Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-18T23:08:44.320Z Has data issue: false hasContentIssue false
  • English
  • Français

The Effects of Computerized Cognitive Control Training on Community Adults with Depressed Mood

Published online by Cambridge University Press:  03 March 2014

Amanda W. Calkins ,
Katherine E. McMorran ,
Greg J. Siegle  and
Michael W. Otto
Amanda W. Calkins*
Affiliation:
Massachusetts General Hospital, Harvard Medical School, USA
Katherine E. McMorran
Affiliation:
The Catholic University of America, USA
Greg J. Siegle
Affiliation:
University of Pittsburgh, Pittsburgh Medical Center, USA
Michael W. Otto
Affiliation:
Boston University, USA
*
Reprint requests to Amanda W. Calkins, Massachusetts General Hospital, One Bowdoin Square, Boston MA 02114, USA. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background: Depression is frequently characterized by patterns of inflexible, maladaptive, and ruminative thinking styles, which are thought to result from a combination of decreased attentional control, decreased executive functioning, and increased negative affect. Cognitive Control Training (CCT) uses computer-based behavioral exercises with the aim of strengthening cognitive and emotional functions. A previous study found that severely depressed participants who received CCT exhibited reduced negative affect and rumination as well as improved concentration. Aims: The present study aimed to extend this line of research by employing a more stringent control group and testing the efficacy of three sessions of CCT over a 2-week period in a community population with depressed mood. Method: Forty-eight participants with high Beck Depression Inventory (BDI-II) scores were randomized to CCT or a comparison condition (Peripheral Vision Training; PVT). Results: Significant large effect sizes favoring CCT over PVT were found on the BDI-II (d = 0.73, p < .05) indicating CCT was effective in reducing negative mood. Additionally, correlations showed significant relationships between CCT performance (indicating ability to focus attention on CCT) and state affect ratings. Conclusions: Our results suggest that CCT is effective in altering depressed mood, although it may be specific to select mood dimensions.

Keywords

Depressionadultsattentional trainingcomputer-aided psychotherapy
Type
Research Article
Information
Behavioural and Cognitive Psychotherapy , Volume 43 , Issue 5 , September 2015 , pp. 578 - 589
Copyright
Copyright © British Association for Behavioural and Cognitive Psychotherapies 2014 

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

Amir, N., Beard, C., Burns, M. and Bomyea, J. (2009). Attention modification program in individuals with generalized anxiety disorder. Journal of Abnormal Psychology, 118, 28–33.Google Scholar
Andrade, L., Caraveo-Anduaga, J. J., Berglund, P., Bijl, R. V., De Graaf, R., Wollebergh, W., et al. (2006). The epidemiology of major depressive episodes: results from the International Consortium of Psychiatric Epidemiology (ICPE) surveys. Psychiatric Research, 12, 3–21.Google Scholar
Baxter, L. R., Schwartz, J. M., Phelps, M. E. and Mazziotta, J. C. (1989). Reduction of prefrontal cortex glucose metabolism common to three types of depression. Archives of General; Psychiatry, 46, 243–250.Google Scholar
Beck, A. T., Steer, R. A. and Brown, G. K. (1996). Manual for the Beck Depression Inventory-II. San Antonio, TX: Psychological Corporation.Google Scholar
Bench, C. J., Friston, K. J., Brown, R. G., Frackowiak, R. S. and Dolan, R. J. (1993). Regional cerebral blood flow in depression measured by positron emission tomography: the relationship with clinical dimensions. Psychological Medicine, 23, 579–590.Google Scholar
Calkins, A. W., Deveney, C. M., Weitzman, M. L., Hearon, B. A., Siegle, G. J. and Otto, M. W. (2010). The effects of prior cognitive control task exposure on responses to emotional tasks in healthy participants. Behavioural and Cognitive Psychotherapy, 39, 205–220.CrossRefGoogle ScholarPubMed
Casacalenda, N., Perry, J. C. and Looper, K. (2002). Remission in major depressive disorder: a comparison of pharmacotherapy, psychotherapy, and control conditions. American Journal of Psychiatry, 159, 1354–1360.Google Scholar
Davidson, R. J. (2000). Affective style, psychopathology, and resilience: brain mechanisms and plasticity. American Psychology, 55, 1196–1214.CrossRefGoogle ScholarPubMed
Davidson, R. J., Irwin, W., Anderle, M. J. and Kalin, N. H. (2003). The neural substrates of affective processing in depressed patients treated with venlafaxine. American Journal of Psychiatry, 160, 64–75.Google Scholar
Diener, C., Kuehner, C., Brusniak, W., Ubl, B., Wessa, M. and Flor, H. (2012). A meta-analysis of neurofunctional imaging studies of emotion and cognition in major depression. Neuroimage, 61, 677–685. doi: 10.1016/j.neuroimage.2012.04.005Google Scholar
Drevets, W. C. and Raichle, M. E. (1998). Reciprocal suppression of regional cerebral blood flow during emotional versus higher cognitive processes: implications for interactions between emotion and cognition. Cognition and Emotion, 12, 353–385.Google Scholar
Elgamal, S., McKinnon, M. C., Ramakrishnan, K., Joffe, R. T. and MacQueen, G. (2007). Successful computer-assisted cognitive remediation therapy in patients with unipolar depression: a proof of principle study. Psychological Medicine: A Journal of Research in Psychiatry and the Allied Sciences, 37, 1229–1238.Google Scholar
Erk, S., Mikschl, A., Stier, S., Ciaramidaro, A., Gapp, V., Weber, B., et al. (2010). Acute and sustained effects of cognitive emotion regulation in major depression. Journal of Neuroscience, 30, 15726–15734.CrossRefGoogle ScholarPubMed
Fales, C. L., Barch, D. M., Rundle, M. M., Mintun, M. A., Mathews, J., Snyder, A. Z., et al. (2009). Antidepressant treatment normalizes hypoactivity in dorsolateral prefrontal cortex during emotional interference processing in major depression. Journal of Affective Disorders, 112, 206–211.CrossRefGoogle ScholarPubMed
Goldin, P. R. and Gross, J. J. (2010). Effects of mindfulness-based stress reduction (MBSR) on emotion regulation in social anxiety disorder. Emotion, 10, 83–91.Google Scholar
Gronwall, D. M. (1977). Paced auditory serial-addition task: a measure of recovery from concussion. Perceptual and Motor Skills, 44, 367–373.Google Scholar
Kühn, S., Vanderhasselt, M. A., De Raedt, R. and Gallinat, J. (2012). Why ruminators won't stop: the structural and resting state correlates of rumination and its relation to depression. Journal of Affective Disorders, 141, 352–360. doi: 10.1016/j.jad.2012.03.024.Google Scholar
Lazeron, R. H., Rombouts, S. A., de Sonneville, L., Barkhof, F. and Scheltens, P. (2003). A paced visual serial addition test for fMRI. Journal of Neurological Science, 213, 29–34.Google Scholar
Liotti, M. and Mayberg, H. S. (2001). The role of functional neuroimaging in the neuropsychology of depression. Journal of Clinical and Experimental Neuropsychology, 23, 121–136.Google Scholar
Liotti, M., Mayberg, H. S., McGinnis, S., Brannan, S. L. and Jerabek, P. (2002). Unmasking disease-specific cerebral blood flow abnormalities: mood challenge in patients with remitted unipolar depression. American Journal of Psychiatry, 159, 1830–1840.Google Scholar
Little, J. and McPhail, N. I. (1973). Measures of depressive mood at monthly intervals. British Journal of Psychiatry, 122, 447–452.Google Scholar
Mayberg, H. S., Liotti, M. D., Brannan, S. K., McGuinnis, S., Mahurin, R. K., Jerabek, P. A., et al. (1999). Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. American Journal of Psychiatry, 156, 675–682.Google Scholar
McLaughlin, K. A. (2011). The public health impact of major depression: a call for interdisciplinary prevention efforts. Prevention Science, 12, 361–371.Google Scholar
Meyer, T. J., Miller, M. L., Metzger, R. L. and Borkovec, T. D. (1990). Development and validation of the Penn State Worry Questionnaire. Behavior Research and Therapy, 28, 487–495.Google Scholar
Ochsner, K. N., Bunge, S. A., Gross, J. J. and Gabrieli, J. D. E. (2002). Rethinking feelings: an fMRI study of the cognitive regulation of emotion. Journal of Cognitive Neuroscience, 14, 1215–1229.Google Scholar
Park, N. W. and Ingles, J. L. (2001). Effectiveness of attention rehabilitation after an acquired brain injury: a meta-analysis. Neuropsychology, 15, 199–210.Google Scholar
Ray, R. D., Ochsner, K. N., Cooper, J. C., Robertson, E. R., Gabrieli, J. D. E. and Gross, J. J. (2005). Individual differences in trait rumination and the neural systems supporting cognitive reappraisal. Cognitive, Affective and Behavioral Neuroscience, 5, 156–168.CrossRefGoogle ScholarPubMed
Rush, A. J., Trivedi, M. H., Wisniewski, S. R., Nierenberg, A. A., Steward, J. W., Warden, D., et al. (2006). Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. American Journal of Psychiatry, 163, 1905–1917.Google Scholar
Siegle, G. J., Ghinassi, F. and Thase, M. E. (2007). Neurobehavioral therapies in the 21st century: summary of an emerging field and an extended example of cognitive control training for depression. Cognitive Therapy and Research, 31, 235–262.Google Scholar
Siegle, G. J., Steinhauer, S. R., Thase, M. E., Stenger, V. A. and Carter, C. S. (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
Siegle, G. J., Thompson, W., Carter, C. S., Steinhauer, S. R. and Thase, M. E. (2007). Increased amygdala and decreased dorsolateral prefrontal BOLD responses in unipolar depression: related and independent features. Biological Psychiatry, 61, 198–209.CrossRefGoogle ScholarPubMed
Siegle, G. J., Price, R. B., Jones, N. P., Ghinassi, F. and Thase, M. E. (in press). You gotta work at it: pupillary indices of task focus are prognostic for response to a neurocognitive intervention for depression. Clinical Psychological Science.Google Scholar
Surguladze, S., Brammer, M. J., Keedwell, P., Giampietro, V., Young, A. W., Travis, M. J., et al. (2005). A differential pattern of neural response toward sad versus happy facial expressions in major depressive disorder. Biological Psychiatry, 57, 201–209.Google Scholar
Taylor Tavares, J. V., Clark, L., Furey, M. L., Williams, G. B., Sahakian, B. J. and Drevets, W. C. (2008). Neural basis of abnormal response to negative feedback in unmedicated mood disorders. Neuroimage, 42, 1118–1126.Google Scholar
Thase, M. E., Dubé, S., Bowler, K. and Howland, R. H. (1996). Hypothalamic-pituitary-adrenocortical activity and response to cognitive behavior therapy in unmedicated, hospitalized depressed patients. American Journal of Psychiatry, 153, 886–891.Google Scholar
Watson, D., Clark, L. A. and Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070.Google Scholar
Wells, A. (2000). Emotional Disorders and Metacognition: innovative cognitive therapy. New York: John Wiley and Sons Ltd.Google Scholar
Submit a response

Comments

No Comments have been published for this article.