Understanding patient beliefs regarding the use of imaging in the management of low back pain
Bibliographic record
Abstract
BACKGROUND: Imaging for low back pain (LBP) remains common despite guidelines recommending against routine imaging. Patient beliefs about imaging may contribute to the problem. This study aimed to quantitatively investigate patient beliefs regarding the need for imaging in managing LBP and to investigate whether personal characteristics, pain characteristics or back pain beliefs are associated with imaging beliefs. METHODS: A survey was performed of consecutive patients presenting to general medical practitioners in Sydney, Australia. Nine medical clinics were selected across varied socioeconomic regions. Survey questions assessed beliefs about the importance of imaging for LBP, collected demographic information, LBP history and general beliefs about back pain. Descriptive statistics and multivariate logistic regression were used to analyse findings. RESULTS: Three hundred completed surveys were collected with a 79.6% response rate. The mean age was 44 years and 60.7% of respondents were women. Exactly, 54.3% (95% CI: 48.7-58.9%) believed that imaging was necessary for the best medical care for LBP. Exactly, 48.0% (95% CI: 42.4-53.6%) believed that everyone with LBP should obtain imaging. Increased age, lower education level, non-European or non-Anglo-saxon cultural background, history of previous imaging and Back Beliefs Questionnaire scores were associated with beliefs that imaging was necessary. CONCLUSION: Approximately, half of all patients presenting to a medical doctor consider low back imaging to be necessary. This may have important implications for overutilization of low back imaging investigations. Knowledge of the factors associated with the patient's belief that imaging is necessary may be helpful in designing appropriate interventions to reduce unnecessary imaging for LBP.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".