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MS patients with depressive symptoms exhibit affective memory biases when verbal encoding strategies are suppressed

Published online by Cambridge University Press:  26 August 2005

JARED M. BRUCE  and
PETER A. ARNETT
JARED M. BRUCE
Affiliation:
Psychology Department, Penn State University, University Park, Pennsylvania
PETER A. ARNETT
Affiliation:
Psychology Department, Penn State University, University Park, Pennsylvania
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Abstract

As many as 50% of multiple sclerosis (MS) patients experience clinical or subclinical depression. A voluminous literature has documented affective memory biases (AMB) among depressed individuals. Despite this, little is known regarding how depressive symptoms may affect MS patients' ability to recall positive and negative material. The present study employed an affective list-learning task that increased cognitive load and inhibited the use of higher order encoding strategies. The purpose of the study was twofold: to determine whether MS patients exhibit AMB and to examine whether subvocal repetition and other higher order encoding strategies are essential to the formation of AMB among people experiencing depression. Results indicated a strong relationship between depression and AMB in MS. The results are discussed in relation to existing biological research that indicates limbic and/or other subcortical systems may play a role in the formation of AMB. (JINS, 2005, 11, 514–521.)

Keywords

Multiple sclerosisDepressionMemoryCognitive load
Type
Research Article
Information
Journal of the International Neuropsychological Society , Volume 11 , Issue 5 , September 2005 , pp. 514 - 521
Copyright
© 2005 The International Neuropsychological Society

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References

REFERENCES

Abela, J. (2002). Depressive mood reactions to failure in the achievement domain: A test of the integration of the hopelessness and self-esteem theories of depression. Cognitive Therapy and Research, 26, 531–552.Google Scholar
Abramson, L., Alloy, L., Hogan, M., Whitehouse, W., Donovan, P., Rose, D., Panzarella, C., & Raniere, D. (1999). Cognitive vulnerability to depression: Theory and evidence. Journal of Cognitive Psychotherapy: An International Quarterly, 13, 5–19.Google Scholar
Alford, B., Lester, J., Patel, R., Buchanan, J., & Guinta, L. (1995). Hopelessness predicts future depressive symptoms: A prospective analysis of cognitive vulnerability and cognitive content specificity. Journal of Clinical Psychology, 51, 331–339.Google Scholar
Arnett, P., Higginson, C., Voss, W., Bender, W., Wurst, J., & Tippin, J. (1999a). Depression in multiple sclerosis: Relationship to working memory capacity. Neuropsychology, 13, 546–556.Google Scholar
Arnett, P., Higginson, C., Voss, W., Wright, B., Bender, W., & Wurst, J. (1999b). Depressed mood in multiple sclerosis: Relationship to capacity-demanding memory and attentional functioning. Neuropsychology, 13, 434–446.Google Scholar
Beck, A., Rush, A., Shaw, B., & Emery, G. (1979). Cognitive therapy of depression. New York: Guilford Press.
Beck, A.T., Steer, R.A., & Brown, G.K. (1996). Beck Depression Inventory–2nd edition manual. New York: Psychological Corporation.
Blaney, P. (1986). Affect and memory: A review. Psychological Bulletin, 99, 229–246.Google Scholar
Bruce, J. & Arnett, P. (2004). Self-reported everyday memory and depression in patients with multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 26, 200–214.Google Scholar
Cahill, L. & McGaugh, J. (1998). Mechanisms of emotional arousal and lasting declarative memory. Trends in Neurosciences, 21, 294–299.Google Scholar
Canli, T., Zhao, Z., Desmond, J., Glover, G., & Gabrieli, J. (1999). FMRI identifies a network of structures correlated with retention of positive and negative emotional memory. Psychobiology, 27, 441–452.Google Scholar
Daneman, M. & Carpenter, P. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Behavior, 19, 450–466.Google Scholar
Dobson, K. & Franche, R. (1989). A conceptual and empirical review of the depressive realism hypothesis. Canadian Journal of Behavioural Science, 21, 419–433.CrossRefGoogle Scholar
Foley, F., Miller, A., Traugott, U., LaRocca, N., Scheinberg, L., Bedell, J., & Lenox, S. (1988). Psychoimmunological dysregulation in multiple sclerosis. Psychosomatics, 29, 398–403.Google Scholar
Francis, N. & Kucera, H. (1982). Frequency analysis of English usage: Lexicon and grammer. Boston: Houghton Mifflin.
Fruehwald, S., Loeffler-Stastka, H., Eher, R., Saletu, B., & Baumhackl, U. (2001). Depression and quality of life in multiple sclerosis. Acta Neurologica Scandinavia, 104, 257–261.Google Scholar
Hankin, B., Abramson, L., & Stiler, M. (2001). A prospective test of the hopelessness theory of depression in adolescence. Cognitive Therapy and Research, 25, 607–632.Google Scholar
Harmer, C., Hill, S., Taylor, M., Cohen, P., & Goodwin, G. (2003). Toward a neuropsychological theory of antidepressant drug action: Increase in positive emotional bias after potentiation of norepinephrine activity. American Journal of Psychiatry, 160, 990–992.Google Scholar
Hupet, M., Desmette, D., & Schelstraiete, M. (1997). What does Daneman and Carpenter's reading span really measure? Perceptual and Motor Skills, 84, 603–608.Google Scholar
Kandel, E., Schwartz, J., & Jessell, T. (2000). Principles of Neural Science. New York: McGraw-Hill.
Kurtzke, J. (1983). Rating neurological impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology, 33, 1444–1445.Google Scholar
LaPointe, L. & Engle, R. (1990). Simple and complex spans as measures of working memory capacity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16, 1118–1133.Google Scholar
Li, K. (1999). Selection from working memory: On the relationship between information processing and storage components. Aging, Neuropsychology, and Cognition, 6, 99–116.Google Scholar
Lublin, F. & Reingold, S. (1996). Defining the clinical course of multiple sclerosis: Results of an international survey. Neurology, 46, 907–911.Google Scholar
Minden, S., Orav, J., & Reich, P. (1987). Depression in multiple sclerosis. General Hospital Psychiatry, 9, 426–434.Google Scholar
Mohr, D. & Cox, D. (2001). Multiple sclerosis: Empirical literature for the clinical health psychologist. Journal of Clinical Psychology, 57, 479–499.Google Scholar
Mohr, D. & Goodkin, D. (1999). Treatment of depression in multiple sclerosis: Review and meta-analysis. Clinical Psychology: Science and Practice, 6, 1–9.Google Scholar
Mohr, D., Goodkin, D., Likosky, W., Gatto, N., Baumann, K., & Rudick, R. (1997). Treatment of depression improves adherence to interferon beta-1b therapy for multiple sclerosis. Archives of Neurology, 54, 531–533.Google Scholar
Naveh-Benjamin, M. & Jonides, J. (1984). Cognitive load and maintenance rehearsal. Journal of Verbal Learning and Verbal Behavior, 23, 494–507.Google Scholar
Nyenhuis, D., Luchetta, T., Yamamoto, C., Terrien, A., Bernardin, L., Rao, S., & Garron, D. (1998). The development, standardization, and initial validation of the Chicago Multiscale Depression Inventory. Journal of Personality Assessment, 70, 386–401.Google Scholar
Nyenhuis, D., Rao, S., Zajecka, J., Luchetta, T., Bernardin, L., & Garron, D. (1995). Mood disturbance versus other symptoms of depression in multiple sclerosis. Journal of the International Neuropsychological Society, 1, 291–296.Google Scholar
Poser, C., Paty, D., Scheinberg, L., McDonald, I., Davis, F., Ebers, G., Johnson, K., Sibley, W., Silberberg, D., & Tourtellotte, W. (1983). New diagnostic criteria for multiple sclerosis: Guidelines for research protocols. Annals of Neurology, 13, 227–231.Google Scholar
Pryse-Phillips, W. & Costello, F. (2001). The epidemiology of multiple sclerosis. In S. Stuart (Ed.), Handbook of multiple sclerosis. New York: Marcel Dekker.
Rude, S., Valdex, C., Odom, S., & Ebrahimi, A. (2003). Negative cognitive biases predict subsequent depression. Cognitive Therapy and Research, 27, 415–429.Google Scholar
Schubert, D. & Foliart, R. (1993). Increased depression in multiple sclerosis: A meta-analysis. Psychosomatics, 34, 124–130.Google Scholar
Segal, Z. (1988). Appraisal of the self-schema construct in cognitive models of depression. Psychological Bulletin, 103, 147–162.Google Scholar
Siegle, G., Steinhaer, S., Thase, M., Stenger, A., & Carter, C. (2002). Can't shake that feeling: Event-related fMRI assessment of sustained amygdala activity in response to emotional information in depressed individuals. Biological Psychiatry, 51, 693–707.Google Scholar
Watkins, P., Martin, C., & Stern, L. (2000). Unconscious memory bias in depression: Perceptual and conceptual processes. Journal of Abnormal Psychology, 109, 282–289.Google Scholar
Wenzlaff, R., Rude, S., Taylor, C., Stultz, C., & Sweatt, R. (2001). Beneath the veil of thought suppression: Attentional bias and depression risk. Cognition and Emotion, 15, 435–452.Google Scholar
Whitney, P., Arnett, P., & Driver, A. (2001). Measuring central executive functioning: What's in a reading span? Brain and Cognition, 45, 1–14.Google Scholar
Zachary, R. (1986). Shipley Institute of Living Scale: Revised manual. Los Angeles: Western Psychological Services.