Clinical Effectiveness and Efficacy of Chiropractic Spinal Manipulation for Spine Pain
Bibliographic record
Abstract
Spine pain is a highly prevalent condition affecting over 11% of the world's population. It is the single leading cause of activity limitation and ranks fourth in years lost to disability globally, representing a significant personal, social, and economic burden. For the vast majority of patients with back and neck pain, a specific pathology cannot be identified as the cause for their pain, which is then labeled as non-specific. In a growing proportion of these cases, pain persists beyond 3 months and is referred to as chronic primary back or neck pain. To decrease the global burden of spine pain, current data suggest that a conservative approach may be preferable. One of the conservative management options available is spinal manipulative therapy (SMT), the main intervention used by chiropractors and other manual therapists. The aim of this narrative review is to highlight the most relevant and up-to-date evidence on the effectiveness (as it compares to other interventions in more pragmatic settings) and efficacy (as it compares to inactive controls under highly controlled conditions) of SMT for the management of neck pain and low back pain. Additionally, a perspective on the current recommendations on SMT for spine pain and the needs for future research will be provided. In summary, SMT may be as effective as other recommended therapies for the management of non-specific and chronic primary spine pain, including standard medical care or physical therapy. Currently, SMT is recommended in combination with exercise for neck pain as part of a multimodal approach. It may also be recommended as a frontline intervention for low back pain. Despite some remaining discrepancies, current clinical practice guidelines almost universally recommend the use of SMT for spine pain. Due to the low quality of evidence, the efficacy of SMT compared with a placebo or no treatment remains uncertain. Therefore, future research is needed to clarify the specific effects of SMT to further validate this intervention. In addition, factors that predict these effects remain to be determined to target patients who are more likely to obtain positive outcomes from SMT.
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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 | 0.059 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".