Short summary

People respond differently to chiropractic care and it remains unknown who responds and who does not. This mixed-methods study will characterize responders and non-responders to chiropractic care using a biopsychosocial approach. Early identification of responders and non-responders to chiropractic care can lead to significant clinical advances and management improvement.

Rationale

Musculoskeletal conditions affect a large part of the population worldwide(1). Specifically, LBP results in more years lived with disability than any other condition, with more than half a billion cases in 2020(1). Chiropractors play an important role in managing LBP, with a 22% lifetime utilization of chiropractic services and LBP being the most common reason for people to seek chiropractic care(2). Chiropractors offer a conservative and non-pharmacological management for people with LBP that includes manual therapy, exercise, lifestyle advice, and other interventions(3). Historically, randomized clinical trials focused on chiropractic care for people with LBP have mainly observed small effect sizes, failing to identify an intervention or approach with superior efficacy(4). This could partially be due to the inclusion of heterogeneous samples in terms of care response(5). Specifically, previous studies have shown that people respond differently to chiropractic care: while some people improve (classified as "responders"); others do not ("non-responders")(6, 7). Although clinical and biomechanical characteristics of people with LBP likely to respond to spinal manipulative therapy(7, 8) and other conservative interventions(9, 10) have been investigated, replication limitations have raised questions related to their validity and generalizability to real-world practice(11). Identifying responders and non-responders to chiropractic care can allow future clinical trials to focus on the people who are likely to respond, which may significantly impact observed effect sizes of chiropractic care. It is well known that LBP is a multifactorial condition, including biological, psychological, and social factors(12). However, previous studies have failed to consider BPS factors, focusing primarily on the biological dimension(7-10). This may have contributed to the limited utility of previously identified responder characteristics. Therefore, integrating BPS factors when investigating who are likely to benefit from chiropractic care is fundamental and can enhance the validity and utility of identified characteristics. Additionally, the typical assessment of responder status has been mainly based on before-after intervention single-point estimates(7-10), which, based on current advances in pain trajectories(13), is not sufficient for measuring changes that chiropractors often report empirically. Therefore, more frequent (daily measurements), additional factors (BPS factors), and including patients' perspectives may enable the identification and differentiation of responders and non-responders at different timeframes of care.

Description of the cohort

Adult patients (≥18 years old) seeking new care for an episode of low back pain, with or without leg pain (≥ 3 months since last visit to participating chiropractic clinics) from chiropractic clinics in The Region of Southern Denmark.

Data and biological material

Demographic data, health history, Patient-Reported Outcomes (e.g., pain intensity, disability, work ability, expectations), experimental outcomes (e.g., pain sensitivity, stiffness, kinetics and kinematics)

Collaborating researchers and departments

Division of Research and Innovation, Canadian Memorial Chiropractic College

• Martha Funabashi
• Samuel Howarth

Center for Muscle and Joint Health, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark

• Steen Harsted
• Jan Hartvigsen

Research Centre, Parker University

• Kent Stuber

Community Health Services & Rehabilitation Science, University of Pittsburgh

• Michael J. Schneider

Department of Physical Therapy, University of Alberta

• Greg Kawchuk

The spine centre of Southern Denmark, hospital Lillebælt, University Hospital of Southern Denmark

• Soren O'Neil

Chiropractic Knowledge Hub

• Henrik Wulf Christensen

Publications associated with the project

Ferreira ML, De Luca K, Haile LM, Steinmetz JD, Culbreth GT, Cross M, et al. Global, regional, and national burden of low back pain, 1990-2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021. Lancet Rheumatol. 2023;5(6):e316-29.

Beliveau PJH, Wong JJ, Sutton DA, Simon N Ben, Bussières AE, Mior SA, et al. The chiropractic profession: A scoping review of utilization rates, reasons for seeking care, patient profiles, and care provided. Chiropr Man Therap. 2017;25(1):1-17.

Jenkins HJ, Downie A, Wong JJ, Young JJ, Roseen EJ, Nim CG, et al. Patient and provider characteristics associated with therapeutic intervention selection in a chiropractic clinical encounter: a cross-sectional analysis of the COAST and O-COAST study data. Chiropr Man Therap. 2023 Dec 1;31(1).

Rubinstein SM, De Zoete A, Van Middelkoop M, Assendelft WJJ, De Boer MR, Van Tulder MW. Benefits and harms of spinal manipulative therapy for the treatment of chronic low back pain: Systematic review and meta-analysis of randomised controlled trials. BMJ (Online). 2019;364.

Leboeuf-Yde C, Grønstvedt A, Borge JA, Lothe J, Magnesen E, Nilsson Ø, et al. The nordic back pain subpopulation program: Demographic and clinical predictors for outcome in patients receiving chiropractic treatment for persistent low-back pain. J Manipulative Physiol Ther. 2004;27(8):493-502.

Maiers M, Forte ML. Association Between Psychosocial Parameters and Response to Chiropractic Care Among Older Adults With Chronic Low Back Pain: Secondary Analysis of a Randomized Clinical Trial. J Manipulative Physiol Ther. 2021 Nov 1;44(9):675-82.

Childs JD, Fritz JM, Flynn TW, Irrgang JJ, Johnson KK, Majkowski GR, et al. A clinical prediction rule to identify patients with low back pain most likely to benefit from spinal manipulation: a validation study. Ann Intern Med. 2004;141(12):920-8.

Hadizadeh M, Kawchuk G, Prasad N, Fritz J. Predicting who responds to spinal manipulative therapy using a short-time frame methodology: Results from a 238- participant study. PLoS One. 2020 Nov 1;15(11 November).

Cecchi F, Pasquini G, Paperini A, Boni R, Castagnoli C, Pistritto S, et al. Predictors of response to exercise therapy for chronic low back pain: result of a prospective study with one year follow-up. Eur J Phys Rehabil Med [Internet]. 2014 Apr;50(2):143-51.

Koppenhaver SL, Walker MJ, Smith RW, Booker JM, Walkup ID, Su J, et al. Baseline examination factors associated with clinical improvement after dry needling in individuals with low back pain. Journal of Orthopaedic and Sports Physical Therapy. 2015 Aug 1;45(8):604-12.