The PROMIS-16 reproduces the PROMIS-29 physical and mental health summary scores accurately in a probability-based internet panel.

PURPOSE: The Patient-Reported Outcomes Measurement Information System® (PROMIS)-16 assesses the same multi-item domains but does not include the pain intensity item in the PROMIS-29. We evaluate how well physical and mental health summary scores estimated from the PROMIS-16 reproduce those estimated using the PROMIS-29. METHODS: An evaluation of data collected from 4130 respondents from the KnowledgePanel. Analyses include confirmatory factor analysis to assess physical and mental health latent variables based on PROMIS-16 scores, reliability estimates for the PROMIS measures, mean differences and correlations of scores estimated by the PROMIS-16 with those estimated by the PROMIS-29, and associations between differences in corresponding PROMIS-16 and PROMIS-29 scores by sociodemographic characteristics. RESULTS: A two-factor (physical and mental health) model adequately fits the PROMIS-16 scores. Reliability estimates for the PROMIS-16 measures were slightly lower than for the PROMIS-29 measures. There were minimal differences between PROMIS physical and mental health summary scores estimated using the PROMIS-16 or the PROMIS-29. PROMIS-16 and PROMIS-29 score differences by sociodemographic characteristics were small. Using the PROMIS pain intensity item when scoring the PROMIS-16 produced similar estimates of physical and mental health summary scores. CONCLUSION: The PROMIS-16 provides similar estimates of the PROMIS-29 physical and mental health summary scores. The high reliability of these scores indicates they are accurate enough for use with individual patients.

Qualitative Assessment CIH Institutions' Engagement With Underserved Communities to Enhance Healthcare Access and Utilization.

Background: In North America, there is a notable underutilization of complementary and integrative health approaches (CIH) among non-White and marginalized communities. Objectives: This study sought to understand how CIH educational instutitions are proactively working to redress this disparity in access and utilization among these communities. Methods: We conducted interviews with 26 key informants, including presidents, clinicians, and research deans across 13 CIH educational institutions across the US and Canada. Thematic analysis included deductive codes based on the interview guide during interview scripts review. Results: Six themes were identified: (1) CIH institutions often had a long and varied history of community engaged care through partnerships to increase access and utilization; (2) CIH institutions' long-standing community outreach had been intentionally designed; (3) CIH institutions provided an array of services to a wide range of demographics and communities; (4) addressing healthcare access and utilization through community partnerships had a strong positive impact; (5) funding, staffing and COVID-19 were significant challenges that impeded efforts to increase CIH access through community engaged work; (6) identified gaps in community partnerships and services to increase access and utilization were recognized. Conclusion: These findings underscore significant efforts made to enhance healthcare access and utilization among marginalized, underserved, and racial and ethnic communities. However, barriers such as funding constraints, resource allocation, and the need for proper measurement and accountability hinder proactive initiatives aimed at redressing disparities in CIH utilization within these communities.

Development of an ultra-short measure of eight domains of health-related quality of life for research and clinical care: the patient-reported outcomes measurement information system® PROMIS®-16 profile.

PURPOSE: We describe development of a short health-related quality of life measure, the patient-reported outcomes measurement information system® (PROMIS®)-16 Profile, which generates domain-specific scores for physical function, ability to participate in social roles and activities, anxiety, depression, sleep disturbance, pain interference, cognitive function, and fatigue. METHODS: An empirical evaluation of 50 candidate PROMIS items and item pairs was conducted using data from a sample of 5775 respondents from Amazon's Mechanical Turk (MTurk). Results and item response theory information curves for a subset of item pairs were presented and discussed in a stakeholder meeting to narrow the candidate item sets. A survey of the stakeholders and 124 MTurk adults was conducted to solicit preferences among remaining candidate items and finalize the measure. RESULTS: Empirical evaluation showed minimal differences in basic descriptive statistics (e.g., means, correlations) and associations with the PROMIS-29 + 2 Profile, thus item pairs were further considered primarily based on item properties and content. Stakeholders discussed and identified subsets of candidate item pairs for six domains, and final item pairs were agreed upon for two domains. Final items were selected based on stakeholder and MTurk-respondent preferences. The PROMIS-16 profile generates eight domain scores with strong psychometric properties. CONCLUSION: The PROMIS-16 Profile provides an attractive brief measure of eight distinct domains of health-related quality of life, representing an ideal screening tool for clinical care, which can help clinicians quickly identify distinct areas of concern that may require further assessment and follow-up. Further research is needed to confirm and extend these findings.

Mapping of the PROMIS global health measure to the PROPr in the United States.

BACKGROUND: The Patient-Reported Outcomes Measurement and Information System (PROMIS®) global health items (global-10) yield physical and mental health scale scores and the PROMIS-Preference (PROPr) scoring system estimated from PROMIS domain scores (e.g., PROMIS-29 + 2) produces a single score anchored by 0 (dead or as bad as being dead) to 1 (full health). A link between the PROMIS global-10 and the PROPr is needed. METHODS: The PROMIS-29 + 2 and the PROMIS global-10 were administered to 4102 adults in the Ipsos KnowledgePanel in 2022. The median age was 52 (range 18-94), 50% were female, 70% were non-Hispanic White, and 64% were married or living with a partner. The highest level of education completed for 26% of the sample was a high school degree or general education diploma and 44% worked full-time. We estimated correlations of the PROPr with the PROMIS global health items and the global physical and mental health scales. We examined the adjusted R2 and estimated correlations between predicted and observed PROPr scores. RESULTS: Product-moment correlations between the PROMIS global health items and the PROPr ranged from 0.50 to 0.63. The PROMIS global physical health and mental health scale scores correlated 0.74 and 0.60, respectively, with the PROPr. The adjusted R2 in the regression of the PROPr on the PROMIS global health items was 64%. The equated PROPr preference scores correlated (product-moment) 0.80 (n = 4043; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation (two-way random effects model) was 0.80. The normalized mean absolute error (NMAE) was 0.45 (SD = 0.43). The adjusted R2 in the OLS regression of the PROPr on the PROMIS global health scales was 59%. The equated PROPr preference scores correlated (product-moment) was 0.77 (n = 4046; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation was 0.77. The NMAE was 0.49 (SD = 0.45). CONCLUSIONS: Regression equations provide a reasonably accurate estimate of the PROPr preference-based score from the PROMIS global health items or scales for group-level comparisons. These estimates facilitate cost-effectiveness research and meta-analyses. The estimated PROPr scores are not accurate enough for individual-level applications. Future evaluations of the prediction equations are needed.

Dosing of lumbar spinal manipulative therapy and its association with escalated spine care: A cohort study of insurance claims.

OBJECTIVE: The objective of this study was to evaluate the relationship between three distinct spinal manipulative therapy dose groups and escalated spine care by analyzing insurance claims from a cohort of patients with low back pain. METHODS: We compared three distinct spinal manipulative therapy dose groups (low = 1 SMT visits, moderate = 2-12 SMT visits, high = 13+ SMT visits), to a control group (no spinal manipulative therapy) regarding the outcome of escalated spine care. Escalated spine care procedures include imaging studies, injection procedures, emergency department visits, surgery, and opioid medication use. Propensity score matching was performed to address treatment selection bias. Modified Poisson regression modeling was used to estimate the relative risk of spine care escalation among three spinal manipulative therapy doses, adjusting for age, sex, retrospective risk score and claim count. RESULTS: 83,025 claims were categorized into 11,114 unique low back pain episodes; 8,137 claims had 0 spinal manipulative therapy visits, with the remaining episodes classified as low dose (n = 404), moderate dose (n = 1,763) or high dose (n = 810). After propensity score matching, 5,348 episodes remained; 2,454 had 0 spinal manipulative therapy visits with the remaining episodes classified as low dose (n = 404), moderate dose (n = 1,761), or high dose (n = 729). The estimated relative risk (vs no spinal manipulative therapy) for any escalated spine care was 0.45 (95% confidence interval 0.38, 0.55, p <0.001), 0.58 (95% confidence interval 0.53, 0.63, p <0.001), and 1.03 (95% confidence interval 0.95, 1.13, p = 0.461) for low, moderate, and high dose spinal manipulative therapy groups, respectively. CONCLUSIONS: For claims associated with initial episodes of low back pain, low and moderate dose spinal manipulative therapy groups were associated with a 55% and 42% reduction, respectively, in the relative risk of any escalated spine care.

How Well Do Seven Self-Report Measures Represent Underlying Back Pain Impact?

BACKGROUND: The extent to which different measures of back pain impact represent an underlying common factor has implications for decisions about which one to use in studies of pain management and estimating one score from others. AIMS: To determine if different self-report back pain impact measures represent an underlying pain latent variable and estimate associations with it. METHOD: Seven pain impact measures completed by Amazon Mechanical Turk adults are used to estimate internal consistency reliability and associations: Oswestry Disability Index (ODI), Roland-Morris Disability Questionnaire (RMDQ), short form of the Örebro Musculoskeletal Pain Questionnaire (OMPQ), Subgroups for Targeted Treatment (STarT) Back Tool, the Graded Chronic Pain Scale (GCPS) disability score, PEG (Pain intensity, interference with Enjoyment of life, interference with General activity), and Impact Stratification Score (ISS). RESULTS: The sample of 1,874 adults with back pain had an average age of 41 and 52% were female. Sixteen percent were Hispanic, 7% non-Hispanic Black, 5% non-Hispanic Asian, and 71% non-Hispanic White. Internal consistency reliability estimates ranged from 0.710 (OMPQ) to 0.923 (GCPS). Correlations among the measures ranged from 0.609 (RMDQ with OMPQ) to 0.812 (PEG with GCPS). Standardized factor loadings on the pain latent variable ranged from 0.782 (RMDQ) to 0.870 (ISS). CONCLUSIONS: Scores of each measure can be estimated from the others for use in research.

Predictors of Pain Management Strategies in Adults with Low-Back Pain: A Secondary Analysis of Amazon Mechanical Turk Survey Data.

Objective: To evaluate the associations between baseline demographics, health conditions, pain management strategies, and health-related quality-of-life (HRQoL) measures with pain management strategies at 3-month follow-up in respondents reporting current low-back pain (LBP). Study design: Cohort study of survey data collected from adults with LBP sampled from Amazon Mechanical Turk crowdsourcing panel. Methods: Demographics, health conditions, and the Patient-Reported Outcomes Measurement Information System (PROMIS)-10 were included in the baseline survey. Respondents reporting LBP completed a more comprehensive survey inquiring about pain management strategies and several HRQoL measures. Bivariate then multivariate logistic regression estimated odds ratios (ORs) with 95% confidence intervals (CIs) for the association between baseline characteristics and pain management utilization at 3-month follow-up. Model fit statistics were evaluated to assess the predictive value. Results: The final cohort included 717 respondents with completed surveys. The most prevalent pain management strategy at follow-up was other care (n = 474), followed by no care (n = 94), conservative care only (n = 76), medical care only (n = 51), and medical and conservative care combined (n = 22). The conservative care only group had higher (better) mental and physical health PROMIS-10 scores as opposed to the medical care only and combination care groups, which had lower (worse) physical health scores. In multivariate models, estimated ORs (95% CIs) for the association between baseline and follow-up pain management ranged from 4.6 (2.7-7.8) for conservative care only to 16.8 (6.9-40.7) for medical care only. Additional significant baseline predictors included age, income, education, workman's compensation claim, Oswestry Disability Index score, and Global Chronic Pain Scale grade. Conclusions: This study provides important information regarding the association between patient characteristics, HRQoL measures, and LBP-related pain management utilization.

Comparison of patient-reported outcomes measurement information system (PROMIS®)-29 and PROMIS global physical and mental health scores.

PURPOSE: The Patient-Reported Outcomes Measurement and Information System (PROMIS®): includes the PROMIS-29 physical and mental health summary and the PROMIS global physical and mental health scores. It is unknown how these scores coincide with one another. This study examines whether the scores yield similar or different information. METHODS: The PROMIS-29 and the PROMIS global health items were administered to 5804 adults from Amazon's Mechanical Turk (MTurk) in 2021-2022 and to 4060 adults in the Ipsos KnowledgePanel (KP) in 2022. RESULTS: The median age of those in MTurk (KP) was 36 (54) and 53% (50%) were male. Mean T-scores on the PROMIS-29 and PROMIS global physical health scales were similar, but PROMIS global mental health was 3-4 points lower than the PROMIS-29 mental health summary score. Product-moment correlations ranged from 0.69 to 0.81 between the PROMIS-29 physical health and PROMIS global physical health scales and 0.56-0.69 between the mental health scales. Multi-trait multimethod analyses indicated that only a small proportion of the correlations between the two methods of measuring mental health were significantly more highly correlated with one another than correlations between physical and mental health. CONCLUSIONS: PROMIS-29 and PROMIS global mental health scales provide different information and, therefore, study conclusions may vary depending on which measure is used. Interpretation of results needs to consider that the PROMIS-29 mental health scale is a weighted combination of specific domains while the PROMIS global mental health scale is based on general mental health perceptions. Further comparisons of methods of assessing mental health are needed.

Estimating individual health-related quality of life changes in low back pain patients.

BACKGROUND: There is a need to evaluate different options for estimating individual change in health-related quality of life for patients with low back pain. METHODS: Secondary analysis of data collected at baseline and 6 weeks later in a randomized trial of 749 adults with low back pain receiving usual medical care (UMC) or UMC plus chiropractic care at a small hospital at a military training site or two large military medical centers. The mean age was 31; 76% were male and 67% were White. The study participants completed the Patient-Reported Outcomes Measurement Information System (PROMIS®)-29 v 1.0 physical function, pain interference, pain intensity, fatigue, sleep disturbance, depression, anxiety, satisfaction with participation in social roles, physical summary, and mental health summary scores (T-scored with mean = 50 and standard deviation (SD) = 10 in the U.S. general population). RESULTS: Reliability estimates at the baseline ranged from 0.700 to 0.969. Six-week test-retest intraclass correlation estimates were substantially lower than these estimates: the median test-retest intraclass correlation for the two-way mixed-effects model was 0. 532. Restricting the test-retest reliability estimates to the subset who reported they were about the same as at baseline on a retrospective rating of change item increased the median test-retest reliability to 0.686. The amount of individual change that was statistically significant varied by how reliability was estimated, and which SD was used. The smallest change needed was found when internal consistency reliability and the SD at baseline were used. When these values were used, the amount of change needed to be statistically significant (p < .05) at the individual level ranged from 3.33 (mental health summary scale) to 12.30 (pain intensity item) T-score points. CONCLUSIONS: We recommend that in research studies estimates of the magnitude of individual change needed for statistical significance be provided for multiple reliability and standard deviation estimates. Whenever possible, patients should be classified based on whether they 1) improved significantly and perceived they got better, 2) improved significantly but did not perceive they were better, 3) did not improve significantly but felt they got better, or 4) did not improve significantly or report getting better.

Classifying patients with non-specific chronic low back pain using the impact stratification score in an online convenience sample.

BACKGROUND: In 2014, the National Institute of Health Pain Consortium's research task force (RTF) on research standards for chronic low back pain (CLBP) proposed the Impact Stratification Score (ISS) as a patient-reported outcome measure that could stratify patients by the impact CLBP has on their lives. This work compares three newly developed ISS-based classifications to the RTF's original to provide an optimal recommendation. METHODS: The online sample included 1226 individuals from Amazon's Mechanical Turk who indicated having non-specific CLBP, average age of 40, 49% female, and 67% White. Participants completed the PROMIS-29 v2.1 profile survey that contains the 9 ISS items as well the Roland-Morris Disability Questionnaire (RMDQ) and Graded Chronic Pain Scale (GCPS). Other items included high-impact chronic pain; not working due to health problems; overall health; and number of healthcare visits for back pain in the past 6 months. Three new classifications were created using quartiles (Classification 2), latent profile analysis (Classification 3), and one modeled after the GCPS (Classification 4). Classifications were subsequently compared to the RTF-proposed classification (Classification 1) on several concurrent and prognostic criteria. RESULTS: Classification 1 had three CLBP severity groups, four in Classification 2, three in Classification 3, and four in Classification 4. All novel classifications improved upon the original. Classification 2 performed best at minimizing the classification of those with negative outcomes into the lowest severity groups at baseline (e.g., 11% with RMDQ ≥ 7) and 6 months (e.g., 8.2% had fair/poor health). Classification 4 performed best at maximizing classification of those with negative outcomes into the most severe group concurrently (e.g., 100% had GCPS grade ≥ 2) and at 6 months (e.g., 100% with RMDQ ≥ 7). CONCLUSIONS: We developed three ISS-based classification schemes and tested them against several outcomes. All three improved upon the original scheme. While appearing more optimal than other classifications in the lowest severity groups, Classification 2 presents some considerations and limitations. Given that Classification 4 was an improvement at the lowest end of severity and was the best at the highest end, it is our tentative recommendation that this approach be adopted to classify individuals with non-specific CLBP.

Building Bridges Toward Common Goals - A Call for Greater Collaboration Between Public Health and Integrative, Complementary and Traditional Health Providers.

This commentary makes the case for greater collaboration between public health professionals and integrative, complementary and traditional health practitioners (ICTHP). Previous partnerships have been successful, and more such collaborative work is needed to help overcome division, enhance the health workforce, and move all involved toward shared goals. ICTHP providers may be uniquely able to work across ideological differences and engage individuals and communities who are less trusting of public health, including those who are vaccine hesitant. Diverse partnerships can be difficult to maintain, but the application of equitable processes may aid their success. In the face of highly complex public health challenges, partnerships with ICTHP are critical.

Effects of Excluding Those Who Report Having "Syndomitis" or "Chekalism" on Data Quality: Longitudinal Health Survey of a Sample From Amazon's Mechanical Turk.

BACKGROUND: Researchers have implemented multiple approaches to increase data quality from existing web-based panels such as Amazon's Mechanical Turk (MTurk). OBJECTIVE: This study extends prior work by examining improvements in data quality and effects on mean estimates of health status by excluding respondents who endorse 1 or both of 2 fake health conditions ("Syndomitis" and "Chekalism"). METHODS: Survey data were collected in 2021 at baseline and 3 months later from MTurk study participants, aged 18 years or older, with an internet protocol address in the United States, and who had completed a minimum of 500 previous MTurk "human intelligence tasks." We included questions about demographic characteristics, health conditions (including the 2 fake conditions), and the Patient Reported Outcomes Measurement Information System (PROMIS)-29+2 (version 2.1) preference-based score survey. The 3-month follow-up survey was only administered to those who reported having back pain and did not endorse a fake condition at baseline. RESULTS: In total, 15% (996/6832) of the sample endorsed at least 1 of the 2 fake conditions at baseline. Those who endorsed a fake condition at baseline were more likely to identify as male, non-White, younger, report more health conditions, and take longer to complete the survey than those who did not endorse a fake condition. They also had substantially lower internal consistency reliability on the PROMIS-29+2 scales than those who did not endorse a fake condition: physical function (0.69 vs 0.89), pain interference (0.80 vs 0.94), fatigue (0.80 vs 0.92), depression (0.78 vs 0.92), anxiety (0.78 vs 0.90), sleep disturbance (-0.27 vs 0.84), ability to participate in social roles and activities (0.77 vs 0.92), and cognitive function (0.65 vs 0.77). The lack of reliability of the sleep disturbance scale for those endorsing a fake condition was because it includes both positively and negatively worded items. Those who reported a fake condition reported significantly worse self-reported health scores (except for sleep disturbance) than those who did not endorse a fake condition. Excluding those who endorsed a fake condition improved the overall mean PROMIS-29+2 (version 2.1) T-scores by 1-2 points and the PROMIS preference-based score by 0.04. Although they did not endorse a fake condition at baseline, 6% (n=59) of them endorsed at least 1 of them on the 3-month survey and they had lower PROMIS-29+2 score internal consistency reliability and worse mean scores on the 3-month survey than those who did not report having a fake condition. Based on these results, we estimate that 25% (1708/6832) of the MTurk respondents provided careless or dishonest responses. CONCLUSIONS: This study provides evidence that asking about fake health conditions can help to screen out respondents who may be dishonest or careless. We recommend this approach be used routinely in samples of members of MTurk.

Acupuncture for chronic low back pain in older adults: Design and protocol for the BackInAction pragmatic clinical trial.

BACKGROUND: Back pain prevalence and burden increase with age; approximately one-third of U.S. adults 65 years of age and older experience lower back pain (LBP). For chronic low back pain (cLBP), typically defined as lasting three months or longer, many treatments for younger adults may be inappropriate for older adults given their greater prevalence of comorbidities with attendant polypharmacy. While acupuncture has been demonstrated to be safe and effective for cLBP in adults overall, few studies of acupuncture have either included or focused on adults ≥65 years old. METHODS: The BackInAction study is a pragmatic, multi-site, three-arm, parallel-groups randomized controlled trial designed to test the effectiveness of acupuncture needling for improving back pain-related disability among 807 older adults ≥65 years old with cLBP. Participants are randomized to standard acupuncture (SA; up to 15 treatment sessions across 12 weeks), enhanced acupuncture (EA; SA during first 12 weeks and up to 6 additional sessions across the following 12 weeks), and usual medical care (UMC) alone. Participants are followed for 12 months with study outcomes assessed monthly with the primary outcome timepoint at 6 months. DISCUSSION: The BackInAction study offers an opportunity to further understand the effectiveness, dose-dependence, and safety of acupuncture in a Medicare population. Additionally, study results may encourage broader adoption of more effective, safer, and more satisfactory options to the continuing over-reliance on opioid- and invasive medical treatments for cLBP among older adults. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04982315. Clinical trial registration date: July 29, 2021.

Definitions of Chronic Low Back Pain From a Scoping Review, and Analyses of Narratives and Self-Reported Health of Adults With Low Back Pain.

Among those with low back pain (LBP), individuals with chronic LBP (CLBP) face different treatment recommendations and incur the majority of suffering and costs. However, the way CLBP has been defined varies greatly. This study used a scoping review and qualitative and quantitative analyses of data from LBP patients to explore this variation. CLBP in most recent randomized controlled trials (RCTs) was defined by duration of pain, most commonly ≥3 months. However, individuals with LBP most often define CLBP by frequency. CLBP has also been defined using a combination of duration and frequency (16% of RCTs and 20% of individuals), including 6% of recent RCTs that followed the NIH Pain Consortium research task force (RTF) definition. Although not a defining characteristic of CLBP for individuals, almost 15% of recent RCTs required CLBP to have a healthcare provider diagnosis. In our LBP sample moving from ≥3 months to the RTF definition reduced the CLBP group size by 25% and resulted in a group that used more pain management options and reported worse health across all outcome measures. A pain duration definition offers ease of application. However, refinements to this definition (eg, RTF) can identify those who may be better intervention targets. PERSPECTIVE: This article presents the definitions used for CLBP by researchers and individuals, and the impact of these definitions on pain management and health outcomes. This information may help researchers choose better study inclusion criteria and clinicians to better understand their patients' beliefs about CLBP.

Longitudinal Associations of PROMIS-29 Anxiety and Depression Symptoms With Low Back Pain Impact in a Sample of U.S. Military Service Members.

INTRODUCTION: The Impact Stratification Score (ISS) is a measure of the impact of chronic low back pain (LBP) consisting of nine Patient-Reported Outcomes Measurement Information System (PROMIS-29) items, but no studies have examined the ISS or its association with psychological symptoms in military samples. This study examines longitudinal associations between psychological symptoms and the ISS among military service members. MATERIAL AND METHODS: The study involved secondary data analysis of a sample of active duty U.S. military service members aged 18-50 years with LBP (n = 733). Participants completed the PROMIS-29 at three time points during treatment: baseline (time 1, T1), week 6 of treatment (time 2, T2), and week 12 of treatment (time 3, T3). The impact of LBP was quantified using the ISS (ranging from 8 = least impact to 50 = greatest impact). Psychological symptoms were assessed as PROMIS-29 anxiety and depression scores. Separate autoregressive cross-lagged models examined reciprocal associations of ISSs with anxiety, depression, and emotional distress scores from T1 to T3. RESULTS: Within each time point, the ISS was significantly and positively correlated with anxiety and depression. In autoregressive cross-lagged models, anxiety and depression predicted the ISS at the next time point and associations were similar in magnitude (e.g., anxiety T2 to ISS T3: ß = 0.12, P < .001; depression T2 to ISS T3: ß = 0.12, P <.001). The ISS did not predict future depression or emotional distress scores at any time point, but the ISS at T2 was significantly, positively associated with anxiety scores at T3 (ß = 0.07, P = .04). CONCLUSION: Psychological symptoms consistently and prospectively predict the impact of LBP as measured by the ISS among service members undergoing pain treatment. The ISS may also be associated with future anxiety but not depression. PROMIS-29 anxiety and depression items may be useful adjunctive measures to consider when using the ISS to support LBP treatment planning and monitoring with service members.

Crosswalking the National Institutes of Health Impact Stratification Score to the PEG.

OBJECTIVE: To crosswalk the National Institutes of Health (NIH) Pain Consortium's Research Task Force proposed Impact Stratification Score (ISS) to the PEG (Pain Intensity, Interference With Enjoyment of Life, Interference With General Activity) Scale. DESIGN: Cross-sectional data collected in 2021. Ordinary least squares regression analyses of ISS and PEG. SETTING: Amazon Mechanical Turk workers. PARTICIPANTS: 1931 adults with back pain with an average age of 41 (range, 19-77); 48% were female, 16% Hispanic, 7% non-Hispanic Black, 5% non-Hispanic Asian, and 71% non-Hispanic White (N=1931). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The Patient-Reported Outcomes Measurement Information System (PROMIS)-29+2 v2.1 survey that includes the ISS, and the 3-item PEG. RESULTS: The ISS and PEG had a correlation coefficient of 0.74. The ISS accounted for 55% of the adjusted variance in the PEG and the standardized average deviation between observed and predicted scores (normalized mean absolute error) was 0.53. Likewise, the PEG explained 55% of the variance in the ISS with a normalized mean absolute error of 0.52. CONCLUSIONS: This study provides a crosswalk between the ISS and PEG that can be used to predict one from the other. The regression equations can facilitate comparisons in studies that use different measures.

Comparing Data Collected on Amazon's Mechanical Turk to National Surveys.

OBJECTIVE: In this study, we examined the impact of a range of methods to improve data quality on the demographic and health status representativeness of Amazon Mechanical Turk (MTurk) samples. METHODS: We developed and field-tested a general survey of health on MTurk in 2017 among 5755 participants and 2021 among 6752 participants. We collected information on participant demographic characteristics and health status and implemented different quality checks in 2017 and 2021. RESULTS: Adding data quality checks generally improves the representativeness of the final MTurk sample, but there are persistent differences in mental health and pain conditions, age, education, and income between the MTurk population and the broader US population. CONCLUSION: We conclude that data quality checks improve the data quality and representativeness.

Incorporating Complementary and Integrative Health Providers in the Public Health Pandemic Response: Lessons from COVID-19 and Recommendations for the Future from a Multidisciplinary Expert Panel.

Complementary and integrative health (CIH) providers, such as chiropractors and naturopathic doctors, have been an underutilized public health asset in the response to the COVID-19 pandemic. This article seeks to inform how they can be better integrated into future responses to public health emergencies. The authors convened an expert panel of ten CIH and public health practitioners and researchers for a daylong discussion of how the CIH workforce could be better mobilized during future crises. In this article, the authors summarize the key barriers identified in the discussion and make recommendations on how they can be overcome.

A Scoping Review of Chronic Low Back Pain Classification Schemes Based on Patient-Reported Outcomes.

BACKGROUND: In 2014, the National Institutes of Health Pain Consortium Research Task Force recommended that patients with chronic low back pain (CLBP) be stratified by its impact on their lives. They proposed the Impact Stratification Score (ISS) to help guide therapy and facilitate study comparability. The ISS has been evaluated as a continuous measure, but not for use as a stratification or classification scheme. OBJECTIVES: Identify the characteristics of successful schemes to inform the use of the ISS for stratification or classification. STUDY DESIGN: Scoping review of the peer-reviewed literature. METHODS: Search of PubMed, CINAHL, and APA PsycInfo to identify patient self-report-based classification schemes applicable to CLBP. Data were captured on the methods used for each scheme's development, the domains covered, their scoring criteria and what the classification has successfully measured. The study was reviewed and approved by the RAND Human Subjects Protection Committee (2019-0651-AM02). RESULTS: The search identified 87 published articles about the development and testing of 5 classification schemes: 1) The Subgroups for Targeted Treatment (STarT) Back Screening Tool, 2) Multiaxial Assessment of Pain, 3) Graded Chronic Pain Scale, 4) Back Pain Classification Scale, and 5) Chronic Pain Risk Score. All have been shown to be predictive of future outcomes and the STarT Back has been found useful in identifying effective classification-specific treatment. Each scheme had a different classification scoring structure, was developed using different methods, and 3 included domains not found in the ISS. LIMITATIONS: Expanding the search to other databases may have identified more classification schemes. Our minimum number of publications inclusion criterion eliminated dozens of cluster analyses, some of which may have eventually been replicated. CONCLUSIONS: The methods used to develop these successful classification schemes, especially those that use straightforward scoring schemes, should be considered for use in the development of a scheme based on the ISS.