The journal of pain : official journal of the American Pain Society
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The use of electronic health records (EHR) for chronic pain phenotyping has gained significant attention in recent years, with various algorithms being developed to enhance accuracy. Structured data fields (e.g., pain intensity, treatment modalities, diagnosis codes, and interventions) offer standardized templates for capturing specific chronic pain phenotypes. This study aims to determine which chronic pain case definitions derived from structured data elements achieve the best accuracy, and how these validation metrics vary by sociodemographic and disease-related factors. ⋯ While our current algorithms provide valuable insights, enhancement is needed to ensure more reliable chronic pain identification across diverse patient populations. PERSPECTIVES: This study evaluates chronic pain phenotyping algorithms using electronic health records, highlighting variability in performance across sociodemographic and disease-related factors. By combining structured data elements, the findings advance chronic pain identification, promoting equitable healthcare practices and highlighting the need for tailored algorithms to address subgroup-specific biases and improve outcomes.
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Group-delivered programs for chronic pain are evidence-based and frequently used. The contribution of group factors to outcomes is unclear and there are no integrated findings on consumer perceptions of the group itself in programs for people with chronic pain. The aim of this systematic review was to search and synthesise qualitative data specifically related to the group itself in studies investigating group-delivered programs for people with chronic pain (PROSPERO, CRD42023382447). ⋯ PERSPECTIVE: This review demonstrates that many consumers valued peer interaction and used comparison-based cognitive processing within group-delivered programs for chronic pain. Dialogue-based interactions with similar others promoted cognitive, affect, and behaviour changes. Group factors may have been underestimated and outcomes could be influenced if peer interactions within programs were optimised.
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Multiple large longitudinal cohorts provide opportunities to address questions about predictors of pain and pain trajectories, even when not anticipated in the design of the historical databases. This focus article uses 2 empirical examples to illustrate the processes of assessing the measurement properties of data from large cohort studies to answer questions about pain. In both examples, data were screened to select candidate variables that captured the impact of chronic pain on self-care activities, productivity, and social activities. ⋯ In conjunction with its Supplementary Material, this focus article aims to encourage exploration of these valuable prospectively collected data to support researchers to make explicit the relationships between items in the databases and constructs of interest in pain research and to use empirical methods to estimate the possible biases in these variables. PERSPECTIVE: This focus article outlines a theory-driven approach for fitting new measurement models to data from large cohort studies and evaluating their psychometric properties. This aims to help researchers develop an empirical understanding of the gains and limitations connected with the process of repurposing the data stored in these datasets.
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Interventions aimed at preventing chronic pain after acute traumatic injury have significant potential to reduce healthcare expenditures and improve quality of life for millions of individuals. Given recent development of such interventions, limited research has examined mechanisms of change using repeated measures (e.g., session-by-session assessments). This study examines within-person relationships between pain catastrophizing and intensity during and after a four-session mind-body intervention for individuals with acute traumatic orthopedic injury (N = 76, T = 445). ⋯ PERSPECTIVE: This study examines within-person relationships between pain catastrophizing and intensity during and after a four-session mind-body intervention to prevent persistent pain after acute traumatic orthopedic injury. Improved catastrophizing at post-test was associated with reduced pain with activity at three-month follow-up. Within-person analyses enhance understanding of psychosocial mechanisms for preventing chronic pain after injury.
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Randomized Controlled Trial Multicenter Study
The use of abstract animations and a graphical body image for assessing pain outcomes among adults with sickle cell disease.
Painimation, a novel digital pain assessment tool, allows patients to communicate their pain quality, intensity, and location using abstract animations (painimations) and a paintable body image. This study determined the construct validity of painimations and body image measures by testing correlations with validated pain outcomes in adults with sickle cell disease (SCD). Analyses used baseline data from a multisite randomized trial of 359 adults with SCD and chronic pain. ⋯ This demonstrates animations and body image data can assess SCD pain severity, potentially with more accuracy than a 0-10 scale. Future research will explore whether Painimation can differentiate biological and psychosocial pain components. PERSPECTIVE: This article presents the preliminary construct validity of Painimation in SCD by examining the associations of "painimations" and body area image data with daily e-diary and traditional self-report pain outcomes.