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      Placebo hypoalgesia: racial differences

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          Abstract

          No large-cohort studies that examine potential racial effects on placebo hypoalgesic effects exist. To fill this void, we studied placebo effects in healthy and chronic pain participants self-identified as either African American/black (AA/black) or white. We enrolled 372 study participants, 186 with a diagnosis of temporomandibular disorder (TMD) and 186 race-, sex-, and age-matched healthy participants to participate in a placebo experiment. Using a well-established paradigm of classical conditioning with verbal suggestions, each individual pain sensitivity was measured to calibrate the temperatures for high- and low-pain stimuli in the conditioning protocol. These 2 temperatures were then paired with a red and green screen, respectively, and participants were told that the analgesic intervention would activate during the green screens to reduce pain. Participants then rated the painfulness of each stimulus on a visual analog scale ranging from 0 to 100. Racial influences were tested on conditioning strength, reinforced expectations, and placebo hypoalgesia. We found that white participants reported greater conditioning effects, reinforced relief expectations, and placebo effects when compared with their AA/black counterparts. Racial effects on placebo were observed in TMD, although negligible, short-lasting, and mediated by conditioning strength. Secondary analyses on the effect of experimenter-participant race and sex concordance indicated that same experimenter-participant race induced greater placebo hypoalgesia in TMDs while different sex induced greater placebo hypoalgesia in healthy participants. This is the first and largest study to analyze racial effects on placebo hypoalgesia and has implications for both clinical research and treatment outcomes.

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          An Index and Test of Linear Moderated Mediation.

          I describe a test of linear moderated mediation in path analysis based on an interval estimate of the parameter of a function linking the indirect effect to values of a moderator-a parameter that I call the index of moderated mediation. This test can be used for models that integrate moderation and mediation in which the relationship between the indirect effect and the moderator is estimated as linear, including many of the models described by Edwards and Lambert ( 2007 ) and Preacher, Rucker, and Hayes ( 2007 ) as well as extensions of these models to processes involving multiple mediators operating in parallel or in serial. Generalization of the method to latent variable models is straightforward. Three empirical examples describe the computation of the index and the test, and its implementation is illustrated using Mplus and the PROCESS macro for SPSS and SAS.
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            Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) for Clinical and Research Applications: recommendations of the International RDC/TMD Consortium Network* and Orofacial Pain Special Interest Group†.

            The original Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) Axis I diagnostic algorithms have been demonstrated to be reliable. However, the Validation Project determined that the RDC/TMD Axis I validity was below the target sensitivity of ≥ 0.70 and specificity of ≥ 0.95. Consequently, these empirical results supported the development of revised RDC/TMD Axis I diagnostic algorithms that were subsequently demonstrated to be valid for the most common pain-related TMD and for one temporomandibular joint (TMJ) intra-articular disorder. The original RDC/TMD Axis II instruments were shown to be both reliable and valid. Working from these findings and revisions, two international consensus workshops were convened, from which recommendations were obtained for the finalization of new Axis I diagnostic algorithms and new Axis II instruments. Through a series of workshops and symposia, a panel of clinical and basic science pain experts modified the revised RDC/TMD Axis I algorithms by using comprehensive searches of published TMD diagnostic literature followed by review and consensus via a formal structured process. The panel's recommendations for further revision of the Axis I diagnostic algorithms were assessed for validity by using the Validation Project's data set, and for reliability by using newly collected data from the ongoing TMJ Impact Project-the follow-up study to the Validation Project. New Axis II instruments were identified through a comprehensive search of the literature providing valid instruments that, relative to the RDC/TMD, are shorter in length, are available in the public domain, and currently are being used in medical settings. The newly recommended Diagnostic Criteria for TMD (DC/TMD) Axis I protocol includes both a valid screener for detecting any pain-related TMD as well as valid diagnostic criteria for differentiating the most common pain-related TMD (sensitivity ≥ 0.86, specificity ≥ 0.98) and for one intra-articular disorder (sensitivity of 0.80 and specificity of 0.97). Diagnostic criteria for other common intra-articular disorders lack adequate validity for clinical diagnoses but can be used for screening purposes. Inter-examiner reliability for the clinical assessment associated with the validated DC/TMD criteria for pain-related TMD is excellent (kappa ≥ 0.85). Finally, a comprehensive classification system that includes both the common and less common TMD is also presented. The Axis II protocol retains selected original RDC/TMD screening instruments augmented with new instruments to assess jaw function as well as behavioral and additional psychosocial factors. The Axis II protocol is divided into screening and comprehensive self report instrument sets. The screening instruments' 41 questions assess pain intensity, pain-related disability, psychological distress, jaw functional limitations, and parafunctional behaviors, and a pain drawing is used to assess locations of pain. The comprehensive instruments, composed of 81 questions, assess in further detail jaw functional limitations and psychological distress as well as additional constructs of anxiety and presence of comorbid pain conditions. The recommended evidence-based new DC/TMD protocol is appropriate for use in both clinical and research settings. More comprehensive instruments augment short and simple screening instruments for Axis I and Axis II. These validated instruments allow for identification of patients with a range of simple to complex TMD presentations.
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              Prevalence of Chronic Pain and High-Impact Chronic Pain Among Adults — United States, 2016

              Chronic pain, one of the most common reasons adults seek medical care ( 1 ), has been linked to restrictions in mobility and daily activities ( 2 , 3 ), dependence on opioids ( 4 ), anxiety and depression ( 2 ), and poor perceived health or reduced quality of life ( 2 , 3 ). Population-based estimates of chronic pain among U.S. adults range from 11% to 40% ( 5 ), with considerable population subgroup variation. As a result, the 2016 National Pain Strategy called for more precise prevalence estimates of chronic pain and high-impact chronic pain (i.e., chronic pain that frequently limits life or work activities) to reliably establish the prevalence of chronic pain and aid in the development and implementation of population-wide pain interventions ( 5 ). National estimates of high-impact chronic pain can help differentiate persons with limitations in major life domains, including work, social, recreational, and self-care activities from those who maintain normal life activities despite chronic pain, providing a better understanding of the population in need of pain services. To estimate the prevalence of chronic pain and high-impact chronic pain in the United States, CDC analyzed 2016 National Health Interview Survey (NHIS) data. An estimated 20.4% (50.0 million) of U.S. adults had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain, with higher prevalences of both chronic pain and high-impact chronic pain reported among women, older adults, previously but not currently employed adults, adults living in poverty, adults with public health insurance, and rural residents. These findings could be used to target pain management interventions. NHIS is a cross-sectional, in-person, household health survey of the civilian noninstitutionalized U.S. population, conducted by the National Center for Health Statistics (NCHS).* Data from the 2016 Sample Adult Core for adults aged ≥18 years (33,028; response rate = 54.3%) † were analyzed. Information about pain was collected through responses to the following questions: “In the past six months, how often did you have pain? Would you say never, some days, most days, or every day?” and “Over the past six months, how often did pain limit your life or work activities? Would you say never, some days, most days, or every day?” Chronic pain was defined as pain on most days or every day in the past 6 months, as recommended by the International Association for the Study of Pain, § modified to account for intermittent pain, and used in both the National Pain Strategy and National Institutes of Health Task Force on Chronic Back Pain ( 6 ). As suggested in the National Pain Strategy, high-impact chronic pain was defined as chronic pain that limited life or work activities on most days or every day during the past 6 months ( 5 ). The prevalence of chronic pain and high-impact chronic pain (both crude and age-adjusted, with 95% confidence intervals) were estimated for the U.S. adult population overall and by various sociodemographic characteristics. These characteristics, collected with the Family Core questionnaire, included age, sex, race/ethnicity, education level, current employment status, ¶ poverty status (calculated using NHIS imputed income files),** veteran status, health insurance coverage type (reported separately for adults aged <65 and ≥65 years), and urbanicity. All prevalence estimates met NCHS reliability standards. †† Because pain prevalence varies by age, age-adjusted estimates were used in comparisons of chronic pain and high-impact chronic pain between subgroups. Based on two-tailed Z-tests, all reported differences between subgroups are statistically significant (unless otherwise noted; p<0.05). Analyses were conducted using statistical software that accounts for the stratification and clustering of households in the NHIS sampling design. Estimates incorporated the final sample adult weights adjusted for nonresponse and calibrated to population control totals to enable generalization to the civilian noninstitutionalized population aged ≥18 years. In 2016, an estimated 20.4% of U.S. adults (50.0 million) had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain (Table), with higher prevalence associated with advancing age. Age-adjusted prevalences of both chronic pain and high-impact chronic pain were significantly higher among women, adults who had worked previously but were not currently employed, adults living in or near poverty, and rural residents. In addition, the age-adjusted prevalences of chronic pain and high-impact chronic pain were significantly lower among adults with at least a bachelor’s degree compared with all other education levels. TABLE Prevalence of chronic pain* and high impact chronic pain † among U.S. adults aged ≥18 years, by sociodemographic characteristics—National Health Interview Survey, 2016 Characteristic Chronic pain* High-impact chronic pain† Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Total 50,009,000 20.4 (19.7–21.0) 19.4 (18.7–20.0) 19,611,000 8.0 (7.6–8.4) 7.5 (7.1–7.9) Age group (yrs) 18–24 2,082,000 7.0 (5.8–8.5) —** 446,000 1.5 (0.9–2.3) —** 25–44 11,042,000 13.2 (12.3–14.1) —** 3,681,000 4.4 (3.9–5.0) —** 45–64 23,269,000 27.8 (26.6–29.0) —** 10,044,000 12.0 (11.2–12.9) —** 65–84 11,808,000 27.6 (26.4–29.0) —** 4,578,000 10.7 (9.9–11.6) —** ≥85 1,766,000 33.6 (30.1–37.3) —** 830,000 15.8 (13.2–18.9) —** Sex Male 21,989,000 18.6 (17.7–19.5) 17.8 (17.0–18.7) 8,276,000 7.0 (6.5–7.6) 6.7 (6.2–7.3) Female 28,049,000 22.1 (21.2–23.0) 20.8 (19.9–21.6) 11,296,000 8.9 (8.4–9.4) 8.2 (7.7–8.7) Race/Ethnicity Hispanic 5,856,000 15.1 (13.6–16.7) 16.7 (15.2–18.4) 2,754,000 7.1 (6.0–8.3) 7.9 (6.9–9.2) White, non-Hispanic 36,226,000 23.0 (22.2–23.8) 21.0 (20.3–21.8) 13,230,000 8.4 (7.9–8.9) 7.4 (7.0–7.9) Black, non-Hispanic 5,148,000 17.9 (16.4–19.6) 17.8 (16.3–19.4) 2,387,000 8.3 (7.2–9.4) 8.1 (7.1–9.2) Other, non-Hispanic†† 2,774,000 13.8 (12.1–15.7) 14.4 (12.7–16.3) 1,326,000 6.6 (5.3–8.1) 7.0 (5.7–8.5) Education Less than high school 7,809,000 26.1 (24.2–28.2) 23.7 (21.7–25.7) 4,069,000 13.6 (12.3–15.2) 12.1 (10.7–13.7) High school/GED 14,441,000 23.7 (22.5–25.0) 22.6 (21.2–23.9) 5,910,000 9.7 (9.0–10.6) 9.1 (8.4–10.0) Some college 17,129,000 22.6 (21.5–23.8) 22.9 (21.8–24.0) 6,518,000 8.6 (7.9–9.4) 8.7 (8.0–9.5) Bachelor's degree or higher 10,383,000 13.4 (12.6–14.3) 12.4 (11.7–13.3) 2,944,000 3.8 (3.4–4.3) 3.5 (3.1–4.0) Employment status Employed 22,085,000 14.7 (14.1–15.5) 14.5 (13.8–15.2) 5,108,000 3.4 (3.1–3.8) 3.2 (2.9–3.6) Not employed; worked previously 25,737,000 31.5 (30.3–32.7) 29.2 (27.8–30.6) 13,318,000 16.3 (15.4–17.2) 16.1 (15.0–17.3) Not employed; never worked 2,083,000 15.9 (13.8–18.2) 18.7 (16.1–21.6) 1,192,000 9.1 (7.6–10.9) 11.1 (9.1–13.4) Poverty status <100% FPL 8,017,000 25.8 (24.2–27.6) 29.6 (27.9–31.3) 4,630,000 14.9 (13.6–16.4) 17.5 (16.1–19.0) 100% ≤FPL<200% 11,357,000 26.2 (24.5–27.9) 25.9 (24.2–27.7) 5,375,000 12.4 (11.3–13.6) 12.3 (11.2–13.5) 200% ≤FPL<400% 14,181,000 20.3 (19.2–21.4) 19.3 (18.3–20.4) 5,100,000 7.3 (6.7–8.1) 6.9 (6.2–7.6) ≥400% FPL 16,441,000 16.3 (15.4–17.2) 14.6 (13.8–15.5) 4,438,000 4.4 (4.0–4.9) 3.9 (3.5–4.4) Veteran Yes 6,379,000 29.1 (27.1–31.2) 26.0 (23.5–28.7) 2,258,000 10.3 (9.1–11.8) 9.2 (7.7–11.1) No 43,519,000 19.5 (18.9–20.2) 19.0 (18.4–19.7) 17,407,000 7.8 (7.4–8.2) 7.5 (7.1–7.9) Health insurance coverage§§ Age <65 yrs Private 20,539,000 15.1 (14.3–15.8) 14.0 (13.3–14.8) 5,713,000 4.2 (3.8–4.7) 3.8 (3.4–4.2) Medicaid and other public coverage 8,215,000 29.3 (27.3–31.5) 30.0 (28.0–32.2) 4,822,000 17.2 (15.6–19.0) 17.8 (16.2–19.6) Other 3,860,000 43.5 (40.0–47.2) 34.8 (31.2–38.7) 2,263,000 25.5 (22.5–28.8) 19.3 (16.4–22.5) Uninsured 3,683,000 16.2 (14.4–18.2) 17.0 (15.2–19.0) 1,319,000 5.8 (4.7–7.2) 6.2 (5.0–7.6) Age ≥65 yrs Private 5,606,000 28.0 (26.3–29.9) 28.1 (26.3–30.0) 1,842,000 9.2 (8.1–10.5) 9.3 (8.2–10.6) Medicare and Medicaid 1,428,000 42.5 (37.6–47.5) 42.5 (37.6–47.5) 816,000 24.3 (20.4–28.6) 24.3 (20.4–28.6) Medicare Advantage 3,094,000 25.5 (23.1–28.1) 25.8 (23.4–28.4) 1,226,000 10.1 (8.5–11.8) 10.3 (8.7–12.1) Medicare only, excluding Medicare Advantage 2,115,000 25.9 (23.1–28.9) 25.9 (23.1–28.9) 939,000 11.5 (9.5–13.7) 11.5 (9.5–13.7) Other 1,229,000 31.6 (27.2–36.3) 31.8 (27.4–36.5) 545,000 14.0 (11.3–17.3) 14.3 (11.5–17.7) Uninsured 106,000 —¶¶ —¶¶ 59,000 —¶¶ —¶¶ Urbanicity*** Urban 38,401,000 19.0 (18.3–19.7) 18.4 (17.7–19.0) 14,754,000 7.3 (6.9–7.8) 7.0 (6.6–7.4) Rural 11,575,000 26.9 (25.4–28.5) 24.0 (22.5–25.6) 4,776,000 11.1 (10.2–12.2) 9.8 (8.8–10.9) Abbreviations: CI = confidence interval; FPL = federal poverty level; GED = General Educational Development certification. * Pain on most days or every day in the past 6 months. † Chronic pain limiting life or work activities on most days or every day in the past 6 months. § The estimated numbers, rounded to 1,000s, were annualized based on the 2016 data. Counts for adults of unknown status (responses coded as “refused,” “don’t know,” or “not ascertained”) with respect to chronic pain and high-impact chronic pain are not shown separately in the table, nor are they included in the calculation of percentages (as part of either the denominator or the numerator), to provide a more straightforward presentation of the data. ¶ Estimates are age-adjusted using the projected 2000 U.S. population as the standard population and five age groups: 18–29, 30–39, 40–49, 50–59, and ≥60 years. ** Not applicable. †† Non-Hispanic other includes non-Hispanic American Indian and Alaska Native only, non-Hispanic Asian only, non-Hispanic Native Hawaiian and Pacific Islander only, and non-Hispanic multiple race. §§ Based on a hierarchy of mutually exclusive categories. Adults reporting both private and Medicare Advantage coverage were assigned to the Medicare Advantage category. “Uninsured” includes adults who had no coverage as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. “Other” comprises military health care including TRICARE, VA, and CHAMP-VA, and certain types of local and state governmental coverage, not including the Children’s Health Insurance Program. ¶¶ Estimates are considered unreliable according to the National Center for Health Statistics’ standards of reliability. *** Based on U.S. Census Bureau definitions of urban and rural areas (https://www2.census.gov/geo/pdfs/reference/ua/Defining_Rural.pdf). Whereas non-Hispanic white adults had a significantly higher age-adjusted prevalence of chronic pain than did all other racial and ethnic subgroups, no significant differences in high-impact chronic pain prevalence by race/ethnicity were observed. Similarly, the age-adjusted prevalence of chronic pain was significantly higher among veterans than among nonveterans, but no significant difference was observed in the prevalence of high-impact chronic pain. Among adults aged <65 years, the age-adjusted prevalences of chronic pain and high-impact chronic pain were higher among those with Medicaid and other public health care coverage or other insurance (e.g., Veteran’s Administration, certain local and state government) than among adults with private insurance or those who were uninsured. Among adults aged ≥65 years, those with both Medicare and Medicaid had higher age-adjusted prevalences of chronic pain and high-impact chronic pain than did adults with all other types of coverage. Discussion Pain is a component of many chronic conditions, and chronic pain is emerging as a health concern on its own, with negative consequences to individual persons, their families, and society as a whole ( 4 , 5 ). Healthy People 2020 (https://www.healthypeople.gov/), the nation’s science-based health objectives, has a developmental objective to “decrease the prevalence of adults having high-impact chronic pain.” This analysis extends previous national studies of chronic pain prevalence by identifying adults with high-impact chronic pain. In 2016, approximately 20% of U.S. adults had chronic pain (approximately 50 million), and 8% of U.S. adults (approximately 20 million) had high-impact chronic pain. This estimate of high-impact chronic pain is similar to or slightly lower than estimates reported in the few studies that have looked at pain using a similar construct. For example, a recent study that used a measure of high-impact chronic pain similar to the one used in this study reported an estimate of 13.7% among a sample of U.S. adult health plan enrollees ( 7 ). Similarly, a 2001 study of adults from a region in Scotland found that 14.1% of survey participants reported significant chronic pain, and 6.3% reported severe chronic pain, and a 2001 study of Australian adults reported that 11.0% of men and 13.5% of women reported chronic pain that interfered, to some degree, with daily life activities ( 3 , 8 ). The results of subgroup analyses in the current study were consistent with findings in these studies ( 3 , 8 ) insofar as the prevalence of high-impact chronic pain was higher among women, adults who had achieved lower levels of education, and those who were not employed at the time of the survey, and was lower among adults with private health insurance compared with public and other types of coverage. In addition, high-impact chronic pain was also found to be higher among adults living in poverty and among rural residents. Socioeconomic status appears to be a common factor in many of the subgroup differences in high-impact chronic pain prevalence reported here. Indicators of socioeconomic status such as education, poverty, and health insurance coverage have been determined to be associated with both general health status and the presence of specific health conditions ( 9 ) as well as with patients’ success in navigating the health care system ( 9 ). Identifying populations at risk is necessary to inform efforts for developing and targeting quality pain services. The findings in this report are subject to at least five limitations. First, data are self-reported and subject to recall bias. Second, data are cross-sectional, precluding drawing causal inferences. This might be particularly relevant for socioeconomic status, which can be both a risk factor for and a consequence of chronic pain or high-impact chronic pain, or both. Third, no information is available on treatment for chronic pain to assess the prevalence of chronic pain and high-impact chronic pain among those with and without treatment. Fourth, NHIS excludes important populations, such as active duty military and residents of long-term care facilities or prisons. And finally, NHIS does not collect data on chronic pain or high-impact chronic pain in children. Despite these limitations, three strengths of this study are that it used a large, nationally representative data source to produce estimates of chronic pain and high-impact chronic pain across many demographic subgroups, it used standard broad definitions of pain that were not limited to one or more specific health conditions (e.g., headache or arthritis), and it used the standard case definition for high-impact chronic pain proposed by the National Pain Strategy. Chronic pain contributes to an estimated $560 billion each year in direct medical costs, lost productivity, and disability programs ( 4 ). The National Pain Strategy, which is the first national effort to transform how the population burden of pain is perceived, assessed, and treated, recognizes the need for better data to inform action and calls for estimates of chronic pain and high-impact chronic pain in the general population ( 5 ). This report helps fulfill this objective and provides data to inform policymakers, clinicians, and researchers focused on pain care and prevention. Summary What is already known about this topic? Chronic pain has been linked to numerous physical and mental conditions and contributes to high health care costs and lost productivity. A limited number of studies estimate that the prevalence of chronic pain ranges from 11% to 40%. What is added by this report? In 2016, an estimated 20.4% of U.S. adults had chronic pain and 8.0% of U.S. adults had high-impact chronic pain. Both were more prevalent among adults living in poverty, adults with less than a high school education, and adults with public health insurance. What are the implications for public health practice? This report helps fulfill a National Pain Strategy objective of producing more precise estimates of chronic pain and high-impact chronic pain.
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                Author and article information

                Journal
                Pain
                Pain
                PAIN
                Ovid Technologies (Wolters Kluwer Health)
                0304-3959
                1872-6623
                2020
                August 2020
                March 20 2020
                : 161
                : 8
                : 1872-1883
                Article
                10.1097/j.pain.0000000000001876
                7502457
                32701846
                3749abfa-bcec-4a87-b559-2dadfc018c43
                © 2020
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