European Journal of PsychologicalAssessmentPsychometric Properties of the 44-Item Version of RyffsPsychological Well-Being Scaleva Kllay and Claudia RusOnline First Publication, April 10, 2013. doi: 10.1027/1015-5759/a000163

CITATIONKllay, ., & Rus, C. (2013, April 10). Psychometric Properties of the 44-Item Version ofRyffs Psychological Well-Being Scale. European Journal of Psychological Assessment.Advance online publication. doi: 10.1027/1015-5759/a000163

. Kllay & C. Rus: Psychometric Prop erties of Ryffs PWBSEuropean Journal of Psychological Assessment 2013 2013 Hogrefe Publishing

Original Article

Psychometric Propertiesof the 44-Item Version of RyffsPsychologicalWell-Being Scale

va Kllay and Claudia Rus

Babes-Bolyai University, Cluj-Napoca, Romania

Abstract. This study examined the factorial validity and reliability (w) of the nonreversed, 44-item version of Ryffs PsychologicalWell-Being Scale (PWBS; Ryff, 1989) on a Romanian convenience sample of 664 participants from the general population. The resultsshowed that the correlated six-factor model presented a relatively good fit, (887) = 2922.85, p < .001, RMSEA = .059, RMSEA 90%CI = [.056; .062], SRMR = .048, CFI = .973, compared to single-factor and independent six-factor models. Based on the CFI value,we found no significant differences between the correlated six-factor and the hierarchical model. Although the correlated six-factor modelhad a relatively good fit, the high correlations between the six latent factors suggest a high overlap among them. Our results indicate thatwell-being can be conceptualized as a second-order factor encompassing six dimensions, represented by autonomy, positive relations,environmental mastery, personal growth, purpose in life, and self-acceptance. The value of the w reliability coefficient of the sixsubscales as well as the whole instrument was above .70. The present study has a practical implication by highlighting the factorialvalidity of a shorter (44-item) instrument, thus shortening the time necessary for data collection.

Keywords: psychological well-being, factorial validity, omega-weighted reliability, psychometrics, confirmatory factor analysis

IntroductionUntil quite recently, psychological research almost exclu-sively focused on the investigation of negative human func-tioning (Huppert, 2010). But if we take into considerationthat health is defined as a state of complete physical, men-tal, and social well-being, i.e., more than just the absenceof illness and malfunctioning (WHO, 1948), then the pro-motion of well-being becomes imperative (Kirkwood,Bond, May, McKeith, & Teh, 2010). Since the dimensionsof human functioning are strongly related and interwoven,having a direction and a goal in life, developing and main-taining positive, high-quality human relationships as wellas striving toward attaining ones potential may all signif-icantly contribute to the maintenance of health and to re-covery from illness (Ryff & Singer, 1998). As Ryff, Singer,and Love (2004) emphasized, the experience of well-be-ing contributes to the effective function of multiple biolog-ical systems, which may help keep the organism from suc-cumbing to disease, or, when illness or adversity occurs,may help promote rapid recovery (p. 1383).

The promotion of well-being becomes even more impor-tant if we consider the rapid social and economic changesoccurring world-wide. Globalization, demographic shifts,increasing competition and pressure for excellence in pro-ductivity, less predictable career paths, increased uncer-

tainty at the workplace, changes in basic norms and valuessystems, etc. (Amundson, 2006), have not only impactedour working lives, but have also carried over their effectsto the domain of personal lives (Weehuizen, 2008). Thesechanges were also experienced in Romania during the lastdecade. Depending on the constant interplay of a myriadof factors, successful adaptation would lead to flourishing(Seligman, 2011). On the other hand, unsuccessful adapta-tion would lead to emptiness and stagnation, elevated lev-els of negative emotions, low levels of positive emotions,also known as languishing (Keyes, 2008), while severemaladaptation leads to different forms of physical and psy-chological disorders (Levenson, 2005). Thus, the last cou-ple of decades have witnessed a significant increase of in-terest in the investigation of well-being (Ryff & Singer,2006), targeting the identification of its constituents, andmapping its characteristics, causes, and consequences(Huppert, Keverne, & Bayliss, 2004).

From its inception, the empirical investigation of well-being had two separate thrusts, concentrating on these twodistinct approaches: research on hedonic well-being (sub-jective well-being, SWB) and eudaimonic well-being (psy-chological well-being, PWB) (Ryan & Deci, 2001). In thehedonic approach, a well-lived life is equated with happi-ness, contentment, and life satisfaction, as experienced onthe subjective level of human functioning (see Diener,

DOI: 10.1027/1015-5759/a000163 2013 Hogrefe Publishing European Journal of Psychological Assessment 2013

1984). As a result, the major target of hedonic psychologybecame the maximization of human pleasure and happiness(Ryan & Deci, 2001). According to the eudaimonic ap-proach, on the other hand, a well-lived life should exceedthe mere pursuit of pleasure and avoidance of pain. Eudai-monia occurs when life activities are most congruent withdeeply held values, and when individuals are fully engagedin the actualization of their potentials (Waterman, 1993).

One of the most influential approaches to eudaimonia isrepresented by Carol Ryffs multidimensional conceptual-ization of PWB. This approach is based on several accountsinvestigating PWB, namely, psychosocial development(Erikson, 1959), the mature personality (Allport, 1961), thefully functioning individual (Rogers, 1961), the need forself-actualization (Maslow, 1968), and others. Ryff (1989)and Ryff and Keyes (1995) aggregated and complementedthe above-mentioned concepts, conceptualizing PWB as aconstruct encompassing the following six dimensions: self-acceptance, positive relations with others, autonomy, envi-ronmental mastery, purpose in life, and personal growth: Self-acceptance is considered an indispensable aspect of

mental health, being both a characteristic and a neces-sary element of self-actualization and optimal humanfunctioning.

Positive relations with others represent the capacity todevelop and maintain warm, affectionate, and trustinghuman relationships a criterion of maturity. Individualswho are able to feel affection for others, who are empa-thetic and capable of maintaining durable friendships at-tain their human potential much easier and recover at afaster pace (Corrigan & Phelan, 2004).

Autonomy is the individuals ability to function free fromthe influence and control of others, to regulate emotionsand behavior from within.

Environmental mastery reflects a persons capacity todesign environments appropriate for their own propen-sities, the ability to manipulate and control complex en-vironments (Ryff, 1989, p. 1071).

Purpose in life represents the capacity to determine and(re)construct meaning in life. It was proven to have aprotective effect in light of adversities and is generallyassociated with positive mental health (Skrabski, Kopp,Rozsa, Rethelyi, & Rahe, 2005).

Personal growth refers to our capacity to realize our po-tentials, to perceive life as a process of continuouschange, challenges, and opportunities, through which wecontinuously grow. This dimension of well-being comesclosest to the core of eudaimonia.

The various conceptualizations of well-being led to specif-ic approaches toward its assessment. One of the most fre-quently used instruments to measure PWB is Ryffs (1989)six-factor scale (PWBS). Various versions of Ryffs PWBShave been used extensively in a variety of samples and set-tings (Abbott et al., 2010). Evidence on the factorial valid-ity and reliability of this instrument was provided by em-pirical studies that used exploratory factor analyses (EFA)

and confirmatory factor analyses (CFA). Most of the stud-ies that used EFAs revealed that the number of the extractedfactors was higher than the number of dimensions of PWBas specified by Ryff (1989). This pattern of results was ob-tained when the analyses were conducted without specify-ing the number of factors to be extracted (Villar, Triad, &Celdrn, 2010) or when the factors were limited to six (Kaf-ka & Kozma, 2002; Triad, Villar, Sol, & Celdrn, 2007).Other studies using EFA fully replicated the existence ofthe six-factor structure (Akin, 2008). However, studies ex-amining structural validity of this instrument using CFAsprovided only contradictory and inconsistent results. Someof these studies empirically supported the correlated six-factor and the second-order model (Akin, 2008; Cheng &Chan, 2005; Clarke, Marshall, Ryff, & Wheaton, 2001;Daz et al., 2006; Lindfors, Berntsson, & Lundberg, 2006;Ryff & Keyes, 1995; van Dierendonck, Daz, Rodrguez-Carvajal, Blanco, & Moreno-Jimnez, 2008). On the otherhand, some of them revealed the six-factor model proposedby Ryff (1989) only after having excluded items from theanalyses (Kitamura et al., 2004). Moreover, some studiesdid not empirically provide a total support for the six-factormodel of PWB (Abbott et al., 2006; Burns & Machin, 2009;Springer & Hauser, 2006; Triad et al., 2007; van Dieren-donck, 2005).

Because of the growing interest for studying well-beingin cross-cultural settings, it is vital to obtain more informa-tion on the validity of Ryffs measure in different countriesand, especially, in different cultures (van Dierendock et al.,2008). Moreover, it is known that culture affects people ina variety of basic psychological domains, such as self-con-cept, interpersonal relationships, and PWB (Chen, 2008;Lehman, Chiu, & Schaller, 2004).

Recently, data published by the Romanian Research In-stitute of Quality of Life (MOrginean & Precupetu, 2010)discovered a serious decline in the quality of several lifedomains in the Romanian population. Since PWB may sig-nificantly contribute to the development and maintenanceof quality of life, and there are no validated, well-knowninstruments targeting the assessment of PWB in Romaniancontext, we thought it would be useful to test the psycho-metric properties of a well-functioning instrument of PWB,such as Ryffs scale. The use of such a scale may simulta-neously permit the cross-cultural comparison of well-be-ing, necessary for the development of community policiesfor enhancing the quality of life of the Romanian popula-tion.

To date, no study has been conducted in Romania ana-lyzing the psychometric properties (structural validity andreliability) of this instrument, based on the results providedby CFAs. Considering that reverse-scored items influencethe psychometric properties of the assessment instruments(Lindwall et al., 2012), our study examined the factorialvalidity and the w reliability coefficient of the nonre-versed, 44-item of Ryffs original 84-item PWB scale. Wechose this coefficient because the literature suggests thatw is more appropriate to be computed in the case of mul-

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tidimensional instruments comprising a superordinate con-struct, analyzed through structural equation modeling (Ed-wards, 2001, 2011).

Materials andMethods

Participants

This study included a convenience sample of 664 healthyparticipants, 246 (37.04%) male and 418 (62.95%) female,from the general population, residing in the main regionsof Romania. Ages ranged from 19 to 65 years, mean agebeing 39 years (SD = 8.53 years). As to residence, 500(75.30%) reported living in an urban and 155 (23.34%) arural environment.

Instrument

We used Ryffs PWBS (Ryff, 1989) translated into Roma-nian. The scale was backtranslated into English by an autho-rized translator. Item inconsistencies were discussed by threepsychologists and a statistician. Minor changes were imple-mented in order to maintain a simple and clear formulationof items, consistent with the Romanian language in use.

The nonreversed, 44 items from Ryffs PWBS (Ryff,1989) were rated on a 6-point Likert scale ranging from 1(= strongly disagree) to 6 (= strongly agree). The itemswere distributed in six subscales: Autonomy = 7 items (e.g., I am not afraid to voice my

opinions, even when they are in opposition to the opin-ions of most people),

Environmental mastery = 8 items (e.g., In general, I feelin charge of the situation in which I live),

Personal growth = 8 items (e.g., In general, I feel thatI continue to learn more about myself as time goes by),

Positive relations with others = 7 items (e.g., Most peo-ple see me as loving and affectionate),

Purpose in life = 7 items (e.g., I feel good when I thinkof what Ive done in the past and what I hope to do inthe future),

Self-acceptance = 7 items (e.g., When I look at the storyof my life, I am pleased with how things have turnedout).

Higher scores on each scale indicated greater well-beingon each dimension.

Procedure

All participants agreed to voluntarily take part in this studyand signed an informed consent of participation. The in-strument was administered in a paper-and-pencil format.

Data Analysis

First, the means, standard deviations, skewness, and kurto-sis values of the items were computed. Second, the factorialvalidity of the instrument was examined through confirma-tory factor analysis (CFA) using LISREL 8.8 (Jreskog &Srbom, 1993). CFA was used to test the a-priori six-factorstructure of the instrument used. This factorial structurewas compared with other three competing models: hierar-chical, single-factor, and uncorrelated six-factor model.

The global fit of the models was assessed using sta-tistics, the comparative fit index (CFI), the root meansquared error of approximation (RMSEA), its associated90% confidence interval (90% CI), and standardized rootmean square residual (SRMR). In their combinatorial rule,Hu and Bentler (1999) argued that relatively good fittingmodels should have two of three indices that met the min-imum cutoffs: CFI .95, RMSEA .06, and SRMR .08.

The comparison of the nested models was based on 2,CFI, and Akaikes information criterion (AIC). A valueof CFI greater than .01 indicates that the models are sig-nificantly different (Cheung & Rensvold, 2002). The non-nested models were compared based only on their CFIand AIC. The model with the highest CFI and the lowestAIC fits best. The weighted-omega reliability coefficient(w) was computed based on standardized estimated pa-rameters from CFA (Bacon, Sauer, & Young, 1995) andcompared to the cutoff value of .70 (Lance, Butts, & Mi-chels, 2006).

Results

Means, standard deviations, skewness, kurtosis, reliability,and factor loading of the correlated six-factor and hierar-chical models are presented in Table 1. Considering thatthe value of the relative multivariate kurtosis of the itemsincluded in the analyses was below 3 (1.23; Pellegrini &Scandura, 2005), the maximum likelihood estimationmethod was used.

The results indicated that the correlated six-factor modelpresented a relatively good fit to the data, (887) =2922.85, p < .001, RMSEA = .059, RMSEA 90% CI =[.056; .062], SRMR = .048, CFI = .973 (Table 2).

The factor loadings ranged from .35 to .76. The w re-liability coefficient of the subscales was greater than .70.The correlations between the six factors indicated that theyshare a high degree of variance. They ranged from .55 to1.00 (Table 3).

Although the correlated six-factor model presented a rel-atively good fit to the data it was not the only model thatfit the data adequately. According to Hu and Bentlers(1999) combinatorial rule, the hierarchical and single-fac-tor model had at least two indicators (SRMR .08, CFI .95) that indicated the relatively good fit to the data. But

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Table 1. Means, standard deviations, skewness, kurtosis, reliability and completely standardized factor loadings for thecorrelated six-factor and hierarchical models (N = 664)

Model 1 Model 2Scale items Mean SD Skewness Kurtosis Autonomy (.88) .72 (.88)

Item1 (#2) 4.75 1.38 .46 .73 .52 .52Item2 (#3) 4.30 1.50 .22 .71 .35 .36Item3 (#5) 4.71 1.36 .42 .70 .48 .48Item4 (#7) 4.53 1.39 .33 .71 .51 .51Item5 (#9) 4.78 1.13 .35 .54 .66 .65Item6 (#12) 4.65 1.34 .34 .68 .54 .54Item7 (#14) 5.00 1.21 .60 .61 .56 .56

Environmental mastery (.91) .97 (.91)Item1 (#1) 4.77 1.12 .32 .50 .66 .66Item2 (#4) 4.80 1.13 .34 .50 .61 .61Item3 (#6) 4.84 1.33 .54 .69 .42 .42Item4 (#7) 4.75 1.29 .40 .64 .60 .61Item5 (#9) 4.78 1.13 .35 .54 .65 .65Item6 (#10) 4.61 1.21 .28 .53 .68 .68Item7 (#12) 4.64 1.17 .27 .50 .71 .72Item8 (#14) 4.84 1.34 .51 .70 .65 .65

Personal growth (.92) .90 (.92)Item1 (#2) 4.87 1.16 .44 .62 .56 .57Item2 (#3) 4.67 1.29 .36 .63 .47 .47Item3 (#5) 4.91 1.12 .46 .60 .45 .43Item4 (#7) 4.95 1.35 .65 .66 .43 .42Item5 (#8) 5.09 1.08 .64 .55 .76 .77Item6 (#9) 5.07 1.03 .55 .56 .78 .79Item7 (#11) 5.24 1.04 .80 .41 .67 .66Item8 (#12) 5.14 0.99 .60 .55 .75 .75

Positive relations with others (.89) .76 (.89)Item1 (#1) 4.81 1.06 .31 .44 .61 .61Item2 (#4) 5.38 1.09 .93 .26 .51 .50Item3 (#5) 5.12 1.06 .63 .53 .53 .52Item4 (#7) 4.75 1.29 .40 .64 .60 .59Item5 (#9) 4.83 1.07 .36 .54 .68 .68Item6 (#12) 4.81 1.31 .46 .70 .56 .57Item7 (#14) 4.54 1.28 .26 .61 .50 .51

Purpose in life (.91) 1.00 (.91)Item1 (#1) 5.14 1.07 .63 .50 .60 .61Item2 (#4) 4.98 1.18 .56 .63 .68 .69Item3 (#8) 4.97 1.22 .60 .62 .58 .58Item4 (#9) 4.94 1.11 .46 .59 .73 .73Item5 (#10) 4.51 1.49 .36 .79 .37 .38Item6 (#12) 4.83 1.28 .48 .70 .72 .73Item7 (#13) 4.70 1.32 .38 .69 .77 .75

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the results showed that the correlated six-factor and the hi-erarchical models presented a better fit compared to thesingle-factor model. Also, there was no significant differ-ence between the CFI values of the correlated six-factorand hierarchical model, although the correlated six-factormodel present slightly better fit indicators than the hierar-chical model.

Discussion

The study of PWB becomes imperative since human soci-ety is presently undergoing significant changes. Dependingon the culture, these changes may exert different influencesin PWB. Nevertheless, there may be some dimensions ofPWB that are cross-culturally resistant, such as the need for

positive relations with others, purpose in life, and personalgrowth (Lent, 2004). The rapid changes to which Romaniais being exposed to require the investigation of those areasof well-being that are affected and of those that remain in-tact. At the same time, the concept of well-being balancesthe assessments concentrating on deficits (mental ill-health) with the possibility of measuring positive humanfunctioning. Thus, our inquiries began by testing the psy-chometric properties of the best-known PWB scale in termsof construct validity and reliability.

The analysis of the factorial validity andw internal con-sistency coefficient of a short version of Ryffs PWB scaleon a Romanian sample provided results that are similar tothose reported in the studies that examined other versionsof this instrument (e.g., Ryff & Keyes, 1995). Although thecorrelated six-factor model had a relatively good fit, thehigh correlations between personal growth, positive rela-tions with others, purpose in life, and self-acceptance sug-gest a high overlap between these dimensions of PWB.These results are similar to those provided by other studiesthat did not empirically provide a total support for the six-factor model of PWB (Abbott et al., 2006, 2010; Kafka &Kozma, 2002; Toms, Sancho, Melndez, & Mayordomo,2012). As literature suggested, these results may be due tothe specificity of this instrument, its underlying theory, orboth (Springer, Hauser, & Freese, 2006). Since it is notabsolutely clear what these latent factors represent, we rec-ommend further and more detailed analyses of the psycho-metric properties of this instrument. Given that factorial

Model 1 Model 2Scale items Mean SD Skewness Kurtosis Self-acceptance (.92) .95 (.92)

Item1 (#1) 4.74 1.29 .37 .60 .73 .73Item2 (#2) 4.82 1.20 .41 .59 .73 .74Item3 (#5) 4.59 1.21 .26 .50 .68 .68Item4 (#6) 4.54 1.34 .29 .67 .46 .47Item5 (#8) 4.88 1.22 .49 .65 .81 .82Item6 (#12) 4.75 1.49 .39 .81 .61 .60Item7 (#13) 4.68 1.32 .38 .69 .72 .72

Psychosocial Well-Being (.99)Notes. SD = standard deviation; = factor loading; ( ) =w reliability coefficient. Model 1 = correlated six-factor; Model 2 = hierarchical model.(#) = the number of item in the original scale. PWB = Psychological well-being.

Table 1. continued

Table 2. CFA fit indexes of the examined factorial structures (N = 664)CFA model df df RMSEA RMSEA 90% CI SRMR CFI AICModel 1: Correlated 6-factor 2922.85*** 887 .059 [.056; .062] .048 .973 3128.85Model 2: Hierarchical model 3067.43*** 897 144.58*** 10 .060 [.058; .063] .050 .971 3253.43Model 3: Single-factor model 4379.59*** 902 1456.74*** 15 .076 [.074; .079] .055 .960 4555.59Model 4: Uncorrelated 6-factor model 6876.34*** 902 3953.49*** 15 .100 [.097; .102] .285 .926 7052.34Notes. CFA = confirmatory factor analysis; = chi-squared; df = degrees of freedom; = difference in chi-squared; df = difference indegrees of freedom; RMSEA = root mean squared error of approximation; RMSEA 90% CI = 90% confidence interval of root mean squarederror of approximation; SRMR = standardized root mean square residual; CFI = comparative fit index; AIC = Akaikes information criterion.***p < .001.

Table 3. Interfactor correlations for the correlated six-factormodel (N = 664)

Factor 1 2 3 4 5 61. Autonomy 12. Environmental mastery .55 13. Personal growth .70 .72 14. Positive relations with others .78 .73 .87 15. Purpose in life .75 .69 1.00 .91 16. Self-acceptance .73 .66 .92 .81 .99 1

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validity is only one aspect of the construct validity of aninstrument, future studies should also examine other typesof validity, such as convergent, divergent, criterion, andcontent validity (Urbina, 2004) of Ryffs PWBS in Roma-nian context.

The interpretation of our results must take into accountthat our study was not conducted on a nationally represen-tative sample. Future studies using representative samplesfor the Romanian population could provide more relevantinformation about the factorial structure of Ryffs PWBSand implicitly, about PWB as a subjacent factor of positiverelations, autonomy, environmental mastery, personalgrowth, purpose in life, and self-acceptance. However, asobtained in this study, not all of the PWBS subscales formdistinct factors. Even if, from a practical point of view, ashortened valid and reliable instrument would permit thereduction of temporal costs associated to data collection,the use of this scale without sufficient clarity on its factorialstructure might have negative impact on the validity ofPWB assessments.

In sum, this study extends the knowledge related to thepsychometric properties of Ryffs PWBS, by evincing thatPWB measured with this instrument may be conceptual-ized as a second-order factor. Consequently, we emphasizethe need of more studies aiming to examine how this in-strument works in other cultures than that in which it wasdeveloped.

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Date of acceptance: January 18, 2013Published online: April 10, 2013

va KllayDepartment of PsychologyFaculty of Psychology and Educational SciencesBabe5-Bolyai University37 Republicii Street400015 Cluj-NapocaRomaniaTel. +40 744345639E-mail evakallay@gmail.com

. Kllay & C. Rus: Psychometric Properties of Ryffs PWBS 7

2013 Hogrefe Publishing European Journal of Psychological Assessment 2013