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.

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.

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.

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.

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.

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.

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.

Unpacking the impact of chronic pain as measured by the impact stratification score.

BACKGROUND: In 2014, the National Institute of Health Pain Consortium's research task force on research standards for chronic low back pain (CLBP) proposed a measure that could be used to stratify patients by the impact CLBP has on their lives, namely the Impact Stratification Score (ISS). This study examines the dimensionality of the ISS and support for its single total score, and evaluates its overall psychometric properties. METHODS: The sample included 1677 chiropractic patients being treated for CLBP and chronic neck pain, had an average age of 49, 71% female, and 90% White. Study participants completed the PROMIS-29 v2.1 profile survey that contains the 9 ISS items. The ISS was evaluated using item-total correlations, Cronbach's alpha, factor analysis (i.e., correlated factors and bifactor models), and item response theory (IRT). Reliability indices and item properties were evaluated from bifactor and IRT models, respectively. RESULTS: Item-total correlations were high (0.64-0.84) with a Cronbach's alpha of 0.93. Eigenvalues suggested the possibility of two factors corresponding to physical function and pain interference/intensity. Bifactor model results indicated that data were essentially unidimensional, primarily reflecting one general construct (i.e., impact) and that after accounting for 'impact' very little reliable variance remained in the two group factors. General impact scores were reliable (omegaH = .73). IRT models showed that items were strong indicators of impact and provided information across a wide range of the impact continuum and offer the possibility of a shorter 8-item ISS. Finally, it appears that different aspects of pain interference occur prior to losses in physical function. CONCLUSIONS: This study presents evidence that the ISS is sufficiently unidimensional, covers a range of chronic pain impact and is a reliable measure. Insights are obtained into the sequence of chronic pain impacts on patients' lives.

Barriers to the Engagement of Complementary and Integrative Health Providers in Public Health Responses to COVID-19: Recommendations From a Multidisciplinary Expert Panel.

OBJECTIVE: The purpose of this project was to explore barriers to the involvement of complementary and integrative health (CIH) providers in the public health response to COVID-19 and potential solutions for future involvement in public health crises. METHODS: An expert panel of 10 people, which included doctors of chiropractic, naturopathic doctors, public health practitioners, and researchers from the United States, was convened for a day-long online panel discussion. Facilitators asked panelists how CIH practitioners could contribute and be mobilized. We summarized themes and recommendations from the discussion. RESULTS: Despite their skills and resources, few CIH providers participated in public health efforts like testing and contact tracing during the COVID-19 pandemic. Panelists described that CIH professionals may not have participated in those efforts due to the CIH providers possibly not having sufficient public health training and limited contact with public health professionals, as well as policy and financial challenges during the pandemic. Panelists proposed solutions to these barriers, including more public health training, stronger formal relationships between CIH and public health organizations, and improved financial support for both CIH care and public health efforts. CONCLUSION: Through an expert panel discussion, we identified barriers that hindered the involvement of CIH providers in the public health response to the COVID-19 pandemic. During future pandemics in the United States, public health planners should recognize CIH providers as part of the existing labor resource, with clinical expertise and community-level connections that can be called upon in a crisis. During future events, CIH professional leaders should be more proactive in seeking out a supportive role and sharing their knowledge, skills, and expertise.

Diet quality improvement and 30-year population health and economic outcomes: a microsimulation study.

OBJECTIVE: Diets closer aligned with nutritional guidelines could lower the risk of several chronic conditions and improve economic outcomes, such as employment and healthcare costs. However, little is known about the range, order of magnitude and timing of these potential effects. DESIGN: We used a microsimulation approach to predict US population changes over 30 years in health and economic outcomes that could result from a substantial (but not impossible) improvement in diet quality - an improvement from the third to the fifth quintile of US scores on the Alternate Healthy Eating Index, 2010 version. SETTING: Risk ratios from the literature for diabetes, heart disease and stroke were used to modify the Future Adult Model (FAM) to simulate outcomes from a higher-quality diet. Model parameter uncertainty was assessed using bootstrap and sensitivity analysis examined the variation in published risk ratios. PARTICIPANTS: FAM simulates outcomes for the US adult population aged 25 and older. RESULTS: Improved diet quality initially leads to very small changes in chronic disease prevalence, but these accumulate over time. If diets improved beginning in 2019, after 30 years diabetes prevalence could be reduced by 5·9 million cases (11·5 %), heart disease prevalence by 4·0 million cases (7·2 %) and stroke prevalence by 1·9 million cases (10·3 %). These reductions in disease prevalence would be accompanied that same year by fewer deaths (88 000) and healthcare cost savings of $144·0 billion (2019 USD). CONCLUSIONS: This microsimulation study suggests that improvements in diet are likely to improve health and economic population outcomes over time.

Assessing the Significance of Individual Change in 2 Samples of Patients in Treatment for Low Back Pain Using 5 Different Statistical Indicators.

OBJECTIVE: The purpose of this study was to estimate the significance of individual change using 5 statistical indicators in 2 samples of patients treated for low back pain. METHODS: This secondary analysis used observational and clinical trial data from 2 samples of patients with low back pain to compare 5 ways of estimating significant individual change on the Impact Stratification Score (ISS) administered at the following 2 time points: 3 months apart in an observational study of 1680 patients undergoing chiropractic care, and 6 weeks apart in a randomized trial of 750 active-duty military personnel with low back pain. The following 5 methods were compared: (1) standard deviation index; (2) standard error of measurement (SEM); (3) standard error of estimate (SEE); (4) standard error of prediction (SEP); and (5) the reliable change index (RCI). The ISS is the sum of the Patient-Reported Outcomes Measurement Information System (PROMIS)-29 v2.1 physical function, pain interference, and pain intensity scores and is scored to have a possible range of 8 (least impact) to 50 (greatest impact). RESULTS: The amount of change on the ISS needed for significant individual change in both samples was 5 for the SEM and for the SEE and 7 for the SEP and RCI. CONCLUSIONS: The results of the current study provide some preliminary support for use of the SEP or the RCI to identify significant individual change and provide estimated thresholds of individual change that can be used for the ISS. The SEP and RCI estimates of significant change were consistent with retrospective ratings of change of at least moderately better in prior research. These 2 were less likely than other methods to classify people with low back pain as responders who have not actually gotten better (false positive). In contrast, the SEM and SEE were less likely to miss real change (false negative).

Income as a Predictor of Self-Efficacy for Managing Pain and for Coping With Symptoms Among Patients With Chronic Low Back Pain.

OBJECTIVES: The purpose of this study was to evaluate pain self-efficacy (PSE) and coping self-efficacy (CSE) for people with chronic low back pain (CLBP), and to assess whether lower income may be associated with less PSE and CSE in the United States. METHODS: We conducted a cross-sectional study using survey data collected between June 2016 and February 2017 from n = 1364 patients with CLBP from chiropractic clinics in the United States to measure the relationship between income and both types of self-efficacy. We created 4 multivariate models predicting PSE and CSE scores. We used both a parsimonious set of covariates (age, sex) and a full set (age, sex, education, neck pain comorbidity, catastrophizing, and insurance). We also calculated effect sizes (Cohen's d) for unadjusted differences in PSE and CSE score by income. RESULTS: Lower income was associated with lower PSE and CSE scores across all 4 models. In the full models, the highest-income group had an average of 1 point (1-10 scale) higher PSE score and CSE score compared to the lowest income group. Effect sizes for the unadjusted differences in PSE and CSE scores between the highest and lowest income groups were 0.94 and 0.84, respectively. CONCLUSIONS: Our findings indicate that people with lower income perceive themselves as less able to manage their pain, and that this relationship exists even after taking into account factors like health insurance and educational attainment. There is a need to further investigate how practitioners and policymakers can best support low-income patients with chronic pain.

Effects of a Community-to-Clinic Navigation Intervention on Colorectal Cancer Screening Among Underserved People.

BACKGROUND: Colorectal cancer screening remains suboptimal among poor and underserved people. PURPOSE: We tested the effectiveness of a community-to-clinic navigator intervention to guide multicultural, underinsured individuals into primary care clinics to complete colorectal cancer screening. METHODS: This two-phase behavioral intervention study was conducted in Phoenix, Arizona (2012-2018). Community sites were randomized to group education or group education plus tailored navigation to increase attendance at primary care clinics (Phase I). Individuals who completed a clinic appointment received the tailored navigation in person or via phone (Phase II). RESULTS: In Phase I (N = 345), 37.9% of the intervention group scheduled a clinic appointment versus 19.4% of the comparison group. In Phase II, 26.5% of the original intervention group were screened versus only 10.4% of the original comparison group. Those in the intervention group were 3.84 times more likely to be screened than were those in the comparison group (odds ratio = 3.84; 95% confidence interval = 1.81-6.92). CONCLUSIONS: Translation of an efficacious tailored navigation intervention for colorectal cancer screening to a community-to-clinic context is associated with significantly increased rates of colorectal cancer screening. Navigation assistance to address barriers to screening may serve as the most important component of any educational program to increase individual adherence to colorectal cancer screening.

Predictors of visit frequency for patients using ongoing chiropractic care for chronic low back and chronic neck pain; analysis of observational data.

BACKGROUND: Chronic spinal pain is prevalent, expensive and long-lasting. Several provider-based nonpharmacologic therapies have now been recommended for chronic low-back pain (CLBP) and chronic neck pain (CNP). However, healthcare and coverage policies provide little guidance or evidence regarding the long-term use of this care. To provide one glimpse into the long-term use of nonpharmacologic provider-based care, this study examines the predictors of visit frequency in a large sample of patients with CLBP and CNP using ongoing chiropractic care. METHODS: Observational data were collected from a large national sample of chiropractic patients in the US with non-specific CLBP and CNP. Visit frequency was defined as average number of chiropractic visits per month over the 3-month study period. Potential baseline predictor variables were entered into two sets of multi-level models according to a defined causal theory-in this case, Anderson's Behavioral Model of Health Services Use. RESULTS: Our sample included 852 patients with CLBP and 705 with CNP. Visit frequency varied significantly by chiropractor/clinic, so our models controlled for this clustering. Patients with either condition used an average of 2.3 visits per month. In the final models visit frequency increased (0.44 visits per month, p = .008) for those with CLBP and some coverage for chiropractic, but coverage had little effect on visits for patients with CNP. Patients with worse function or just starting care also had more visits and those near to ending care had fewer visits. However, visit frequency was also determined by the chiropractor/clinic where treatment was received. Chiropractors who reported seeing more patients per day also had patients with higher visit frequency, and the patients of chiropractors with 20 to 30 years of experience had fewer visits per month. In addition, after controlling for both patient and chiropractor characteristics, the state in which care was received made a difference, likely through state-level policies and regulations. CONCLUSIONS: Chiropractic patients with CLBP and CNP use a range of visit frequencies for their ongoing care. The predictors of these frequencies could be useful for understanding and developing policies for ongoing provider-based care.

A protocol for chronic pain outcome measurement enhancement by linking PROMIS-29 scale to legacy measures and improving chronic pain stratification.

BACKGROUND: Substantial investment has gone into research on the efficacy and effectiveness of pharmaceutical and nonpharmacologic interventions for chronic pain. However, synthesizing this extensive literature is challenging because of differences in the outcome measures used in studies of similar or competing interventions. The absence of a common metric makes it difficult to replicate findings, pool data from multiple studies, resolve conflicting conclusions, or reach consensus when interpreting findings. METHODS: This study has a seven-member Advisory Council of chronic pain experts. Preliminary analyses will be performed on data from several large existing datasets; intermediate analyses will be performed using primary data collected from Amazon's Mechanical Turk (MTurk); and cross-validation will use primary data collected from a nationally-representative, probability-based panel. Target sample size for both primary datasets is 1500. The three study aims are as follows: Aim 1 will develop and evaluate links between the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS®-29) and legacy measures used for chronic pain such as the Roland-Morris Disability Questionnaire (RMDQ) and the Oswestry Disability Index (ODI). We will assess the best method of score linking and create crosswalk tables. Aim 2 will evaluate and refine the Impact Stratification Score (ISS) based on 9 PROMIS-29 items and proposed by the NIH Research Task Force on chronic low back pain. We will evaluate the ISS in terms of other indicators of condition severity and patient prognosis and outcomes and identify cut-points to stratify chronic pain patients into subgroups. Aim 3 will evaluate the strengths and limitations of MTurk as a data collection platform for estimating chronic pain by comparing its data to other data sources. DISCUSSION: The accomplishment of Aims 1 and 2 will allow direct comparison of results across past and future studies of chronic pain. These comparisons will help us to understand different results from seemingly similar studies, and to determine the relative effectiveness of all pharmaceutical and nonpharmacologic interventions for chronic pain across different trials. Aim 3 findings will provide valuable information to researchers about the pros and cons of using the MTurk platform for research-based data collection. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04426812 ; June 10, 2020.

Cost analysis of a randomized trial of Getting to Outcomes implementation support for a teen pregnancy prevention program offered in Boys and Girls Clubs in Alabama and Georgia.

Implementation support can improve outcomes of evidence-based programs (EBP) for adolescents, but with a cost. To assist in determining whether this cost is worthwhile, this study estimated the cost of adding Getting To Outcomes© (GTO) implementation support to a teen pregnancy and sexually transmitted infection prevention EBP called Making Proud Choices (MPC) in 32 Boys and Girls Clubs (BGCs) in Alabama and Georgia. Enhancing Quality Interventions Promoting Healthy Sexuality (EQUIPS) was a 2-year, cluster-randomized controlled trial comparing MPC with MPC + GTO. We used micro-costing to estimate costs and captured MPC and GTO time from activity logs completed by GTO staff. Key resource use and cost components were compared between the randomized groups, years, and states (to capture different community site circumstances) using 2-sample t tests. There were no significant differences between randomized groups in attendees per site, resource use, or costs for either year. However, there were significant differences between states. Adding GTO to MPC increased the societal costs per attendee from $67 to $144 (2015 US dollars) in Georgia and from $106 to $314 in Alabama. The higher Alabama cost was due to longer travel distances and to more BGC staff time spent on GTO in that state. GTO also improved adherence, classroom delivery, and condom-use intentions more in Alabama youth. Thus, Alabama's GTO-related BGC staff time costs may be better estimates of effective GTO. If teen childbearing costs taxpayers approximately $20,000 per teen birth, adding GTO to MPC would be worthwhile to society if it prevented one more teen birth per 140 attendees than MPC alone.Trial registration. ClinicalTrials.gov , NCT01818791. Registered March 26, 2013, https://clinicaltrials.gov/ct2/show/NCT01818791?term=NCT01818791&draw=2&rank=1.

Cost Analysis of a Randomized Trial of Getting to Outcomes Implementation Support of CHOICE in Boys and Girls Clubs in Southern California.

Costs of supporting prevention program implementation are not well known. This study estimates the societal costs of implementing CHOICE, a voluntary after-school alcohol and other drug prevention program for adolescents, in Boys and Girls Clubs (BGCs) across Southern California with and without an implementation support system called Getting To Outcomes© (GTO). This article uses micro-costing methods to estimate the cost of the CHOICE program and GTO support. Labor and expense data were obtained from logs kept by the BGC staff and by the GTO technical assistance (TA) staff, and staff time was valued based on Bureau of Labor Statistics estimates. From the societal perspective, the cost of implementing CHOICE at BGCs over the 2-year study period was $27 per attendee when CHOICE was offered by itself (all costs incurred by the BGCs) and $177 per attendee when CHOICE was offered with GTO implementation support ($67 cost to the BGCs; $110 to the entity funding GTO). These results were most sensitive to assumptions as to the number of times CHOICE was offered per year. Adding GTO implementation support to CHOICE increased the cost per attendee by approximately $150. For this additional cost, there was evidence that the CHOICE program was offered with more fidelity and offered more often after the 2-year intervention ended. If the long-term benefits of this better and continued implementation are found to exceed these additional costs, GTO could be an attractive structure to support evidence-based substance misuse prevention programs. Trial Registration. This project is registered at ClinicalTrials.gov with number NCT02135991 (URL: https://clinicaltrials.gov/show/NCT02135991). The trial was registered May 12, 2014.

Clinical Scenarios for Which Spinal Mobilization and Manipulation Are Considered by an Expert Panel to be Inappropriate (and Appropriate) for Patients With Chronic Low Back Pain.

BACKGROUND: Spinal mobilization and manipulation are 2 therapies found to be generally safe and effective for chronic low back pain (CLBP). However, the question remains whether they are appropriate for all CLBP patients. RESEARCH DESIGN: An expert panel used a well-validated approach, including an evidence synthesis and clinical acumen, to develop and then rate the appropriateness of the use of spinal mobilization and manipulation across an exhaustive list of clinical scenarios which could present for CLBP. Decision tree analysis (DTA) was used to identify the key patient characteristics that affected the ratings. RESULTS: Nine hundred clinical scenarios were defined and then rated by a 9-member expert panel as to the appropriateness of spinal mobilization and manipulation. Across clinical scenarios more were rated appropriate than inappropriate. However, the number patients presenting with each scenario is not yet known. Nevertheless, DTA indicates that all clinical scenarios that included major neurological findings, and some others involving imaging findings of central herniated nucleus pulposus, spinal stenosis, or free fragments, were rated as inappropriate for both spinal mobilization and manipulation. DTA also identified the absence of these imaging findings and no previous laminectomy as the most important patient characteristics in predicting ratings of appropriate. CONCLUSIONS: A well-validated expert panel-based approach was used to develop and then rate the appropriateness of the use of spinal mobilization and manipulation across the clinical scenarios which could present for CLBP. Information on the clinical scenarios for which these therapies are inappropriate should be added to clinical guidelines for CLBP.