Developing guidelines to support injured workers who live and work with chronic pain
Bibliographic record
Abstract
BACKGROUND: Living and working with chronic pain requires persons to alter lifestyles and have the knowledge as well as support to manage unforeseen challenges. Knowledge for persons living with pain who want to participate in meaningful paid and unpaid work is not easily accessible. While there is literature on chronic pain management, work transitions and return to work, less emphasis has been placed on the complexity of living and working with chronic pain. The Creating a Way Forward Project was envisioned to address this gap and to identify the informational needs of workers with pain, health/helping professionals (workers' advisors, return to work specialists, legal representatives), and stakeholders. The overarching aim of the project was to use evidence and experiential knowledge to inform the development of a foundation for educational guides and toolkits to support workers with pain to achieve their outcomes for remaining at work. METHODS: Phase one of the project involved a scoping review of chronic pain and work. Phase two involved stakeholder consultations, a focus group and knowledge integration of the literature and experiential insights. Knowledge synthesis drew on a Template Analysis of multiple sources of data. RESULTS: Knowledge domains and key components were identified for persons with pain and for the health/helping professions. CONCLUSION: These domains reflect a foundation for knowledge in practical training and the development of curriculum for education in self-management program and in inter professional health profession education. These knowledge domains provide a basis for future research in integrated approaches and knowledge use toward improving transitions for persons living with chronic pain who want to participate in productive paid and unpaid work. Ongoing research in knowledge domains that health providers and persons with pain need will expand the potential for improving health outcomes in living with and managing pain.
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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 | 0.034 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".