<i>It might take a village</i> : developing a rehabilitation program of care for degenerative cervical radiculopathy from the patient perspective
Bibliographic record
Abstract
PURPOSE: The aim of our study is to inform the development of a rehabilitation program of care from the perspectives of those suffering from degenerative cervical radiculopathy (DCR). MATERIAL AND METHODS: We conducted a qualitative study, purposefully recruiting individuals with DCR. Transcripts from virtual semi-structured interviews were iteratively analyzed using interpretative phenomenological methods. RESULTS: Eleven participants were recruited and depicted their ideal rehabilitation program of care. Participants described the importance of a patient centered-approach, health care providers who were validating, reassuring and attentive, easier access to health services, a supportive and collaborative team environment, and receiving peer support. Furthermore, participants expressed that they would expect the program of care to result in their symptoms being less intense and intermittent. In consideration of the participant perspectives, the ideal rehabilitation program of care can be conceptualized by the enactive-biopsychosocial model, which provides a theoretical framework for developing and implementing the program of care. CONCLUSION: We obtained valuable information from individuals living with DCR regarding their preferences and expectations of a rehabilitation program of care. The participant descriptions will provide the groundwork for its development to meet patient needs and expectations. Future research to guide implementation will also be explored.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".