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Psychometric Properties of the 44-Item Version of Ryff's Psychological Well- Being Scale

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Psychometric Properties of the 44-Item Version of Ryff’s Psychological Well-Being Scale

Éva Kállay and Claudia Rus

Babes-Bolyai University, Cluj-Napoca, Romania

Abstract.This study examined the factorial validity and reliability (Ωw) of the nonreversed, 44-item version of Ryff’s Psychological Well-Being Scale (PWBS; Ryff, 1989) on a Romanian convenience sample of 664 participants from the general population. The results showed that the correlated six-factor model presented a relatively good fit,χ²(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 theΔCFI value, we found no significant differences between the correlated six-factor and the hierarchical model. Although the correlated six-factor model had a relatively good fit, the high correlations between the six latent factors suggest a high overlap among them. Our results indicate that well-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 Ωwreliability coefficient of the six subscales as well as the whole instrument was above .70. The present study has a practical implication by highlighting the factorial validity 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

Introduction

Until quite recently, psychological research almost exclu- sively focused on the investigation of negative human functioning (Huppert, 2010). But if we take into consideration that health is defined as a state of complete physical, mental, and social well-being, i.e., more than just the absence of illness and malfunctioning (WHO, 1948), then the promotion of well-being becomes imperative (Kirkwood, Bond, May, McKeith, & Teh, 2010). Since the dimensions of human functioning are strongly related and interwoven, having a direction and a goal in life, developing and maintaining positive, high-quality human relationships as well as striving toward attaining one’s potential may all signif- icantly contribute to the maintenance of health and to recovery from illness (Ryff & Singer, 1998). As Ryff, Singer, and Love (2004) emphasized, “the experience of well-being 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 important if we consider the rapid social and economic changes occurring 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 values systems, etc. (Amundson, 2006), have not only impacted our working lives, but have also carried over their effects to the domain of personal lives (Weehuizen, 2008). These changes were also experienced in Romania during the last decade. Depending on the constant interplay of a myriad of factors, successful adaptation would lead to flourishing (Seligman, 2011). On the other hand, unsuccessful adaptation would lead to emptiness and stagnation, elevated levels of negative emotions, low levels of positive emotions, also known as languishing (Keyes, 2008), while severe maladaptation leads to different forms of physical and psychological disorders (Levenson, 2005). Thus, the last cou- ple of decades have witnessed a significant increase of interest in the investigation of well-being (Ryff & Singer, 2006), targeting the identification of its constituents, and mapping 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 two distinct approaches: research on hedonic well-being (subjective well-being, SWB) and eudaimonic well-being (psychological well-being, PWB) (Ryan & Deci, 2001). In the hedonic approach, a well-lived life is equated with happiness, contentment, and life satisfaction, as experienced on the subjective level of human functioning (see Diener,

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1984). As a result, the major target of hedonic psychology became the maximization of human pleasure and happiness (Ryan & Deci, 2001). According to the eudaimonic approach, on the other hand, a well-lived life should exceed the mere pursuit of pleasure and avoidance of pain. Eudai- monia occurs when life activities are most congruent with deeply held values, and when individuals are fully engaged in the actualization of their potentials (Waterman, 1993).

One of the most influential approaches to eudaimonia is represented by Carol Ryff’s multidimensional conceptual- ization of PWB. This approach is based on several accounts investigating PWB, namely, psychosocial development (Erikson, 1959), the mature personality (Allport, 1961), the fully functioning individual (Rogers, 1961), the need for self-actualization (Maslow, 1968), and others. Ryff (1989) and Ryff and Keyes (1995) aggregated and complemented the above-mentioned concepts, conceptualizing PWB as a construct encompassing the following six dimensions: self- acceptance, positive relations with others, autonomy, environmental mastery, purpose in life, and personal growth:

– Self-acceptanceis considered an indispensable aspect of mental health, being both a characteristic and a necessary element of self-actualization and optimal human functioning.

– Positive relations with othersrepresent the capacity to develop and maintain warm, affectionate, and trusting human relationships – a criterion of maturity. Individuals who 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 a faster pace (Corrigan & Phelan, 2004).

– Autonomyis the individual’s ability to function free from the influence and control of others, to regulate emotions and behavior from within.

– Environmental mastery reflects a person’s capacity to design environments appropriate for their own propen- sities, the ability to “manipulate and control complex environments” (Ryff, 1989, p. 1071).

– Purpose in liferepresents the capacity to determine and (re)construct meaning in life. It was proven to have a protective effect in light of adversities and is generally associated with positive mental health (Skrabski, Kopp, Rozsa, Rethelyi, & Rahe, 2005).

– Personal growthrefers to our capacity to realize our potentials, to perceive life as a process of continuous change, challenges, and opportunities, through which we continuously grow. This dimension of well-being comes closest 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 Ryff’s (1989) six-factor scale (PWBS). Various versions of Ryff’s PWBS have been used extensively in a variety of samples and settings (Abbott et al., 2010). Evidence on the factorial validity and reliability of this instrument was provided by empirical studies that used exploratory factor analyses (EFA)

and confirmatory factor analyses (CFA). Most of the studies that used EFAs revealed that the number of the extracted factors was higher than the number of dimensions of PWB as specified by Ryff (1989). This pattern of results was obtained when the analyses were conducted without specify- ing the number of factors to be extracted (Villar, Triadó, &

Celdrán, 2010) or when the factors were limited to six (Kaf- ka & Kozma, 2002; Triadó, Villar, Solé, & Celdrán, 2007).

Other studies using EFA fully replicated the existence of the six-factor structure (Akin, 2008). However, studies ex- amining structural validity of this instrument using CFAs provided only contradictory and inconsistent results. Some of these studies empirically supported the correlated six- factor and the second-order model (Akin, 2008; Cheng &

Chan, 2005; Clarke, Marshall, Ryff, & Wheaton, 2001;

Díaz et al., 2006; Lindfors, Berntsson, & Lundberg, 2006;

Ryff & Keyes, 1995; van Dierendonck, Díaz, Rodríguez- Carvajal, Blanco, & Moreno-Jiménez, 2008). On the other hand, some of them revealed the six-factor model proposed by Ryff (1989) only after having excluded items from the analyses (Kitamura et al., 2004). Moreover, some studies did not empirically provide a total support for the six-factor model of PWB (Abbott et al., 2006; Burns & Machin, 2009;

Springer & Hauser, 2006; Triadó et al., 2007; van Dieren- donck, 2005).

Because of the growing interest for studying well-being in cross-cultural settings, it is vital to obtain more information on the validity of Ryff’s measure in different countries and, especially, in different cultures (van Dierendock et al., 2008). Moreover, it is known that culture affects people in a variety of basic psychological domains, such as self-concept, 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 life domains in the Romanian population. Since PWB may sig- nificantly contribute to the development and maintenance of quality of life, and there are no validated, well-known instruments targeting the assessment of PWB in Romanian context, we thought it would be useful to test the psychometric properties of a well-functioning instrument of PWB, such as Ryff’s scale. The use of such a scale may simulta- neously permit the cross-cultural comparison of well-being, necessary for the development of community policies for enhancing the quality of life of the Romanian population.

To date, no study has been conducted in Romania ana- lyzing the psychometric properties (structural validity and reliability) of this instrument, based on the results provided by CFAs. Considering that reverse-scored items influence the psychometric properties of the assessment instruments (Lindwall et al., 2012), our study examined the factorial validity and the Ωw reliability coefficient of the nonreversed, 44-item of Ryff’s original 84-item PWB scale. We chose this coefficient because the literature suggests that Ωwis more appropriate to be computed in the case of mul- 16 É. Kállay & C. Rus: Psychometric Properties of Ryff’s PWBS

European Journal of Psychological Assessment2014; Vol. 30(1):15–21 © 2013 Hogrefe Publishing This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

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

Materials and Methods

Participants

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

Instrument

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

The nonreversed, 44 items from Ryff’s PWBS (Ryff, 1989) were rated on a 6-point Likert scale ranging from 1 (= strongly disagree) to 6 (= strongly agree). The items were 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 opinions of most people”),

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

– Personal growth = 8 items (e.g., “In general, I feel that I 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 think of what I’ve done in the past and what I hope to do in the future”),

– Self-acceptance = 7 items (e.g., “When I look at the story of my life, I am pleased with how things have turned out”).

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

Procedure

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

Data Analysis

First, the means, standard deviations, skewness, and kurtosis values of the items were computed. Second, the factorial validity of the instrument was examined through confirmatory factor analysis (CFA) using LISREL 8.8 (Jöreskog &

Sörbom, 1993). CFA was used to test the a-priori six-factor structure of the instrument used. This factorial structure was compared with other three competing models: hierarchical, single-factor, and uncorrelated six-factor model.

The global fit of the models was assessed usingχ² sta- tistics, the comparative fit index (CFI), the root mean squared error of approximation (RMSEA), its associated 90% confidence interval (90% CI), and standardized root mean square residual (SRMR). In their combinatorial rule, Hu and Bentler (1999) argued that relatively good fitting models 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 onΔχ², ΔCFI, and Akaike’s information criterion (AIC). A value ofΔCFI greater than .01 indicates that the models are sig- nificantly different (Cheung & Rensvold, 2002). The non- nested models were compared based only on theirΔCFI and AIC. The model with the highest CFI and the lowest AIC fits best. The weighted-omega reliability coefficient (Ω^w) was computed based on standardized estimated pa- rameters from CFA (Bacon, Sauer, & Young, 1995) and compared 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 hierarchical models are presented in Table 1. Considering that the value of the relative multivariate kurtosis of the items included in the analyses was below 3 (1.23; Pellegrini &

Scandura, 2005), the maximum likelihood estimation method was used.

The results indicated that the correlated six-factor model presented a relatively good fit to the data, χ²(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. TheΩwre- liability coefficient of the subscales was greater than .70.

The correlations between the six factors indicated that they share a high degree of variance. They ranged from .55 to 1.00 (Table 3).

Although the correlated six-factor model presented a relatively good fit to the data it was not the only model that fit the data adequately. According to Hu and Bentler’s (1999) combinatorial rule, the hierarchical and single-factor model had at least two indicators (SRMR≤.08, CFI≥ .95) that indicated the relatively good fit to the data. But This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

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

Model 1 Model 2

Scale items Mean SD Skewness Kurtosis λ λ

Autonomy (.88) .72 (.88)

Item1 (#2) 4.75 1.38 –.46 –.73 .52 .52

Item2 (#3) 4.30 1.50 –.22 –.71 .35 .36

Item3 (#5) 4.71 1.36 –.42 –.70 .48 .48

Item4 (#7) 4.53 1.39 –.33 –.71 .51 .51

Item5 (#9) 4.78 1.13 –.35 –.54 .66 .65

Item6 (#12) 4.65 1.34 –.34 –.68 .54 .54

Item7 (#14) 5.00 1.21 –.60 –.61 .56 .56

Environmental mastery (.91) .97 (.91)

Item1 (#1) 4.77 1.12 –.32 –.50 .66 .66

Item2 (#4) 4.80 1.13 –.34 –.50 .61 .61

Item3 (#6) 4.84 1.33 –.54 –.69 .42 .42

Item4 (#7) 4.75 1.29 –.40 –.64 .60 .61

Item5 (#9) 4.78 1.13 –.35 –.54 .65 .65

Item6 (#10) 4.61 1.21 –.28 –.53 .68 .68

Item7 (#12) 4.64 1.17 –.27 –.50 .71 .72

Item8 (#14) 4.84 1.34 –.51 –.70 .65 .65

Personal growth (.92) .90 (.92)

Item1 (#2) 4.87 1.16 –.44 –.62 .56 .57

Item2 (#3) 4.67 1.29 –.36 –.63 .47 .47

Item3 (#5) 4.91 1.12 –.46 –.60 .45 .43

Item4 (#7) 4.95 1.35 –.65 –.66 .43 .42

Item5 (#8) 5.09 1.08 –.64 –.55 .76 .77

Item6 (#9) 5.07 1.03 –.55 –.56 .78 .79

Item7 (#11) 5.24 1.04 –.80 –.41 .67 .66

Item8 (#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 .61

Item2 (#4) 5.38 1.09 –.93 –.26 .51 .50

Item3 (#5) 5.12 1.06 –.63 –.53 .53 .52

Item4 (#7) 4.75 1.29 –.40 –.64 .60 .59

Item5 (#9) 4.83 1.07 –.36 –.54 .68 .68

Item6 (#12) 4.81 1.31 –.46 –.70 .56 .57

Item7 (#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 .61

Item2 (#4) 4.98 1.18 –.56 –.63 .68 .69

Item3 (#8) 4.97 1.22 –.60 –.62 .58 .58

Item4 (#9) 4.94 1.11 –.46 –.59 .73 .73

Item5 (#10) 4.51 1.49 –.36 –.79 .37 .38

Item6 (#12) 4.83 1.28 –.48 –.70 .72 .73

Item7 (#13) 4.70 1.32 –.38 –.69 .77 .75

18 É. Kállay & C. Rus: Psychometric Properties of Ryff’s PWBS

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the results showed that the correlated six-factor and the hierarchical models presented a better fit compared to the single-factor model. Also, there was no significant difference between the CFI values of the correlated six-factor and hierarchical model, although the correlated six-factor model present slightly better fit indicators than the hierarchical model.

Discussion

The study of PWB becomes imperative since human society is presently undergoing significant changes. Depending on the culture, these changes may exert different influences in PWB. Nevertheless, there may be some dimensions of PWB that are cross-culturally resistant, such as the need for

positive relations with others, purpose in life, and personal growth (Lent, 2004). The rapid changes to which Romania is being exposed to require the investigation of those areas of well-being that are affected and of those that remain in- tact. At the same time, the concept of well-being balances the assessments concentrating on deficits (mental ill- health) with the possibility of measuring positive human functioning. Thus, our inquiries began by testing the psychometric properties of the best-known PWB scale in terms of construct validity and reliability.

The analysis of the factorial validity andΩ^winternal con- sistency coefficient of a short version of Ryff’s PWB scale on a Romanian sample provided results that are similar to those reported in the studies that examined other versions of this instrument (e.g., Ryff & Keyes, 1995). Although the correlated six-factor model had a relatively good fit, the high correlations between personal growth, positive relations with others, purpose in life, and self-acceptance suggest a high overlap between these dimensions of PWB.

These results are similar to those provided by other studies that did not empirically provide a total support for the six- factor model of PWB (Abbott et al., 2006, 2010; Kafka &

Kozma, 2002; Tomás, Sancho, Meléndez, & Mayordomo, 2012). As literature suggested, these results may be due to the specificity of this instrument, its underlying theory, or both (Springer, Hauser, & Freese, 2006). Since it is not absolutely clear what these latent factors represent, we rec- ommend further and more detailed analyses of the psychometric properties of this instrument. Given that factorial

Model 1 Model 2

Scale items Mean SD Skewness Kurtosis λ λ

Self-acceptance (.92) .95 (.92)

Item1 (#1) 4.74 1.29 –.37 –.60 .73 .73

Item2 (#2) 4.82 1.20 –.41 –.59 .73 .74

Item3 (#5) 4.59 1.21 –.26 –.50 .68 .68

Item4 (#6) 4.54 1.34 –.29 –.67 .46 .47

Item5 (#8) 4.88 1.22 –.49 –.65 .81 .82

Item6 (#12) 4.75 1.49 –.39 –.81 .61 .60

Item7 (#13) 4.68 1.32 –.38 –.69 .72 .72

Psychosocial Well-Being (.99)

Notes. SD= standard deviation;λ= factor loading; ( ) =Ωwreliability 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 χ² df Δχ² Δdf RMSEA RMSEA 90% CI SRMR CFI AIC

Model 1: Correlated 6-factor 2922.85*** 887 – – .059 [.056; .062] .048 .973 3128.85

Model 2: Hierarchical model 3067.43*** 897 144.58*** 10 .060 [.058; .063] .050 .971 3253.43 Model 3: Single-factor model 4379.59*** 902 1456.74*** 15 .076 [.074; .079] .055 .960 4555.59 Model 4: Uncorrelated 6-factor model 6876.34*** 902 3953.49*** 15 .100 [.097; .102] .285 .926 7052.34 Notes.CFA= confirmatory factor analysis;χ² = chi-squared;df= degrees of freedom;Δχ² = difference in chi-squared;Δdf= difference in degrees of freedom; RMSEA = root mean squared error of approximation; RMSEA 90% CI = 90% confidence interval of root mean squared error of approximation; SRMR = standardized root mean square residual; CFI = comparative fit index; AIC = Akaike’s information criterion.

***p< .001.

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

Factor 1 2 3 4 5 6

1. Autonomy 1

2. Environmental mastery .55 1

3. Personal growth .70 .72 1

4. Positive relations with others .78 .73 .87 1 5. Purpose in life .75 .69 1.00 .91 1 6. Self-acceptance .73 .66 .92 .81 .99 1

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validity is only one aspect of the construct validity of an instrument, future studies should also examine other types of validity, such as convergent, divergent, criterion, and content validity (Urbina, 2004) of Ryff’s PWBS in Roma- nian context.

The interpretation of our results must take into account that our study was not conducted on a nationally representative sample. Future studies using representative samples for the Romanian population could provide more relevant information about the factorial structure of Ryff’s PWBS and implicitly, about PWB as a subjacent factor of positive relations, autonomy, environmental mastery, personal growth, purpose in life, and self-acceptance. However, as obtained in this study, not all of the PWBS subscales form distinct factors. Even if, from a practical point of view, a shortened valid and reliable instrument would permit the reduction of temporal costs associated to data collection, the use of this scale without sufficient clarity on its factorial structure might have negative impact on the validity of PWB assessments.

In sum, this study extends the knowledge related to the psychometric properties of Ryff’s PWBS, by evincing that PWB measured with this instrument may be conceptualized as a second-order factor. Consequently, we emphasize the need of more studies aiming to examine how this instrument works in other cultures than that in which it was developed.

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

Éva Kállay

Department of Psychology

Faculty of Psychology and Educational Sciences Babe5-Bolyai University

37 Republicii Street 400015 Cluj-Napoca Romania

Tel. +40 744345639

E-mail [email protected]

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