Hostname: page-component-8448b6f56d-gtxcr Total loading time: 0 Render date: 2024-04-19T12:30:22.371Z Has data issue: false hasContentIssue false

Looming cognitive style and quality of life in a cancer cohort

Published online by Cambridge University Press:  28 September 2010

Tomer T. Levin*
Affiliation:
Department of Psychiatry and Behavioral Sciences, Memorial Sloan-Kettering Cancer Center, New York, New York
John Riskind
Affiliation:
George Mason University, Fairfax, Virgina
Yuelin Li
Affiliation:
Department of Psychiatry and Behavioral Sciences, Memorial Sloan-Kettering Cancer Center, New York, New York
*
Address correspondence and reprint requests to: Tomer Levin, Department of Psychiatry and Behavioral Sciences, 641 Lexington Ave., New York, NY 10022. E-mail: levint@mskcc.org

Abstract

Objective:

Looming cognitive styles (LCS) bias the velocity of potential threats and have been implicated in anxiety and depression vulnerability. This study aims to explore their contribution to impaired quality of life (QOL), beyond that of depression and anxiety, in a cancer cohort.

Method:

In a cross-sectional design, an ambulatory chronic lymphocytic leukemia (CLL) cohort completed a psychological battery that included the Beck Depression and Anxiety Inventories, the SF-36 Health Survey, the Functional Assessment of Chronic Illness Therapy (FACT), the Looming Cognitive Style Questionnaire (LCSQ), and the Looming Cancer measure.

Results:

The Looming Cancer measure correlated significtly with overall QOL (FACT-G, p = 0.005). This effect was largely due to the contribution of emotional QOL (Mental Component Score: SF-36, p = 0.001; FACT-emotional, p = 0.001) and functional QOL (FACT-functional, p = 0.001). Looming, unlike anxiety and depression, did not correlate with a worse physical QOL (Physical Component Score: SF-36, FACT-physical). Looming did not impact on social QOL. Hierarchical regression analysis showed that looming predicted 5.4% of the varience on the FACT-emotional, 5.1% on the Mental Component Score (SF-36), and 9.3% on the mental health subscale (SF-36), above and beyond the varience predicted by a constellation of psychosocial factors (including age, marital status, education, income) and the combined effect of depression and anxiety

Significance of results:

LCS predicts worse emotional and functional QOL, above and beyond the contribution of anxiety, depression, and other psycho-social variables. This suggests that it makes a unique contribution to a worse QOL. Nevertheless, the looming construct still remains primarily a research tool in psycho-oncology at this time.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Beck, A. & Steer, R. (1993). Beck Anxiety Inventory Manual. San Antonio: The Psychological Corporation.Google Scholar
Beck, A., Steer, R. & Brown, G. (1996). Beck Depression Inventory Manual (2nd ed.). San Antonio: The Psychological Corporation, Harcourt Brace and Company.Google Scholar
Brucker, P., Yost, K., Cashy, J., et al. (2005). General population and cancer patient norms for the Functional Assessment of Cancer Therapy-General (FACT-G). Evaluation & the Health Professions, 28, 192211.CrossRefGoogle ScholarPubMed
Cella, D.F., Tulsky, D.S., Gray, G., et al. (1993). The Functional Assessment of Cancer Therapy Scale: Development and validation of the general measure. Journal of Clinical Oncology, 11, 570579.CrossRefGoogle ScholarPubMed
Levin, T.T., Riskind, J.H. & Li, Y. (2007a). Looming threat processing style in a cancer cohort. General Hospital Psychiatry, 29, 3238.CrossRefGoogle Scholar
Levin, T.T., Riskind, J.H., Li, Y, et al. (2007b). Depression, anxiety and quality of life in a chronic lymphocytic leukemia cohort. General Hospital Psychiatry, 29, 251256.CrossRefGoogle Scholar
Maxwell, S. & Delaney, H. (1990). Designing Experiments and Analyzing Data. Belmont: Wadsworth Inc.Google Scholar
Maxwell, S. & Delaney, H. (1993). Bivariate median splits and spurious statistical significance. Psychological Bulletin, 113, 181190.CrossRefGoogle Scholar
Riskind, J.H. & Williams, N.L. (1999). Specific cognitive content of anxiety and catastrophizing: Looming vulnerability and looming maladaptive style. Journal of Cognitive Psychotherapy, 13, 4154.CrossRefGoogle Scholar
Riskind, J.H., Williams, N.L., Gessner, T.L., et al. (2000). The Looming Maladaptive Style: Anxiety, danger and schematic processing. Journal Personality and Social Psychology, 79, 837852.CrossRefGoogle ScholarPubMed
Riskind, J.H., Moore, R. & Bowley, L. (1995). The looming of spiders: The fearful perceptual distortion of movement and menace. Behavior Research and Therapy, 33, 171178.CrossRefGoogle ScholarPubMed
Spitzer, R., Kroenke, K. & Williams, J. (1999). Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. Journal of the American Medical Association, 282, 17371744.CrossRefGoogle ScholarPubMed
Turner, J.A. & Aaron, L.A. (2001). Pain-related catastrophizing: What is it? Clinical Journal of Pain, 17, 6571.CrossRefGoogle ScholarPubMed
Ware, J. & Gandek, B. (1994). IQOLA-Project-Group: The SF-36 Health Survey: Development and use in mental health research and the IQOLA Project. International Journal of Mental Health, 23, 4973.CrossRefGoogle Scholar
Williams, N.L., Shahar, G., Riskind, J.H., et al. (2005). The looming maladaptive style predicts shared variance in anxiety symptoms: Further support for a cognitive model of vulnerability to anxiety. Journal of Anxiety Disorders, 19, 157175.CrossRefGoogle ScholarPubMed