Patient perspectives on the desirability of social worker support in outpatient orthopaedic trauma clinics
Bibliographic record
Abstract
Objectives: This study examined the benefits of a dedicated social worker in the fracture clinic setting as perceived by patients and caregivers. Methods: This cross-sectional survey engaged patients aged 18 and older presenting to the fracture clinic associated with a level 1 trauma center. Surveys were available in English and Arabic and included 11 questions designed to measure level of agreement with various aspects of social worker presence in the outpatient fracture clinic. Results: A total of 199 patients and caregivers participated in this study. Most of the participants were female (61.8%) and older than the age of 50 (57.1%). While there was nuance in the circumstances and issues participants felt were appropriate for social worker assistance, most (95.4%) found the general premise of having a dedicated social worker available in the fracture clinic to be acceptable and believed that it would be beneficial to fracture clinic patients. Participants indicated that social workers could support trauma patients with multiple issues (≥60% level of agreement across all items). Conclusions: Orthopaedic trauma patients and their caregivers overwhelmingly support the addition of a dedicated social worker to the fracture clinic, with a high level of agreement across demographic groups and proposed social worker interventions. The patient and caregiver population finds the fracture clinic to be an appropriate and viable setting for the mitigation of nonphysical impacts of orthopaedic trauma. These findings can inform the development of potential future additions of social services to the fracture clinic. Level of Evidence: Level IV.
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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 | 0.013 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".