Developing consensus on core outcome sets of domains for acute, the transition from acute to chronic, recurrent/episodic, and chronic pain: results of the INTEGRATE-pain Delphi process.

Background: Pain is the leading cause of disability worldwide among adults and effective treatment options remain elusive. Data harmonization efforts, such as through core outcome sets (COS), could improve care by highlighting cross-cutting pain mechanisms and treatments. Existing pain-related COS often focus on specific conditions, which can hamper data harmonization across various pain states.

Challenges and opportunities for research clinicians interested in pain: results of a survey.

The National Institutes of Health and its independent advisors recognize the need to develop a strong pain research workforce and provide opportunities, particularly for clinicians, to pursue research careers. A survey was conducted to better understand the challenges facing the clinical pain research community. Respondents reported that time and funding to pursue research were the most critical factors either enabling or holding them back from a research career.

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures.

Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention.

Comparing the clinical and cost-effectiveness of remote (telehealth and online) cognitive behavioral therapy-based treatments for high-impact chronic pain relative to usual care: study protocol for the RESOLVE multisite randomized control trial.

Background: Cognitive behavioral therapy for chronic pain (CBT-CP) is an effective but underused treatment for high-impact chronic pain. Increased access to CBT-CP services for pain is of critical public health importance, particularly for rural and medically underserved populations who have limited access due to these services being concentrated in urban and high income areas. Making CBT-CP widely available and more affordable could reduce barriers to CBT-CP use.

NIH HEAL Clinical Data Elements (CDE) implementation: NIH HEAL Initiative IMPOWR network IDEA-CC.

Objective: The National Institutes of Health (NIH) HEAL Initiative is making data findable, accessible, interoperable, and reusable (FAIR) to maximize the value of the unprecedented federal investment in pain and opioid-use disorder research. This involves standardizing the use of common data elements (CDE) for clinical research.

Methods: This work describes the process of the selection, processing, harmonization, and design constraints of CDE across a pain and opioid use disorder clinical trials network (NIH HEAL IMPOWR).

Multi-Site Observational Study to Assess Biomarkers for Susceptibility or Resilience to Chronic Pain: The Acute to Chronic Pain Signatures (A2CPS) Study Protocol.

Chronic pain has become a global health problem contributing to years lived with disability and reduced quality of life. Advances in the clinical management of chronic pain have been limited due to incomplete understanding of the multiple risk factors and molecular mechanisms that contribute to the development of chronic pain. The Acute to Chronic Pain Signatures (A2CPS) Program aims to characterize the predictive nature of biomarkers (brain imaging, high-throughput molecular screening techniques, or "omics," quantitative sensory testing, patient-reported outcome assessments and functional assessments) to identify individuals who will develop chronic pain following surgical intervention.

NIH's Helping to End Addiction Long-term Initiative (NIH HEAL Initiative) Clinical Pain Management Common Data Element Program.

The Helping to End Addiction Long-term Initiative (NIH HEAL Initiative) is an aggressive trans-NIH effort to speed solutions to stem the national opioid public health crisis, including through improved pain management. Toward this end, the NIH HEAL Initiative launched a common data element (CDE) program to ensure that NIH-funded clinical pain research studies would collect data in a standardized way. NIH HEAL Initiative staff launched a process to determine which pain-related core domains should be assessed by every clinical pain study and what questionnaires are required to ensure that the data is collected uniformly.

Guest editorial: Psychologists aim to HEAL the opioid and pain crises.

The opioid and pain crises affect every domain of family and community life with two million Americans living with opioid addiction, and 46,802 people dying from opioid overdoses in 2018 alone (National Center for Health Statistics, 2019). In addition, over 50 million Americans experience chronic pain, and half of those people suffer from chronic pain daily. Opioids are widely used to treat acute and chronic pain, and the lack of widespread access to nonpharmacological strategies to manage pain has contributed to the misuse of opioids.

Treatment of a Large Cohort of Veterans Experiencing Musculoskeletal Disorders with Spinal Cord Stimulation in the Veterans Health Administration: Veteran Characteristics and Outcomes.

Objective: Spinal cord stimulator (SCS) implantation is used to treat chronic pain, including painful musculoskeletal disorders (MSDs). This study examined the characteristics and outcomes of veterans receiving SCSs in Veterans Health Administration (VHA) facilities.

Methods: The sample was drawn from the MSD Cohort and limited to three MSDs with the highest number of implants (N=815,475).

Core competencies for the emerging specialty of pain psychology.

The Institute of Medicine (IOM) has reported that approximately 100 million Americans experience chronic pain. The IOM report on pain and the subsequent National Pain Strategy (NPS) issued by the U.S.

Using Virtual Human Technology to Examine Weight Bias and the Role of Patient Weight on Student Assessment of Pediatric Pain.

The purpose of the study was to investigate the influence of weight bias and demographic characteristics on the assessment of pediatric chronic pain. Weight status, race, and sex were manipulated in a series of virtual human (VH) digital images of children. Using a web-based platform, 96 undergraduate students with health care-related majors (e.

Racial and Ethnic Differences in Total Knee Arthroplasty in the Veterans Affairs Health Care System, 2001-2013.

Objective: To examine black-white and Hispanic-white differences in total knee arthroplasty from 2001 to 2013 in a large cohort of patients diagnosed with osteoarthritis (OA) in the Veterans Affairs (VA) health care system.

Methods: Data were from the VA Musculoskeletal Disorders cohort, which includes data from electronic health records of more than 5.4 million veterans with musculoskeletal disorders diagnoses.

Assessment of the Influence of Demographic and Professional Characteristics on Health Care Providers' Pain Management Decisions Using Virtual Humans.

Disparities in health care associated with patients' gender, race, and age are well documented. Previous studies using virtual human (VH) technology have demonstrated that provider characteristics may play an important role in pain management decisions. However, these studies have largely emphasized group differences.

Effect of a perspective-taking intervention on the consideration of pain assessment and treatment decisions.

Objectives: Pain is often poorly managed, highlighting the need to better understand and treat patients' pain. Research suggests that pain is assessed and treated differently depending on patient sex, race, and/or age. Perspective-taking, whereby one envisions the perspective of another, has been found to reduce racial disparities in pain management.

The influence of health care professional characteristics on pain management decisions.

Objective: Evidence suggests that patient characteristics such as sex, race, and age influence the pain management decisions of health care providers. Although this signifies that patient demographics may be important determinants of health care decisions, pain-related care also may be impacted by the personal characteristics of the health care practitioner. However, the extent to which health care provider characteristics affect pain management decisions is unclear, underscoring the need for further research in this area.

Using virtual human technology to provide immediate feedback about participants' use of demographic cues and knowledge of their cue use.

Unlabelled: Demographic characteristics have been found to influence pain management decisions, but limited focus has been placed on participants' reactions to feedback about their use of sex, race, or age to make these decisions. The present study aimed to examine the effects of providing feedback about the use of demographic cues to participants making pain management decisions. Participants (N = 107) viewed 32 virtual human patients with standardized levels of pain and provided ratings for virtual humans' pain intensity and their treatment decisions.

The role of anger in psychosocial subgrouping for patients with low back pain.

Background: Low back pain (LBP) is a common and costly condition that often becomes chronic if not properly addressed. Recent research has shown that psychosocial symptoms can complicate LBP, necessitating more comprehensive screening measures.

Aim: The present study investigated the role of psychosocial factors, including anger regulation, in pain and disability using a screening measure designed for LBP treated with physical therapy.

The impact of patients' gender, race, and age on health care professionals' pain management decisions: an online survey using virtual human technology.

Background: Previous literature indicates that biases exist in pain ratings. Healthcare professionals have been found to use patient demographic cues such as sex, race, and age when making decisions about pain treatment. However, there has been little research comparing healthcare professionals' (i.

Pain assessment and treatment decisions for virtual human patients.

Laypeople and healthcare professionals use demographic cues when making pain management decisions. These decisions can negatively affect patient outcomes. This study examined whether laypeople base their pain management decisions in part on pain-related postures and demographic cues.

The influence of sex, race, and age on pain assessment and treatment decisions using virtual human technology: a cross-national comparison.

Purpose: Studies in the United States have found that patients' sex, race, and age influence the pain assessment and treatment decisions of laypeople and medical professionals. However, there is limited research as to whether people of other nationalities make pain management decisions differently based on demographic characteristics. Therefore, the purpose of the following study was to compare pain assessment and treatment decisions of undergraduate students in Jordan and the United States as a preliminary examination of nationality as a potential proxy for cultural differences in pain decisions.

The perception of pain in others: how gender, race, and age influence pain expectations.

Unlabelled: Sex, race/ethnic, and age differences in pain have been reported in clinical and experimental research. Gender role expectations have partly explained the variability in sex differences in pain, and the Gender Role Expectations of Pain questionnaire (GREP) was developed to measure sex-related stereotypic attributions about pain. It is hypothesized that similar expectations exist for age- and race-related pain decisions.

Virtual human technology: patient demographics and healthcare training factors in pain observation and treatment recommendations.

Background: Patients' sex, race, and age have been found to affect others' perception of their pain. However, the influence of these characteristics on treatment recommendations from laypersons and healthcare providers is understudied.

Design: To address this issue, 75 undergraduates and 107 healthcare trainees (HTs) used a web-based delivery system to view video clips of virtual human (VH) patients presenting with different standardized levels of pain.