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Imagery and Likelihood Cognitive Bias in Pain

Published online by Cambridge University Press:  27 November 2013

H. C. Philips
H. C. Philips*
Affiliation:
Back in Motion Rehabilitation Centre, Richmond, Canada
*
Reprint requests to H.C. Philips, Back in Motion Rehabilitation Centre, Richmond, BC, Canada. E-mail: clarephilips@yahoo.com
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Abstract

Background: Distressing intrusive images are frequently experienced by sufferers from chronic and acute pain. The images (Index images) are correlated with elevations in anxiety, threat, and a cognition that the imaged event might actually happen. The over-estimation that having a negative cognition about an adverse event will increase the probability of the negative event occurring - the likelihood bias - has been observed in a variety of psychological disorders. Preliminary research indicated this cognitive bias might occur in pain sufferers. Aims: To investigate the occurrence of a cognitive likelihood bias associated with imagery in acute and chronic pain sufferers, and to relate the postulated cognitive bias to psychological characteristics of participants, and four other important cognitive responses to their Index images. Method: Fifty-nine pain sufferers completed a newly developed questionnaire (Image-Event-Fusion-pain: IEF-p) to assess cognitive likelihood bias in pain sufferers. The internal consistency, reliability, factor structure and validity of the scale were evaluated. Psychological measures to assess anxiety, depression, PTSD symptoms, and levels of mental defeat were administered. Results: The IEF-p was found to be psychometrically robust with satisfactory test-retest reliability, good internal consistency, single factor structure and criterion validity. The IEF-p was significantly correlated with four key cognitive appraisals of the Index Images (responsibility, likelihood, premonition, and threat). Three of these correlations were independent of depression. High cognitive bias scores were significantly associated with elevated levels of anxiety symptoms, depression, PTSD symptoms, and mental defeat. Conclusion: Pain Index images were significantly associated with cognitive bias (IEF-p), increased threat levels, and raised estimate of the likelihood of imaged events actually occurring. The results indicate the prevalence of a cognitive bias associated with pain imagery cognitions, comparable to that established with intrusive cognitions in OCD, notably Thought-Action- Fusion.

Keywords

Cognitive biaslikelihoodIndex imagesIEF-p scalepainchronicacutedepression
Type
Research Article
Information
Behavioural and Cognitive Psychotherapy , Volume 43 , Issue 3 , May 2015 , pp. 270 - 284
Copyright
Copyright © British Association for Behavioural and Cognitive Psychotherapies 2013 

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References

Aldrich, S., Eccleston, C. and Crombez, G. (2000). Worrying about chronic pain: vigilance to threat and misdirected problem solving. Behaviour Research and Therapy, 38, 457–470.Google Scholar
Berle, D. and Starcevic, V. (2005). Thought-action fusion: review of the literature and future directions. Clinical Psychology Review, 25, 263–284.CrossRefGoogle ScholarPubMed
Berna, C., Tracey, I. and Holmes, E. A. (2012). How a better understanding of spontaneous mental imagery linked to pain could enhance imagery-based therapy in chronic pain. Journal of Experimental Psychopathology, 3, 258–273.CrossRefGoogle ScholarPubMed
Blanchard, E. B., Jones-Alexander, J., Buckley, T. C. and Forneris, C. (1996). Psychometric properties of the Post-Traumatic Stress Disorder Checklist (PCL). Behaviour Research and Therapy, 34, 669–673.Google Scholar
Brewin, C. R., Wheatley, J., Patel, T., Fearon, P., Hackmann, A., Wells, A., et al. (2009). Imagery rescripting as a brief stand-alone treatment for depressed patients with intrusive memories. Behaviour Research and Therapy, 47, 569–576.Google Scholar
Carroll, J. S. (1978). The effect of imagining an event on expectations for the event: an interpretation in terms of the availability heuristic. Journal of Experimental Social Psychology, 14, 88–96.Google Scholar
Eccleston, C., Crombez, G., Aldrich, S. and Stannard, C. (1997). Attention and somatic awareness in chronic pain. Pain, 72, 209–215.CrossRefGoogle ScholarPubMed
Gillanders, D., Potter, L. and Morris, P. (2012). Pain related-visual imagery is associated with distress in chronic pain sufferers. Behavioural and Cognitive Psychotherapy, 40, 577–589.Google Scholar
Helmes, E. and Goburdhun, A. (2007). Cognitions related to chronic pain: revision and extension of the Cognitive Evaluation Questionnaire. The Clinical Journal of Pain, 23, 53–61.Google Scholar
Holmes, E. A. and Mathews, A. (2010). Mental imagery in emotion and emotional disorders. Clinical Psychology Review, 30, 349–362.Google Scholar
Kahneman, D. (2011). Thinking, Fast and Slow. Canada: Doubleday.Google Scholar
Keefe, J, and Wren, A. A. (2013). Optimism and pain: a positive move forward. Pain, 154, 7–8.Google Scholar
Koehler, D. J. (1991). Explanation, imagination, and confidence in judgment. Psychological Bulletin, 110, 499–519.Google Scholar
Lang, A. J. and Stein, M. B. (2005). An abbreviated post-traumatic stress disorder checklist for use as a screening instrument in primary care. Behaviour Research and Therapy, 43, 585–594.Google Scholar
Marino-Carper, T., Negy, C., Burns, G. and Lunt, R. A. (2010). The effects of psycho-education on thought-action fusion, thought suppression, and responsibility. Journal of Behavior Therapy and Experimental Psychiatry, 41, 289–296.Google Scholar
Philips, H. C. (1989). Thoughts provoked by pain. Behaviour Research and Therapy, 27, 469–473.Google Scholar
Philips, H. C. (2010). Pilot Study. Unpublished manuscript.Google Scholar
Philips, H. C. (2011). Imagery and pain: the prevalence, characteristics, and potency of imagery associated with pain. Behavioural and Cognitive Psychotherapy, 39, 523–540.CrossRefGoogle ScholarPubMed
Philips, H. C. and Samson, D. (2012). The rescripting of pain images. Behavioural and Cognitive Psychotherapy, 40, 558–576.Google Scholar
Pincus, T. and Morley, S. (2001). Cognitive-processing bias in chronic pain: a review and integration. Psychological Bulletin, 127, 599–617.Google Scholar
Pincus, T., Rusu, A. and Santos, R. (2008). Responsiveness and construct validity of the Depression, Anxiety and Positive Outlook Scale (DAPOS). Clinical Journal of Pain, 24, 431–437.Google Scholar
Rachman, S. (2013). Anxiety (3rd edn). Hove: Psychology Press.Google Scholar
Ruggiero, K. J., Del Ben, K., Scotti, J. R. and Rabalais, A. E. (2003). Psychometric properties of the Post-Traumatic Stress Disorder Check-Civilian Version. Journal of Traumatic Stress, 16, 495–502.CrossRefGoogle ScholarPubMed
Salkovskis, P. (1996). The cognitive approach to anxiety. In Salkovskis, P. (Ed.), The Frontiers of Cognitive Therapy. New York: Guilford Press.Google Scholar
Shafran, R. and Rachman, S. (2004). Thought-action fusion: a review. Journal of Behavior Therapy and Experimental Psychiatry, 35, 87–107.Google Scholar
Shafran, R., Teachman, B. A., Kerry, S. and Rachman, S. (1999). A cognitive distortion associated with eating disorders: thought-shape fusion. British Journal of Clinical Psychology, 38, 167–179.Google Scholar
Shafran, R., Thordarson, D. S. and Rachman, S. (1996). Thought-action fusion in obsessive compulsive disorder. Journal of Anxiety Disorders, 10, 379–391.Google Scholar
Sherman, S. J., Cialdini, R. B., Schwartzman, D. F. and Reynolds, K. D. (1985). Imagining can heighten or lower the perceived likelihood of contracting a disease: the mediating effect of ease of imagery. Personality and Social Psychology Bulletin, 11, 118–127.Google Scholar
Sutherland, S. (1992). Irrationality: the enemy within. London: Constable and Company.Google Scholar
Sullivan, M. J. L., Bishop, S. R. and Pabik, J. (1995). The Pain Catastrophizing Scale: developments and validation. Psychological Assessment, 7, 524–532.Google Scholar
Tang, N. K., Salkovskis, P. M. and Hanna, M. (2007). Mental defeat in chronic pain: initial exploration of the concept. Clinical Journal of Pain, 23, 222–232.CrossRefGoogle ScholarPubMed
Tang, N. K., Goodchild, C. E., Hester, J. and Salkovskis, P. M. (2010). Mental defeat is linked to interference, distress, and disability in chronic pain. Pain, 149, 547–554.Google Scholar
Taylor, R., Lovibond, P. F., Nicholas, M. K., Cayley, C. and Wilson, P. H. (2005). The utility of somatic items in the assessment of depression in patients with chronic pain: a comparison of the Zung Self-rating Depression Scale and the Depression Anxiety Stress Scale in chronic pain and clinical and community samples. Clinical Journal of Pain, 21, 91–100.Google Scholar
Thordarson, D., Radomsky, A., Rachman, S. and Shafran, R. (2004). Vancouver OC Inventory. Behaviour Research and Therapy, 42, 1289–1314.Google Scholar
Tversky, A. and Kahneman, D. (1973). Availability: a heuristic for judging frequency and probability. Cognitive Psychology, 5, 207–232.Google Scholar
Zucker, B. G., Craske, M. G., Barrios, V. and Holguin, M. (2002). Thought action fusion: can it be corrected? Behaviour Research and Therapy, 40, 652–664.Google Scholar
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