Investigating Validity Evidence of the Satisfaction with Life Scale Adapted for Children

This study introduces the Satisfaction with Life Scale adapted for Children (SWLS-C) and presents psychometric findings regarding its validation. The SWLS-C was adapted from the Satisfaction with Life Scale (SWLS; Diener et al. 1985), which is one of the most commonly used measures to assess satisfaction with life in adults. Three subject matter experts adapted the SWLS by changing the wording of the item stem and response format in order to make it more understandable for children. A stratified random sample of 1,233 students (48% girls) in grades 4–7 (mean age 11 years and 7 months) provided data on the SWLS-C and measures of optimism, self-concept, self-efficacy, depression, emphatic concern, and perspective taking. The SWLS-C demonstrated a unidimensional factor structure and high internal consistency. Furthermore, differential item functioning and differential scale functioning analyses indicated that the SWLS-C measures satisfaction with life in the same way for different groups of children (i.e., with regard to gender, first language learned at home—English vs. other language(s) than English—and across different grades) at the item and at the scale level. Associations between scores on the SWLS-C and demographic variables were statistically non-significant or of small effect size. In addition, the SWLS-C showed evidence of convergent and discriminant validity in relation to the other measures. Our results indicate that the SWLS-C is a psychometrically sound instrument that demonstrated evidence of construct validity for this age group. Limitations and future directions are discussed.     

Understanding and Using Mediators and Moderators

Mediation and moderation are two theories for refining and understanding a causal relationship. Empirical investigation of mediators and moderators requires an integrated research design rather than the data analyses driven approach often seen in the literature. This paper described the conceptual foundation, research design, data analysis, as well as inferences involved in a mediation and/or moderation investigation in both experimental and non-experimental (i.e., correlational) contexts. The essential distinctions between the investigation of mediators and moderators were summarized and juxtaposed in an example of a causal relationship between test difficulty and test anxiety. In addition, the more elaborate models, moderated mediation and mediated moderation, the use of structural equation models, and the problems with model misspecification were discussed conceptually.

An Investigation of Measures of Modern and Old-Fashioned Sexism

Working from the Principle of Beneficence we make the case that there is a need for adequate measures of sexism in men and women. Swim, Aikin, Hall and Hunter (1995) suggest that modern sexism represents a constellation of beliefs in which individuals: (a) disavow women's present-day discrimination; (b) reject women's demands for political and economic power; and (c) disapprove of policies designed to promote gender equality. To assess this construct, Swim et al. (1995) developed the Modern Sexism Scale (MSS), and to date, few studies have assessed its reliability and factor structure. Using data from 187 Canadian participants, confirmatory factor analysis was used to assess the unidimensionality of the MSS and Swim and associates' (1995) Old-Fashioned Sexism Scale (OFSS). Results do not support Swim et al.'s conceptualization of modern sexism as a unidimensional construct; however, the OFSS fit a unidimensional model. The implications of these findings are discussed.     

Psychometric Evaluation of the Hebrew Language Version of the Satisfaction with Life Scale

The satisfaction with life scale (SWLS) is a widely accepted and widely used tool for measuring well-being. Although its potential as a cross-cultural index is recognized, an introduction and systematic validation of the Hebrew version is needed. Thus, the purpose of this study is: (1) to describe the process of developing the Hebrew version of the SWLS, and (2) to examine its construct validity as well as its internal consistency. Four hundred and eighty seven working adults completed the following self reported Hebrew language versions of the: (1) SWLS, (2) positive affect and negative affect scales (PANAS), and (3) the self-rated health (SRH) scale. In addition, as way of gathering additional evidence of validity, the SWLS was completed by proxy (i.e., each participant’s life partner or significant other). Confirmatory factor analysis supported a single-factor structure with significant correlations between the SWLS and the rest of the measures—PANAS scores, the SRH scores as well as the SWLS scores as measured by proxy. In addition, item-analysis supports the internal consistency of the scale. The Hebrew version of the SWLS is a valid and reliable scale and can be utilized in the Israeli context.     

A Note on the Dimensionality of Quality of Life Scales: An Illustration with the Satisfaction with Life Scale (SWLS)

A case is made that measures used in quality of life and happiness research will be essentially unidimensional: inherently tapping minor dimensions. This is illustrated using Diener’s Satisfaction with Life Scale (SWLS). It is shown that the SWLS does not meet the standard of strict unidimensionality, but that the interpretation of the total scale score is not compromised because the additional dimensions are relatively minor. In the context of the example, a multi-step strategy is described that allows researchers to test for essential unidimensionality. Throughout the article, essential unidimensionality is contrasted with the received view of strict unidimensionality and confirmatory factor analysis methods.

Health and the Quality of Life

The aim of this investigation was to explain theimpact of peoples self-reported health on theirlevels of satisfaction with their health, and theimpact of these things plus satisfaction with otherspecific domains of their lives on the perceivedquality of their lives. The latter was operationalized as general happiness, satisfactionwith life as a whole and overall satisfaction with thequality of life. Seven hundred and twenty-three (723)usable questionnaires returned from a mailout randomsample of 2500 households of Prince George, BritishColumbia in November 1998 formed the working data-setfor our analyses. Among other things, mean respondentscores on the SF-36 health profile were found to belower than published norms from the UK, USA,Netherlands and Sweden, but higher than scores fromAberdeen, Scotland. Mean scores on the CES-Ddepression scale also indicated that our respondentstended to have more depressive symptoms thancomparison groups in Winnipeg and the USA. A review oftrends in mean scores on 17 quality of life items(e.g., satisfaction with family life, financialsecurity, recreation, etc.) from 1994, 1997 and 1998revealed that there were only 7 statisticallysignificant changes across the four year period andthey were all negative. Multivariate regressionanalysis showed that health status measured with avariety of indicators could explain 56% of thevariation in respondents reported satisfaction withtheir health. A combination of health status plusdomain satisfaction indicators could explain 53% ofthe variation in respondents reported happiness, 68%of reported life satisfaction and 63% of reportedsatisfaction with the overall quality of life. Sixtypercent of the explained variation in happiness scoreswas attributable to self-reported health scores, whileonly 18% of the explained variation in satisfactionwith life and with the overall quality of life scoreswas attributable self-reported health scores.     

Healthy Days,Health Satisfaction and Satisfaction with the Overall Quality of Life

In this note we report results of 6 surveysusing the United States Centers for DiseaseControl and Prevention indicators of healthstatus, taken from the Behavioral Risk FactorSurveillance System. Generally speaking, wefound that the CDC healthy days variables couldplay a useful role in survey research aimed atassessing the impact of measured health statuson people's satisfaction with their own healthand with the overall quality of their lives.More precisely, using stepwise regressions wefound: (1) The three healthy days variablesexplained from 16 to 27 percent of the variancein General Health scores. The limited activitydays variable remained as a significantpredictor in only one of the six regressionsand the not good physical health days variablewas most influential in every sample. (2) Thethree healthy days variables explained from 19to 32 percent of the variance in healthsatisfaction scores, and the not good physicalhealth days variable was again most influentialin every sample. (3) The three healthy daysvariables explained from 12 to 39 percent ofthe variance in quality-of-life satisfactionscores, with the not good mental healthvariable most influential in every sample. (4)The four CDC variables together explained from40 to 55 percent of the variance in healthsatisfaction scores, with the General Healthvariable always dominating the set ofpredictors by a fairly wide margin. (5) Thefour CDC variables together explained from 17to 28 percent of the variance inquality-of-life satisfaction scores, with theGeneral Health variable most influential inthree samples and the not good mental healthvariable most influential in the other three.(6) When the four CDC variables plus the healthsatisfaction variable were used as potentialpredictors, we were able to explain from 29 to40 percent of the variance in quality-of-lifesatisfaction scores. In every sample, theGeneral Health and limited activity daysvariables had no significant impact. (7) Usingstructural equation modeling, we found GeneralHealth does not have a direct effect onsatisfaction with the overall quality of lifebut rather only an indirect effect throughhealth satisfaction. The General Health, notgood physical health, and not good mentalhealth days variables account for 51% of thevariation in health satisfaction, and healthsatisfaction, not good physical health and notgood mental health days variables account for30% of the variation in satisfaction with theoverall quality of life.     

Does Weighting Capture What’s Important? Revisiting Subjective Importance Weighting with a Quality of Life Measure

The present study evaluated subjective importance weighting using data collected with the Injection Drug User Quality of Life Scale (IDUQOL). Weighted and unweighted IDUQOL scores from 241 adults were correlated with convergent, discriminant, and criterion measures. Regression analysis was used to examine the contribution of importance ratings to scores on a global measure of life satisfaction and the corrected weighted IDUQOL total scores. Overall, the results showed that weighted scores did not perform better than unweighted scores in measuring quality of life. However, the mean satisfaction ratings for important domains correlated significantly higher with convergent measures than did the mean satisfaction ratings for unimportant domains. This finding suggests further attention needs to be paid to the meaning and measurement of subjective importance and how it may be incorporated more effectively into measures of quality of life.     

Contents of Volume 68

Volume Contents

Contents of Volume 68     

The use of population‐level data to advance interdisciplinary methodology: a cell‐through‐society sampling framework for child development research

The authors argue that population‐level data should be used to advance interdisciplinary research about community effects on early development. These data permit the identification of neighborhoods in which development patterns deviate from predictions based on local socioeconomic status (SES). So‐called ‘off‐diagonal’ places signal where researchers are likely to discover processes that either deflect the risks of low SES or dampen the salutary impact of favorable SES. Since such neighborhoods will be best understood relative to nearby ‘on‐diagonal’ neighborhoods where macro‐economic and/or public policy factors are constant, the authors present a methodology for illuminating these regional clusters. The method is deployed in British Columbia, Canada, where a team has collected developmental observations from two censuses of kindergarten children (n = 82,632). The article discusses how these clusters can be used to coordinate sampling decisions among academics representing the range of disciplines needed to study child development from cell‐through‐society, as is recommended in the literature.