Baseline sample characteristics for the BackInAction pragmatic trial of acupuncture for chronic low back pain in older adults.

Baseline Sample Characteristics for the BackInAction Pragmatic Trial of Acupuncture for Chronic Low Back Pain in Older Adults - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Contemp Clin Trials . Author manuscript; available in PMC: 2026 Jun 6. Published in final edited form as: Contemp Clin Trials. 2025 Jun 6;155:107981. doi: 10.1016/j.cct.2025.107981 Baseline Sample Characteristics for the BackInAction Pragmatic Trial of Acupuncture for Chronic Low Back Pain in Older Adults Morgan Justice a, * , Annie Piccorelli a , Andrew L Avins b, c , Andrea J Cook a , Carolyn M Eng a , Arya Nielsen d , Alice Pressman c, e, f , Katie L Stone c, g , Raymond Y Teets h , Robert Wellman a , Lynn L DeBar i Author information Article notes Copyright and License information a Kaiser Permanente Washington Health Research Institute, Seattle WA. b Kaiser Permanente Northern California Division of Research, Oakland, CA. c University of California Department of Epidemiology and Biostatistics, San Francisco, CA. d Icahn School of Medicine at Mount Sinai, Department of Family Medicine & Community Health, New York, NY. e Kaiser Permanente Bernard J Tyson School of Medicine, Pasadena, CA f Sutter Health Center for Health Systems Research, Walnut Creek, CA. g Sutter Health California Pacific Medical Center Research Institute, San Francisco, CA. h Institute for Family Health, New York, NY. i Kaiser Permanente Center for Health Research, Portland, OR. 7. Contributors Morgan Justice: Conceptualization, Methodology, Validation, Investigation, Data Curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration. Annie Piccorelli: Validation, Formal analysis, Methodology, Investigation, Writing – review & editing. Andrew L. Avins: Conceptualization, Methodology, Investigation, Writing – review & editing, Supervision, Project administration, Funding acquisition. Andrea Cook: Conceptualization, Validation, Formal analysis, Methodology, Investigation, Writing – review & editing. Carolyn M. Eng: Methodology, Validation, Investigation, Data curation, Writing – original draft, Writing – review & editing, Visualization, Project administration. Arya Nielsen: Methodology, Writing – review & editing. Alice Pressman: Conceptualization, Methodology, Investigation, Writing – review & editing, Supervision, Project administration, Funding acquisition. Katie L. Stone: Investigation, Writing – review & editing, Supervision. Raymond Y. Teets: Conceptualization, Methodology, Investigation, Writing – review & editing, Supervision, Project administration, Funding acquisition. Robert Wellman: Validation, Formal analysis, Methodology, Investigation, Writing – review & editing. Lynn DeBar: Conceptualization, Methodology, Validation, Investigation, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition. * Corresponding author; morgan.j.fuoco@kp.org ; 1730 Minor Avenue, Suite 1600, Seattle, WA 98101 Issue date 2025 Aug. PMC Copyright notice PMCID: PMC12303732  NIHMSID: NIHMS2088672  PMID: 40484274 The publisher's version of this article is available at Contemp Clin Trials Abstract Background: Chronic low back pain (cLBP) is a leading cause of disability, particularly among older adults. Despite this, effective nonpharmacologic treatments such as acupuncture have not been adequately studied in older adults. The “BackInAction” pragmatic clinical trial aims to address this gap by evaluating the effectiveness of acupuncture in reducing back pain-related disability among adults aged ≥65. The purpose of this manuscript is to compare sample characteristics across sites and across waves of COVID-19. Methods: We describe participant baseline characteristics for the BackInAction trial, a three-arm randomized trial conducted across four U.S. healthcare systems: two integrated care delivery, a fee-for-service (FFS) system, and an urban federally qualified health center (FQHC). Participants (N = 800) with cLBP were randomized to receive standard acupuncture, standard acupuncture plus maintenance sessions, or usual medical care. Baseline data were collected through self-reported measures and electronic health records. Recruitment trends are evaluated during COVID waves. Results: The sample was predominantly female (61.9%) and non-Hispanic white (64.6%), with an average age of 73.6 years. The FQHC enrolled a younger, more diverse and socioeconomically disadvantaged population with higher levels of back pain-related dysfunction. The FFS enrolled an older population but had similar rates of back pain-related dysfunction and pain intensity as in the integrated care delivery systems. There were no differences by site corresponding to the circulation of COVID-19 strains. Conclusion: Findings suggest that FQHC populations have higher-than-average social and clinical risks, illustrating the complexity of delivering treatment for cLBP and the urgency to ensure such clinical environments are included in trials. Trial Registration: ClinicalTrials.gov Identifier: NCT04982315 . Clinical trial registration date: July 29, 2021 Keywords: Chronic low back pain, acupuncture, pragmatic clinical trial, older adults 1. Background Low back pain (LBP) is the leading cause of disability worldwide, affecting up to 46% 1 of adults in the United States (U.S.) and is expected to increase significantly by 2050. 2 The prevalence of chronic LBP (cLBP), defined as pain lasting more than 3 months, increases with age with an estimated 36% of older adults in the United States experiencing cLBP. 3 , 4 Pharmacologic and other biomedical treatments for cLBP are not as effective at reducing pain and improving functioning as they once were thought to be and older adults are particularly vulnerable to their adverse effects. 5 Nonpharmacologic treatments (NPT), particularly acupuncture therapy, have shown effectiveness in general populations at reducing pain and improving functioning, 6 – 9 but no clinical trials of acupuncture have focused solely on older adults and many clinical trials 10 , 11 exclude older adults altogether, assuming that findings will be generalizable. However, physical limitations and comorbid conditions may change how older adults benefit from NPTs including acupuncture. 12 – 14 It is important to understand NPT intervention effects in real-world settings with diverse populations. BackInAction is a three-arm pragmatic clinical trial to test the effectiveness of acupuncture needling for improving back pain-related disability among 800 adults aged 65 and older with cLBP. BackInAction individually randomized participants from four US healthcare systems to a standard course of acupuncture (up to 15 treatment sessions in 12 weeks), a standard course of acupuncture plus maintenance sessions (up to 6 additional treatment sessions in the following 12 weeks), and usual medical care alone. Participants were followed for 12 months post-randomization with the primary outcome time point at 6-months post-randomization. Details of the trial design and intervention have been previously published. 15 , 16 This study describes the baseline patient characteristics of the BackInAction participants from the four healthcare systems who were enrolled in the trial using participant reported data and data from the electronic health record (EHR). The objectives are to compare demographic and clinical characteristics across diverse healthcare settings and to evaluate trends in demographic and clinical characteristics of enrolled participants to determine if there were temporal-related recruitment changes coinciding with COVID-19 waves. High circulation periods of COVID-19 had the potential to impact recruitment, retention, or treatment response through mechanisms such as stress and isolation and therefore could affect trial analyses. 1.0. Methods 1.1. Setting and population The data reported here are from participants enrolled in the BackInAction trial and includes patient reported outcomes (PROs), participant reported socio-demographics, and EHR data. The study participants were from four healthcare systems across the United States including the Institute for Family Health (IFH; N=123), Kaiser Permanente (KP) Northern California (KPNC; N=286), KP Washington (KPWA; N=185), and Sutter Health (SH; N=206) across 3 states (New York, California, and Washington). The sample size at each healthcare system was scaled based on the size of the eligible populations and the actual recruitment reflects the target sample sizes at all sites. The types of healthcare systems included a network of Federally Qualified Health Centers (FQHCs) in an urban setting serving primary care patients (IFH), two integrated health insurance and care delivery systems serving broad geographic regions with the full range of healthcare services (e.g., primary care, acute care, specialty care, pharmacy: KPNC and KPWA), and a fee-for-service (FFS) system serving a relatively urban and suburban population with a full range of healthcare services for patients who sought care within their system (SH). All systems used Epic Systems Corporation’s EpicCare ® EHR and provided EHR data. Participants were enrolled in BackInAction if they were ≥ 65 years old, receiving primary care at one of the sites, met criteria for chronic low back pain as measured by self-report of experiencing low back pain for 3 months and met the threshold on the 3-item PEG (composite of pain intensity and interference with enjoyment of life and general activity). Participants were excluded if they met any of the following criteria: received acupuncture within the past six months, had low back surgery within the past 3 months, had a nonqualifying pain diagnosis, had a current cancer-related diagnosis or other serious underlying health issue, were residing in a nursing home, receiving hospice or palliative care, were unable to communicate in English (KPNC, KPWA, SH, IFH) or Spanish (IFH), or had cognitive impairment of a severity that precluded reasonable participation in study assessments. Details of the inclusion and exclusion criteria have been previously published. 16 Participants were enrolled in the study between August 12, 2021 – October 27, 2022 and provided verbal or written consent (electronically or on paper). This study was approved (#1474280) by the KPNC Institutional Review Board (IRB), with each of the healthcare system IRBs ceding to KPNC IRB after verifying HIPAA compliance and minimal risk to the participants. 1.2. Data collection The baseline data reported here were collected from participants immediately prior to randomization and from the EHR during the 1-year period prior to randomization. Participant demographics, clinical characteristics, and baseline measures of the outcomes were collected by each site’s research team via telephone and entered into a secure and HIPAA-compliant web-based electronic data capture and management tool, REDCap, 17 – 19 hosted at each of the study sites. Data are reported only on participants who were subsequently randomized and enrolled. EHR data were collected on enrolled participants during the 1-year period prior to randomization and include clinical characteristics, i.e., mental health conditions, substance use conditions, pain diagnoses, and other comorbidities. Diagnoses were based on the International Classification of Disease-10 th edition (ICD-10-CM) diagnostic codes. 1.3. Measures 1.3.1. Patient characteristics This study used the Helping to End Addiction Long-term (HEAL) Initiative common data elements (CDEs) 20 to collect information on participants’ age, sex, gender, education, race, ethnicity, marital status, employment status and household income. Additionally, participants reported whether pain limited their ability to work, whether they’ve applied for or received disability insurance for their low back pain, and measures needed to calculate their body mass index (BMI). ICD-10 codes documented anytime during the 1-year baseline period were used to create indicators for medical morbidity, 21 specific pain conditions, 22 substance use conditions, and mental health conditions (e.g., anxiety and depression). A combination of EHR-documented comorbidity diagnoses and patient-collected data were used to create a measure of frailty. 23 We also obtained long-term opioid therapy (LTOT) status in the quarter before randomization from dispensed medication information available at KPNC, KPWA, and SH. LTOT status was not available at IFH. 1.3.2. Baseline values for outcome measures and other PROs Baseline responses to the primary, secondary, and exploratory outcomes for the BackInAction trial were collected from participant’s self-report. The primary baseline outcome was back pain-related dysfunction measured by the Roland Morris Disability Questionnaire (RMDQ). 24 RMDQ scores range from 0–24, with higher values indicating more difficulty doing things participants would normally do as a result of back pain. 24 We report the average level of back pain-related dysfunction. The two main secondary baseline outcomes were physical functioning measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function – Short Form 6b 25 – 27 and the composite of pain intensity and interference with enjoyment of life and general activity questionnaire (PEG) 28 . We additionally report the standard numerical rating scale for pain intensity extracted from the PEG. The PEG pain intensity subscale ranges from 0–10 with 0 indicating “no pain” and 10 indicating “pain as bad as you can imagine”. 28 The PROMIS Physical Function raw outcome measure ranges from 6–30, with lower scores indicating less capability. Scores for all PROMIS measures are then transformed into a T-score distribution in which 50 is the mean for the reference population (general adult population unless otherwise specified) and 40 is one standard deviation lower than the mean and 60 is one standard deviation above the mean. 29 For PROMIS Physical Function T-score clinical cut points are: >45 Within Normal Limits; 45–40 Mild; 40–30 Moderate; and <30 Severe. Exploratory outcomes measured at baseline include: sleep quality measured by the PROMIS Sleep Disturbance – Short Form 6a; 30 , 31 anxiety and depression symptoms measured by the Patient Health Questionnaire screener (PHQ-4); 32 fatigue measured by the PROMIS Fatigue – Short Form 4a; 33 , 34 and engagement in social roles measured by the PROMIS Ability to Participate in Social Roles – Short Form 4a. 35 , 36 The PROMIS Sleep Disturbance – Short Form 6a raw score ranges from 6–30, with higher scores indicating greater sleep disturbance and T-score clinical cut points are: <55 Within Normal Limits; 55–60 Mild; 60–70 Moderate; and >70 Severe with the reference population being adults with chronic pain conditions. 37 The PHQ-4 is comprised of an anxiety symptom component with scores that range from 0–6 with higher scored indicating increased anxiety symptoms 38 and a depression symptom component with scores that range from 0–6 with higher scores indicating increased depression symptoms. 32 The PROMIS Fatigue - Short Form 4a raw score ranges from 4–20, with higher scores indicating more fatigue and T-score clinical cut points are: <55 Within Normal Limits; 55–60 Mild; 60–70 Moderate; and >70 Severe. 34 The PROMIS Ability to Participate in Social Roles raw score ranges from 4–29, with lower scores indicating greater limitation and T-score clinical cut points are: >45 Within Normal Limits; 45–40 Mild; 40–30 Moderate; and <30 Severe. 39 The study also collected other measures to characterize participants at baseline, including pain catastrophizing, 40 high impact chronic pain, 41 sciatica symptoms, 42 fear avoidance, 42 expectations of acupuncture (scale 1–10, with high scores indicating higher expectations; study developed), substance use measured by the TAPS screener, 43 the impact of the COVID pandemic on participants’ health and access to healthcare, 44 and use of pain medications, cannabis, herbs or nutritional supplements, self-management programs, mind-body techniques, online programs, or psychological counseling for back pain management. Participants were also asked about their use of active exercise, low back exercise, and other movement-based therapies (such as Tai Chi or yoga) over the past month. 1.3.3. COVID-19 pandemic waves during recruitment The recruitment for the trial occurred July 2021-November 2022 which coincided with the COVID-19 pandemic that began in the US in early 2020. During the recruitment period there were different frequencies and strains of COVID-19 circulating creating COVID waves of circulation. To capture these COVID waves we have defined the following COVID wave variable based on test positivity rates from the CDC 45 as: Delta Wave (July-Sept. 2021), 1 st Lull (Oct.-Nov. 2021), 1 st Omicron Wave (Dec. 2021-Feb. 2022), 2 nd Lull (Mar.-Apr. 2022), 2 nd Omicron Wave (May-Aug. 2022), and 3 rd Lull (Sept.-Nov. 2022). These time periods will be used in the COVID wave analysis. Further we have created a high COVID circulation variable (Delta Wave and both Omicron Waves) relative to the lulls in COVID circulation variables (Lulls 1–3). 1.4. Analyses Descriptive summary statistics are presented for participant baseline demographic characteristics, baseline clinical characteristics, and baseline outcomes overall and stratified by healthcare system. Then we present descriptive summary statistics of site, baseline participant demographic characteristics, and baseline back pain-related dysfunction, depression and anxiety stratified by high COVID-19 circulation and COVID-19 wave. Descriptive summary statistics include frequency and percentages for categorical variables and mean and standard deviations (SD) for continuous variables. For a given variable, those with missing values were excluded from the calculations and the amount of missingness by variable is reported as a footnote in each table. The analyses for this paper were generated using SAS software version 9.4. 2. Results The study sample included 800 primary care patients with chronic low back pain aged 65 and older with 123 participants enrolled in the FQHC site (15.4%), 286 in the California integrated care delivery site (35.8%), 185 in the Pacific Northwest integrated care delivery site (23.1%), and 206 in the FFS site (25.8%). As shown in Table 1 the overall sample was primarily female (61.9%) and white non-Hispanic (64.6%). The average age was 73.6 years old (SD: 6.0). FQHC participants were younger on average (mean age 71.2 years, SD: 5.7), and more likely to be female (72.4%), Black non-Hispanic (35.6%), and Hispanic (39.0%) compared to each of the other three healthcare systems. The FFS site had an older (55.8% 75+), more highly educated (41.3% with a doctoral or post-graduate degree), and higher income (27.2% with income $150,000 or higher) population than the other three healthcare systems. Additionally, FQHC participants were more likely to have a high school degree or less (40.7%) and have a household income less than $25,000 (62.6%) compared to the other healthcare systems. The FQHC site was also the only healthcare system to enroll Spanish-speaking participants (26.8%). Table 1. Baseline Demographic Characteristics CHARACTERISTICS Overall N=800 IFH N=123 KPNC N=286 KPWA N=185 SH N=206 Age, b mean (sd) 73.6 (6.0) 71.2 (5.7) 73.2 (5.6) 73.3 (5.8) 76.1 (6.0) Age Category, b N (%) 65–74 472 (59.0) 95 (77.2) 175 (61.2) 111 (60.0) 91 (44.2) 75–84 287 (35.9) 23 (18.7) 103 (36.0) 66 (35.7) 95 (46.1) 85+ 41 (5.1) 5 (4.1) 8 (2.8) 8 (4.3) 20 (9.7) Female, b N (%) 495 (61.9) 89 (72.4) 171 (59.8) 108 (58.4) 127 (61.7) Education b N (%) High school degree or less 107 (13.4) 50 (40.7) 30 (10.6) 17 (9.2) 10 (4.9) At least some college 442 (55.4) 58 (47.2) 164 (57.3) 109 (58.9) 111 (53.9) Doctoral or postgraduate degree 249 (31.2) 15 (12.2) 90 (31.7) 59 (31.9) 85 (41.3) Spanish Language preference, N (%) 33 (4.1) 33 (26.8) 0 (0.0) 0 (0.0) 0 (0.0) Race and Ethnicity, b N (%) White Non-Hispanic 510 (64.6) 26 (22.0) 179 (63.5) 148 (80.0) 157 (77.0) Black or African American Non-Hispanic 132 (16.7) 42 (35.6) 52 (18.4) 11 (6.0) 27 (13.2) Hispanic 86 (10.9) 46 (39.0) 21 (7.5) 17 (9.2) 2 (1.0) Asian 42 (5.3) 0 (0.0) 20 (7.1) 7 (3.8) 15 (7.4) American Indian/ Alaska Native 3 (0.4) 2 (1.7) 1 (0.4) 0 (0.0) 0 (0.0) Native Hawaiian or Other Pacific Islander 3 (0.4) 0 (0.0) 3 (1.1) 0. (0.0) 0 (0.0) Multiple race (only non-Hispanic) 13 (1.7) 2 (1.7) 6 (2.1) 2 (1.1) 3 (1.5) Household income, b N (%) Less than $25,000 99 (15.4) 57 (62.6) 20 (9.3) 12 (7.1) 10 (5.9) $25,000 – $49,999 124 (19.3) 22 (24.2) 35 (16.3) 48 (28.6) 19 (11.2) $50,000 – $99,999 212 (33.0) 9 (9.9) 84 (39.1) 59 (35.1) 60 (35.5) $100,000 – $149,999 104 (16.2) 1 (1.1) 43 (20.0) 26 (15.5) 34 (20.1) $150,000 or more 104 (16.2) 2 (2.2) 33 (15.4) 23 (13.7) 46 (27.2) Received disability for LBP, b N (%) 77 (9.8) 18 (14.9) 22 (7.8) 11 (6.0) 26 (12.8) Pain limits work, b N (%) 389 (48.8) 77 (62.6) 128 (44.8) 76 (41.1) 108 (52.9) Married or domestic partnered, b N (%) 455 (57.6) 31 (25.4) 170 (60.9) 128 (69.2) 126 (61.8) Open in a new tab a Data are presented as number (percentage) of participants observed. Data were missing for the following: education 2; race and ethnicity 11; household income 157; received disability for LBP 10; pain limits work 2; married or domestic partnered 10. b HEAL common data element Table 1 also shows the prevalence for participants overall and at each healthcare system who reported receiving disability for LBP (9.8%), pain that limited their work on most or every day in the prior 3 months (48.8%), and those who were married or domestic partnered (57.6%). The two integrate care delivery systems are similar in the percent of participants who reported receiving disability for LBP and those who reported pain that limits their work, while the FQHC and FFS sites have the two highest prevalence of participants who reported receiving disability for LBP (14.9% and 12.8% respectively) and having pain that limits their work (62.6% and 52.9% respectively). Overall, 57.6% of the sample was married or domestic partnered, although prevalence was lower among FQHC participants (25.4%). Table 2 shows clinical characteristics of participants based on the electronic health record (EHR). Overall, 32.1% of the sample met criteria for obesity, ranging from a high of 52.5% of FQHC participants to 21.5% of FFS participants. The two integrated care delivery sites and the FFS site SH had similar proportions of participants who were frail while the FQHC site had over twice the proportion as other sites who were frail (40.7% v. 16–18%). The overall sample had an average of 2.7 (SD: 2.0) medical comorbidities based on the Elixhauser Index with FFS participants having a slightly lower average (mean 2.1, SD: 1.9) than the other three healthcare systems. Overall, 17.4% of participants had at least one dispensing of opioid medication and 3.8% were on long-term opioid therapy during the three months prior to randomization. Medication data were not available at the FQHC site. All sites had a high prevalence of participants with EHR-identified multiple non-back musculoskeletal pain conditions. The most common pain conditions were arthritis (71.3%), general pain (55.9%), and neck pain (20.8%). Overall, 26.9% of the sample had an EHR-documented diagnosis for anxiety or depression with FQHC participants having the highest proportion (35.8%) and FFS participants having the lowest (19.4%). Table 2. Baseline Clinical Characteristics CHARACTERISTICS Overall N=800 IFH N=123 KPNC N=286 KPWA N=185 SH N=206 BMI Obese (>=30 kg/m2), N (%) 253 (32.1) 63 (52.5) 81 (29.0) 65 (35.3) 44 (21.5) BMI, mean (sd) 28.1 (6.1) 31.6 (7.8) 27.7 (5.6) 28.6 (5.6) 26.3 (5.2) Frailty, c , f mean (sd) 1.4 (1.2) 2.1 (1.2) 1.2 (1.1) 1.2 (1.1) 1.3 (1.2) Robust, N (%) 222 (28.9) 14 (11.9) 91 (33.6) 57 (32.0) 60 (30.0) Pre-frail, N (%) 389 (50.7) 56 (47.5) 136 (50.2) 92 (51.7) 105 (52.5) Frail, N (%) 156 (20.3) 48 (40.7) 44 (16.2) 29 (16.3) 35 (17.5) Medical Morbidity (Elixhauser), c mean (sd) 2.7 (2.0) 2.9 (1.8) 3.0 (2.0) 2.6 (2.3) 2.1 (1.9) Any opioid in prior 3 months, N (%) 110 (17.4) - 57 (19.9) 23 (12.5) 30 (18.5) Long-term opioid therapy, N (%) 24 (3.8) - 13 (4.6) 4 (2.2) 7 (4.3) Multiple non-back musculoskeletal pain conditions, c N (%) 687 (85.9) 103 (83.7) 261 (91.3) 168(90.8) 155 (75.2) Number of pain conditions, c mean (sd) 1.75 (1.1) 1.6 (1) 1.89 (1.1) 1.97 (1.1) 1.44 (1.1) Types of pain conditions, c , d N (%) Neck pain 166 (20.8) 16 (13.0) 57 (19.9) 59 (31.9) 34 (16.5) Fibromyalgia 14 (1.8) 5 (4.1) 3 (1.1) 3 (1.6) 3 (1.5) Limb/extremity, joint, and non-systemic, non-inflam arthritic pain 570 (71.3) 89 (72.4) 207 (72.4) 142 (76.8) 132 (64.1) Muskuloskeletal chest pain 115 (14.4) 10 (8.1) 48 (16.8) 36 (19.5) 21 (10.2) Headache or migraine 70 (8.8) 7 (5.7) 36 (12.6) 18 (9.7) 9 (4.4) Toothache, ear, or jaw pain 17 (2.1) 0 (0.0) 8 (2.8) 7 (3.8) 2 (1.0) General pain 447 (55.9) 70 (56.9) 182 (63.6) 99 (53.5) 96 (46.6) Mental Health Mood Disorder, c , d N (%) 215 (26.9) 44 (35.8) 76 (26.6) 55 (29.7) 40 (19.4) Anxiety, N (%) 138 (17.3) 24 (19.5) 54 (18.9) 30 (16.2) 30 (14.6) Depression, N (%) 128 (16.0) 32 (26.0) 36 (12.6) 43 (23.2) 17 (8.3) Open in a new tab a Data are presented as number (percentage) of participants observed. Data were missing for the following: BMI 12; frailty 33; medical morbidity (Elixhauser) 2. b HEAL common data element c Derived from the electronic health record (EHR) d Categories are not mutually exclusive e Active use disorders and use conditions f Patient reported Table 3 shows patient-reported outcome measures by site. The average level of back pain-related dysfunction on RMDQ was 13.2 (SD: 5.5) with 24.5% of the sample having a score 18 or higher. The average PEG score of the sample was 5.6 (SD: 2.2) and the average PROMIS Physical Function score was 38.2 (SD: 6.6). The average level of pain intensity was 5.9 (SD: 2.0) and FQHC participants had the highest average pain intensity score (mean: 7.5, SD: 1.7) among the four healthcare systems. For back pain-related dysfunction, FQHC participants were nearly 5 points higher (mean: 17.3, SD: 5.3), on average, and were nearly three times more likely to have a score of 18 or higher on the RMDQ than each of the other healthcare systems’ participants. FQHC participants also reported higher baseline PEG scores (mean 7.3, SD: 2.0) while the other healthcare systems were similar to each other. The California integrated care delivery site (mean: 39.9, SD: 6.2), the Pacific Northwest integrated care delivery site (mean: 39.4, SD: 5.3), and the FFS site (mean: 37.9, SD: 6.4) participants reported higher levels of physical functioning compared to the FQHC site (mean: 32.8, SD: 6.7). Table 3. Baseline Patient-Reported Outcome Measures CHARACTERISTICS Overall N=800 IFH N=123 KPNC N=286 KPWA N=185 SH N=206 Baseline Primary Outcome Back-Related Dysfunction (RMDQ) mean (sd) 13.2 (5.5) 17.3 (5.3) 12.6 (5.4) 12.2 (4.9) 12.5 (5.2) ≥18 score, N (%) 196 (24.5) 73 (59.4) 59 (20.6) 27 (14.6) 37 (18.0) Baseline Secondary Outcomes Pain (PEG), b mean (sd) 5.6 (2.2) 7.3 (2.0) 5.3 (2.1) 5.0 (1.9) 5.4 (2.2) Pain Intensity, mean (sd) 5.9 (2.0) 7.5 (1.7) 5.6 (1.8) 5.4 (1.7) 5.7 (2.0) PROMIS Physical Function - SF6b, b mean (sd) 38.2 (6.6) 32.8 (6.7) 39.9 (6.2) 39.4 (5.3) 37.9 (6.4) Baseline Tertiary Outcomes PROMIS Sleep Disturbance - SF6a, b mean (sd) 53.6 (8.3) 56.7 (9.5) 53.3 (8.1) 52.7 (8.2) 53.6 (7.9) Anxiety symptoms (GAD Subscale of PHQ-4), b mean (sd) 1.5 (1.7) 2.2 (2.1) 1.3 (1.5) 1.2 (1.6) 1.7 (1.8) Positive anxiety screen (score of 3+), N (%) 173 (22.0) 43 (36.1) 46 (16.6) 35 (18.9) 49 (24.0) Depression symptoms (PHQ-2), b mean (sd) 1.4 (1.6) 2.2 (2.0) 1.3 (1.4) 1.0 (1.3) 1.4 (1.6) Positive depression screen (score of 3+), N (%) 162 (20.8) 49 (41.2) 45 (16.4) 25 (13.7) 43 (21.3) PROMIS Fatigue - SF4a, mean (sd) 55.3 (8.9) 59.1 (10.7) 54.1 (8.3) 54.1 (8.3) 55.9 (8.4) PROMIS Engagement in Social Roles - SF4a, mean (sd) 45.5 (8.3) 41.8 (9.4) 46.3 (8.5) 46.5 (7.4) 45.4 (7.7) Other Measures High impact chronic pain, N (%) 375 (47.2) 74 (61.2) 124 (43.5) 73 (39.5) 104 (51.0) Pain catastrophizing, b mean (sd) 9.8 (5.9) 13.4 (6.7) 9.5 (5.7) 8.2 (5.0) 9.4 (5.7) Expectations of acupuncture, mean (sd) 6.4 (2.4) 7.9 (2.3) 6.0 (2.3) 6.0 (2.4) 6.3 (2.4) Sleep duration, b mean (sd) 6.4 (1.4) 5.9 (1.6) 6.6 (1.3) 6.5 (1.3) 6.6 (1.4) Fear avoidance, N (%) 150 (19.3) 39 (34.2) 52 (18.8) 24 (13.0) 35 (17.4) TAPS b positive screen, N (%) 233 (29.2) 33 (27.1) 81 (28.3) 55 (29.7) 64 (31.1) Tobacco use 49 (6.2) 13 (10.9) 16 (5.6) 11 (6.0) 9 (4.4) Alcohol use 114 (14.6) 14 (13.0) 34 (12.0) 34 (18.4) 32 (15.6) Illicit drug use 107 (13.5) 16 (13.3) 45 (16.0) 18 (9.8) 28 (13.6) Prescription drug misuse 24 (3.0) 2 (1.7) 4 (1.4) 3 (1.6) 15 (7.3) Self-management program for back pain, N (%) 74 (9.3) 13 (10.7) 37 (13.0) 14 (7.6) 10 (4.9) Mind-body techniques for back pain, N (%) 173 (21.9) 14 (12.1) 71 (24.8) 48 (26.2) 40 (19.4) Online pain management program for back pain, N (%) 22 (2.8) 0 (0.0) 12 (4.2) 8 (4.3) 2 (1.0) Psychological counseling for back pain, N (%) 11 (1.4) 4 (3.3) 2 (0.7) 3 (1.6) 2 (1.0) How has COVID affected you in last 3 months, N (%) Reduced your ability to get healthcare a lot 70 (8.8) 20 (16.3) 19 (6.7) 15 (8.2) 16 (7.8) Reduced your ability to get healthcare a little 167 (21.0) 21 (17.1) 59 (20.8) 50 (27.3) 37 (18.1) Not affected your ability to get healthcare. 543 (68.3) 69 (56.10%) 206 (72.5) 117 (63.9) 151 (73.7) Improved your ability to get healthcare. 15 (1.9) 13 (10.6) 0 (0.0) 1 (0.6) 1 (0.5) How has COVID affected overall health in the last 3 months? Your overall health is a lot worse 57 (7.2) 27 (22.3) 10 (3.6) 5 (2.7) 15 (7.3) Your overall health is a little worse 238 (30.1) 28 (23.1) 78 (27.8) 60 (32.6) 72 (35.1) Not affected your overall health 483 (61.1) 60 (49.6) 189 (67.3) 118 (64.1) 116 (56.6) Improved your overall health 13 (1.6) 6 (5.0) 4 (1.4) 1 (0.5) 2 (1.0) Sciatica, N (%) 544 (68.6) 95 (81.9) 184 (64.3) 127 (68.7) 138 (67.0) Use of NSAIDs for back pain, N (%) 435 (55.7) 42 (39.6) 176 (61.5) 113 (61.4) 104 (50.7) Use of acetaminophen for back pain, N (%) 425 (53.3) 64 (53.3) 147 (51.4) 102 (55.1) 112 (54.4) Use of cannabis for back pain, N (%) 130 (16.3) 11 (9) 61 (21.3) 28 (15.1) 30 (14.6) Use of CBD only for back pain, N (%) 109 (13.7) 8 (6.6) 44 (15.4) 25 (13.6) 32 (15.5) Use of herbal/nutritional supplements for back pain, N (%) 91 (11.5) 4 (3.4) 37 (12.9) 28 (15.2) 22 (10.7) Active exercise at least weekly, N (%) 564 (70.7) 73 (59.4) 220 (77.2) 131 (70.8) 140 (68.3) Days of Exercise, mean (sd) 4.6 (2) 4.3 (2.2) 4.6 (2.1) 4.7 (1.8) 4.6 (1.9) ≥3 days, N (%) 448 (79.4) 40 (54.8) 179 (81.4) 115 (87.8) 114 (81.4) Low back exercise at least weekly, N (%) 381 (48.1) 29 (24.0) 151 (53.6) 96 (52.2) 105 (51.2) Days of Low Back Exercise, mean (sd) 4.5 (2.1) 3.6 (1.8) 4.8 (2.1) 4.3 (2.1) 4.4 (2) ≥3 days, N (%) 294 (77.2) 13 (44.8) 127 (84.1) 70 (72.9) 84 (80) Other movement at least weekly, N (%) 128 (16.0) 18 (14.6) 54 (18.9) 28 (15.1) 28 (13.6) Days of other movement, mean (sd) 3.5 (2.1) . 3.3 (2.1) 3.4 (2.1) 4.00 (2.2) ≥3 days, N (%) 67 (52.3) 0 (0) 29 (53.7) 17 (60.7) 21 (75) Open in a new tab a Data are presented as number (percentage) of participants observed. Data were missing for the following: pain (PEG) 6; pain intensity 5; PROMIS Physical Function 31; PROMIS Sleep Duration 50; Anxiety symptoms (GAD Subscale of PHQ-4) 14; Depression symptoms (PHQ-2) 22; Fatigue 10; PROMIS Social Engagement 50; high impact chronic pain 5; pain catastrophizing 1; expectations of acupuncture 29; sleep duration 7; fear avoidance 23; TAPS positive 1; tobacco use 6; alcohol use 18; illicit drug use 9; prescription drug misuse 6; self-management 2; mind-body techniques 9; online pain management program 7; psychological counseling 4; how has COVID affected you in last 3 months 5; how has COVID affected overall health in the last 3 months 9; sciatica 7; use of NSAIDs 3; use of acetaminophen 1; use of cannabis 1; use of CBD only 2; use of herbal/nutritional supplements 2; active exercise at least weekly 2; days of exercise 24; low back exercise at least weekly 8; days of low back exercise 15; days of other movement 18. b HEAL common data element c Derived from the electronic health record (EHR) d Categories are not mutually exclusive Participants across all healthcare systems reported similar levels of sleep quality, fatigue, and engagement in social roles, although FQHC participants had higher levels of sleep disturbance and lower ability to participate in social roles compared to the other sites. FQHC participants were more likely to screen positive for anxiety (36.1%) and depression (41.2%) than other healthcare systems’ participants. FQHC participants had higher average scores on pain catastrophizing (mean: 13.4, SD: 6.7) and had a higher prevalence of participants who reported fear avoidance (34.2%) and high impact chronic pain (61.2%) than other healthcare systems’ participants. FQHC participants also reported slightly higher expectations of acupuncture (mean: 7.9, SD: 2.3) than the other three healthcare systems. The majority of participants reported having sciatica (68.6%) with FQHC participants more likely than the other three healthcare systems to report sciatica (81.9%). Most participants did not report using self-management programs, mind-body techniques, online pain management programs, or psychological counseling to manage their back pain. Over half of the sample used NSAIDs (55.7%) or acetaminophen (53.3%) for their back pain. Less than a quarter of participants reported using cannabis (16.3%) or CBD (13.7%) for their back pain. Most participants reported actively exercising at least weekly (70.7%) and slightly less than half (48.1%) reported doing low back-specific exercises at least weekly. Among those who actively exercise at least weekly, 79.4% reported exercising at least three days a week. Similarly, 77.2% of those who do low back-specific exercises reported doing them at least three days a week. However, FQHC participants were less likely than participants from other healthcare systems to report exercising (59.4%) or doing low back exercises (24.0%) at least weekly. Overall, 68.3% reported that COVID-19 did not affect their ability to get healthcare while 21.0% reported that it affected their ability to get healthcare ‘a little’ and 8.8% said it affected their ability to get healthcare ‘a lot’. Similarly, the majority (61.1%) reported that their health was not affected by COVID-19 while 30.1% said their health was a little worse and 7.2% said their health was a lot worse. FQHC participants reported more frequently than those from other healthcare systems that COVID-19 reduced their ability to get healthcare ‘a lot’ (16.3% v. KPNC 6.7%, KPWA 8.2%, and SH 7.8%) and that their overall health was a lot worse (22.3% v. KPNC 3.6%, KPWA 2.7%, SH 7.3%). However, FQHC participants were also more likely to report that the pandemic improved their ability to get healthcare (10.6%) and their overall health (5.0%). To meet our recruitment goals for specific racial and ethnic groups, the recruitment of certain racial and ethnic groups of participants changed over time coinciding to different COVID-19 waves ( Table 4 ). There was a higher proportion of non-Hispanic white participants recruited early in the study (80.0%–;82.5% in the Delta Wave and 1 st Lull (Jul-Nov 2021) vs 58.0%–;65.4% in the 1 st Omicron to the 2 nd Omicron Waves (Dec 2021-Nov 2022)). However, the number of non-Hispanic white participants recruited during a high COVID circulation period versus a low circulation period was comparable (63.8% vs 65.6, respectively). There were no substantive differences in recruitment during high COVID circulation versus a lull in COVID by age (mean 73.6 vs 73.7), back-related dysfunction (mean 13.3 vs 13.1) or anxiety (21.4% vs 21.9%). However, there was a slightly higher percent reporting depression during high COVID circulation periods (22.3%) versus during the lulls in COVID (17.7%). Table 4. Baseline Characteristics Overall and by COVID Wave Overall July - September 2021 October - November 2021 December - February 2022 March - April 2022 May - August 2022 September - November 2022 CHARACTERISTICS HIGH COVID CIRCULATION LULL IN COVID Delta Wave N=41 Lull N=120 1st Omicron Wave N=129 Lull N=171 2nd Omicron Wave N=269 Lull N=70 Healthcare System, N (%) IFH 76 (17.3) 47 (13.0) 6 (14.6) 8 (6.7) 18 (14.0) 21 (12.3) 52 (19.3) 18 (15.7) KPNC 177 (40.3) 109 (30.2) 0 (0.0) 0 (0.0) 57 (44.2) 80 (46.8) 120 (44.6) 29 (41.4) KPWA 62 (14.1) 123 (34.1) 35 (85.4) 89 (74.2) 22 (17.1) 23 (13.5) 5 (1.9) 11 (15.7) SH 124 (28.3) 82 (22.7) 0 (0.0) 23 (19.2) 32 (24.8) 47 (27.5) 92 (34.2) 12 (17.1) Age, b mean (sd) 73.6 (6.1) 73.7 (5.8) 73.4 (5.3) 73.6 (6.1) 72.9 (6.2) 73.9 (5.7) 73.9 (6.2) 73.4 (5.7) Age Category, b N (%) 65–74 264 (60.1) 208 (57.6) 25 (61.0) 71 (59.2) 83 (64.3) 94 (55.0) 156 (58.0) 43 (61.4) 75–84 152 (34.6) 135 (37.4) 15 (36.6) 42 (35.0) 40 (31.0) 69 (40.4) 97 (36.1) 24 (34.3) 85+ 23 (5.2) 18 (5.0) 1 (2.4) 7 (5.8) 6 (4.7) 8 (4.7) 16 (6.0) 3 (4.3) Female, b N (%) 264 (60.1) 231 (64.0 27 (65.9) 65 (54.2) 82 (63.6) 114 (66.7) 155 (57.6) 52 (74.3) Education b High school degree or less 59 (13.4) 48 (13.3) 4 (9.8) 15 (12.5) 8 (6.2) 19 (11.1) 47 (17.5) 14 (20.0) Associate, Technical or College Degree 249 (56.7) 193 (53.5) 27 (65.9) 63 (52.5) 80 (62.0) 94 (55.0) 142 (52.8) 36 (51.4) Doctoral or postgraduate Degree 130 (29.6) 119 (33.0 10 (24.4) 42 (35.0) 40 (31.0) 57 (33.3) 80 (29.7) 20 (28.6) Race and Ethnicity, b N(%) White Non-Hispanic 275 (62.6) 235 (65.1) 33 (82.5) 96 (80.0) 83 (64.3) 98 (57.3) 159 (59.1) 41 (58.6) Black or African American Non-Hispanic 66 (15.0) 66 (18.3) 3 (7.5) 11 (9.2) 21 (16.3) 40 (23.4) 42 (15.6) 15 (21.4) Hispanic 56 (12.8) 30 (8.3) 1 (2.5) 7 (5.8) 16 (12.4) 16 (9.4) 39 (14.5) 7 (10.0) Asian 22 (5.0) 20 (5.5) 3 (7.5) 5 (4.2) 4 (3.1) 10 (5.8) 15 (5.6) 5 (7.1) American Indian/ Alaska Native 0 (0.0) 3 (0.8) 0 (0.0) 1 (0.8) 0 (0.00%) 1 (0.6) 0 (0.0) 1 (1.4) Native Hawaiian or Other Pacific Islander 3 (0.7) 0 (0.0) 0 (0.0) 0 (0.0) 2 (1.6) 0 (0.0) 1 (0.4) 0 (0.0) Multiple race (only non-Hispanic) 9 (2.1) 4 (1.1) 0 (0.0) 0 (0.0) 1 (0.8) 4 (2.3) 8 (3.0) 0 (0.0) Household income, b N (%) Less than $25,000 59 (13.4) 40 (11.1) 7 (17.1) 10 (8.3) 17 (13.2) 17 (9.9) 35 (13.0) 13 (18.6) $25,000 – $49,999 60 (13.7) 64 (17.7) 11 (26.8) 28 (23.3) 24 (18.6) 28 (16.4) 25 (9.3) 8 (11.4) $50,000 – $99,999 109 (24.8) 103 (28.5) 14 (34.1) 33 (27.5) 31 (24.0) 52 (30.4) 64 (23.8) 18 (25.7) $100,000 – $149,999 61 (13.9) 43 (11.9) 3 (7.3) 19 (15.8) 12 (9.3) 21 (12.3) 46 (17.1) 3 (4.3) $150,000 or more 58 (13.2) 46 (12.7) 3 (7.3) 14 (11.7) 19 (14.7) 19 (11.1) 36 (13.4) 13 (18.6) Married or domestic partnered, b N (%) 238 (54.2) 217 (60.1) 23 (56.1) 81 (67.5) 63 (48.8) 98 (57.3) 152 (56.5) 38 (54.3) Back-Related Dysfunction (RMDQ) mean (sd) 13.3 (5.6) 13.1 (5.3) 12.7 (5.6) 12.6 (4.7) 12.9 (5.3) 13.5 (5.5) 13.6 (5.8) 12.75 (5.79) ≥18 score, N (%) 112 (25.5) 84 (23.3) 9 (22.0) 19 (15.8) 28 (21.7) 47 (27.5) 75 (27.9) 18 (25.7) Positive Anxiety Screen(GAD≥3), N (%) 94 (21.4) 79 (21.9) 7 (17.1) 23 (19.2) 26 (20.2) 45 (26.3) 61 (22.7) 11 (15.7) Positive Depression Screen (PHQ-2≥3), N(%) 98 (22.3) 64 (17.7) 7 (17.1) 14 (11.7) 23 (17.8) 37 (21.6) 68 (25.3) 13 (18.6) Open in a new tab a Data are presented as number (percentage) of participants observed. Data were missing for the following: education 2; race and ethnicity 11; household income 157; married or domestic partnered 10; positive anxiety screen 14; positive depression screen (PHQ-2) 22. b HEAL common data element 3. Discussion Despite having a younger population, the FQHC site had the highest proportion of participants with disability, pain that limited work, medical comorbidities, mental health conditions, back pain-related dysfunction, heightened pain intensity, fear avoidance, and pain catastrophizing. The FQHC site also enrolled the highest proportion of ‘Black, Indigenous, and other people of color (BIPOC) participants’ and those with the lowest education and income. 46 This was accomplished through ensuring the research team had the skillset and resources necessary to help individuals historically excluded from research overcome barriers to inclusion, a practice used by other studies in this site. 47 Conversely, the FFS site had the second highest rates of disability, pain that limited work, and pain intensity, but also had the oldest population which could account for this. The two integrated care delivery sites were similar in most demographics (except racial and ethnic distributions), clinical characteristics, and patient-reported outcome measures. Pharmacologic use for chronic pain poses particular risks for older adults due to the increased polypharmacy as people age and associated adverse effects, such as falls, cognitive impairment, drug interactions, addiction, or death due to unintentional overdose. 48 , 49 The prevalence of participants receiving opioids in the integrated delivery and FFS sites was consistent with or lower than national averages. 50 Additionally, participants from these sites had fewer older adults with chronic pain who were on LTOT than the national average. 51 Opioid medication data were not available at the FQHC site. Most participants had clinical diagnoses of multiple musculoskeletal pain conditions and nearly half reported having high impact chronic pain (HICP). Adults 65 and older have higher odds of having HICP versus pain without functional limitation (OR: 6.04, 95% CI: 2.90–12.58) and individuals with low back pain are more likely to have HICP than chronic pain without limitations (OR: 1.67, 95% CI: 1.34–2.08). 52 Additionally, the majority of participants reported having symptoms of sciatica, indicating that our participants had a mix of both nonspecific back pain, for which no clear cause can be identified, and more specific pain, such as sciatica, potentially increasing pain severity. This combination suggests a population with potentially complex cLBP. There were minimal differences in characteristics of those enrolling during high COVID circulation waves relative to when COVID had less circulation. The circulation periods of various COVID-19 strains were similar across the geographic regions and therefore unlikely to impact site differences in recruitment. Differences over time in the recruitment of different racial and ethnic groups were driven by several factors including: high levels of early recruitment from the Pacific Northwest integrated care delivery system which had a less racially and ethnically diverse population, later recruitment from the urban California integrated care delivery system and the New York City FQHC, both of which had higher racial and ethnic diversity, and finally, oversampling at all sites during various times to ensure overall trial enrollment mirrored the racial and ethnic distribution of Medicare-aged older adults. However, these recruitment differences in racial and ethnic groups did not coincide with high COVID circulation waves which likely should minimize the impact of calendar-time bias on the race and ethnicity subgroup analyses of the study. Differences in site recruitment between COVID-19 waves is attributable to interruptions in recruitment at certain sites to ensure participant safety and comply with healthcare system requirements when COVID-19 variants were peaking. 47 , 53 Surprisingly, the older adult participants did not express reluctance to enroll in the trial due to concerns about COVID-19. The study team worked with the acupuncturists to ensure safety precautions were in place in each of the clinics and vaccinations were widely available when trial recruitment began. 47 These safety measures along with periods of isolation during the early part of the pandemic may have increased older adults’ interest in trial participation. While there are many strengths to our PCT, we also had several limitations. We were geographically restricted to California, Washington, and New York, and therefore we do not have representation from the Midwest, Southern, or Southwestern US. We also do not have high representation from rural areas. Additionally, we did not ask participants about a range of nonpharmacologic treatments for cLBP (e.g., physical therapy, massage, and chiropractic services). 54 Finally, opioid use is more common among those with lower socioeconomic statuses compared to people from higher socioeconomic statuses, 51 so it is a limitation of our study that opioid medications were not available at the FQHC site with the highest proportion of individuals from lower socioeconomic statuses. 4. Conclusion A strength of pragmatic clinical trials (PCTs) 55 is that the results can often be generalized, applied in real-world clinical settings and, used to inform policy decisions at the federal, state, or local clinical level. 56 Therefore, including participants who are diverse in race, ethnicity, age, gender, and socioeconomic status ensures that scientists, healthcare system leaders, and policymakers know what interventions are effective for a range of populations and settings. 57 Across all sites, we successfully enrolled a racially and ethnically diverse sample of participants proportionally representing U.S. census data on older adults’ race/ethnicity and the inclusion of an FQHC site allowed us to assess intervention effect across a broad range of healthcare system types (i.e., FQHC, FFS, and integrated care delivery). Inclusion of FQHCs in clinical trials is critical to expanding the generalizability of PCTs and informing equitable treatment policy. Results from this descriptive baseline analysis suggest that FQHC populations may have higher-than-average social and clinical risks, illustrating both the complexity of delivering treatment for cLBP and the urgency to ensure such clinical environments are included in multi-site trials. 5. Funding resource This work was supported within the National Institutes of Health (NIH) Pragmatic Trials Collaboratory through the NIH HEAL Initiative under award number UG3AT010739 and UH3AT010739 administered by the National Center for Complementary and Integrative Health (NCCIH). This work also received logistical and technical support from the PRISM Resource Coordinating Center under award number U24AT010961 from the NIH through the NIH HEAL Initiative. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NCCIH or the NIH or its HEAL Initiative. 6. Role of funding source As a cooperative agreement with the NIH (UG3/UH3 funding mechanism) we have had advisory input throughout the project with regards to design and conduct of the study, collection, management, analysis, and interpretation of the data from our program officer and others from the NCCIH (funder) and NIA project scientist. However, final decisions for this and other manuscript is at the independent discretion of our research team. Footnotes Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. 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