Clinical care standards for the management of low back pain: a scoping review
Bibliographic record
Abstract
The objective of this study is to compare and contrast the quality statements and quality indicators across clinical care standards for low back pain. Searches were performed in Medline, guideline databases, and Google searches to identify clinical care standards for the management of low back pain targeting a multidisciplinary audience. Two independent reviewers reviewed the search results and extracted relevant information from the clinical care standards. We compared the quality statements and indicators of the clinical care standards to identify the consistent messages and the discrepancies between them. Three national clinical care standards from Australia, Canada, and the United Kingdom were included. They provided from 6 to 8 quality statements and from 12 to 18 quality indicators. The three standards provide consistent recommendations in the quality statements related to imaging, and patient education/advice and self-management. In addition, the Canadian and Australian standards also provide consistent recommendations regarding comprehensive assessment, psychological support, and review and patient referral. However, the three clinical care standards differ in the statements related to psychological assessment, opioid analgesics, non-opioid analgesics, and non-pharmacological therapies. The three national clinical care standards provide consistent recommendations on imaging and patient education/advice, self-management of the condition, and two standards (Canadian and Australian) agree on recommendations regarding comprehensive assessment, psychological support, and review and patient referral. The standards differ in the quality statements related to psychological assessment, opioid prescription, non-opioid analgesics, and non-pharmacological therapies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".