Hope and optimism as related to life satisfaction

Abstract

This study explored the hope and optimism constructs and their unique variances in predicting life satisfaction. The subscales (Agency and Pathways) of the Adult Hope Scale (Snyder, Harris et al., 1991) and optimism and pessimism as measured by the Life Orientation Test-Revised (LOT-R; Scheier, Carver, & Bridges, 1994) were compared in terms of ability to predict life satisfaction as measured by the domain-specific Quality of Life Inventory (QOLI®; Frisch, 1994; Study 1, N = 331) and the global measure Satisfaction with Life Scale (Diener, Emmons, Larsen, & Griffin, 1985; Study 2, N = 215). The Agency subscale of the Adult Hope Scale was the better predictor of life satisfaction in both studies. The implications of these findings for theory and measurement of hope and optimism are discussed.

Keywords:

• Positive psychology
• hope
• optimism
• quality of life
• satisfaction with life
• subjective well-being

Acknowledgements

This research was supported, in part, by 2000 and 2002 sabbaticals granted to Michael B. Frisch, and a 2003 sabbatical from the University of Kansas to C. R. Snyder. The authors gratefully acknowledge the invaluable assistance of Dr. Richard G. Heimberg of Temple University Adult Anxiety Clinic for his laboratory resources. A special thank you is also extended to Thomas Bailey's graduate assistants Helen Currens and Bryanna Shanefelter for their assistance.

Notes

It is with great sadness that we note that our friend and colleague C. R. (Rick) Snyder began this project and was not able to see it through to its completion. Rick passed away in January 2006 leaving a deep void in many people's lives. This was one of several remaining projects that he touched and will add to his lasting contributions to the field of positive psychology.

†Deceased

Note

1.  Although the chi-square is the primary indication of goodness-of-fit, possible distortions may occur due to sample size (Bentler, 1992; Mulaik et al., 1989). Alternative indices are included that more accurately indicate fit. These indices include: Root mean square of error approximation (RMSEA; Steiger, 1990) where RMSEA less than 0.05 indicates a close fit, 0.05 to 0.08 indicates a reasonable fit, and greater than 0.10 would indicate an unacceptable model (Browne & Cudeck, 1992); goodness-of-fit index (GFI; Jöreskog & Sörbom, 1996); comparative fit index (CFI; Bentler, 1990); and non-normed fit index (NNFI, originally identified as TLI; Tucker & Lewis, 1973). GFI, CFI, and NNFI indices are generally acceptable when greater than 0.90 (Bentler & Bonett, 1980). A maximum likelihood (ML) estimation using a variance-covariance matrix, generated by a component (PRELIS) of the LISREL 8 software was used in the confirmatory factor analyses. Regression analyses were performed using SPSS 11.5. Concerns of collinearity between variables used in the regression analysis were analysed using tolerance (TOL) greater than 0.1, variable inflation factor (VIF) less than 10, and a condition index (CI) value less than 30 (see Coenders & Saez, 2000).

Additional information

Notes on contributors

C. R. Snyder†

It is with great sadness that we note that our friend and colleague C. R. (Rick) Snyder began this project and was not able to see it through to its completion. Rick passed away in January 2006 leaving a deep void in many people's lives. This was one of several remaining projects that he touched and will add to his lasting contributions to the field of positive psychology. †Deceased