Pain
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The variability in pain drawing styles and analysis methods has raised concerns about the reliability of pain drawings as a screening tool for nonpain symptoms. In this study, a data-driven approach to pain drawing analysis has been used to enhance the reliability. The aim was to identify distinct clusters of pain patterns by using latent class analysis (LCA) on 46 predefined anatomical areas of a freehand digital pain drawing. ⋯ Statistically significant differences were found between these clusters in every self-reported health domain. Similarly, for both LBP and MBPNP, pain drawings involving more extensive pain areas were associated with higher activity limitation, more intense pain, and more psychological distress. This study presents a versatile data-driven approach for analyzing pain drawings to assist in managing spinal pain.
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The 11th revision of the International Classification of Diseases and Related Health Problems (ICD-11) aims at improving the lives of persons with the lived experience of chronic pain by providing clearly defined and clinically useful diagnoses that can reduce stigma, facilitate communication, and improve access to pain management, among others. The aim of this study was to assess the perspective of people with chronic pain on these diagnoses. An international web-based survey was distributed among persons with the lived experience of chronic pain. ⋯ Participants with CPP and CSP did not differ in their ratings; however, those with CSP indicated an improved diagnostic fit of the new diagnoses, whereas participants with CPP rated the diagnostic fit of the new diagnoses similar to the fit of their current diagnoses. These results show that persons with the lived experience of chronic pain accept and endorse the new diagnoses. This endorsement is an important indicator of the diagnoses' clinical utility and can contribute to implementation and advocacy.
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Pain perception and its modulation are fundamental to human learning and adaptive behavior. This study investigated the hypothesis that pain perception is tied to pain's learning function. Thirty-one participants performed a threat conditioning task where certain cues were associated with a possibility of receiving a painful electric shock. ⋯ Prediction errors were also related to physiological nociceptive responses, including the amplitude of nociceptive flexion reflex and electroencephalography markers of cortical nociceptive processing (N1-P2-evoked potential and gamma-band power). In addition, higher pain expectations were related to increased late event-related potential responses and alpha/beta decreases in amplitude during cue presentation. These results further strengthen the idea of a crucial link between pain and learning and suggest that understanding the influence of learning mechanisms in pain modulation could help us understand when and why pain perception is modulated in health and disease.