Since the first so-called “medical marijuana” legislation was passed in California in 1996, a total of twenty states and the District of Columbia have passed laws permitting limited use of cannabis. Despite the changes in state laws, cannabis remains illegal for any purpose under federal law. Changes in state laws have coincided with a renewed interest in the substance for the treatment of a variety of conditions. There has been a significant increase in published data over the past twenty years examining the efficacy of cannabis as an appetite stimulant, antiemetic agent, and analgesic adjuvant. The purpose of this meta-analysis was to synthesize published data on cannabis use as an analgesic agent. Five studies meeting inclusion criteria were located through searches of online databases, review of reference lists, author correspondence, and review of clinical trials databases. Meta-analysis was conducted using fixed-effects modeling. The overall effect of mean reduction of pain intensity was -4.895 (Z-score) with an associated p value of 0.003. The combined standardized mean difference (SMD) was -0.362 (CI -0.507 to -0.217), indicating on average a moderate significant reduction in pain intensity for patients with chronic pain. As the legal status of the substance evolves, additional research is needed to establish evidence-based clinical recommendations regarding the use of medicinal cannabis in pain management.

Indiana University-Purdue University Indianapolis (IUPUI) / Symptoms of post-traumatic stress disorder (PTSD) are a common comorbidity in veterans seeking treatment of chronic musculoskeletal pain (CMP). However, little is known regarding the mutual influence of PTSD and CMP in this population. Using cross-sectional and longitudinal data from a randomized clinical trial evaluating a stepped care intervention for CMP in Iraq/Afghanistan veterans (ESCAPE), this dissertation examined the relationships between PTSD and CMP along with other factors including depression, anxiety, catastrophizing and health-related quality of life. The Classification and Regression Tree (CART) analysis was conducted to identify key factors associated with baseline PTSD besides CMP severity. A series of statistical analyses including logistical regression analysis, mixed model repeated measure analysis, confirmatory factor analysis and cross-lagged panel analysis via structural equation modeling were conducted to test five competing models of PTSD symptom clusters, and to examine the mutual influences of PTSD symptom clusters and CMP outcomes. Results showed baseline pain intensity and pain disability predicted PTSD at 9 months. And baseline PTSD predicted improvement of pain disability at 9 months. Moreover, direct relationships were found between PTSD and the disability component of CMP, and indirect relationships were found between PTSD, CMP and CMP components (intensity and disability) mediated by depression, anxiety and pain catastrophizing. Finally, the coexistence of PTSD and more severe pain was associated with worse SF-36 Physical Component Summary (PCS) and Mental Component Summary (MCS) scores. Together these findings provided empirical support for the mutual maintenance theory.