Variance in Manual Treatment of Nonspecific Low Back Pain Between Orthomanual Physicians, Manual Therapists, and Chiropractors
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to identify differences in the diagnosis and treatment of nonspecific low back pain among 3 professional groups in the Netherlands: orthomanual physicians, manual therapists, and chiropractors. METHODS: Information was obtained from training materials from professional groups, literature searches, and observation of selected practitioners at work. RESULTS: In The Netherlands, there are differences in education between the 3 professional groups. The focus of orthomanual medicine is on abnormal positions of components of the skeleton and symmetry in the spine. Manual therapy focuses on functional disorders of the musculoskeletal system. Chiropractic focuses on the musculoskeletal and nervous systems in relation to patients' health in general. Orthomanual medicine considers inspection and palpation the most important diagnostic tools. Manual therapists and chiropractors additionally perform tests to determine functional disorders and manual therapists evaluate psychosocial influences. Chiropractors take radiographs if necessary. Orthomanual physicians apply mobilization techniques using fixed protocols. Manual therapists and chiropractors use various manipulation and mobilization techniques and their manipulation techniques differ in amplitude and velocity. CONCLUSIONS: Diagnostic techniques and treatment methods of the 3 professional groups differ considerably. For more accurate reporting of the efficacy of manipulative and mobilizing therapies, the characteristics of treatments should be described in more detail when reported in studies such as randomized clinical trials.
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 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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".