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Outcome expectations and self-regulation in cancer patients: Reliability, initial factor structure, and relationships with benefit finding

Published online by Cambridge University Press:  03 March 2006

KRISTI D. GRAVES  and
CINDY L. CARTER
KRISTI D. GRAVES
Affiliation:
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina 29435, USA
CINDY L. CARTER
Affiliation:
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina 29435, USA
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Abstract

Objective: The purpose of this research was to investigate outcome expectation and self-regulation measures within a sample of cancer patients and to explore relationships of these variables with benefit finding. The outcome expectation and self-regulation measures were evaluated for reliability and initial factor structure.

Method: A convenience sample of 141 cancer patients completed study measures while waiting for appointments at a cancer center.

Results: The measures demonstrated good reliability (alphas = .88 and .92, for outcome expectation and self-regulation respectively). Initial factor structure suggested six outcome expectation factors (managing symptoms, expressing emotions, talking about cancer, learning about cancer, managing self-image, and managing needs) and one self-regulation factor. Gender and treatment status were related to outcome expectations but not self-regulation. Outcome expectations and self-regulation were significant predictors of benefit-finding, F(8, 80) = 3.1, p = .005.

Significance of the research: Measures of outcome expectations and self-regulation are reliable, are related to gender and clinical variables, and may be useful as predictors of cancer patients' ability to find benefits in their cancer experience.

Keywords

CancerOutcome expectationsSelf-regulationSocial Cognitive TheoryBenefit finding
Type
Research Article
Information
Palliative & Supportive Care , Volume 3 , Issue 3 , September 2005 , pp. 209 - 219
Copyright
© 2005 Cambridge University Press

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References

REFERENCES

Anderson, E.S., Winett, R.A., & Wojcik, J.R. (2000). Social cognitive determinants of nutrition behavior among supermarket food shoppers: A structural equation analysis. Health Psychology, 19, 479–486.Google Scholar
Antoni, M.H., Lehman, L.M., Kilbourn, K.M., et al. (2001). Cognitive-behavioral stress management intervention decreases the prevalence of depression and enhances benefit finding among women under treatment for early-stage breast cancer. Health Psychology, 20, 20–32.Google Scholar
Bandura, A. (1997) Self-efficacy: The Exercise of Control. New York: W.H. Freeman.
Buckelew, S.P., Parker, J.C., Keefe, F.J., et al. (1994). Self-efficacy and pain behavior among subjects with fibromyalgia. Pain, 59, 377–384.Google Scholar
Burt, M.R. & Katz, B.L. (1987). Dimensions of recovery from rape: Focus on growth outcomes. Journal of Interpersonal Violence, 2, 57–81.Google Scholar
Carver, C.S., Pozo, C., Harris, S.D., et al. (1993). How coping mediates the effect of optimism on distress: A study of women with early stage breast cancer. Journal of Personality and Social Psychology, 65, 375–390.Google Scholar
Carver, C.S. & Scheier, M.F. (1981). Attention and Self-Regulation: A Control-Theory Approach to Human Behavior. New York: Springer Verlag.
Carver, C.S. & Scheier, M.F. (1998). On the Self-Regulation of Behavior. New York: Cambridge University Press.
DeGeest, S., Borgermans, L., Gemoets, H., et al. (1995). Incidence, determinants, and consequences of subclinical noncomliance with immunosuppressive therapy in renal transplant recipients. Transplantation, 59, 340–346.Google Scholar
Dow, K.H., Ferrell, B.R., Leigh, S., et al. (1996). An evaluation of the quality of life among long-term survivors of breast cancer. Breast Cancer Research and Treatment, 39, 261–273.Google Scholar
Fabrigar, L.R., Wegener, D.T., MacCallum, R.C., et al. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272–299.Google Scholar
Fromm, K., Andrykowski, M.A., & Hunt, J. (1996). Positive and negative psychosocial sequelae of bone marrow transplantation: Implications for quality of life assessment. Journal of Behavioral Medicine, 19, 221–240.Google Scholar
Giese-Davis, J., Koopman, C., Butler, L.D., et al. (1999). Self-efficacy with emotions predicts higher quality of life in primary breast cancer patients. Annals of Behavioral Medicine, 21, S199.Google Scholar
Graves, K.D. (2003). Social cognitive theory and cancer patients' quality of life: Meta-analysis of psychosocial intervention components. Health Psychology, 22, 210–219.Google Scholar
Graves, K.D., Carter, C.L., Anderson, E.S., et al. (2003). Quality of life pilot intervention for breast cancer patients: Use of social cognitive theory. Palliative and Supportive Care, 1, 121–134.Google Scholar
Holman, H. & Lorig, K. (1992). Perceived self-efficacy in self-management of chronic disease. In Self-Efficacy: Thought Control of Action, Schwarzer, R. (ed.), pp. 305–323. Washington, DC: Hemisphere.
Lechner, S.C., Zakowski, S.G., Antoni, M.H., et al. (2003). Do sociodemographic and disease-related variables influence benefit-finding in cancer patients? Psycho-Oncology, 12, 491–499.Google Scholar
Lent, R.W., Lopez, F.G., & Bieschke, K.J. (1993). Predicting mathematics-related choice and success behaviors: Test of an expanded social cognitive model. Journal of Vocational Behavior, 42, 223–236.Google Scholar
Lepore, S.J. (2001). A social cognitive processing model of emotional adjustment to cancer. In Psychosocial Interventions for Cancer, Baum, A. & Anderson, B.L. (eds.), pp. 99–116. Washington, DC: American Psychological Association.
Lev, E.L. (1997). Bandura's theory of self-efficacy: Applications to oncology. Scholarly Inquiry for Nursing Practice: An International Journal, 11, 21–37.Google Scholar
Lev, E.L., Daley, K.M., Conner, N.E., et al. (2001). An intervention to increase quality of life and self-care self-efficacy and decrease symptoms in breast cancer patients. Scholarly Inquiry for Nursing Practice, 15, 277–294.Google Scholar
Lev, E.L. & Owen, S.V. (2000). Counseling women with breast cancer using principles developed by Albert Bandura. Perspectives in Psychiatric Care, 36, 131–138.Google Scholar
Leventhal, H., Brissett, I., & Leventhal, E. (2003). The common-sense model of self-regulation of health and illness. In The Self-Regulation of Health and Illness Behavior, Cameron, L.D. & Leventhal, H. (eds.), pp. 42–65. London: Routledge.
Leventhal, H., Leventhal, E.A., & Contrada, R.J. (1998). Self-regulation, health and behavior: A perceptual-cognitive approach. Psychology and Health, 13, 717–733.Google Scholar
Lipsey, M.W. (1990). Design Sensitivity: Statistical Power for Experimental Research. Newbury Park, CA: Sage.
Maddux, J.E. (1995). Self-efficacy theory: An introduction. In Self-Efficacy, Adaptation, and Adjustment: Theory, Research and Application, Maddux, J.E. (ed.), pp. 3–36. New York: Plenum.
Merluzzi, T.V. & Martinez Sanchez, M.A. (1997). Assessment of self-efficacy and coping with cancer: Development and validation of the Cancer Behavior Inventory. Health Psychology, 16, 163–170.Google Scholar
Merluzzi, T.V. & Nairn, R.C. (1999). An exploration of self-efficacy and longevity in persons with cancer. Annals of Behavioral Medicine, 21, S200.Google Scholar
Merluzzi, T.V., Nairn, R.C., Hedge, K., et al. (2001). Self-efficacy for coping with cancer: Revision of the Cancer Behavior Inventory (version 2.0). Psycho-Oncology, 10, 206–217.Google Scholar
Montanelli, R.G. & Humphreys, L. (1976). Latent roots of random data correlation matrices with squared multiple correlations on the diagonal: A Monte Carlo study. Psychometrika, 41, 341–348.Google Scholar
O'Leary, A., Shoor, S., Lorig, K., et al. (1988). A cognitive-behavioral treatment for rheumatoid arthritis. Health Psychology, 7, 527–544.Google Scholar
Shadel, W.G. & Mermelstein, R.J. (1993). Cigarette smoking under stress: The role of coping expectancies among smokers in a clinic-based smoking cessation program. Health Psychology, 12, 443–450.Google Scholar
Scheier, M.F. & Carver, C.S. (2003). Goals and confidence as self-regulatory elements underlying health and illness behavior. In The Self-Regulation of Health and Illness Behavior, Cameron, L.D. & Leventhal, H. (eds.), pp. 17–41. London: Routledge.
Smyth, J.M., Stone, A.A., Hurewitz, A., et al. (1999). Effects of writing about stressful experiences on symptom reduction in patients with asthma or rheumatoid arthritis. Journal of the American Medical Association, 281, 1304–1309.Google Scholar
Snodgrass, S.E. (1998). A personal account. Journal of Social Issues, 54, 373–380.Google Scholar
Stanton, A.L., Danoff-Burg, S., Sworowski, L.A., et al. (2002). Randomized, controlled trial of written emotional expression and benefit finding in breast cancer patients. Journal of Clinical Oncology, 20, 4160–4168.Google Scholar
Stanton, A.L. & Snider, P.R. (1993). Coping with a breast cancer diagnosis: A prospective study. Health Psychology, 12, 16–23.Google Scholar
Telch, C.F. & Telch, M.J. (1986). Group coping skills instruction and supportive group therapy for cancer patients: A comparison of strategies. Journal of Consulting and Clinical Psychology, 54, 802–808.Google Scholar