Pain practice : the official journal of World Institute of Pain
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The growing emphasis on evidence-based medicine dictates that reliable, evidence-based outcomes be utilized in documenting response to treatment, as well as determining the treatment efficacy and cost-effectiveness of different treatment modalities. The biopsychosocial model conceptualizes pain as a complex multifactorial interaction of biological, psychological, and social components that play a role in the development, exacerbation, and perpetuation of pain. As a result, outcomes relevant to pain management are necessarily complex and multifactorial in nature. ⋯ Patient-reported outcomes are discussed within the context of pain measures, health-related quality of life, and psychological constructs. Objective outcomes are discussed within the context of healthcare utilization and occupational status. The discussion within each section highlights the unique constructs measured by each category of outcome measure and highlights their consistency with current evidence-based guidelines and knowledge from pain research.
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Acute pain is reported as a presenting symptom in over 80% of physician visits. Chronic pain affects an estimated 76.2 million Americans--more than diabetes, heart disease, and cancer combined. It has been estimated to be undertreated in up to 80% of patients in some settings. ⋯ The numeric pain scale certainly has a place in care and in pain management; however, it is important to assess the patient's communication and self-management style and to recognize that patients, like pain, are on a continuum with varied styles of communication and adaptation. It is easy to get lost in the process, even when the process is initiated with the best of intentions. In the quest for individualized medicine, it might be best to keep pain assessment in the individualization arena.
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Conducting a clinical trial involves various stages of planning and implementation. The three major components involved in clinical trials are the management of data, the quality control to ensure data integrity, and the interpretation of the data at the conclusion of the trial. Although each process is distinct and involves different levels of effort and knowledge to implement, all processes are intimately linked. ⋯ Taking into account baseline characteristics of the patient sample is also discussed as an extension to maintaining the internal validity of the study. Additionally, some common threats to statistical conclusion validity, including Type I error inflation and the problem of overpowered tests, are highlighted. Finally, the concept of the effect size as an important complement to statistical significance and how the various types of effect size measures can be interpreted within the context of a clinical trial are discussed.