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An attention and interpretation bias for illness-specific information in chronic fatigue syndrome

Published online by Cambridge University Press:  29 November 2016

A. M. Hughes
Affiliation:
Psychology Department, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
T. Chalder
Affiliation:
Department of Psychological Medicine, King's College London, London, UK
C. R. Hirsch
Affiliation:
Psychology Department, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
R. Moss-Morris*
Affiliation:
Psychology Department, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
*
*Address for correspondence: R. Moss-Morris, Health Psychology Section, Psychology Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5th Floor Bermondsey Wing, Guy's Hospital Campus, London Bridge, London SE1 9RT, UK. (Email: Rona.moss-morris@kcl.ac.uk)

Abstract

Background

Studies have shown that specific cognitions and behaviours play a role in maintaining chronic fatigue syndrome (CFS). However, little research has investigated illness-specific cognitive processing in CFS. This study investigated whether CFS participants had an attentional bias for CFS-related stimuli and a tendency to interpret ambiguous information in a somatic way. It also determined whether cognitive processing biases were associated with co-morbidity, attentional control or self-reported unhelpful cognitions and behaviours.

Method

A total of 52 CFS and 51 healthy participants completed self-report measures of symptoms, disability, mood, cognitions and behaviours. Participants also completed three experimental tasks, two designed specifically to tap into CFS salient cognitions: (i) visual-probe task measuring attentional bias to illness (somatic symptoms and disability) v. neutral words; (ii) interpretive bias task measuring positive v. somatic interpretations of ambiguous information; and (iii) the Attention Network Test measuring general attentional control.

Results

Compared with controls, CFS participants showed a significant attentional bias for fatigue-related words and were significantly more likely to interpret ambiguous information in a somatic way, controlling for depression and anxiety. CFS participants had significantly poorer attentional control than healthy individuals. Attention and interpretation biases were associated with fear/avoidance beliefs. Somatic interpretations were also associated with all-or-nothing behaviour and catastrophizing.

Conclusions

People with CFS have illness-specific biases which may play a part in maintaining symptoms by reinforcing unhelpful illness beliefs and behaviours. Enhancing adaptive processing, such as positive interpretation biases and more flexible attention allocation, may provide beneficial intervention targets.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

† Joint last authors.

References

Armstrong, T, Olatunji, BO (2012). Eye tracking of attention in the affective disorders: a meta-analytic review and synthesis. Clinical Psychology Review 32, 704723.Google Scholar
Brown, HM, Eley, TC, Broeren, S, MacLeod, C, Rinck, M, Hadwin, JA, Lester, KJ (2014). Psychometric properties of reaction time based experimental paradigms measuring anxiety-related information-processing biases in children. Journal of Anxiety Disorders 28, 97107.Google Scholar
Burgess, M, Andiappan, M, Chalder, T (2012) Cognitive behaviour therapy for chronic fatigue syndrome in adults: face to face versus telephone treatment – a randomized controlled trial. Behavioural Cognitive Psychotherapy 40, 175191.Google Scholar
Cella, M, Chalder, T (2010). Measuring fatigue in clinical and community settings. Journal of Psychosomatic Research 69, 1722.Google Scholar
Cella, M, Chalder, T, White, PD (2011 a). Does the heterogeneity of chronic fatigue syndrome moderate the response to cognitive behaviour therapy? An exploratory study. Psychotherapy and Psychosomatics 80, 353358.Google Scholar
Cella, M, Sharpe, M, Chalder, T (2011 b). Measuring disability in patients with chronic fatigue syndrome: reliability and validity of the Work and Social Adjustment Scale. Journal of Psychosomatic Research 71, 124128.Google Scholar
Cella, M, White, PD, Sharpe, M, Chalder, T (2013). Cognitions, behaviours and co-morbid psychiatric diagnoses in patients with chronic fatigue syndrome. Psychological Medicine 43, 375380.Google Scholar
Chalder, T, Berelowitz, G, Pawlikowska, T, Watts, L, Wessely, S, Wright, D, Wallace, E (1993). Development of a fatigue scale. Journal of Psychosomatic Research 37, 147153.Google Scholar
Chalder, T, Goldsmith, KA, White, PD, Sharpe, M, Pickles, AR (2015). Rehabilitative therapies for chronic fatigue syndrome: a secondary mediation analysis of the PACE trial. Lancet Psychiatry 2, 141152.CrossRefGoogle ScholarPubMed
Chalder, T, Power, MJ, Wessely, S (1996). Chronic fatigue in the community: ‘a question of attribution’. Psychological Medicine 26, 791800.Google Scholar
Chapman, S, Martin, M (2011). Attention to pain words in irritable bowel syndrome: increased orienting and speeded engagement. British Journal of Health Psychology 16, 4760.Google Scholar
Cockshell, SJ, Mathias, JL (2010). Cognitive functioning in chronic fatigue syndrome: a meta-analysis. Psychological Medicine 40, 12531267.Google Scholar
Creswell, C, Chalder, T (2002). Underlying self-esteem in chronic fatigue syndrome. Journal of Psychosomatic Research 53, 755761.Google Scholar
Crombez, G, Van Ryckeghem, DM, Eccleston, C, Van Damme, S (2013 a). Attentional bias to pain-related information: a meta-analysis. Pain 154, 497510.Google Scholar
Crombez, G, Viane, I, Eccleston, C, Devulder, J, Goubert, L (2013 b). Attention to pain and fear of pain in patients with chronic pain. Journal of Behavioral Medicine 36, 371378.Google Scholar
Deary, V, Chalder, T, Sharpe, M (2007). The cognitive behavioural model of medically unexplained symptoms: a theoretical and empirical review. Clinical Psychology Review 27, 781797.Google Scholar
Erdfelder, E, Faul, F, Buchner, A (1996). GPOWER: a general power analysis program. Behavior Research Methods, Instruments, and Computers 28, 111.Google Scholar
Eysenck, MW, Derakshan, N, Santos, R, Calvo, MG (2007). Anxiety and cognitive performance: attentional control theory. Emotion 7, 336353.Google Scholar
Fan, J, McCandliss, BD, Fossella, J, Flombaum, JI, Posner, MI (2005). The activation of attentional networks. NeuroImage 26, 471479.Google Scholar
Fan, J, McCandliss, BD, Sommer, T, Raz, A, Posner, MI (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience 14, 340347.Google Scholar
Fritzsche, A, Dahme, B, Gotlib, IH, Joormann, J, Magnussen, H, Watz, H, Nutzinger, DO, von Leupoldt, A (2010). Specificity of cognitive biases in patients with current depression and remitted depression and in patients with asthma. Psychological Medicine 40, 815826.Google Scholar
Fukuda, K, Straus, SE, Hickie, I, Sharpe, MC, Dobbins, JG, Komaroff, A (1994). The chronic fatigue syndrome: a comprehensive approach to its definition and study. Annals of Internal Medicine 121, 953959.Google Scholar
Heathcote, LC, Vervoort, T, Eccleston, C, Fox, E, Jacobs, K, Van Ryckeghem, DM, Lau, JY (2015). The relationship between adolescents’ pain catastrophizing and attention bias to pain faces is moderated by attention control. Pain 156, 13341341.Google Scholar
Heeren, A, Philippot, P, Koster, E (2015). Impact of the temporal stability of preexistent attentional bias for threat on its alteration through attention bias modification. Journal of Behavior Therapy and Experimental Psychiatry 49, 6975.Google Scholar
Hirsch, CR, Mathews, A (2000). Impaired positive inferential bias in social phobia. Journal of Abnormal Psychology 109, 705712.Google Scholar
Hirsch, CR, Meeten, F, Krahé, C, Reeder, C (2016). Resolving ambiguity in emotional disorders: the nature and role of interpretation biases. Annual Review of Clinical Psychology 12, 281305.Google Scholar
Hou, R, Moss-Morris, R, Bradley, BP, Peveler, R, Mogg, K (2008). Attentional bias towards health-threat information in chronic fatigue syndrome. Journal of Psychosomatic Research 65, 4750.Google Scholar
Hou, R, Moss-Morris, R, Risdale, A, Lynch, J, Jeevaratnam, P, Bradley, BP, Mogg, K (2014). Attention processes in chronic fatigue syndrome: attentional bias for health-related threat and the role of attentional control. Behaviour Research and Therapy 52, 916.Google Scholar
Hughes, A, Hirsch, C, Chalder, T, Moss-Morris, R (2016 a). Attentional and interpretative biases towards illness-related information in chronic fatigue syndrome: a systematic review. British Journal of Health Psychology 21, 741763.Google Scholar
Hughes, AM, Gordon, R, Chalder, T, Hirsch, CR, Moss-Morris, R (2016 b). Maximizing potential impact of experimental research into cognitive processes in health psychology: a systematic approach to material development. British Journal of Health Psychology 21, 764780.Google Scholar
Jones, EB, Sharpe, L (2014). The effect of cognitive bias modification for interpretation on avoidance of pain during an acute experimental pain task. PAIN® 155, 15691576.Google Scholar
Jurado, MB, Rosselli, M (2007). The elusive nature of executive functions: a review of our current understanding. Neuropsychology Review 17, 213233.Google Scholar
Knoop, H, Prins, JB, Moss-Morris, R, Bleijenberg, G (2010). The central role of cognitive processes in the perpetuation of chronic fatigue syndrome. Journal of Psychosomatic Research 68, 489494.Google Scholar
Lautenbacher, S, Huber, C, Schöfer, D, Kunz, M, Parthum, A, Weber, PG, Sittl, R (2010). Attentional and emotional mechanisms related to pain as predictors of chronic postoperative pain: a comparison with other psychological and physiological predictors. PAIN® 151, 722731.Google Scholar
Lewis, G, Pelosi, AJ, Araya, R, Dunn, G (1992). Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychological Medicine 22, 465486.CrossRefGoogle ScholarPubMed
MacLeod, C, Mathews, A (2012). Cognitive bias modification approaches to anxiety. Annual Review of Clinical Psychology 8, 189217.Google Scholar
MacLeod, C, Mathews, A, Tata, P (1986). Attentional bias in emotional disorders. Journal of Abnormal Psychology 95, 1520.Google Scholar
Martin, M, Alexeeva, I (2010). Mood volatility with rumination but neither attentional nor interpretation biases in chronic fatigue syndrome. British Journal of Health Psychology 15, 779796.Google Scholar
Mathews, A, Mackintosh, B (2000). Induced emotional interpretation bias and anxiety. Journal of Abnormal Psychology 109, 602615.Google Scholar
Mathews, A, MacLeod, C (1994). Cognitive approaches to emotion and emotional disorders. Annual Review of Psychology 45, 2550.Google Scholar
Mogg, K, Bradley, BP (2016). Anxiety and attention to threat: cognitive mechanisms and treatment with attention bias modification. Behaviour Research and Therapy 87, 76108.Google Scholar
Moss-Morris, R, Deary, V, Castell, B (2013). Chronic fatigue syndrome. Handbook of Clinical Neurology 110, 303314.Google Scholar
Moss-Morris, R, Petrie, KJ (2003). Experimental evidence for interpretive but not attention biases towards somatic information in patients with chronic fatigue syndrome. British Journal of Health Psychology 8, 195208.CrossRefGoogle Scholar
Moss-Morris, R, Sharon, C, Tobin, R, Baldi, JC (2005). A randomized controlled graded exercise trial for chronic fatigue syndrome: outcomes and mechanisms of change. Journal of Health Psychology 10, 245259.Google Scholar
Moss-Morris, R, Spence, M, Hou, R (2011). The pathway from glandular fever to chronic fatigue syndrome: can the cognitive behavioural model provide the map? Psychological Medicine 41, 10991107.Google Scholar
Mundt, JC, Marks, IM, Shear, MK, Greist, JM (2002). The Work and Social Adjustment Scale: a simple measure of impairment in functioning. British Journal of Psychiatry 180, 461464.Google Scholar
Pergamin-Hight, L, Naim, R, Bakermans-Kranenburg, MJ, van IJzendoorn, MH, Bar-Haim, Y (2015). Content specificity of attention bias to threat in anxiety disorders: a meta-analysis. Clinical Psychology Review 35, 1018.CrossRefGoogle ScholarPubMed
Pool, E, Brosch, T, Delplanque, S, Sander, D (2016). Attentional bias for positive emotional stimuli: a meta-analytic investigation. Psychological Bulletin 142, 79106.Google Scholar
Price, M, Tone, EB, Anderson, PL (2011). Vigilant and avoidant attention biases as predictors of response to cognitive behavioral therapy for social phobia. Depression and Anxiety 28, 349353.Google Scholar
Riemann, BC, McNally, RJ (1995). Cognitive processing of personally relevant information. Cognition and Emotion 9, 325340.Google Scholar
Salemink, E, Wiers, RW (2012) Adolescent threat-related interpretive bias and its modification: the moderating role of regulatory control. Behaviour Research and Therapy 50, 4046.Google Scholar
Schoth, DE, Georgalli, T, Liossi, C (2013). Attentional bias modification in people with chronic pain: a proof of concept study. Cognitive Behaviour Therapy 42, 233243.Google Scholar
Sharpe, L, Haggman, S, Nicholas, M, Dear, BF, Refshauge, K (2014). Avoidance of affective pain stimuli predicts chronicity in patients with acute low back pain. PAIN® 155, 4552.Google Scholar
Sharpe, L, Ianiello, M, Dear, BF, Perry, KN, Refshauge, K, Nicholas, MK (2012). Is there a potential role for attention bias modification in pain patients? Results of 2 randomised, controlled trials. Pain 153, 722731.Google Scholar
Sharpe, L, Johnson, A, Dear, B (2015). Attention bias modification and its impact on experimental pain outcomes: comparison of training with words versus faces in pain. European Journal of Pain 19, 12481257.Google Scholar
Sharpe, M, Archard, L, Banatvala, J, Borysiewicz, L, Clare, A, David, A, Edwards, R, Hawton, K, Lambert, H, Lane, R (1991). A report – Chronic fatigue syndrome: guidelines for research. Journal of the Royal Society of Medicine 84, 118121.Google Scholar
Skerrett, TN, Moss-Morris, R (2006). Fatigue and social impairment in multiple sclerosis: the role of patients’ cognitive and behavioral responses to their symptoms. Journal of Psychosomatic Research 61, 587593.Google Scholar
Stahl, D, Rimes, K, Chalder, T (2014). Mechanisms of change underlying the efficacy of cognitive behaviour therapy for chronic fatigue syndrome in a specialist clinic: a mediation analysis. Psychological Medicine 44, 13311344.Google Scholar
Surawy, C, Hackmann, A, Hawton, K, Sharpe, M (1995). Chronic fatigue syndrome: a cognitive approach. Behaviour Research and Therapy 33, 535544.Google Scholar
Todd, J, Sharpe, L, Colagiuri, B, Khatibi, A (2016). The effect of threat on cognitive biases and pain outcomes: an eye-tracking study. European Journal of Pain 20, 13571368.Google Scholar
Togo, F, Lange, G, Natelson, BH, Quigley, KS (2015). Attention network test: assessment of cognitive function in chronic fatigue syndrome. Journal of Neuropsychology 9, 19.Google Scholar
Van Damme, S, Legrain, V, Vogt, J, Crombez, G (2010). Keeping pain in mind: a motivational account of attention to pain. Neuroscience and Biobehavioral Reviews 34, 204213.Google Scholar
Waters, AM, Mogg, K, Bradley, BP (2012). Direction of threat attention bias predicts treatment outcome in anxious children receiving cognitive–behavioural therapy. Behaviour Research and Therapy 50, 428434.Google Scholar
Wearden, AJ, Emsley, R (2013). Mediators of the effects on fatigue of pragmatic rehabilitation for chronic fatigue syndrome. Journal of Consulting and Clinical Psychology 81, 831838.CrossRefGoogle ScholarPubMed
White, P, Goldsmith, K, Johnson, A, Potts, L, Walwyn, R, DeCesare, J, Baber, H, Burgess, M, Clark, L, Cox, D (2011). Comparison of adaptive pacing therapy, cognitive behaviour therapy, graded exercise therapy, and specialist medical care for chronic fatigue syndrome (PACE): a randomised trial. Lancet 377, 823836.Google Scholar
White, P, Thomas, J, Amess, J, Grover, S, Kangro, H, Clare, A (1995). The existence of a fatigue syndrome after glandular fever. Psychological Medicine 25, 907916.Google Scholar
Wiborg, JF, Knoop, H, Prins, JB, Bleijenberg, G (2011). Does a decrease in avoidance behavior and focusing on fatigue mediate the effect of cognitive behavior therapy for chronic fatigue syndrome? Journal of Psychosomatic Research 70, 306310.Google Scholar
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