Expectations influence treatment outcomes in patients with low back pain. A secondary analysis of data from a randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Low back pain (LBP) is a global public health challenge, which causes high healthcare costs and the highest burden on society in terms of years lived with disability. While patients' expectations for improvement may have effects on LBP treatment outcomes, it remains unclear if psychological profiles modify this relationship. Therefore, the objectives of this study were to investigate if (a) patients' expectations predicted short-term outcome, and (b) psychological profile, pain intensity and self-rated health modified the relationship between expectations and outcome. METHODS: Data were collected between April 2012 and January 2016 during the inclusion into a randomized controlled trial. Potentially eligible participants were identified through 40 chiropractic clinics located across Sweden. Patients' expectations, psychological profile, pain intensity, activity limitation and self-rated health were collected from patients with recurrent persistent LBP during their first chiropractic visit (n = 593). Subjective improvement was measured at the fourth visit. RESULTS: Patients with a high expectation of improvement had 58% higher risk to report an improvement at the fourth visit (RR = 1.58, 95% CI: 1.28, 1.95). Controlling for potential confounders only slightly decreased the strength of this association (RR = 1.49, 95% CI: 1.20, 1.86). Baseline pain intensity, psychological profile and self-rated health did not modify the effect of expectation on outcome. CONCLUSIONS: Baseline patients' expectations play an important role when predicting LBP treatment outcomes. Clinicians should consider and address patients' expectations at the first visit to best inform prognosis. SIGNIFICANCE: This study confirms the importance of patients' expectations in a clinical setting. Patients' expectations predict the short-term outcome of chiropractic care for LBP. Pain intensity, psychological profile and self-rated health did not modify this relationship.
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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 | 0.033 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".