Reference : Attentional bias to pain-related information: A meta-analysis of dot-probe studies
Scientific journals : Article
Social & behavioral sciences, psychology : Theoretical & cognitive psychology
Attentional bias to pain-related information: A meta-analysis of dot-probe studies
Todd, Jemma* [> >]
Van Ryckeghem, Dimitri* mailto [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Integrative Research Unit: Social and Individual Development (INSIDE) > ; Ghent University > Experimental-Clinical Health Psychology]
Sharpe, Louise [> >]
Crombez, Geert [> >]
* These authors have contributed equally to this work.
Health Psychology Review
Yes (verified by ORBilu)
[en] Pain ; Attentional bias ; Meta-analysis ; Dot-probe
[en] Studies investigating attentional biases towards pain information vary widely in both design
and results. The aim of this meta-analysis was to determine the degree to which attentional
biases towards pain occur when measured with the dot-probe task. A total of 2168 references
were screened, resulting in a final sample of 4466 participants from 52 articles. Participants
were grouped according to pain experience: chronic pain, acute pain, anticipating
experimental/procedural pain, social concern for pain, or healthy people. In general, results
revealed a significant, but small bias towards pain words (d= 0.136), and pain pictures (d=
0.110) in chronic pain patients, but not in those with acute pain, those anticipating pain, or
healthy people. Follow-up analyses revealed an attentional bias towards sensory pain words
in the chronic pain group (d= 0.198), and the acute pain group (d= 0.303), but not other
groups. In contrast, attentional biases towards affective pain stimuli were not significant for
any pain groups. This meta-analysis found support for attentional biases towards sensory pain
stimuli in patients with chronic pain in comparison to healthy individuals across a range of
common parameters. Future researchers need to consider task design when seeking to
optimally measure pain-relevant attentional biases

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