priorhassleshad been removed. From the ir ana l y s es , theauthors concl u ded thatcurrent , and no t pri or,da ily stressorscontribute to le vel s of SWB.

Reca ll fromthe domai n indicato rssection that l if e eve nt chan g e ha s been found toef fe ct change in domain satisfac tionsto a qt-e atie rdegree thanit does in SWB . Hee dey et al. (1985) useda measure th a t includ ed both lif e eventsand hassles intheir stiu dy of the relationshi p

Jl between SWB and domain satisfactions. In one structural equation model that was tested, direct links between IHe stress and 2-yearchange inS\~Bdid not reach significance and were subsequently dropped from the final model. Indirect links from life stress through domain satisfactions to SWB were euppcrtied ,

Zika and Chamberlain (1987) found low to moderate zero - order correlations between hassles and SWBin two samples and these relationships endured when the effects of a number of personality variables were removed in mUltiple regression ene ryses . The unique r-e Lat.Lo ns hLp between hasslesor life events and SWB will require inclusion of allrelevantSWB correlatesto assess any mediating pathways and confounding variables.

Daily events versus life events.Studies comparing the differential predictive ability of hassles and life events on psychologicaldistress or health outcomes have consistently found hassles to be the more powarful pradictor (see Chamberlain&z Ixe , 1990, for a review; Johnson&

Bornstein, 1993; Lu, 199 1 ). Studies using SWB as the outcome var-Lab l e are less commonbut obtain similar results.

32 Lewinsohnet al. (1991) ut ilizedmeasuresof ha s s l e s and major lite events andfound si g ni f i c an t zero-orde r correla tio nsbetweenboth meaSUrt:!sand SWB In two samp l e s. However, in ..ul tipl e re gre ss i o n analyses ,onlymic ro- stressors re e a Ineesignif icant, contributing 1.4 \:and 2.5\

ineach sample. Simila r resul ts were ob ta ined by Holaha n , Hola h a n, and f1el k (19 8 4 )with an elde r lysample.

Cha mb e rlo.i n and z Ixa (199 0 )alsofound simi l a r resu l ts : Has s le s predicted SWB whe n the eff e ct s of life eve n tswere partialled out. Whe ntheyrep eate d the re g r e s si on ana l ys I s in the reverseorder, life ev e nts didnot signi fi c a nt ly predic t anyof the ir well-be i ng measures. Furt he r more, no evide nce for aninte racti on eff e c t betweenthe two measures was obtained, suggesting th a t each exertsanindepende nt inf. lu enc e on SWB.

Accordingto Kozma et al. (1991). eac hlifestres s inde xis diffe rentia l l ysu i ted tothedi ff erenttimefra llles ofSWBmeasu reme nt.The hassles measure pre dicts greater prop o rtion s of variancein currentSW'B Whereas life events are better at predictingSUbsequentlevel sof SWB.

Individ ua l pis positions

3J Th e cor r elates to be re viewe d underthis heading includeestablishedpersonalitytraits (Le., ext r a ve r s i o n and ne urotic ism) ,as well as psychologi calresourcesor dispositionswhichre fl e c t individual differencesin characte rist icways of inte r ac tin g wit hthe environment.

Extrave rsionand ne uro t i ci s m.Accordin~ to McCrae (1983) , extraversio n (E) ty pi cally accounts for bet ween 5\

to10\ of the varianc ein SWB and 10%to 20%of SWB variance can be explainedby neuroti cism (N). Percentages of var ia nce explained by these pe rsona lityt ra its var ygreatly between studies, perhaps due to diff erences illsample

characteristicsand measures of SWB. For example, extravers ion has recently been reported to explain from 3%

to 23% of SWB variance (Argyle & Martin, 1991;Headey , 1993)•

Headey and we a ring (1991 ) foun d uncorr e cted a-year stab ilit iesof .63 forEand .67 for N.Costaand Mc Cr a e (1980) cite a 12-year test-retestco e ffi ci ent of .7 0 for N and a 6-monthtest- retest coe f f i c ie n t of .7 9 was obtained for E (xccree&Costa, 1983 ).These fi gu res are co mpa r a b l e to the stabilityestimates of reliablemeasure sOf SWB (sec Table 1). with regard to indi vidualchange, Magnus, Diener,

34

Fuji t a, andPa vot (1993) fou ndtwe nty percen t ofrespondent s ch a nged more tha n one standarddeviationon E and 31\

ch anged as mu c h onN overa 4-year period. Inte r e s ti ngly , the s efiqures are on par ....ith the reportedchange in ha pp ine s s over time (Headey &Wearing, 1991).

Al thoughthese well-studiedpersonalitytraits are purported to be re s p o n s i b le for thestabilityinBIoi'B (Costa, xccrae , &scnceman,1987), i t is interesting thaton average, they do not accoun t for any more than 15%of the variance in SWB(Kozma et al.• 199 1). Furthermo re , as noted above, SWBappears to be as stableas cnesepersona lity traits.

Fina ll y, although E and N appeartobe as eff ectiveas SWBis itself in predicting later SWS (Costa&McCrae , 1980 ; Costa, Mc Cr a e ,&Norris, 19 8 1 ; Costa, McCrae, &Zonderma n, 19 87 ), the inter relationsh ip between thethr e e constructsis unknown. Costa (1983,p.73 ) made the followingdescription of the re l at i o nsh i p between high E or N peopleand SWB:

In divid ua lswho are chee rful ,warm}and exciteme nt- see king ar eli ke ly to experience a life timeof posit ive affec t; thosewho are depress ive, anxious , andhosti l e are li ke ly tore ma inunha ppy.

35 Putti ng as idethe referencesto sta bility , the above descript ionis taut o logical andpoi n t s to theneed for fur therwork tope r hap s tease-out a component structu re for thecombined measures.

Purpose. The constructof lifepur pos eis future- orientedand cerre e e e a generalintention to fulf il functions or achieve goals inli fe (Reker, Peacock, &-Wong, 198 7 ) . Li f e purpose is most ofte nassessed withth e Purpose in Life Test. The psychometric propertiesof are v i s ed version ofthe scale were evalua tedby HaL'low, Newcomb, &- Bentler (1987). Fa c t or analysisrev e aied 4 primary facto rs in addit ion to a largegenera l fact or: lac k ofpurpos e in life;positivesenseof pUrpos e; motivatio nformeaning ; and existe nt ialconfusio n. Purpose inlife was stro ngly related tohapp i ne s s (.I;:• •84).

Reker and Peacock's(1981) Life Attitude Profi le (LAP) ha s alsobeen used to assess life purpose,although not as exte nsive l yas the Purpose inLifeTest. Seven subscales measure: lifepur po s e (zest for li f e , fulfilment, contentment, satis f a c tion); will to meaning (strivi ng to findmeaningin personalexistence); futuremeani ng (d e t e r mi nat i on to make thefuture mean ingful ); life cont ro l (freedomto make life choices, exerciseof re s po ns i bil ity);

36 exis t e n tial vac u u m(l ack of purpose andgoals) ; death ac c e p t a nc e (l ac koffe a r or anxiety about death); and goal seeking (d e s ire to achieve new goals).In addi t ionto a numberof interestingage-re lated ch ange s onthese eubacaLea, Rek er et a1. (1987) foun d all sucsce Lee except

"will to meani ng"tobesign i f i can t l y correlated inthe expecteddirection with SWB.

~tt2!. Sh u pe (1985 )define s perc eivedcontrolas the expe ctati on of ha vi ng control over one' s envi ro n men t. The co nstruc t ha s beenope r a tio na l i zed in two di s t inct , yet re latedfo r ms : (1) as a genera l ind ividu aldi s p o s iti o n to view environ menta l events as bei ngwithinone 's cont ro l , labelledon aco nt i nuum frominte r n alit y to ex te r na lit y ; and , (2)as a specifi c charac t e risti c ofan environment , for exa mpl e , theamo u nt of cont r o l seniors mayexerci se in a nurs i ng homeenvironment.

Many st ud i e s have found a significant positive relationshipbetween internali ty an d a hostof adap tive he a l t hcha r ac t e r isti cs , inclUdingSWB (seeShupe, 1985, for a revIev}. Reid and Zie gler (1981) report correla tions betweencontrol and life sa t i s f ac t ion in the range of .32to .54 inanumber or st u diesusi ng theirDesired Control Scal e. Furthermore,their me a s ur e ofcon trol predicts lat e r

J7 SWBfollowi ng inte rvalsof 6to 18 mont hs (x:. . .23 to .44 ). Rekeret aL, (1987) founda significant correlationbetwee n SWBand lifecont rol , as measur ed by the Life Attitude Profile.

~. In their rev iew of the relationshipbetween pers onaloptimism and physica l andmental hea l th , Reker and Wong (1985 ) sugg e s t the constru ct is closest,and per h a p s synonymous , toth e constr uctof hope.They pr opo s e J major compone ntsofpers o na l optimism, all r-e La'ted to future lI fe conc e rns: (1) SUb j e cti ve expe c t a nc i e s; (2) feelings; and (3) goal -strivings.Scheie r and Carver (1989, p, 1027) view opt im ismas the"fa vour a b i li t y of the person'sgenerali zed outcomeexpectanc ies."

Asignif ica nt correlationbetween optimismand well- beingvas obtained by Sweetman, Munz, and Whe e l e r (1993). Thei rwell-beingmeasure was A combination of SWB and il l- be i ng but optimism was more closely relatedtothe SWB portion of the measure.Scheieret al. (1989)wer e interes tedin the effec tsof disposi tio nal optimismon re co very fromhea r t sur ge ry.Opti mismassessedpriorto surgery significantlypredicted SWB6-mon t hs post-surgery.

In compar iso ntope s simi s t s , optimists wer e significant ly

38 mo r e likely to have retur ne d to their normal lifeact i v it i es at 6-monthspost-op.The y also resumed both physical and recreatio na lactivitiesmor e quickly tha n didpes s h li st s.

These behavioralindica to rsof SHe arereflected inahi g hl y si gn if i c a nt correlationbetwe e nprior optImismand post-o p SHB.

~. The constr uc t of hardInesswasint roducedby Kobasa (19 7 9) andishypot h e siz e d to consist ofthr e e genera l charac teris tics: (1)commitme nt , or approa c h ing life witha sense of meaningandbeingactively involvedinone 's work or dailyact iv i ti es; (2) contro l , or a feelingof be ing ableto inf l ue nce events; and , (3 ) challenge, or viewing une xpe cte d change asanoppo rtunityfor growth vers u s threat. Togetherth ese characterist icsare believedto buffer the impactof stressbyway of acog ni ti ve med iationalrol e bet wee n st ressand il lness. Hard ine s s has be en found to share 7\va r i a nc e wi t h opti mi s m(Q< .05) Swee t ma n et a1. (1993) .

Mc Neil, Sto nes,Kozma, and Han na h (19 8 6) fo und that hardiness acco unted tor 12%of thevaria nc e inthe SWBot an elderly sample. Sweetman et a1. (199 3) di d notobta i na signi f icantcorrelati onbetween the twoconst ruc t s whe n a combine d well-be ing!ill - bei ngoutcome me a s ure was ue e u ,

39 Howe ve r, only a 27\responserat ewas obt ain e d fromthe ir select samp leof midwes tattorneys.

Self-este em, Diener(1984, p, 558) cited el e ven studies wh ich togetherindic ate tha t se lf -este em is oneof thebest pred i ctor sof SWB. In thei r re v i e wof th eSWB- este e m re l at i on sh i pres e a r c h, Kozma etal. (199 1) emphasize the variabil i tyinthemagnitudeof correlationsobtaine d (rango

= .1 3to.6 1 ) an d suggest theus e of a st andardizedmeasure. Headey,Holmstro m,andWearing (1965) obtaineds IqnifLcant;

betas linkingse l f-esteemto thre e life do ma i n satisfact io ns and SES but nodirect links were found betwe en self-esteem and SWB.

~. It shou ldbe apparent from theprec ed ing rev i e wthat manyof the abovecons t r uc t s share si mil ar , if no t identical, component s: hope,meani ng inli fe , con t r ol.

Fur t he rwork is re qu ire dto teaseout the uniq ueeffe cts of eac h compon e ntinthesemul tidime nsiona l const ruc ts.

All co nstructs wouldappearorha v e be en suggest ed to invo l vepred ispositionstocogni tively eva l uateth e envi r onment in certa inwa ys . For some (i. e., control, hardines s) , the cogn i t i ve compo ne nt has been describedas thepri mary cha ngeelementwhich mediat esthe rel at ionshi p

40 between lifecircumstances andSWB.Whether theydetermine SWBor result fromi trema i ns tobe seen, In part because personalityis beHevedto be engraved in our neuroanatomy andin part becausecognitions are believed tode t ermi ne af f e c t andnot vice versa, the often unchallengedassumption is that dispositions cause happiness.

Model s ofSUb j e c t i v e We l lBeing

To a large extent , the pr e v i o us reviewof correlates was carried- o u t tolaythe groundwork for an understand ing of contemporarymacro-processmodels of SWB. These models attempt toex pl a i n therajati onshipsbetween SWB and some of its major co rre late s.Asprev iou slYstated, the most crit ical re s e a r ch qu estio nis the directi onofcausality within these models. Ignorance of the answer ha s beenca l l e d a "bl a c k hole in current re s ea rc h" {Headey&Wearing , 1992).

Therefore, the present sectlononSWBmodels willbe organiz ed aroundthe three maln types of causal mode ls;

bcetoa- up,to p-down , and bi-directional.

Bottom-upMode l

The difficultywith ma ny studies whichobtain results su pportiveof thebo t t om-u p model of SWB isthat theyare

41 correlationa l inna t ur e. l'Exp l a i ning" or "a c coun t i ng" for portionsof va ri an c e in SWBfrom the comb in a t io n of satis fac tio n in various lifedoma i n s does not tell us anyt h ingab outthe direc tion of causality. Thus. findings that the au linear add ith emo de l accounts for betwee n 20 and50 percentof the variance in SWB do no t address the top-down/bot tom - updistinction,althoughnumerous researchers have either implicitly or exp L icitly cited this type of evidence for 5U support.

To date, th e majorityof approachesto the studyof life domain satisfactionsand SWB has been from a bottom-up perspective (Andrews" Wit he y, 1976; Atkinson, 1982;

campbe llet 011., 1976; Headey et 011.,1985 ;Landua, 1992i Lawton, 1983;Li a ng , 1982; Lohr ,Essex, & Kl ein, 1988;

Mi chalos , 19 8 6 ; Wal tz, 1986; Wheel e r ,19 91 ) .Moreover, severalstudieshave beendesignedto specificallyaddress theTD/ BU distinctionand have reportedfindi ng s supportive of BUeffects.

Headey, Hol ms t r om, and Wearing (198 5 ) explained80.8\

of the variance in wel l-being with a structura l equation model bas e d on a sin glewave (1983) of theAustralia n PerceivedQualityof Li fe pan elsu rvey. Themodel included

42 the followingvariables: five lifesatis fact ion domains;two personality trai ts (se l f - este e m and personalcompetence);

demographic variables(sex,SES)i and four social network variables.

This mode l is characterized as bottom -upinthat domain satisfactionshave directcausallinksto SWB and the remainingvariab lesexer t the i r influence on SWB indirectly throug h domain satisfacti ons. Whenadditionaldirect l inks to SWB were inserted,noincre a s e in thef i tof the model to the data was obtained. TheirTDformulatio n inv o lved persona lity variablesdirectlyaffecting SWB,whichin turn, dotermined le ve l s of dornain satisfactions. The authors repor t edtha t this mode l did notfit thedata as well as their BUformulation.

using LI SREL struc tura l equatio nmodeling , Heade y, Glo wacki, Ho lms t r om , an dWearing(19 8 5) compa re d dyna micau and TOmodels.Their outcome measure involveda combina tion of well-beingand ill-beingindices to represen t PWB. Life eventswer e hypothesizedto effectchange ir.domain satisfactions,Whichcombined to predict change inSWBin their au ecder. In thei r TOmo de l , 1 ite ev entswere purpor t edtodirectly ca usegl obal SWBcha nge, which intur n predictedchange indomain satisfac t ions . The TDmodel fit

OJ the dat a poorl y whereas theBUmo d e l accounted for 70.2\ of thevar iancein SWBchange.

An alter na tive TOmode l asserts thatdoma in sa t isfactio ns aredually influencedby gl oba l 5WB (f r omthe 'to p ') an d life even ts.Unf ortun at ely, theydi d nottest for this TO formula tion. Inste a d , the ydid no t find any direct linksfromlif e events to SWB an dconcluded th a t TOsupport was not evtder re.Recall tha tthey did find strong links between doma in life events andcorresponding changeIn do ma i nsat i s f ac t i ons, but this do e s not invalida te allTO models.

Kra use (199 1)has pr o posed the sametype orTOmodel an dunfortunately, did not test a Itern etiIve TD models. Be s i des demog ra phi c control measures, the varia ble s tested inhis modelswere: object i ve illness; object ive financ ia l loss /he al thsatiSfaction ; financialsat isfa c tio n; and gl obal life sa t isfa c tio n. The elderlysample wa s obtaine d from a singl e wa ve of the Michigansur-veyRese-arch Center's Quality ofLife survey.Fir at, evide nc e was obta i nedfor domain-specifi c stress.Tha tis, financ ial los s an dillness epi s ode s wer e not si gnifica ntly corre la ted and thetes t of a model (M3)Where theselat entconstruc tswere allowed to

44 correlate free lydid not improvethe model'sfi tto the data.

Withrespect tothe TO/BU model comparison, Krause (1991) hypothesizedonly moderatecorrelations (BU) as opposed tohi g h correlations (TO) between financia l satisfaction, he a l t h satisfac tion, and global life satisfaction. At.e st;ofa model (M4)whore structura l disturbance terms associatedwiththeseva r i a b l e s were a r Iowoc to correlate freely revealed a signifi cant improvementin the fit of the modelto the data over thefi t ofmod e l M3 (l!<.001). Neverth e l ess, mode l M3do e s not specificallyaddress dif f e re ntialTo/au predictions so th i s significantimprovement in mod elM4'Sfit totheda t ahas littlebe a ri ng on theTO/ BU distinc tion.

With regardto the strengt hof correlat ions, analyses revealeda correlation of .42 between satisfac tionwith he a l th and satisfac tio nwith finances; .5'2be t we en healt h satisfactionandglobal satisfaction; and .6 2 between financial satisfaction and globa l satisfaction. since Kr a u s e ' s (1991)TD formulation states that domain satisfaction reflects the sale inf l uenceof glo bal satisfaction withdomai neventsdirectl yinfl uenc i ng glob al

45 satisfact i o n , he interp reted the s e correla tio ns as too wea k to suppo rtaTD formula tion of SWB.

~. Alarger number of domai ns shou l dbe ce st.e d in futurewithas manydir ecttests betwee nTOand BU model formula t ions as possible . Th e rea l valueof SEMincreases sUbstanti al l ywi ththenumber- of alte rna tivemode ls whi ch ar e tes t e d (Glymour,Scheines, sprrcee , &Kelly, 1967;

Joreskog S,Sorbam, 1979). Furthermore,some would argue that a superior test of causalityis obtained from longitudi na l dataanalyses, whichallowfor differentialhy po th e s e s bot h withinandacross waves (Stones&Kozma, 1986b) .

To p-DownModel

The modera te long-term stabilityof meanlevel sof SWB hasbe en revi e wedpreviouslywith r-er erenoetote s t-re t e st correlations (Table 1). Ano th e r approac hto the inv est i g at i o n of SWB stab ili tyisto inc lude pri o r SWB in mult ivariate pr e d i c t o r ar r a y s of present well-being.

UtilizingsuchanapproachwithelderlySUbjects, Kozma and Ston es (19 83a ) found an averageof 86% of the explained variance in present SWB to be accounted fQr by la-mon t h priorSWBscores.Th is corresponds to be t we en 45% and 57%

shar ed var i a n ce betwe en ph a s es . Th is finding was replicated

46 in ala t e r study when 51% of phase 2 SWB variancewas exp lai ned by phase 1SWB scores, 18 months prior (stones&

Kozma, 1986a). The best single predictor of current wel l - being has consistently shown to be prior well-being (Chamberlain" Zika, 1992; McNeil, Stones, &Kozma, 198Gb;

Kozma &Stones . 19 8 3a ).

Centralto the TO/SUdebate is theamoun t of variance accounted for by each model.According to Stones andKozma (1989). theminimum r-equir-ed correla tionto support a BU formulation is equal to the square root of the stabil ity coefficientforthe SWB dependent measure. High variabil ity in the psychometricpropertiesof SWBmeasures isev i d e n c e d fr o mth e stability coefficients listed in Table 1, with values ranging from. 38 to.92. If a conservative estimate of .65 is taken as the average of these stability coefficients, the correlation required to suppo rta au mode l wouldbe .8 1. As the authors duly not e, evenmu ltip le co r r el a t i o ns infrequen t l y exceed.6 (a fact tha t ha s n't changed since19891).

Nevertheless, multiplecorrelations which include domainsatisfactionsha ve come close enough tothe re q u i r e d le vel for manyresearche rsto assume eu suppor t.stones and Kozma (1989) elaborateon one possiblere a s o n for th i s

47

moderately high degreeof prediction,or shared variance : Domainsa t is f a cti o nscompr i s e a happines s propen sity componentand a lifedoma in circumsta nc ecomponent.Althol:gh evi dencefor these compo nentsrema ins sc arce, confirmation of this domail" sat i sfa ctioncomponen t structurewouldbe the first alternativeparsimoniousexplanationfor the linear additive BUmodel data.

Dat afro m the Swed i sh /Ad o ptionTwinSt ud y of Agi ng suggeststhat geneticinfluen c es account foras much as)6\

of theva r ia nc e in life satisf action (McClearn ,Pedersen, Plam!n, Nessleroade, &Friberg, 199 1; cited in Bergeman, Plam!n, Pe de r s en, &McClearn, 1991).ThUS, to complicate mat tersfurther, geneti cinfluencesmay med iatesome of the associ ationsbetween SWB and it sco rre l a tes.The finding also points to the fact tha t at le as t a porti onofSWB may be largelyimmutabl e , similarto biologicallY determined traits.

A top-downpropensitytheoryof SWBhasbe e n put forward by stonesand Koz ma (1980, 198 6b). Incomparisonto the TOformulat i onsof Krause (1991) andHeadey,Glowacki, Holms t r o m, and wearing (1985), their propensity formula tion states tha t domainsatisfact ions are directly influencedby