Attention processes in chronic fatigue syndrome: Attentional bias for health-related threat and the role of attentional control
Abstract
Cognitive behavioural models of chronic fatigue syndrome (CFS) propose that attention processes, specifically, enhanced selective attention to health-threat related cues, may play an important role in symptom maintenance. The current study investigated attentional bias towards health-threat stimuli in CFS. It also examined whether individuals with CFS have impaired executive attention, and whether this was related to attentional bias. 27 participants with CFS and 35 healthy controls completed a Visual Probe Task measuring attentional bias, and an Attention Network Test measuring executive attention, alerting and orienting. Participants also completed self-report measures of CFS and mood symptoms. Compared to the control group, the CFS group showed greater attentional bias for health-threat words than pictures; and the CFS group was significantly impaired in executive attention. Furthermore, CFS individuals with poor executive attention showed greater attentional bias to health-threat related words, compared not only to controls but also to CFS individuals with good executive attention. Thus, this study revealed a significant relationship between attentional bias and executive attention in CFS: attentional bias to threat was primarily evident in those with impaired executive attention control. Taking account of individual differences in executive attention control in current intervention models may be beneficial for CFS.
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Individual differences in ABs are not specific to threat cues in anxiety, as they are also found for other motivationally or personally salient information, for example, in illness and pain, and for rewards such as food cues in obesity and drug cues in addiction.
“Individual differences in ABs are not specific to threat cues in anxiety, as they are also found for other motivationally or personally salient information, for example, in illness and pain (Hou et al., 2014;Todd et al., 2015); as well as for rewards, such as food cues in obesity (Castellanos et al., 2009) and drug cues in addiction (Field & Cox, 2008;Field, Mogg, & Bradley, 2006).”
From Anxiety and attention to threat: cognitive mechanisms and treatment with attention bias modification (2016) · cites this paper as Hou et al., 2014
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- Authors
- Hou, R., Moss-Morris, R., Risdale, A., Lynch, J., Jeevaratnam, P., Bradley, B. P., & Mogg, K.
- Affiliations
- University of Southampton (GB)
- King's College London (GB)
- Corresponding author
- Moss-Morris, Rona
- Venue
- Behaviour Research and Therapy
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 52
- Pages
- 9-16
- ISSN
- 0005-7967 (ISSN-L)
- OpenAlex
- W1988998092
- Cited by
- 47
- References
- 56
- Citations by year
- 2025: 3 · 2024: 3 · 2023: 2 · 2022: 2 · 2021: 2 · 2020: 1 · 2019: 3 · 2018: 9 · 2017: 7 · 2016: 9 · 2015: 5 · 2014: 1
- FWCI
- 3.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Behaviour Research and Therapy (publishedVersion)
- PubMed (publishedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Fibromyalgia and Chronic Fatigue Syndrome Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Health Sciences › Medicine › Neurology › Long-Term Effects of COVID-19
- Keywords
- chronic fatigue syndrome, attentional bias, health hazards, executive attention, attentional control, selective attention, symptom maintenance, cognitive-behavioral model, mood symptoms, individual differences
- MeSH terms
- Adult, Attention, Cues, Female, Humans, Health Knowledge, Attitudes, Practice, Male, Middle Aged, Neuropsychological Tests, Photic Stimulation, Reaction Time, Fatigue Syndrome, Chronic, Case-Control Studies, Young Adult, Executive Function, Self Report
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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