A primary care back pain screening tool: identifying patient subgroups for initial treatment
Abstract
Objective: To develop and validate a tool that screens for back pain prognostic indicators relevant to initial decision making in primary care. Methods: The setting was UK primary care adults with nonspecific back pain. Constructs that were independent prognostic indicators for persistence were identified from secondary analysis of 2 existing cohorts and published literature. Receiver operating characteristic curve analysis identified single screening questions for relevant constructs. Psychometric properties of the tool, including concurrent and discriminant validity, internal consistency, and repeatability, were assessed within a new development sample (n = 131) and tool score cutoffs were established to enable allocation to 3 subgroups (low, medium, and high risk). Predictive and external validity were evaluated within an independent external sample (n = 500). Results: The tool included 9 items: referred leg pain, comorbid pain, disability (2 items), bothersomeness, catastrophizing, fear, anxiety, and depression. The latter 5 items were identified as a psychosocial subscale. The tool demonstrated good reliability and validity and was acceptable to patients and clinicians. Patients scoring 0–3 were classified as low risk, and those scoring 4 or 5 on a psychosocial subscale were classified as high risk. The remainder were classified as medium risk. Conclusion: We validated a brief screening tool, which is a promising instrument for identifying subgroups of patients to guide the provision of early secondary prevention in primary care. Further work will establish whether allocation to treatment subgroups using the tool, linked with targeting treatment appropriately, improves patient outcomes.
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Recent work, such as the STarT Back project, has made important advances in prognostic stratification of patients with chronic low back pain.
“Recent work such as the STarT Back project from the U.K. has made important advances in this regard,57–60”
From Report of the NIH Task Force on research standards for chronic low back pain. (2014) · cites this paper as [57]
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- Authors
- Hill, J. C., Dunn, K. M., Lewis, M., Mullis, R., Main, C. J., Foster, N. E., & Hay, E. M.
- Affiliations
- Keele University (GB)
- ORCID
- Venue
- Arthritis Care & Research
- Publisher
- Wiley
- Published
- 2008-04-25
- Volume
- 59
- Issue
- 5
- Pages
- 632-641
- ISSN
- 0893-7524 (ISSN-L)
- 1529-0123
- OpenAlex
- W2067435956
- Cited by
- 1,052
- References
- 57
- Citations by year
- 2026: 35 · 2025: 57 · 2024: 61 · 2023: 70 · 2022: 96 · 2021: 105 · 2020: 103 · 2019: 72 · 2018: 80 · 2017: 58 · 2016: 62 · 2015: 54 · 2014: 56 · 2013: 50 · 2012: 26
- FWCI
- 15.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Arthritis Care & Research (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute for Health and Care Research (RP-PG-0707-10131, PC6/CSA04/03)
- Keele University
- Versus Arthritis (13413)
- Topics
- Health Sciences › Medicine › Pharmacology › Musculoskeletal pain and rehabilitation
- Health Sciences › Medicine › Pathology and Forensic Medicine › Spine and Intervertebral Disc Pathology
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Medical Practices and Rehabilitation
- Keywords
- non-specific low back pain, prognostic factors, pain persistence, psychosocial factors, catastrophizing, fear avoidance, depression, anxiety, comorbid pain, disability, risk stratification, primary care, secondary prevention, tool validation
- MeSH terms
- Adult, Back Pain, Female, United Kingdom, Humans, Male, Mass Screening, Middle Aged, Primary Health Care, Prognosis, Psychometrics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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