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Diagnosis and treatment of lumbar discogenic pain due to internal disc disruption (IDD) remains a challenge. It accounts for 39% of patients with low back pain. The mechanism of discogenic pain remains unclear and its clinical presentation is atypical. Magnetic resonance imaging (MRI) can find high-intensity zone as an indirect indication of IDD. However, relative low sensitivity (26.7% to 59%) and high false-positive (24%) and false-negative (38%) rates reduce the value of MRI in screening for the existence of painful IDD. Provocative discography can provide unique information about the pain source and the morphology of the disc. It may also provide information for selecting appropriate treatment for the painful annular tear. Adjunctive therapies, including nonsteroidal anti-inflammatory drugs, physical therapy, rehabilitation, antidepressants, antiepileptics, and acupuncture, have been used for low back pain. The value of these treatments for discogenic pain is yet to be established. Intradiscal steroid injection has not been proved to provide long-term benefits. Intradiscal electrothermal therapy may offer some pain relief for a group of well-selected patients. No benefits have been found for the intradiscal radiofrequency thermocoagulation. A block in the ramus communicans may interfere with the transition of painful information from the discs to the central nervous system. Disc cell transplantation is in the experimental stage. It has the potential to become a useful tool for the prevention and treatment of discogenic pain. Minimally invasive treatments provide alternatives for discogenic pain with the appeal of cost-effectiveness and, possibly, less long-term side effects. However, the value of most of these therapies is yet to be established. More basic science and clinical studies are needed to improve the clinical efficacy of minimally invasive treatments.

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Social media and online communities provide organizations with new opportunities to support their businessrelated functions. Despite their various benefits, social media technologies present two important challenges for sense-making. First, online discourse is plagued by incoherent, intertwined conversations that are often difficult to comprehend. Moreover, organizations are increasingly interested in understanding social media participants' actions and intentions; however, existing text analytics tools mostly focus on the semantic dimension of language. The language-action perspective (LAP) emphasizes pragmatics; not what people say but, rather, what they do with language. Adopting the design science paradigm, we propose a LAP-based text analytics framework to support sense-making in online discourse. The proposed framework is specifically intended to address the two aforementioned challenges associated with sense-making in online discourse: the need for greater coherence and better understanding of actions. We rigorously evaluate a system that is developed based on the framework in a series of experiments using a test bed encompassing social media data from multiple channels and industries. The results demonstrate the utility of each individual component of the system, and its underlying framework, in comparison with existing benchmark methods. Furthermore, the results of a user experiment involving hundreds of practitioners, and a four-month field experiment in a large organization, underscore the enhanced sense-making capabilities afforded by text analytics grounded in LAP principles. The results have important implications for online sense-making and social media analytics.

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