Self-Management of Chronic Pain: Interventions, Strategies, Barriers, and Facilitators

Background & Purpose: Chronic pain is a prevalent chronic condition for which the best management options rarely provide complete relief. Individuals with chronic pain with neuropathic characteristics (NC) report more severe pain and experience less relief from interventions. Little is known about current self-management practices. The purpose of this dissertation was to inform self-management of chronic pain with and without NC at the individual, health system, and policy levels using the Innovative Care for Chronic Conditions Framework. Methods: The study included a systematic search and review and cross-sectional survey. The review evaluated the evidence for chronic pain self-management interventions and explored the role of health care providers in supporting self-management. The survey was mailed to 8,000 randomly selected Canadians in November 2011, and non-respondents were followed-up in May 2012. Screening questions were included for both chronic pain and NC. The questionnaire captured pain descriptions, self-management strategies, and self-management barriers, and facilitators. Results: Findings of the review suggested that self-management interventions are effective in improving pain and health outcomes. Health care professionals provided self-management advice and referred individuals to self-management interventions. The questionnaire was completed by 1,520 Canadians. Those with chronic pain (n=710) identified primary care physicians as the most helpful pain management professional. Overall, use of non-pharmaceutical medical self-management strategies was low. While use positive emotional self-management strategies was high, individuals with NC were more likely to use negative emotional self-management strategies compared to those without NC. Multiple self-management barriers and facilitators were identified, however those with NC were more likely than those without NC to experience low self-efficacy, depression and severe pain which may impair the ability to self-management. Conclusions: Health care professionals have the opportunity to improve chronic pain outcomes by providing self-management advice, referring to self-management interventions, and addressing self-management barriers and facilitators. Individuals with NC may require additional health services to address their greater self-management challenges, and further research is needed to identify non-pharmaceutical interventions effective in relieving chronic pain with NC. Public policy is needed to facilitate health systems in providing long-term self-management support for individuals with chronic pain.

Process Monitoring and Defect Detection of Additive Manufacturing Using Inline Coherent Imaging

With applications ranging from aerospace to biomedicine, additive manufacturing (AM) has been revolutionizing the manufacturing industry. The ability of additive techniques, such as selective laser melting (SLM), to create fully functional, geometrically complex, and unique parts out of high strength materials is of great interest. Unfortunately, despite numerous advantages afforded by this technology, its widespread adoption is hindered by a lack of on-line, real time feedback control and quality assurance techniques. In this thesis, inline coherent imaging (ICI), a broadband, spatially coherent imaging technique, is used to observe the SLM process in 15 - 45 $\mu m$ 316L stainless steel. Imaging of both single and multilayer builds is performed at a rate of 200 $kHz$, with a resolution of tens of microns, and a high dynamic range rendering it impervious to blinding from the process beam. This allows imaging before, during, and after laser processing to observe changes in the morphology and stability of the melt. Galvanometer-based scanning of the imaging beam relative to the process beam during the creation of single tracks is used to gain a unique perspective of the SLM process that has been so far unobservable by other monitoring techniques. Single track processing is also used to investigate the possibility of a preliminary feedback control parameter based on the process beam power, through imaging with both coaxial and 100 $\mu m$ offset alignment with respect to the process beam. The 100 $\mu m$ offset improved imaging by increasing the number of bright A-lines (i.e. with signal greater than the 10 $dB$ noise floor) by 300\%. The overlap between adjacent tracks in a single layer is imaged to detect characteristic fault signatures. Full multilayer builds are carried out and the resultant ICI images are used to detect defects in the finished part and improve upon the initial design of the build system. Damage to the recoater blade is assessed using powder layer scans acquired during a 3D build. The ability of ICI to monitor SLM processes at such high rates with high resolution offers extraordinary potential for future advances in on-line feedback control of additive manufacturing.