Funded Projects

Cancer remains a leading cause of death among Hispanic/Latino populations in the United States. Compared with non-Hispanic Whites, Hispanic/Latino cancer patients are more likely to experience poor quality of life and inadequate cancer-related care, including less effective pain relief and poor patient‒provider communication. Additionally, Hispanic/Latino populations often have inadequate access to pain treatment, due to both social disparities and language barriers. However, most behavioral and psychosocial oncology research continues to focus on non-Hispanic Whites, and empirically validated and effective treatment interventions, particularly psychosocial interventions, are often not available in Spanish. This project will generate a Spanish-language version of the painTRAINER internet-based coping skills training program that is both linguistically and culturally sensitive and will evaluate its feasibility and acceptability in Hispanic/Latino patients with persistent cancer-related pain.

Cancer remains a leading cause of death among Hispanic/Latino populations in the United States. Compared with non-Hispanic Whites, Hispanic/Latino cancer patients are more likely to experience poor quality of life and inadequate cancer-related care, including less effective pain relief and poor patient‒provider communication. Additionally, Hispanic/Latino populations often have inadequate access to pain treatment, due to both social disparities and language barriers. However, most behavioral and psychosocial oncology research continues to focus on non-Hispanic Whites, and empirically validated and effective treatment interventions, particularly psychosocial interventions, are often not available in Spanish. This project will generate a Spanish-language version of the painTRAINER internet-based coping skills training program that is both linguistically and culturally sensitive and will evaluate its feasibility and acceptability in Hispanic/Latino patients with persistent cancer-related pain.

Pain Coping Skills Training (PCST) uses a cognitive behavioral therapy (CBT) approach to teach patients cognitive and behavioral coping skills shown to reduce pain and pain interference (e.g., relaxation, distraction, cognitive restructuring, activity pacing). Randomized controlled trials show that PCST and similar CBT-based interventions, when delivered in a traditional in-person format, can improve pain and functioning in people with cancer and other conditions. Yet these interventions are underused in clinical care due to barriers such as high resource costs, a shortage of therapists trained to deliver them, and travel requirements for patients. This trial aims to deliver evidence-based behavioral pain interventions such as PCST with methods capable of overcoming barriers currently limiting patient access. This will be investigated using a two-arm trial comparing pain relief with the following interventions: painTRAINER in clinic with eight web-based follow-up sessions; enhanced usual care.

Sickle cell disease (SCD) is an inherited hematologic disorder accompanied by severe pain, inflammation, and vascular injury. We propose that nociceptor activation by ongoing hypoxia/reperfusion (H/R) injury leads to the release of neuropeptides by sensory nerves in the skin, stimulating vascular insult and mast cell activation in SCD. In turn, mast cell tryptase activates protease-activated receptor 2 on sensory nerve endings, resulting in exaggerated neuroinflammation, vascular injury, and central sensitization. Our general hypothesis is that neurogenic inflammation contributes to pain in SCD and that cannabinoids provide analgesia by disrupting neurogenic inflammation and nociceptor sensitization. We also hypothesize that EEG and functional MRI can be used to optimize analgesic treatments in SCD. We propose to use transgenic sickle mice, and individual cells involved in evoking pain, to perform this translational study. A proof of principle study in humans will examine the effect of cannabis on pain in sickle patients.

This project supports a post-doctoral trainee to develop the skills and knowledge needed to pursue a career in clinical pain research. The research will involve optimizing a GetActive mind-body activity program to overcome barriers that prevent disadvantaged older adult populations in community health clinics from access to non-pharmacological pain management strategies. The research will include qualitative analysis of secondary data, a literature review to evaluate methods, and feasibility for establishing a community advisory board for the GetActive project.

This research project will include focus group interviews with clinicians, patients, medical interpreters, and healthcare administrators to identify barriers and facilitators to administering the GetActive+ intervention in a group visit at a clinic for older adults with chronic pain, to inform development of a therapy manual. The project will then test the GetActive+ intervention for changes in physical function immediately post-intervention and after 6 months, as well as for changes in pain, sleep, depression, and anxiety at both time points. This research will also assess feasibility, acceptability, fidelity, and adoption of the intervention with patients, providers, and healthcare staff. 

Chronic low back pain (cLBP) is recurrent and often nonresponsive to conservative treatments. Biomechanists, physical therapists, and surgeons each utilize a variety of tools and techniques to assess and interpret qualitative movement changes to understand potential mechanical and neurological sources of low back pain and as critical elements in their treatment paradigm. However, objectively characterizing and communicating this information is currently impossible, since clinically feasible (i.e., cost-effective, objective, and accurate) tools and quantitative benchmarks do not exist. This research addresses the challenge to improve cLBP outcomes through the use of unique, inexpensive, screen-printable, elastomer-based, nanocomposite, piezoresponsive sensors, which will be integrated into a SPInal Nanosensor Environment (SPINE) sense system to measure lumbar kinematics and provide an objective, quantitative platform for diagnosis, monitoring, and follow-up assessment of cLBP.

Although digital health technologies are now widely available for both therapeutic and monitoring applications, there are wide variations in patient knowledge, attitudes, beliefs, and preferences regarding their uptake and effectiveness. There are also sociodemographic variations in willingness to participate in digital health research studies, both for chronic pain and other common disorders. However, few efforts have systematically examined patient-level predictors of digital health uptake and benefit among diverse individuals who experience chronic pain. This research will employ mixed methods to examine variations in engagement and benefit among diverse participants in a large clinical trial examining the benefits of virtual reality for treatment of chronic lower back pain.

Therapeutic virtual reality (VR) has emerged as a promising and evidence-based treatment modality for musculoskeletal pain, including chronic low back pain (cLBP). Users of VR wear a pair of goggles with a close-proximity stereoscopic screen that creates a sensation of being transported into lifelike, three-dimensional worlds. By stimulating the visual cortex while engaging other senses, VR modulates the user’s processing of nociceptive stimuli. Functional magnetic resonance imaging (fMRI) of the brain reveals that VR has similar effects on the sensory and insular cortex as opioids, and head-to-head trials show that VR achieves similar or greater analgesia as hydromorphone. Since there are few data regarding long-term efficacy and safety of VR in cLBP, this study will measure patient-reported outcomes, biometric outcomes, and opioid use in nonspecific cLBP patients under various experimental conditions using VR therapy.

Identifying optimal chronic low back pain treatments on a patient-specific basis is an important and unresolved challenge. Tailoring interventions according to patient movement characteristics is one option. This research is characterizing patients based on spinal motion during functional tasks and daily activities and will use artificial intelligence to objectively characterize motions of the spine during both clinical assessments and day-to-day life. During clinical assessments, participants will be asked to perform functional tasks while wearing motion sensors. Data collected from the sensors will be used to identify tasks of interest, such as activities of daily living and aberrant/painful motions. An artificial intelligence approach will then interpret data collected continuously during assessment in patients’ homes over a 7-day testing period. Ultimately, this data could be used to help clinicians tailor treatments that are responsive to a patient’s real-world functional impairments.

The NIH Back Pain Consortium (BACPAC) Research Program brings together leading centers with expertise in studying and treating chronic low back pain to advance understanding of the mechanisms that underlie the condition and to identify novel treatment strategies. BACPAC is undertaking a multisite precision medicine clinical trial taking into account patient-specific information to understand which patients with chronic low back pain respond best to various nonopioid, evidence-based treatments. The trial seeks to enroll a racially, ethnically, and socioeconomically diverse patient population to ensure that the results are applicable to all Americans with chronic low back pain. This project aims to develop comprehensive recruitment and retention plans for study sites that can recruit from historically underrepresented populations in clinical research (e.g., Black and Hispanic populations) and to provide dedicated financial resources to engage patients from these populations using tailored, culturally appropriate strategies.

The University of California, San Francisco, as part of the Back Pain Consortium (BACPAC) Research Program, has established a Core Center for Patient-centric Mechanistic Phenotyping in Chronic Low Back Pain (REACH). The main goal of REACH is to define different subtypes (phenotypes) of chronic low back pain as well as to identify underlying pain mechanisms that can lead to effective, personalized treatments for patients across all population subgroups. To achieve this goal, REACH is, or will be, participating in several clinical trials, and it is imperative that the patients participating in these trials reflect the diversity of the U.S. population. Therefore, this project seeks to adapt methods that have successfully improved minority participation in other settings as well as to develop and deploy digital strategies that can promote recruitment and engagement of patients from marginalized populations.

Current diagnostics and treatments of chronic low back pain (cLBP) rely primarily on subjective metrics and do not target all the multidimensional biopsychosocial mechanisms. This multidisciplinary effort will develop and validate a digital health platform and provide meaningful data-driven metrics that enable an integrated approach to clinical evaluation and treatment of cLBP. This platform will facilitate the use of quantitative spinal motion metrics (function), patient-reported outcomes, and patient preference information to enable deep patient phenotyping and inform clinical decision making on personalized treatments in order to improve outcomes. This effort will involve software and hardware development to enable data collection, analysis, and visualization in clinical settings. The outcome of this project will be a digital health platform with data to support regulatory submission for clinical use. At the end of this effort, the researchers will have a validated tool for integration in clinical research studies supported by the BACPAC Consortium.