Introduction
Chronic musculoskeletal pain (CMP) is the leading cause of disability worldwide, affecting millions annually and imposing an economic burden of $560–635 billion in the U.S. alone (Vos et al., Reference Vos, Lim and Abbafati2020; Gaskin & Richard, Reference Gaskin and Richard2012). CMP, characterized by persistent or recurrent pain in the muscles, bones, joints, or tendons, most commonly affects the neck and lower back regions (Treede et al., Reference Treede, Rief and Barke2015; World Health Organization, 2022). Emergency departments (EDs) frequently serve as the initial point of care for individuals experiencing either acute or chronic pain, with musculoskeletal pain-related complaints representing the fourth most common reason for ED visits in 2021 (9.5 million cases) (Centers for Disease Control and Prevention, 2023).
Despite the ED’s important role in addressing pain across the acute-chronic continuum, limited research has examined ED-specific risk factors contributing to the transition from acute to chronic pain, and few interventions have been systematically implemented to prevent this trajectory. In the general population, the annual incidence of chronic pain is 6.3% (Nahin et al., Reference Nahin, Feinberg, Kapos and Terman2023), but among ED patients with acute pain, the risk of chronic pain transition is substantially higher, ranging from 12%–27% (Beaudoin et al., Reference Beaudoin, Merchant and McConaghy2020; Office of the Assistant Secretary for Planning and Evaluation, 2021; Bourassa et al., Reference Bourassa, Lalonde, Racine, Choinière, Moulin and Gordon2020; Barnett et al., Reference Barnett, Olenski and Jena2017), underscoring the ED as a critical setting for early identification and prevention. Prior ED-based studies have identified predictors such as pain intensity, body region, and opioid use (Beaudoin et al., Reference Beaudoin, Merchant and McConaghy2020; Office of the Assistant Secretary for Planning and Evaluation, 2021; Bourassa et al., Reference Bourassa, Lalonde, Racine, Choinière, Moulin and Gordon2020; Barnett et al., Reference Barnett, Olenski and Jena2017), but the role of maladaptive pain beliefs, kinesiophobia, pain catastrophizing, and guideline-discordant care remains largely unexplored. Evidence from post-surgical and outpatient populations has established that these psychological factors and guideline-discordant care (e.g., excessive imaging) are associated with an increased risk of developing chronic pain (Theunissen et al., Reference Theunissen, Peters, Bruce, Gramke and Marcus2012; Stevans et al., 2020), and this is further supported by observational and conceptual studies linking these factors to pain persistence, negative affect, and pain-related disability (Rogers & Farris, Reference Rogers and Farris2022; Coninx et al., Reference Coninx, Ray and Stilwell2025; Ray et al., Reference Ray, Kovaleski, Kelleran, Stilwell, Baraki, Coninx and Eubanks2022; Keller et al., Reference Keller, Ray and Baugher2023; Brown et al., Reference Brown, Hu, Demetriou, Smith and Hing2020; Vivekanantha et al., Reference Vivekanantha, de Sa, Halai, Daniels, Del Balso, Pinsker and Shah2023). However, their potential value in ED-based screening and intervention remains untested.
The overarching goal of this study is to determine whether maladaptive pain beliefs, fear-avoidance behaviours, catastrophizing, and guideline-discordant care contribute to the transition from acute to chronic pain among ED patients with acute post-traumatic musculoskeletal pain. We hypothesize that individuals who transition to CMP will exhibit greater psychological distress (e.g., anxiety, depression, pain catastrophizing), misinformed pain beliefs (e.g., kinesiophobia), higher rates of non-prescribed psycho-active substance use (e.g., alcohol, marijuana), and distinct patterns of ED-based pain management (e.g., increased imaging and pharmacologic interventions).
To guide our study design and selection of predictors, we developed a conceptual framework titled the Cognitive Risk Model for CMP (Figure 1). Grounded in the fear-avoidance and biopsychosocial models (Vlaeyen et al., Reference Vlaeyen, Crombez and Linton2016; Engel, Reference Engel1977), this framework posits that maladaptive pain beliefs influence chronic pain development through psychological and behavioural pathways. It is further informed by emerging affordance-based theories of pain, which suggest that persistent pain alters perceived opportunities for action (i.e. affordances), reinforcing avoidance behaviours (Coninx et al., Reference Coninx, Ray and Stilwell2025). This theoretical lens highlights the importance of addressing cognitive and behavioural responses to acute pain early in the care trajectory. The study aims to test this framework in an ED setting, with the goal of identifying individuals at heightened risk of chronic pain development and informing future early intervention strategies.
Cognitive Risk Model for Chronic Musculoskeletal Pain. This directed acyclic graph (DAG) illustrates hypothesized pathways through which pain beliefs influence the development of chronic musculoskeletal pain (pain frequency) following an ED visit. Psychological and behavioural mediators (grey), confounding variables (white), and primary outcome (blue) are shown, with arrows representing theorized causal relationships.
Methods and analysis
Conceptual framework & analytic rationale
Building upon the framework described above, the Cognitive Risk Model for CMP conceptualizes pain beliefs and attitudes as the primary independent variable, with the presence of CMP as the primary outcome, and functional status and pain intensity as secondary outcomes. By applying this theoretical lens, our study aims to identify how pain beliefs and behavioural responses constrain meaningful action and contribute to pain persistence. This model informed the selection of variables, timing of follow-up assessments, and the structure of our analytic approach. Specifically, it supports the inclusion of psychosocial and behavioural mediators (e.g., catastrophizing, fear-avoidance, physical activity, pain self-efficacy, recovery expectations), and contextual modifiers (e.g., substance use, social determinants of health, mental health conditions), and pathway modelling to explore both direct and indirect effects.
The study design was further refined and strengthened through consultation with ED clinicians, pain researchers, and a patient partner with lived experience of chronic pain, ensuring alignment with clinical priorities and patient-centred outcomes.
Recruitment will occur through direct, in-person approaches in the ED based on screening via the electronic medical record (EMR) tracking system (Figure 2).
Study Flowchart. Flowchart outlining the PREVENT study procedures for participant screening, enrolment, and follow-up. Potential participants are identified through electronic medical record pre-screening, followed by in-person eligibility assessment and informed consent. Enrolled participants complete baseline forms and are followed at 1-, 3-, and 6-month intervals, with chart audits conducted at the 1- and 6-month time points. Screening logs are completed for all screened individuals regardless of eligibility or consent status.
Inclusion criteria
Adult ED patients ≥18 years of age will be eligible for participation if they meet specific criteria: (1) have acute neck and/or low back pain (onset ≤4 weeks); (2) have incurred a recent (≤4 weeks) trauma (e.g., motor vehicle crash, falls, bicycle accidents); (3) have no definitive cause of pain related to unstable fracture, malignancy, active infection, or inflammatory conditions (e.g., ankylosing spondylitis); (4) have no co-occurring progressive neurological symptoms (e.g., spinal cord injury or cauda equina syndrome); (5) are not currently pregnant or planning pregnancy within the next 6 months; (6) have no impairments precluding informed consent (e.g., cognitive dysfunction); (7) are English-speaking; and (8) have a willingness to participate in follow-up assessments.
The ≤4-week trauma window ensures that participants are enrolled during the acute phase of pain and that pain onset can be clearly linked to a specific inciting event. This design feature enhances the precision of prospective tracking of pain progression and aligns with established chronic pain definitions, which require symptoms to persist for ≥3 months on most days or every day (Dahlhamer et al., Reference Dahlhamer, Lucas and Zelaya2018; Nahin et al., Reference Nahin, Feinberg, Kapos and Terman2023; Ray et al., Reference Ray, Washington, Thompson and Kelleran2024). This approach also mirrors methodologies used in post-surgical pain studies, where researchers follow patients from a well-defined index event to assess long-term pain outcomes (Katz & Seltzer, Reference Katz and Seltzer2009). By anchoring enrolment to a recent traumatic event, we minimize misclassification of subacute or chronic pain and increase the validity of modelling. This approach is consistent with prior ED-based longitudinal research (Beaudoin et al., Reference Beaudoin, Merchant and McConaghy2020) and supports reliable identification of acute-to-chronic pain transitions.
Recruitment
After EMR screening, study staff will coordinate with the patient’s primary ED provider to confirm eligibility and ensure that approaching the patient will not interfere with clinical care. To maintain confidentiality and minimize disruption, recruitment discussions will take place in private or semi-private areas (e.g., examination rooms). Study staff will introduce the study, explaining its purpose, procedures, and voluntary nature, while providing the opportunity for patients to ask questions. If the patient expresses interest, staff will proceed with the informed consent process. Consent will only be obtained once the patient is clinically stable, ensuring that they are in a condition where they can fully comprehend the study details. Participants will be given ample time to review the consent document and ask any questions before signing. Research staff will be available to provide explanations and answer any questions the participant or their family may have. Participants will also have the option to discuss the study with their healthcare provider or family members before deciding. To ensure participants fully understand the research, the research staff will ask comprehension questions after the participant has read the consent form. This step will help assess whether the participant has understood the study, its risk, and benefits. If a participant is unable to demonstrate an understanding of the study, they will not be enrolled. If the treating clinical team or research staff suspects that a patient may have diminished capacity to consent, the patient will not be approached for participation. This ensures that all participants can make an informed decision. Participants will receive a PDF copy of the signed consent form immediately after providing consent via the REDCap (Research Electronic Data Capture) e-consent system. This ensures they have a record of their participation and the study details. All signed consent documents will be securely stored in REDCap. REDCap provides secure electronic storage, ensuring the confidentiality and integrity of participant information in compliance with Health Insurance Portability and Accountability Act (HIPAA) regulations. Since this study is under HIPAA guidelines, all consent documents and related research records will be maintained for a minimum of 6 years following study closure. During this time, the documents will remain securely archived in REDCap, which offers audit trails and data encryption to safeguard participant privacy.
Since January 2025, screening efforts at our primary ED site have identified 217 patients with musculoskeletal pain, of whom 28 met all inclusion criteria, including the ≤4-week trauma requirement. Among those eligible, 25 participants consented and were enrolled, while 3 declined participations, yielding an acceptance rate of approximately 89% and an overall enrolment rate of 11.5% based on screened patients. These preliminary data support the feasibility of enrolling the target sample of 246 participants within the planned 24 – 36-month recruitment period.
Financial reimbursement
Patient compensation is allocated to incentivize participation, enhance retention, and reduce attrition during the study’s follow-up assessments. Given the longitudinal nature of the study, financial incentives will support continued engagement at key time points, ensuring high-quality data collection and completeness of outcome measures. The distribution of compensation includes:
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• Baseline: completion of Neck-Pain & Attitude Questionnaire (Neck-PAQ) validation study: $10
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• 1-month follow-up: $50 raffle (four winners; ∼1 in 62 chance)
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• 3-month follow-up: $100 raffle (four winners; ∼1 in 62 chance)
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• 6-month follow-up: $200 raffle (one winner; ∼1 in 246 chance)
Compensation will be provided through prepaid debit cards or electronic payment methods, ensuring timely and convenient distribution to participants. The incentive structure aligns with best practices for participant retention in longitudinal studies, while remaining compliant with NIH and institutional research (Teague et al., Reference Teague, Youssef and Macdonald2018).
Quantitative outcomes & assessment tools
To ensure standardization and data harmonization with other studies, this study aligns with the HEAL Common Data Elements (CDE) repository (Wandner et al., Reference Wandner, Domenichiello, Beierlein, Pogorzala, Aquino, Siddons, Porter and Atkinson2021). Key measures, including pain intensity (VAS), pain frequency (NHIS Pain Chronicity), psychological assessments (PCS, TSK, PHQ-2, GAD-2), functional status (ODI, NDI), and substance use screening (ASSIST), were selected from HEAL’s CDE repository whenever possible (Table 1). Participant follow-up assessments will be conducted at 1-, 3-, and 6-months post-ED visit to track pain progression and related outcomes.
Study measures & assessment tools
The primary outcome is the development of CMP in the neck and/or low back, defined as pain in the same anatomical region as the acute presenting complaint, present on most days or every day for at least three months. Secondary outcomes will include changes in pain beliefs (assessed through B-PAQ/N-PAQ scores), pain catastrophizing (PCS scores), and fear-avoidance behaviours (TSK scores), and healthcare utilization, including recurrent ED visits and outpatient care. Additional secondary measures will evaluate changes in physical activity levels (IPAQ-SF scores), pain self-efficacy (PSEQ-2 scores), and pain-related disability, measured through changes in ODI and NDI scores over time. While this study applies the Cognitive Risk Model for CMP specifically to post-traumatic neck and/or low back pain, the model is designed to be adaptable to other anatomical regions and chronic pain types – including both chronic primary and secondary musculoskeletal pain – in future research (Treede et al., Reference Treede, Rief and Barke2015).
In addition to baseline enrolment forms, we will perform a chart audit post-ED discharge to assess ED management, including ED imaging (x-ray, CT, MRI), medication management (including opioids, NSAIDs, acetaminophen, and muscle relaxants), ED disposition (admission vs discharge), diagnostic codes (ICD-10 for musculoskeletal and neurological conditions), and referrals provided (e.g., primary care, pain specialist, physical therapy). After 1- and 6-month follow-ups, additional audits will be completed utilizing an automated process to query the EMR using the Financial Identification Number (FIN) and Medical Record Number (MRN) from the index ED visit. Using these patient-specific identifiers collected during enrolment, a report can be generated for pre-specified data fields in the EMR which exactly matches the data dictionary in the case report form (CRF) built in REDCap. Data can be imported into REDCap and will be checked for fidelity and missingness. An advantage of this process is reduction in bias inherent in manual chart review (Gilbert et al., Reference Gilbert, Lowenstein, Koziol-McLain, Barta and Steiner1996). As a further check, we will query the regional health information exchange for relevant healthcare utilization at regional outside hospitals.
Sample size & quantitative data analysis
Our primary outcome – pain frequency – is assessed as a categorical variable based on participants’ reported number of days per week experiencing neck or low back pain (0–1 days, 2–3 days, 4–5 days, or 6–7 days). Pain frequency will be assessed at 1, 3, and 6 months. For analysis, responses will be dichotomized to classify CMP status: participants reporting pain on 4–5 or 6–7 days per week will be categorized as having CMP (coded as 1), while those reporting 0–1 or 2–3 days per week will be categorized as not having CMP (coded as 0). Based on prior studies reporting a 12%–27% transition rate from acute to chronic pain (Beaudoin et al., Reference Beaudoin, Merchant and McConaghy2020; Office of the Assistant Secretary for Planning and Evaluation, 2021; Bourassa et al., Reference Bourassa, Lalonde, Racine, Choinière, Moulin and Gordon2020; Barnett et al., Reference Barnett, Olenski and Jena2017), we conducted a power analysis to estimate the incidence of CMP with acceptable precision. Using a small effect size (Cohen’s d 0.2), with α = 0.05 and power = 0.80, a minimum sample size of 197 participants is required. To account for an estimated 25% attrition rate, we will recruit 246 participants to ensure adequate study power. This sample size will also provide sufficient power to explore the association between baseline pain beliefs and subsequent development of CMP, as well as to conduct preliminary analyses for establishing potential clinical cut-offs on pain relief measures. Higher scores may indicate individuals at elevated risk for developing CMP and who may benefit from targeted educational interventions. However, these exploratory analyses will require validation in independent samples.
Quantitative statistical analysis will involve predictive model development using multivariable logistic regression to identify significant predictors of CMP as a binary outcome. Pain beliefs will be modelled as the primary independent variable, with adjustment for potential confounding variables identified in the conceptual framework (e.g., demographics, anxiety, depression, substance use, and social determinants of health). Mediation analyses will explore indirect pathways through cognitive-affective constructs (e.g., pain catastrophizing, fear-avoidance, recovery expectations, and pain self-efficacy) and behavioural responses (e.g., physical activity), using structural equation modelling or mediation analysis to estimate direct and indirect effects. Interaction terms between pain beliefs and demographic variables will be tested to evaluate potential effect modification. Model validation will incorporate cross-validation techniques, such as k-fold cross-validation, to assess robustness. Receiver operating characteristic (ROC) curve analysis will determine the model’s discriminative ability using area under the curve (AUC) estimates, and calibration analysis (e.g., Hosmer–Lemeshow test) will assess model fit. Preliminary clinical cut-offs for pain beliefs scores will also be explored by identifying thresholds that maximize sensitivity and specificity for predicting CMP developed based on ROC analysis. Sensitivity analyses will evaluate the stability of findings under alternative variable definitions and measurement criteria.
Validation of the neck-pain and attitudes questionnaire (Neck-PAQ)
During patient screening in the ED, individuals presenting with acute neck pain will be identified as potential participants for the Neck-PAQ validation study. Eligible and consenting participants will be invited to complete the Neck-PAQ and participate in a Think Aloud interview to evaluate the tool’s clarity, interpretability, and response process validity (Scott et al., Reference Scott, Ummer and LeFevre2021). The Think Aloud methodology involves asking participants to verbalize their thoughts in real-time as they complete the questionnaire (Padilla & Leighton, Reference Padilla, Leighton, Zumbo and Hubley2017). This process enables the research team to assess how respondents interpret and process each item, and whether the intended constructs are being accessed during response formulation. Participants will be reminded that the goal is to capture their natural reasoning and will complete a short practice session to increase comfort with the process (Padilla & Leighton, Reference Padilla, Leighton, Zumbo and Hubley2017). All Think Aloud interviews will be audio-recorded, securely stored in REDCap and assigned an identification number. Audio recordings will be transcribed using Whisper (OpenAI, 2023), an automated speech recognition system that operates locally without requiring internet access, thereby minimizing risks to protected health information (PHI). Manual verification will be conducted to ensure transcription accuracy. Anonymized transcripts will then be uploaded to NVivo (QSR International Pty Ltd, 2020) for qualitative analysis. The original audio files will be securely stored on password-protected drives accessible only to study personnel. Upon study completion, all audio recordings will be permanently deleted. Audio will be used solely for data analysis and will not be included in any presentation, publication, or non-research setting. Only transcribed, de-identified excerpts will be used for dissemination purposes.
Qualitative sample size & data analysis
The target sample size is guided by the concept of information power, which considers the study aim, sample specificity, theoretical grounding, quality of dialogue, and chosen analytical strategy (Malterud et al., Reference Malterud, Siersma and Guassora2016). As the Neck-PAQ is a newly developed instrument and the aim is narrow and well-defined, a sample of approximately 20 participants is expected to yield sufficient information power to evaluate the appropriateness of the tool for capturing maladaptive beliefs about the neck, pain, management, and recovery. Verbal data from the Think Aloud interviews will be analysed using deductive content analysis guided by a predefined cognitive model of response processes (Figure 3). This model includes five domains: Comprehension, Knowledge Recall, Evaluation of Truthfulness, Decision-Making and Response Selection, and Reflection and Adjustment (see appendix Neck-PAQ Coding Manual). Each distinct thought unit will be assigned to one or more of these categories. Coding will be conducted independently by two trained raters. Inter-rater reliability will be calculated using Cohen’s Kappa, with a threshold of ≥0.60 required to indicate acceptable agreement (McHugh, Reference McHugh2012).
Think Aloud Cognitive Model. This model outlines the cognitive processes engaged by participants during the Think Aloud protocol, including comprehension, recall of relevant knowledge, evaluation of truthfulness, decision making and response selection, and optional reflection and adjustment. Each stage highlights key cognitive skills involved, such as reading comprehension, analytical reasoning, and judgement, used to interpret and respond to pain-related questionnaire items.
Discrepancies will be discussed and resolved collaboratively, with updates to rater training or the coding manual as necessary. Although this is a deductive process, qualitative insights may emerge during analysis. These will be descriptively reported, but the core analytic strategy focuses on the structured categorization of verbalized response processes to validate whether items in the Neck-PAQ are functioning as intended.
Stakeholder engagement
The development and refinement of this study were informed by input from multiple stakeholder groups. ED clinicians, pain researchers, and a patient partner contributed to the design phase, providing feedback to ensure clinical feasibility, contextual relevance, and representation of the lived experience of chronic pain. The patient partner will also contribute to the qualitative data analysis, interpretation of findings, and dissemination of results. Stakeholder involvement enhances the study’s relevance, credibility, and potential impact by ensuring that research questions, methods, and outcomes reflect patient-centred priorities and real-world clinical needs, while minimizing patient blaming and stigmatization (Ray et al., Reference Ray, Washington, Thompson and Kelleran2024; Cohen et al., Reference Cohen, Quintner, Buchanan, Nielsen and Guy2011).
Ethical & safety considerations
This study poses minimal risk to participants; however, several protections are in pace to address potential concerns. The primary risk involves the potential loss of confidentiality. Although all study data will be stored securel using HIPAA-compliant REDCap servers with encryption and strict access controls, a small risk of data breach remains. To mitigate this, no PHI will be stored alongside study data, and all identifiable information will be de-identified prior to analysis. Data elements will be clearly labelled as PHI or non-PHI to ensure regulatory compliance.
There are no physical risks associated with this study, as participation involves only surveys and interviews. Psychological or emotional discomfort may occur, particularly when answering questions related to pain, mental health, or substance use. Participants will be informed that they may skip any question or withdraw from the study at any time without penalty or impact on their medical care.
Written informed consent will be obtained from all participants, with clear explanation of study procedures, risks, and confidentiality safeguards. In alignment with mandated reporting procedures, if a participant discloses child or elder abuse, neglect, or an imminent threat of harm such as suicidal or homicidal ideation, the research staff will notify the ED care team and the study’s PI, who will then follow institutional reporting guidelines.
Participants will have access to mental health support throughout the study. Since the study is conducted within the ED, patients will have 24/7 access to social workers and psychological consultations as needed. Participants will also be provided with information about external mental health resources, including the university’s Employee Assistance Program (EAP), student counselling services, and national crisis support lines such as the 988 Suicide & Crises Lifeline.
Data management & dissemination
Study data, including de-identified clinical variables, patient-reported outcomes, and qualitative transcripts, will be stored on HIPAA-compliant servers and shared via NIH-compliant repositories such as Vivli. Access to individual-level data will require data use agreements, while metadata, survey instruments, and analytic code (SAS, R, Python) will be provided to support transparency and reproducibility. Oversight will be maintained by the study PI in collaboration with the IRB and institutional data support teams.
Discussion
Musculoskeletal pain – particularly in the neck and lower back – is the leading cause of disability worldwide and a frequent reason for ED visits (Vos et al., Reference Vos, Lim and Abbafati2020; World Health Organization, 2022; Centers for Disease Control and Prevention, 2023). Despite its high in acute care settings, few studies have systematically investigated early predictors of chronicity or developed target interventions during this critical window. The Pain Recognition and Evaluation to Validate Effective Neck and back Treatment (PREVENT) study addresses this gap by prospectively evaluating cognitive, behavioural, and contextual factors that may contribute to the transition from acute to chronic pain following traumatic injury.
Chronic pain affects approximately 1 in 4 adults and 1 in 5 children, contributing to increased rates of co-morbid health conditions and increased mortality risk. (Dahlhamer et al., Reference Dahlhamer, Lucas and Zelaya2018; Chambers et al., Reference Chambers, Dol, Tutelman, Langley, Parker, Cormier, Macfarlane, Jones, Chapman, Proudfoot, Grant and Marianayagam2024; Foley et al., Reference Foley, Knight, Ploughman, Shabnamc and Audas2021; Ray et al., Reference Ray, Washington, Thompson and Kelleran2024). Individuals with chronic pain experience double the risk mortality compared to those without, and those with high-impact chronic pain – defined as chronic pain that limits life or work activities – face a 2.5-fold increased risk (Dahlhamer et al., Reference Dahlhamer, Lucas and Zelaya2018; Ray et al., Reference Ray, Washington, Thompson and Kelleran2024). Among individuals living with chronic pain, an estimated 8%–12% meet criteria for opioid use disorder, and many also have elevated odds of other substance use disorders (Vowles et al., Reference Vowles, McEntee, Julnes, Frohe, Ney and van der Goes2015; Havlik et al., Reference Havlik, Rhee and Rosenheck2024). Early identification of high-risk individuals, coupled with scalable, evidence-based interventions, is essential to interrupt this trajectory. Findings from this study may inform ED-based strategies to reduce the incidence of CMP, improve long-term health outcomes, and decrease healthcare utilization and opioid-related harms.
One promising framework is the Screening, Brief Intervention, and Referral to Treatment (SBIRT) approach, which has been successfully applied to substance use and mental health conditions but has not yet been adapted for acute pain management (Barata et al., Reference Barata, Shandro, Montgomery, Polansky, Sachs, Duber, Weaver, Heins, Owen, Josephson and Macias-Konstantopoulos2017; Hargraves et al., Reference Hargraves, White, Frederick, Cinibulk, Peters, Young and Elder2017). In musculoskeletal pain scenarios, guideline-concordant care emphasizes a person-centred approach that includes education, shared decision making, and supported self-management (Lin et al., Reference Lin, Wiles and Waller2020; Hutting et al., Reference Hutting, Caneiro, Ong’wen, Miciak and Roberts2022).
Pain science education (PSE) is an evidence-based intervention designed to support individuals seeking care for musculoskeletal pain (Watson et al., Reference Watson, Ryan and Cooper2019). PSE helps patients reconceptualize pain away from being viewed solely as a marker of tissue damage or injury (more pain equals more damage) to that of a protective mechanism. In this way, PSE provides a scientific basis for a BioPsychoSocial model of pain and disability and the enhanced sensitivity generated by central nervous system adaptations as pain persists (Moseley & Butler, Reference Moseley and Butler2015). PSE consists of providing people with information about the various contributors to pain, the meaning of pain, and supported self-management strategies (Moseley & Butler, 2105). High-level evidence from randomized controlled trials have demonstrated positive effects of PSE on disability and fear of movement (Watson et al., 2919). Further, recent evidence identified target concepts important to individuals’ recovery from musculoskeletal pain and included narratives such thoughts, emotions, and experiences affect pain (Leake et al., Reference Leake, Moseley, Stanton, O’Hagan and Heathcote2021). However, to date, PSE interventions have not been adapted for delivery in an ED setting. SBIRT offers a validated framework for embedding PSE and facilitating referrals for treatment in acute pain scenarios, particularly for patients identified at high-risk for CMP via a cognitive risk model.
Ongoing research is adapting SBIRT in an outpatient setting to encourage veterans to seek healthcare for musculoskeletal pain-related disorders through non-pharmacological interventions while also addressing co-occurring mental health and substance use issues (Martino et al., Reference Martino, Lazar, Sellinger, Gilstad-Hayden, Fenton, Barnett, Brummett, Higgins, Holtzheimer, Mattocks, Ngo, Reznik, Semiatin, Stapley and Rosen2020). This provides preliminary evidence that SBIRT can be adapted for pain management scenarios. Building on this work, our planned investigations will adapt SBIRT for acute musculoskeletal pain in the ED setting – an approach we refer to as Pain-SBIRT. In this approach, Pain-SBIRT will incorporate real-time delivery of PSE during the ED consultation and include follow-up assessments after discharge. Patients identified as high-risk through our predictive model will be prioritized, ensuring that intervention resources are directed to those most vulnerable to pain chronicity. These innovations position Pain-SBIRT as a scalable, patient-centred intervention for acute pain in ED settings.
Finally, while this study focuses on post-traumatic neck and back pain, the underlying Cognitive Risk Model is designed to be adaptable across different anatomical regions and applicable to both primary and secondary musculoskeletal pain syndromes (Treede et al., Reference Treede, Rief and Barke2015). Future research may extend its utility to broader populations or settings, such as paediatric care or underserved community clinics, enhancing the model’s translational potential and public health impact.
Conclusion
This research will advance our understanding of the biopsychosocial factors influencing the transition from acute to chronic neck and back pain, particularly within the ED setting. By identifying modifiable psychological and behavioural risk factors – such as maladaptive pain beliefs, fear-avoidance, and low self-efficacy – this study will lay the groundwork for the development of targeted, evidence-informed interventions. Specifically, findings may inform the adaptation of existing frameworks, such as SBIRT for pain management and enable the tailored delivery of PSE to high-risk patients. These approaches could reduce recurrent ED visits, improve long-term patient outcomes, and support the integration of preventative strategies into clinical guidelines and health policy. As a foundational study, this work will also support larger-scale trials and public health efforts to reduce the burden of CMP.
Acknowledgements
Many thanks to Dr. Trudy Mallinson for her continued mentorship and insightful feedback on the prior versions of this study protocol.
Funding statement
This research is supported through a National Research Scientist Award as a T32 distributed by the Primary Care and Research Training program at George Washington University School of Medicine & Health Sciences.
Competing interests
The authors declare that they have no conflicts of interest.
Ethical standards
The authors assert that all procedures contributing to this work comply with the ethical standards of The George Washington University Institutional Review Board and the United States Department of Health and Human Services regulations (45 CFR 46) for the protection of human subjects, and with the Helsinki Declaration of 1975, as revised in 2008. Written (or Verbal) informed consent is being obtained from all subjects/patients.
Open access
