Accessible Patient Education Materials for Low Back Pain Rarely Meet People's Information Needs: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Patient education is a cornerstone of care for individuals with non-specific low back pain (LBP). However, little is known about whether accessible patient education materials (PEMs) meet people's information needs. METHODS: We conducted a scoping review following the JBI methodology and reported results according to PRISMA-ScR. We systematically reviewed three databases: Ovid MEDLINE, Scopus, and CINAHL. The search strategy was iteratively developed and peer-reviewed using the PRESS checklist. Eligible studies had to provide full access to the PEM designed for people with LBP. Study selection and data extraction were performed independently and in duplicate. Five reviewers conducted a consensus-based analysis by independently matching PEM content to eight categories of information needs derived from previous research. RESULTS: Of 9617 citations identified, 23 studies met inclusion criteria, yielding 41 unique PEMs. We excluded many citations (67.3%) because the PEM used in the study was missing. Most PEMs were in English (95%) and took the form of posters, booklets, or leaflets. Only eight PEMs (19.5%) reported readability assessment. Stakeholder involvement was reported in eight studies. Among PEMs with stakeholder input, characteristics from the PROGRESS + framework were rarely disclosed. Only one PEM addressed all eight identified information needs. The most frequently covered information needs were treatment options (65.9%) and imaging (61.0%), while information on prognosis and flare management was scarce (17.1%). CONCLUSION: Accessible PEMs for non-specific LBP rarely meet the full spectrum of patient information needs. Improving stakeholder involvement and readability assessment is essential to enhance the usefulness and equity of educational resources.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.049 | 0.205 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.029 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".