Do patients’ preferences and expectations match clinical guidelines? A survey of individuals seeking private primary care for a musculoskeletal disorder
Bibliographic record
Abstract
BACKGROUND: Physiotherapists often inconsistently adhere to clinical practice guidelines (CPGs) when managing musculoskeletal disorders (MSKDs), potentially due to discrepancies between patient-valued interventions and guideline recommendations. Since patients' expectations are important predictors of outcome, this disparity between CPGs recommendations and patient preferences could be problematic for the effective care of MSKDs. OBJECTIVES: To assess patients' expectations and preferences for the interventions used in their MSKD management and to establish correspondence rates between patients' preferences and recommendations from CPGs. DESIGN: Survey. METHOD: This cross-sectional descriptive study included a survey on sociodemographics, preferences, and expectations towards interventions for their MSKD, acceptable cost of care, number of treatment sessions required, and their involvement in their MSKD management. RESULTS: One hundred and fifty participants (94 women and 56 men; mean age: 51 ± 17) responded to the survey. Eighty percent of respondents expected their involvement in their MSKD management to be equal to or superior than that of the physiotherapist. Sixty-nine percent of respondents expected to receive exercises, and 67% expected to receive education. Based on preference ratings, 95% of respondents chose recommended interventions, 57% chose interventions with uncertain levels of recommendation, and 48% chose interventions not recommended by CPGs. CONCLUSION: Less than 70% of participants expected to receive education and exercises, the two most frequently recommended interventions by CPGs. On the other hand, the majority of respondents indicated that their involvement should be equal to or superior than that of the physiotherapist. This aligns with CPGs, which advocate for active and self-management strategies.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".