Overview
Persistent pain is a public health epidemic. The current protocol seeks to develop technology to aid patients' tracking of patients' pain, medications and pain-related variables. The investigators seek to talk with patients in co-investigator's clinic to solicit feedback, as well as pilot test the technology with pain patients.
Description
Chronic pain affects over 100 million Americans, costs the US over $630 billion annually, and reduces quality of life. It is among the most clinically challenging and financially burdensome conditions facing clinicians and healthcare organizations. Sleep disturbance is common in chronic pain conditions with some studies reporting a prevalence as high as 70%-88%. Psychiatric disorders, including substance abuse and mood disorders are prevalent in chronic pain and are associated with impairment and decreased quality of life. Sleep is increasingly recognized as a critical regulator of mental health. Taken together, epidemiological, cross-sectional, and prospective studies support the hypothesis that insomnia, chronic pain, and depression are mutually interacting, each increasing the risk for the emergence and/or exacerbation of the other. The gold standard of chronic pain management is multidisciplinary pain treatment (MPT), but patients rarely receive MPT secondary to limited access and a severe shortage of pain management specialists. Thus, there is an urgent need for empirically supported, cost-effective multidisciplinary pain self-management options that are accessible to patients and trusted by primary and tertiary care providers. To address this problem, the investigators' group in collaboration with the Johns Hopkins Technology Innovation Center (TIC) has developed a mobile chronic pain, medication and symptom tracking digital technology platform designed to eventually support multidisciplinary pain treatment by enhancing patient-provider communication and delivering comprehensive, personalized, interactive evidence-based pain management strategies. The investigators' App (version 1.3) is currently able to collect self-report data (i.e., pain; sleep; mood; catastrophizing; stress; pain flares) and continuous, passively collected wearable biosensor data (i.e., heart rate; breathing; sleep; heart rate variability/stress). The investigators propose a prospective, observational proof of concept study to demonstrate feasibility and adherence while establishing the psychometric properties of a mobile pain App and to compare these data with passively collected physiological data and laboratory indices of pain in patients with chronic low back pain (CLBP).
Eligibility
Inclusion Criteria:
- ≥ 21 years of age
- Pain duration > 3 months
- Average pain level of >3 out of 10 (0=no pain; 10=worst pain imaginable)
- English fluency
- Are not scheduled to undergo any medical procedures during the course of the study
- Have a physician-confirmed medical diagnosis associated with chronic pain
- Are willing to comply with the study protocol and give written informed consent. Patients taking non-narcotic analgesics must be on a stable dose one month prior to participation.
Exclusion Criteria:
- Delirium, dementia, or cognitive impairment (i.e., Mini Mental State Exam score <24)
- Unstable major psychiatric disorder or history of schizophrenia
- Beck Depression Inventory score >30 or report of suicidal ideation
- Active substance abuse;
- Refusal to provide access to relevant medical record information.