References of "Sharpe, Louise"
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See detailThe time course of attentional biases in pain : a meta-analysis of eye tracking studies
Jones, Emma Blaisdale; Sharpe, Louise; Andrews, Sally et al

in PAIN (2021)

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See detailCognitive biases in pain: An integrated functional-contextual framework
Van Ryckeghem, Dimitri UL; Noel, Melanie; Sharpe, Louise et al

in Pain (2019)

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See detailAttentional bias to pain-related information: A meta-analysis of dot-probe studies
Todd, Jemma; Van Ryckeghem, Dimitri UL; Sharpe, Louise et al

in Health Psychology Review (2018)

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 ... [more ▼]

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 [less ▲]

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