The implications of chronic pain models for rehabilitation of distal radius fracture
Bibliographic record
Abstract
Distal radius fracture (DRF) is the most common fracture and usually occurs as a result of a fall. Most patients recover following DRF with minimal residual pain or disability; however, a small subset of patients continue to experience pain and disability even one year after the injury. Currently, there are no practice guidelines for early identification and treatment of patients who are potentially at greater risk of developing these adverse outcomes. As a result, hand therapy management of patients following DRF does not incorporate screening of these at-risk patients. The objective of this paper is to apply constructs from learned helplessness and cognitive-behavioural models of chronic pain in assessing the psychosocial risk profile of patients following DRF. We have also integrated key findings derived from studies addressing personal and life-style factors in assessing this risk profile. This framework is proposed as a basis to categorize patients as higher or lower psychosocial risk for developing chronic pain and disability following DRF. We outline a model depicting the RACE approach (Reducing pain, Activating, Cognitive reshaping, Empowering) towards the management of patients following DRF. The model suggests that patients with minimal psychosocial risk factors are managed based on their injury profile and those with higher psychosocial risk are treated with the risk-based RACE approach. Using a biopsychosocial RACE approach to prognosis and treatment, hand therapy intervention can be customized for patients recovering from DRF. In future, researchers can conduct clinical trials to compare the RACE-based treatment approach to routine hand therapy in mitigating the risk of chronic pain and disability in patients with elevated risk profile for adverse outcomes following DRF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".