Baseline characteristics of Veterans from improving Veteran access to integrated management of back pain (AIM-Back) - an embedded pragmatic, cluster-randomized trial in the United States.

Baseline characteristics of Veterans from improving Veteran access to integrated management of back pain (AIM-Back) – an embedded pragmatic, cluster-randomized trial in the United States - 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 Pain Manag . 2026 Apr 7;16(6):615–623. doi: 10.1080/17581869.2026.2652307 Baseline characteristics of Veterans from improving Veteran access to integrated management of back pain (AIM-Back) – an embedded pragmatic, cluster-randomized trial in the United States Steven Z George a, b, ✉ , Courtni France c , Cynthia J Coffman c, d , Kelli D Allen c, e , Trevor A Lentz a, b , Rebecca North f , Ashley Choate c , Adam P Goode a , Corey B Simon b, f , Janet M Grubber c, g , Heather King c, h, i , Chad E Cook a, b , Francis J Keefe j , Lindsay A Ballengee c, h , Jennifer Naylor k , Joseph Leo Brothers a , Catherine Stanwyck c , Travis Linton l , Christa Tumminello c , S Nicole Hastings c, h, i Author information Article notes Copyright and License information a Duke Clinical Research Institute and Department of Population Health Sciences, Duke University, Durham, NC, USA b Department of Orthopaedic Surgery, Duke University, Durham, NC, USA c Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Healthcare System, Health Services Research, Durham, NC, USA d Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA e Division of Rheumatology, Department of Medicine, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA f Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA g Boston Cooperative Studies Program Coordinating Center, VA Boston Healthcare System, Boston, MA, USA h Department of Population Health Sciences, Duke University, Durham, NC, USA i Division of General Internal Medicine, Duke University, Durham, NC, USA j Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA k Mental Illness Research, Education and Clinical Centers (MIRECC), Durham Veterans Affairs Health Care System, Duke University, Durham, NC, USA l Department of Rehabilitation Services, Duke University, Durham, NC, USA ✉ CONTACT Steven Z. George steven.george@duke.edu Duke Clinical Research Institute and Department of Population Health Sciences, Duke University, 300 W Morgan St, Durham, NC 27701, USA Received 2025 Nov 26; Accepted 2026 Mar 25; Collection date 2026. © 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. PMC Copyright notice PMCID: PMC13112462  NIHMSID: NIHMS2165561 PMID: 41944169 Previous version available: This article is based on a previously available preprint posted on medRxiv on November 26, 2024: " Cohort Profile: Baseline Characteristics of Veterans from Improving Veteran Access to Integrated Management of Back Pain (AIM-Back) – an Embedded Pragmatic, Cluster Randomized Trial in the United States ". ABSTRACT Objective Describe baseline characteristics and representativeness of AIM-Back trial participants relative to Veterans with low back pain at participating clinics. Methods Veterans were referred to AIM-Back randomized care pathways and included 1) enrolled participants with data collected in the Electronic Health Record (EHR) by clinical staff with no consent required and 2) survey participants who provided informed consent with data collected via surveys by research staff. Descriptive statistics were reported. Participation to prevalence ratios (PPRs) were calculated for sex, age, race, and ethnicity by clinic to describe representativeness. Results Across 17 primary care clinics, the Referral cohort included 2767 unique Veterans with n = 1817 enrolled (attended initial evaluation visit), n = 996 were survey participants; n = 799 of enrolled participants (44%) were also survey participants. More than 59% of Veterans of enrolled and survey participants had High Impact Chronic Pain and approximately 10% of enrolled participants had documented opioid use in the preceding year. Older Veterans (≥65 years) were underrepresented in the Referral cohort compared to those with LBP visits at clinics (PPRs < 0.8). Conclusions These findings provide detailed insights for participants that will be included in future analyses of care pathway effectiveness. Trial registration NCT04411420 . KEYWORDS: Non-pharmacologic pain management, chronic low back pain, care pathways, care models, participation prevalence ratio, Veteran Health Administration 1. Introduction Non-pharmacological treatments that are noninvasive have been endorsed as effective, low-risk approaches (e.g., exercise, manual therapy, yoga, and cognitive behavioral therapies) for treating low back pain (LBP) by multiple entities inside and outside the U.S., including the Centers for Disease Control and Prevention [ 1 ], National Academy of Medicine [ 2 ], American College of Physicians [ 3 ], and World Health Organization [ 4 ]. Furthermore, there is evidence from observational studies indicating that non-pharmacological treatments for LBP reduce the risk of future opioid use [ 5–7 ]. Consensus recommendations in practice guidelines, and encouraging findings from the previously cited observational studies, provide foundational support for non-pharmacological care of LBP, but there is still an urgent need for research designs that address their effectiveness. Pressing research questions about the diverse characteristics of those with LBP and the structuring of non-pharmacologic care pathways to optimize clinical care persists [ 8–10 ]. Accordingly, we conducted the Improving Veteran Access to Integrated Management of Back Pain (AIM-Back) trial [ 11 ] designed as an embedded pragmatic clinical trial (ePCT) with cluster randomization and part of the National Institutes of Health-Department of Defense-Veteran Affairs Pain Management Collaboratory. This Collaboratory focuses on active military and Veterans for clinical trials because of the higher severity from LBP or joint pain reported in these populations [ 12 , 13 ]. The AIM-Back cluster randomized trial developed and implemented two different LBP care pathways designed to improve access to non-pharmacological treatments and in its primary analysis will investigate the comparative effectiveness of these care pathways for reducing pain interference and improving physical function. The AIM-Back trial also has pre-specified sub-group analyses and will identify individual-level characteristics that improve outcome response to a care pathway (i.e., heterogeneity of treatment effect analyses). Results of these analyses will be reported in separate papers after the trial is completed. Then, the purpose of this baseline paper is to provide a detailed overview of trial enrollment and a description of Veteran characteristics of the AIM-Back trial at baseline. The overall objective of the baseline paper is to provide important data on this cohort that will inform understanding and interpretation of trial findings when they are subsequently reported. An important part of this overview is the consideration of how those enrolled in the trial compare to those referred for care to AIM-Back. Specifically, we report on rates of high impact chronic pain (HICP) and opioid use, which are planned subgroups for future analyses. Additional characteristics include baseline measures of pain and function, and the representativeness of those referred to AIM-Back by sex, age, race, and ethnicity, relative to the clinical LBP population at randomized clinics, to provide an indication of the generalizability of these findings. 2. Methods 2.1. Study design AIM-Back (registered at clinicaltrials.gov: NCT04411420 on 1 June 2020) is a multisite, ePCT within the Veterans Health Administration (VHA) Health Care System. The AIM-Back trial has been described previously in our protocol paper, including a description of its pragmatic components [ 11 ]. Both pathways were initiated by a referral from a trained primary care provider and are briefly summarized below. The Sequenced Care Pathway (SCP) started with an evaluation and treatment by a local VHA physical therapist. Veterans were then offered telehealth physical activity calls through a remote centralized care provider, a follow-up assessment with their local physical therapist, and additional remote care focused on pain coping skills training delivered by physical therapists trained in psychologically informed care for those screened for persistent disability at their follow-up visit. Additional details for the SCP and metrics for its usage have been previously described [ 14 ]. The Pain Navigator Pathway (PNP) involved referral of the Veteran to a Pain Navigator, i.e., a local VHA provider that worked with Veterans primarily via telehealth to identify appropriate non-pharmacologic treatment options, decide on the preferred option(s), and coordinate access to selected service(s). Additional details for the PNP and metrics for its usage have been previously described [ 15 ]. 2.2. Patient and public involvement There was no patient and public involvement for the reporting of baseline characteristics from the AIM-Back trial. The SCP and PNP were reviewed and modified in the planning stages of this trial based on input from a Veteran Research Engagement Panel (VetREP) as well as other partners including administrators and clinical providers. Details on this process have been described in a prior publication [ 16 ]. 2.3. Participating clinics eligibility, recruitment, and randomization Veterans Affairs clinics were recruited to participate in AIM-Back in two waves from February 2020–September 2020 and from March 2021–December 2021. The AIM-Back trial received site participation agreements from and randomized 19 VA Primary Care clinics to one of the two pathways. Two clinics withdrew in the early stages of rolling out the AIM-Back program and data from these clinics are excluded from all analyses. The 17 clinics resided in 10 different states: West Virginia, South Carolina, Nevada, Missouri, Texas, Pennsylvania, North Carolina, Kansas, Ohio, and Kentucky. Participating clinics were randomized into two blocks using a blocked covariate constrained randomization [ 11 ] and, after randomization, each clinic underwent training on how to implement their assigned pathway. 2.4. Cohort and participants To be eligible for AIM-Back, Veterans were referred to the randomized pathway at their clinic by trained primary care providers across 17 clinics (9 PNP; 8 SCP) between 1 February 2021 and 31 January 2024 (Referral Cohort). Veterans from the Referral cohort ( n = 2767; 1481 PNP; 1286 SCP) that participated in the study included 1) enrolled participants ( n = 1817; 1006 PNP, 811 SCP), approximately 66% of the Referral cohort; attended initial AIM-Back visit with no consent required and were the primary intention-to-treat (ITT) population, and 2) survey participants ( n = 996; 480 PNP; 516 SCP) that agreed at the AIM-Back referral to be contacted about the research survey study were consented and completed baseline surveys (see Figure 1 ). Approximately 80% of the Referral cohort agreed to be contacted for the survey study ( n = 2183), 45.6% of whom were survey participants. There were n = 799 enrolled participants (44%) who were also survey participants (see Figure 1 ); we planned for approximately 50% of enrolled participants to be survey participants in the design of the study. Figure 1. Open in a new tab CONSORT flow diagram for AIM-Back baseline cohorts. Each clinic had a targeted enrollment of 105 enrolled Veterans with a minimum enrollment target of 65 and a maximum of 130 Veterans to minimize cluster imbalance; for the survey participants the target enrollment was n = 53 per clinic [ 17 ]. Trial enrollment concluded in January 2024. Providers at participating clinics were trained to refer Veterans to AIM-Back who had low back pain, received primary care at a randomized clinic, had a valid telephone number, were not receiving or had not been referred to hospice or palliative care, and were informed that AIM-Back was best suited for Veterans for whom conservative care was appropriate. To be eligible to be contacted by research staff about participating in the survey study that collected more granular data in surveys with additional longer follow-up time points, Veterans referred to AIM-Back had to agree, at the referral, to be contacted for the research study. Further eligibility criteria for the survey participants included not being in institutional care (nursing home or hospital), no cognitive impairment, dementia, or lack of decision-making capacity, no serious mental illness (diagnosis of schizophrenia, bipolar disorder, psychiatric hospitalization) in the previous year or no current high-risk suicide flag in their medical record, and available access to, with ability to communicate on, a telephone. 2.5. Methods of data collection The AIM-Back trial had two data sources: 1) data entered through the Computerized Patient Record System (CPRS), the Veterans Health Administration Health Care System (VHAHCS) EHR, and extracted from the Corporate Data Warehouse (CDW) and 2) data collected via telephone by AIM-Back research staff in REDCap. The data used is governed by the Department of Veteran Affairs, and all necessary data use permissions and approvals were obtained in accordance with VA policies and the study’s IRB approvals. Once an AIM-Back referral was issued by primary care, clinics’ usual care protocols were followed to schedule the baseline evaluation visit by an AIM-Back trained physical therapist or pain navigator (depending on the pathway to which the clinic was randomized). Demographic information (age, race, ethnicity, and sex), HICP, opioid use, PTSD diagnoses in year prior to referral, and Care Assessment Needs (CAN) scores prior to referral date (closest) [ 18 ] were extracted from CDW for the Referral cohort. HICP vs. not was defined by two items from the Graded Chronic Pain Scale Revised questionnaire which incorporates pain duration and limitations due to pain [ 19 ]. Opioid use was classified as a binary variable (use or none) based on whether the Veteran had filled an opioid prescription at the VA in the year prior to referral [ 20 ]. CAN score is a comorbidity measure and is the estimated risk for hospital admission or death within a year calculated weekly for all eligible Veterans. The score is the risk percentile and ranges from 0 (lowest risk) to 99 (highest risk). During the initial evaluation, the provider used a clinical note template specific to the clinic’s assigned AIM-Back pathway to collect data that included the 2-item CDC high impact pain questionnaire [ 15 ], the 2-item NIH Task Force on Research Standards for Chronic Low Back Pain [ 21 ], the 4-item Patient Reported Outcomes Measurement Information System Short Form (PROMIS-SF) Pain Interference [ 22 ], the 4-item PROMIS-SF Physical Function [ 23 ], the 4-item PROMIS-SF Sleep Disturbance [ 24 ], and other relevant care notes. The data from these EHR templates are stored as structured text fields and uploaded nightly to CDW. For the survey participants, patient demographics (baseline only), PROMIS-SF pain interference, PROMIS-SF physical function, PROMIS-SF sleep disturbance, CDC and NIH definitions of HICP, Catastrophizing (2 items recommended by NIH Taskforce), PEG pain intensity, Pain Self-efficacy (PSEQ-2), Depression (PHQ-2), Alcohol use (AUDIT-C), Quality of life (EQ-5D-5 L), and Nonpharmacological and Self-Care Approaches (NSCAP) [ 25 , 26 ] measures were collected. Data were collected electronically into REDCap [ 27 ] at baseline, 3, 6, and 12 months. In addition, to evaluate the representativeness of the Referral cohort for each clinic, we identified all primary care LBP visits based on ICD-10 codes during the study active periods at each clinic and extracted demographics (age, race, ethnicity, and sex) for the Veterans with the LBP visits. 3. Analysis Descriptive statistics were generated for all baseline variables, including means and standard deviations for continuous measures and frequencies and percentages for categorical measures. The representativeness of the Referral cohort was calculated using the participation to prevalence ratio (PPR) [ 28 ] for age, race, sex, and ethnicity. PPRs were calculated as the ratio of those within a specific demographic who were referred to AIM-Back relative to those of that same demographic who were eligible to participate based on a documented LBP visit at a randomized primary care clinic during the active trial period. A PPR value between 0.8 and 1.2 indicates a likely representative sample, while values below 0.8 suggest potential for underrepresentation and values above 1.2 indicate potential for overrepresentation [ 26 ]. 4. Results This study adhered to CONSORT guidelines (extension to cluster randomized trials); however, in this paper, we are only reporting baseline data [ 29 ]. The descriptive data provide a comprehensive summary of measures collected through both the EHR and baseline survey. In addition to demographic characteristics, we emphasized baseline pain interference, physical function, HICP prevalence, opioid use, and selected psychosocial factors, as these domains are most clinically relevant for contextualizing the AIMBack cohort. The additional 260 survey data further allow detailed characterization of participants to complement the EHR-based baseline profile. Age, sex, ethnicity, and race demographics are presented in Table 1 alongside rates of HICP, PTSD, and opioid use for the Referral cohort, enrolled and survey participants overall, and by pathway. The mean ages for the Referral cohort, enrolled and survey participants were similar (51–53 years old). The Referral Cohort was 11.8% female, 28.5% Black/African American, 10.5% had documented opioid use in the year prior, and 23.7% had a documented PTSD ICD-10 code. Enrolled participants were 12.1% female, 29.3% Black/African American, 9.9% had documented opioid use in the year prior, and 23.4% had a documented PTSD ICD-10 code. Survey participants were 10.9% female and 25.0% Black/African American, 9.1% had documented opioid use in the year prior, and 24.7% had a documented PTSD ICD-10 code. Enrolled participants had slightly higher opioid use among those in the PNP (10.8%) than those in the SCP (8.6%), and there was variability across clinics with a minimum opioid use of 2.4% and a maximum opioid use of 15.3% assessed in the year prior to referral (Coefficient of Variation (CV)=0.40). Table 1. Baseline characteristics in the referral cohort and enrolled and survey participants. *N (%) unless specified otherwise Referral cohort Enrolled participants Survey participants Characteristic Overall N = 2767 PNP N = 1481 SCP N = 1286 Overall N = 1817 PNP N = 1006 SCP N = 811 Overall N = 996 PNP N = 480 SCP N = 516 Demographics Age (years) Mean (SD) N 52.1 (15.8) 2767 52.2 (16.0) 1481 52.0 (15.6) 1286 53.0 (15.7) 1817 52.7 (15.9) 1006 53.4 (15.4) 811 51.7 (15.3) 996 52.0 (15.6) 480 51.4 (15.1) 516 Age (categories) <50 1224 (44.2) 654 (44.2) 570 (44.3) 766 (42.2) 435 (43.2) 331 (40.8) 457 (45.9) 216 (45.0) 241 (46.7) 50–64 845 (30.5) 433 (29.2) 412 (32.0) 562 (30.9) 296 (29.4) 266 (32.8) 304 (30.5) 140 (29.2) 164 (31.8) 65–74 486 (17.6) 278 (18.8) 208 (16.2) 330 (18.2) 192 (19.1) 138 (17.0) 166 (16.7) 90 (18.8) 76 (14.7) 75+ 212 (7.7) 116 (7.8) 96 (7.5) 159 (8.8) 83 (8.3) 76 (9.4) 69 (6.9) 34 (7.1) 35 (6.8) Sex Female 326 (11.8) 157 (10.6) 169 (13.1) 220 (12.1) 110 (10.9) 110 (13.6) 109 (10.9) 44 (9.2) 65 (12.6) Male 2441 (88.2) 1324 (89.4) 1117 (86.9) 1597 (87.9) 896 (89.1) 701 (86.4) 887 (89.1) 436 (90.8) 451 (87.4) Race Black or African American 789 (28.5) 315 (21.3) 474 (36.9) 533 (29.3) 232 (23.1) 301 (37.1) 249 (25.0) 83 (17.3) 166 (32.2) White 1784 (64.5) 1054 (71.2) 730 (56.8) 1169 (64.3) 703 (69.9) 466 (57.5) 626 (62.9) 326 (67.9) 300 (58.1) Other/Multiracial 115 (4.2) 67 (4.5) 48 (3.7) 68 (3.7) 44 (4.4) 24 (3.0) 114 (11.4) 68 (14.2) 46 (8.9) DK/Ref/Missing 79 (2.9) 45 (3.0) 34 (2.6) 47 (2.6) 27 (2.7) 20 (2.5) 7 (0.7) 3 (0.6) 4 (0.8) Hispanic Ethnicity Non-Hispanic 2555 (92.3) 1347 (91.0) 1208 (93.9) 1686 (92.8) 920 (91.5) 766 (94.5) 905 (90.9) 429 (89.4) 476 (92.2) Hispanic 149 (5.4) 88 (5.9) 61 (4.7) 95 (5.2) 59 (5.9) 36 (4.4) 85 (8.5) 48 (10.0) 37 (7.2) DK/Ref/Missing 63 (2.3) 46 (3.1) 17 (1.3) 36 (2.0) 27 (2.7) 9 (1.1) 6 (0.6) 3 (0.6) 3 (0.6) Additional Characteristics High Impact Chronic Pain (CDC) 2122 (76.7) 1135 (76.6) 987 (76.7) 1193 (65.7) 659 (65.5) 534 (65.8) 592 (59.4) 293 (61.0) 299 (57.9) Missing 68 (2.5) 11 (0.7) 57 (4.4) 1 (0.1) 1 (0.1) 0 (0.0) 6 (0.6) 3 (0.6) 3 (0.6) Opioid Use% 290 (10.5) 168 (11.3) 122 (9.5) 179 (9.9) 109 (10.8) 70 (8.6) 91 (9.1) 50 (10.4) 41 (7.9) PTSD% 655 (23.7) 340 (23.0) 315 (24.5) 425 (23.4) 215 (21.4) 210 (25.9) 246 (24.7) 116 (24.2) 130 (25.2) 1 yr CAN Score% Mean (SD) N 45.9 (30.3) 2683 47.7 (31.1) 1427 43.8 (29.2) 1256 46.1 (30.5) 1766 47.3 (31.3) 965 44.6 (29.5) 801 45.4 (29.4) 974 47.9 (29.6) 466 43.1 (29.1) 508 Open in a new tab % Extracted from EHR for Referral Cohort, enrolled and survey participants. Survey participants had a higher percentage of Hispanic/Latino participants and lower rates of HICP prevalence compared to the Referral Cohort and enrolled participants. The Referral cohort had the highest rates of HICP (76.7%) compared to enrolled participants (65.7%) and participants (59.4%). There was variation across the 17 clinics in HICP with a Referral cohort range of 49.1–94.6%, an enrolled participants range of 56.3–78.5%, and survey participants range of 43.8–74.0%. Additional findings related to HICP can be found in Table 1 . Table 2 contains the mean and standard deviation for the PROMIS-SF T-scores overall and by pathway for enrolled and survey participants. Enrolled participants had PROMIS-SF Pain Interference and Physical Function mean T-scores of 63.2 and 37.1. Similarly, Veterans in the Survey sample had a mean Pain Interference T-score of 63.1 and a mean Physical Function T-score of 38.1. These scores fall within ranges that can be classified as moderate impairment at baseline. Mean PROMIS-SF scores were similar across pathways for both the enrolled and survey participants. Table 2. PROMIS-SF measures and NIH chronicity. Enrolled participants Survey participants Characteristic Overall N = 1817 PNP N = 1006 SCP N = 811 Overall N = 996 PNP N = 480 SCP N = 516 PROMIS Measures Mean (SD) N PROMIS-SF Physical Function T-Score 37.1 (5.3) 1801 37.0 (5.1) 991 37.2 (5.5) 810 38.1 (5.8) 994 38.0 (5.7) 479 38.2 (5.9) 515 PROMIS-SF Pain Interference T-Score 63.2 (6.8) 1793 63.2 (6.5) 985 63.1 (7.2) 808 63.1 (6.6) 990 62.9 (6.6) 477 63.3 (6.6) 513 PROMIS-SF Sleep T-Score 58.3 (8.4) 1799 58.4 (8.3) 990 58.1 (8.4) 809 58.5 (7.8) 993 58.5 (7.8) 479 58.5 (7.8) 514 NIH Chronicity N (%) 1672 (92.0) 921 (91.6) 751 (92.6) 902 (90.6) 438 (91.3) 464 (89.9) Open in a new tab The pathways were generally balanced on these characteristics that are often used to better describe pain experiences. For example, approximately 43% of participants screened positive for depression on the PHQ-2 and the average PEG score was 6.2/10. Additionally, we collected data on clinically relevant pain-related beliefs like catastrophizing; 31.3% of respondents agreed that it was not safe to be physically active and 47.6% believed their back pain was terrible and would never improve. Furthermore, 90.8% reported using non-pharmacologic care, with exercise (77.8%) and relaxation techniques (41.3%) being the most employed methods. The PPR estimates for age, race, sex, and ethnicity are reported in Table 3 . Veterans aged 50 or younger were consistently overrepresented in referrals to AIM-Back by providers across the 17 clinics, referrals of female Veterans were often overrepresented, and referrals occasionally overrepresented Black/African American Veterans. Conversely, referrals to AIM-back during the trial consistently underrepresented Veterans aged 65+ across clinics. Table 3. Participation to prevalence ratios by AIM-Back pathways and clinics. Open in a new tab *American Indian, Asian, Pacific Islander, and multiple races were excluded from analysis due to a low. 5. Discussion Prior reports from the AIM-Back trial include a summary of our partner engagement process to refine the pathways included in the trial [ 16 ] and descriptive analyses of SCP and PNP use [ 14 , 15 ]. Trial enrollment has been completed and the baseline characteristic results provide foundational data to support later analyses from the AIM-Back trial. Furthermore, reporting these baseline data allows us to provide an empirical assessment of representativeness at baseline to speak to the trial’s generalizability. In this analysis, we used PPR as an indicator to assess the representativeness of those referred to AIM-Back by trained primary care providers to the LBP population at each clinic. Overall, we identified that Veterans referred to the AIM-Back program were representative based on sex and race. However, we also had evidence across multiple enrolling clinics that older Veterans (65+ years) were underrepresented for referral to AIM-Back. The underrepresentation based on age finding from the PPR analysis was unexpected and could be due to the way we implemented the programs (e.g., without an emphasis on including older Veterans) or the perception of referring providers on the treatment delivered (e.g., the care pathways were not well suited for older Veterans). The reasons for this finding are speculative but will be important for those interested in Veteran populations for whom these trial findings will be most relevant. Specifically, the PPR results suggest that our primary findings and planned subgroup analyses for HICP and opioid use at the time of enrollment may not be generalizable to older adults. This could be problematic for settings that have high numbers of older adults seeking care for LBP. The PPR results also inform future implementation efforts aligned with these care pathways. Overall, this AIM-Back baseline paper supports the forthcoming primary outcome analysis (i.e., comparative effectiveness of these care pathways) by providing a comprehensive description of this cohort’s sociodemographic and clinical characteristics, including an assessment of representativeness of enrollment at the clinical level (not commonly performed in randomized trials). Compared to previously reported PROMIS outcomes in Veterans, our cohort of LBP treatment seeking Veterans demonstrated higher distress as evidenced by the higher pain interference, greater sleep disturbance, and lower physical function PROMIS scores [ 30 ]. HICP and opioid usage are reported as factors that will be used for planned subgroup analyses. The elevated presence of HICP provides an additional indication that the AIM-Back samples consist of Veterans with high levels of interference from their LBP, which will serve as a highly relevant characteristic in interpreting findings from the primary analyses. The prevalence of HICP and opioid usage suggests that we will have enough participants to proceed with the planned subgroup analyses. In addition, the baseline data summarize clinically relevant variables including pain-related beliefs (e.g., pain catastrophizing and self-efficacy), sleep disturbance, and engagement in non-pharmacologic therapies. Survey participants, while demonstrating high levels of distress on these measures, were also highly engaged with non-pharmacologic care, most notably with exercise and relaxation techniques. 5.1. Strengths and limitations A notable strength of AIM-Back was designed to add to the evolving evidence base regarding real-world delivery of LBP treatment pathways emphasizing non-drug options. For example, a 2025 Cochrane Review on LBP Care Models [ 31 ] identified that all prior trials used usual care as comparator, whereas AIM-Back is the first trial we are aware of to compare outcomes from two active comparators. Furthermore, both care pathways were aligned with clinical practice guidelines by emphasizing early use of non-drug treatment. We hypothesized that the SCP would be the superior pathway because it provided structured delivery of active components including short-term use of pain modulation, activity or exercise-based goal setting, and psychologically informed physical therapy. These types of treatments were linked to better outcomes in a 2025 network meta-analysis providing additional support for the hypothesis that the SCP would be the superior pathway [ 32 ]. The findings reported in the baseline paper indicate that the AIM-Back trial has several other strengths now that enrollment has been completed, including a) having data from the Referral Cohort to understand provider and patient engagement with these pathways; b) the enrollment goal was met, which allows for adequate power of all planned analyses; c) the use of data from both EHR and surveys provide for a comprehensive assessment, allowing for future robust evaluation and sensitivity analyses of trial findings; and d) the integration of AIM-Back features within existing clinical settings demonstrates the potential for these care pathways to be implemented more broadly in Veteran Health Administration clinics and in other healthcare environments outside the Veteran Health Administration. Additionally, since cluster randomization can result in imbalances, it is encouraging to see balance in our primary and secondary outcome measures at baseline across care pathways [ 17 , 33 ]. Some of the limitations of the trial include recruitment during the COVID-19 pandemic that affected practice patterns for clinics participating during shutdowns compared to telehealth availability, staffing, and referrals delivered pre- and post-shutdown. These changes to care delivery may influence the interpretation of baseline rates of engagement with the care pathways. Leveraging the EHR as a data collection tool presented challenges related to consistent documentation which may impact our analysis, such as the PPR, that is reliant on ICD-10 code documentation for LBP visits which is known to be inconsistently used across healthcare systems and personnel [ 34 ]. Lack of appropriate diagnostic documentation may miss detection of Veterans eligible to receive AIM-Back. Another limitation to consider is that there are many ways to define opioid use and the way the standard definition for opioid use in the VA is defined may influence the interpretation and generalizability of the rates reported in this paper. An important consideration for future research and implementation efforts is to further explore participation among older Veterans to overcome the current limitations of the trial’s generalizability due to the lower referral of this subgroup to the AIM-Back program. 6. Conclusion This baseline profile provides a detailed description of Veterans who participated in the AIM-Back embedded pragmatic trial. The profile indicates that participants had moderate pain interference, physical function, and high rates of high‑impact chronic pain at enrollment. Referral patterns were generally representative by sex and race, though older Veterans were consistently underrepresented, which may limit generalizability for this subgroup and should inform future implementation to improve outreach to this group. This review of enrollment patterns and baseline clinical characteristics establishes the context needed to interpret future comparative effectiveness and subgroup analyses. Acknowledgments AI-tools were not used in the creation of this manuscript. This manuscript is a product of the Pain Management Collaboratory. For more information about the Collaboratory, visit https://painmanagementcollaboratory.org/ . This material is the result of work supported with resources and the use of facilities at the Durham VA Health Care System in Durham North Carolina. Funding Statement This work is supported through cooperative agreement [UH3AT009790] from the NIH, National Center for Complimentary and Integrative Health (NCCIH). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health the U.S Department of Veterans Affairs or the United States Government. Article highlights The AIM‑Back study is a large, multisite VA clinical trial designed to improve access to non‑drug care for Veterans with low back pain. Veterans were referred to either a Sequenced Care Pathway delivered by physical therapists or the Pain Navigator Pathway delivered by clinical personnel that could direct patients to appropriate treatment. This baseline report describes the characteristics of 2,767 Veterans referred to AIM‑Back and 1,817 who initiated care through one of two randomized clinical pathways. Baseline data were drawn from the electronic health records (EHR) documenting care delivered as part of typical clinic workflow and survey responses from a subset of Veterans who provided additional information on pain, function, and psychosocial factors. Veterans entering AIM‑Back had moderate levels of pain interference and physical function impairment at baseline, consistent across pathways and data‑collection methods. High Impact Chronic Pain (HICP) was common, affecting <75% of those referred to the program and <65% of participants. Approximately 10% of Veterans had recorded opioid use in the year prior to referral. Veterans commonly reported using non‑pharmacologic self‑care strategies such as exercise, relaxation, and mindfulness prior to entering the program. Comparison with all Veterans with clinically identified low back pain at participating clinics showed that those referred to AIM-Back were generally representative in terms of sex and race but underrepresented Veterans older than 65. These baseline findings offer essential context for interpreting the forthcoming comparative effectiveness results of the two care pathways. Author contributions Steven Z. George and Susan N. Hastings served as primary investigators for the AIM-Back trial and guided the scientific interpretation of the results reported in this paper (Conceptualization, Methodology, Resources, Writing-Original Draft, Supervision, Project Administration, Funding Acquisition). Cynthia J. Coffman and Rebecca North operated as the biostatisticians conducting the analysis of this work and have directly accessed and verified the underlying data reported in this manuscript (Methodology, Software, Validation, Formal Analysis, Data Curation, Writing Original Draft, Visualization). Trevor A Lentz, Courtni France, Ashley Choate, Janet M. Grubber, Christa Tumminello, Ivonne Guzman, Lindsay Ballengee, and Travis Linton guided the implementation of the trial at the participating clinics, leading to key contributions to the methods of this manuscript (Software, Investigation, Resources, Data Curation, Supervision, Project Administration). Corey B. Simon, Chad E. Cook, Francis J. Keefe, Kelli D. Allen, Adam P. Goode, Heather King, and Jennifer Naylor served as co-investigators and contributed to the design of the intervention pathways and measures used in this trial (Conceptualization, Methodology, Resources, Supervision). Joseph Leo Brothers and Catherine Stanwyck served as the coordinators for AIM-Back ensuring that the trial was in compliance with the laws and regulations that guide the conduct of research (Resources, Supervision, Project Administration). All contributing authors have reviewed and provided their feedback on the manuscript prior to submission (Writing – Reviewing and Editing). Disclosure statement The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript. Reviewer disclosures Peer reviewers on this manuscript have no relevant financial or other relationships to disclose. Ethical declaration For ethics approval and consent to participate, the AIM-Back trial was submitted to and received approved by two local ethics committees. These were the Duke Health Institutional Review Board at Duke University (Protocol#00101938) and the Durham VA Health Care System Institutional Review Board (Protocol#02131). Activities to support AIM-Back implementation were considered to be non-research operations activities as defined in VHA Handbook 1058.05. Individual-level outcome measurement was approved as research by the Institutional Review Board of the Durham Veterans Affairs (IRB #02131) and the Duke Health Institutional Review Board (#00101938). Informed consents were collected prior to baseline interviews for the survey. Accordingly, every Veteran that participated in research activities associated with the AIM-Back trial provided informed consent (e.g., survey participation occurring outside routine care). Informed consent was obtained verbally as approved by the Durham VA Health Care System Institutional Review Board (Protocol#02131). Tracking of verbal consent was done electronically in our research database. The care pathways studied were deemed as standard care by both local review boards and therefore individual consent was not required to receive treatment for back pain through AIM-Back pathways. The AIM-Back trial was conducted in accordance with the Declaration of Helsinki. Data availability statement Data that were cultivated and included in these analyses can be provided upon reasonable request from the author team. Deidentified data will be made available upon request and permission for use granted consistent with VA policy via inquiry to vhaduraimback@va.gov. References Papers of special note have been highlighted as either of interest (•) or of considerable interest (••) to readers. 1. Gangal A, Stoff B, Blalock T.. The 2022 CDC opioid prescription guideline update: relevant recommendations and future considerations. JAAD Int. 2023;13:48–49. doi: 10.1016/j.jdin.2023.07.006 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Global Health; Board on Health Sciences Policy; Global Forum on Innovation in Health Professional Education; Forum on Neuroscience and Nervous System Disorders . The role of nonpharmacological approaches to pain management: proceedings of a workshop. Washington (DC): National Academies Press (US); 2019. [ PubMed ] [ Google Scholar ] 3. Chou R, Deyo R, Friedly J, et al. Noninvasive treatments for low back pain. Rockville (MD): Agency for Healthcare Research and Quality (US); 2016. [ PubMed ] [ Google Scholar ] 4. Alperovitch-Najenson D, Becker A, Belton J, et al. Who guideline for non-surgical management of chronic primary low back pain in adults in primary and community care settings. Published Online First: 2023. Dec 7. doi: 10.5167/UZH-257188 [ DOI ] [ PubMed ] 5. Kazis LE, Ameli O, Rothendler J, et al. Observational retrospective study of the association of initial healthcare provider for new-onset low back pain with early and long-term opioid use. BMJ Open. 2019;9(9):e028633. doi: 10.1136/bmjopen-2018-028633 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 6. Childs JD, Fritz JM, Wu SS, et al. Implications of early and guideline adherent physical therapy for low back pain on utilization and costs. BMC Health Serv Res. 2015;15(1):150. doi: 10.1186/s12913-015-0830-3 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 7. Frogner BK, Harwood K, Andrilla CHA, et al. Physical therapy as the first point of care to treat low back pain: an instrumental variables approach to estimate impact on opioid prescription, health care utilization, and costs. Health Serv Res. 2018;53(6):4629–4646. doi: 10.1111/1475-6773.12984 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 8. George SZ, Lentz TA, Goertz CM.. Back and neck pain: in support of routine delivery of non-pharmacologic treatments as a way to improve individual and population health. Transl Res. 2021;234:129–140. doi: 10.1016/j.trsl.2021.04.006 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 9. Keefe FJ, Jensen MP, Williams ACDC, et al. The yin and yang of pragmatic clinical trials of behavioral interventions for chronic pain: balancing design features to maximize impact. Pain. 2022;163(7):1215–1219. doi: 10.1097/j.pain.0000000000002546 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 10. Hohenschurz-Schmidt DJ, Cherkin D, Rice ASC, et al. Research objectives and general considerations for pragmatic clinical trials of pain treatments: IMMPACT statement. Pain. 2023;164(7):1457–1472. doi: 10.1097/j.pain.0000000000002888 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. George SZ, Coffman CJ, Allen KD, et al. Improving veteran access to integrated management of back pain (AIM-Back): protocol for an embedded pragmatic cluster-randomized trial. Pain Med. 2020;21(Supplement_2):S62–72. doi: 10.1093/pm/pnaa348 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; •• This reference explains AIM-Back trial rationale and design and as such may be of high interest to readers. 12. Amtmann D, Kim J, Chung H, et al. Minimally important differences for patient reported outcomes measurement information system pain interference for individuals with back pain. JPR. 2016;251:251. doi: 10.2147/JPR.S93391 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 13. Nahin RL. Severe pain in veterans: the effect of age and sex, and comparisons with the general population. J Pain. 2017;18(3):247–254. doi: 10.1016/j.jpain.2016.10.021 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. Lentz TA, Coffman CJ, Cope T, et al. If you build it, will they come? Patient and provider use of a novel hybrid telehealth care pathway for low back pain. Phys Ther. 2024;104(2):zad127. doi: 10.1093/ptj/pzad127 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; •• This reference has a detailed explanation of the Sequenced Care Pathway and descriptive statistics of usage patterns. 15. France C, Cook CE, Coffman CJ, et al. “Here be dragons”. The implementation of a pain navigator program in department of Veterans Affairs’ (VA) health care systems. Pain Med. 2024;25(Supplement_1):S83–S90. doi: 10.1093/pm/pnae074 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; •• This reference has a detailed explanation of the Pain Navigator Pathway and descriptive statistics of usage patterns. 16. Ballengee LA, King HA, Simon C, et al. Partner engagement for planning and development of non-pharmacological care pathways in the AIM-Back trial. Clin Trial. 2023;20(5):463–472. doi: 10.1177/17407745231178789 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 17. Coffman CJ, North R, George SZ, et al. Improving veteran access to integrated management of back pain (AIM-Back): updated statistical analysis plan for this embedded pragmatic. Cluster Random. 2023. doi: 10.1101/2023.12.22.23300382 [ DOI ] [ Google Scholar ] 18. US Department of Veterans Affairs . Care assessment needs (can) primer). 2019. 19. Von Korff M, DeBar LL, Krebs EE, et al. Graded chronic pain scale revised: mild, bothersome, and high-impact chronic pain. Pain. 2020;161(3):651–661. doi: 10.1097/j.pain.0000000000001758 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; • This reference provides important information on the operational definition of “high impact chronic pain” used in the AIM-Back trial. 20. Edelman EJ, Gordon K, Becker WC, et al. Receipt of opioid analgesics by HIV-Infected and uninfected patients. J Gen Intern Med. 2013;28(1):82–90. doi: 10.1007/s11606-012-2189-z [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 21. Deyo RA, Dworkin SF, Amtmann D, et al. Report of the NIH task force on research standards for chronic low back pain. Phys Ther. 2015;95(2):e1–18. doi: 10.2522/ptj.2015.95.2.e1 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Amtmann D, Cook KF, Jensen MP, et al. Development of a PROMIS item bank to measure pain interference. Pain. 2010;150(1):173–182. doi: 10.1016/j.pain.2010.04.025 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 23. Rose M, Bjorner JB, Gandek B, et al. The PROMIS physical function item bank was calibrated to a standardized metric and shown to improve measurement efficiency. J Clin Epidemiol. 2014;67(5):516–526. doi: 10.1016/j.jclinepi.2013.10.024 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 24. Yu L, Buysse DJ, Germain A, et al. Development of short forms from the PROMIS TM sleep disturbance and sleep-related impairment item banks. Behav Sleep Med. 2012;10(1):6–24. doi: 10.1080/15402002.2012.636266 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 25. Burgess DJ, Evans R, Allen KD, et al. Learning to apply mindfulness to pain (LAMP): design for a pragmatic clinical trial of two mindfulness-based interventions for chronic pain. Pain Med. 2020;21(Supplement_2):S29–36. doi: 10.1093/pm/pnaa337 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 26. Seal KH, Becker WC, Murphy JL, et al. Whole health options and pain education (wHOPE): a pragmatic trial comparing whole health team vs primary care group education to promote nonpharmacological strategies to improve pain, functioning, and quality of life in veterans-rationale, methods, and implementation. Pain Med. 2020;21(Suppl 2):S91–9. doi: 10.1093/pm/pnaa366 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 27. Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inf. 2019;95:103208. doi: 10.1016/j.jbi.2019.103208 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 28. Poon R, Khanijow K, Umarjee S, et al. Participation of women and sex analyses in late-phase clinical trials of new molecular entity drugs and biologics approved by the FDA in 2007–2009. J Women’s Health. 2013;22(7):604–616. doi: 10.1089/jwh.2012.3753 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 29. Campbell MK, Piaggio G, Elbourne DR, et al. Consort 2010 statement: extension to cluster randomised trials. BMJ. 2012;345(sep04 1):e5661–e5661. doi: 10.1136/bmj.e5661 [ DOI ] [ PubMed ] [ Google Scholar ] 30. LaVela SL, Etingen B, Miskevics S, et al. Use of PROMIS-29® in US veterans: diagnostic concordance and domain comparisons with the general population. J Gen Intern Med. 2019;34(8):1452–1458. doi: 10.1007/s11606-019-05011-9 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 31. Docking S, Sridhar S, Haas R, et al. Models of care for managing non-specific low back pain. Cochrane Database Syst Rev. 2025;2025(3). doi: 10.1002/14651858.CD015083.pub2 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; • This reference has detailed information on effectiveness of care pathways and care models for low back pain similar to what is being tested in the AIM-Back trial. 32. Baroncini A, Maffulli N, Manocchio N, et al. Active and passive physical therapy in patients with chronic low-back pain: a level I Bayesian network meta-analysis. J Orthop Traumatol. 2025;26(1):66. doi: 10.1186/s10195-025-00885-4 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 33. George SZ, France C, Coffman CJ, et al. Cohort profile: baseline characteristics of veterans from improving veteran access to integrated management of back pain (AIM-Back) – an embedded pragmatic, cluster randomized trial in the United States. 2024. doi: 10.1101/2024.11.23.24317833 [ DOI ] [ PMC free article ] [ PubMed ] 34. Purser L, Warfield K, Richardson C. Making pain visible: an audit and review of documentation to improve the use of pain assessment by implementing pain as the fifth vital sign. Pain Manage Nurs. 2014;15(1):137–142. doi: 10.1016/j.pmn.2012.07.007 [ DOI ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Data Availability Statement Data that were cultivated and included in these analyses can be provided upon reasonable request from the author team. Deidentified data will be made available upon request and permission for use granted consistent with VA policy via inquiry to vhaduraimback@va.gov. Articles from Pain Management are provided here courtesy of Taylor & Francis ACTIONS View on publisher site PDF (1.8 MB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

Related documents

• The impact of animations to improve health-information recall in patients with lower back pain: a quasi-experimental study.#218841
• Integrated Neuromuscular Inhibition Versus Instrument Assisted Soft Tissue Mobilization in Chronic Back Pain#908343
• Effects of Different Treatment Methods Applied to Spine in Chronic Non-Spesific Low Back Pain#1060611
• Effect of Virtual Reality Training on Pain, Functional Disability, and Lumbar Reposition Error in Patients With Chronic Non-Specific Low Back Pain#860766
• Evaluating Yoga for Chronic Low Back Pain#846525