An ecosystem of accepting life with chronic pain: A meta-ethnography
Bibliographic record
Abstract
Background: Chronic pain is a highly prevalent long-term condition, experienced unequally, impacting both the individual living with pain, and wider society. 'Acceptance' of chronic pain is relevant to improved consultations in pain care, and navigating an approach towards evidence-based, long-term management and associated improvements in health. However, the concept proves difficult to measure, and primary qualitative studies of lived experiences show complexity related to our socio-cultural-political worlds, healthcare experiences, and difficulties with language and meaning. We framed acceptance of chronic pain as socially constructed and aimed to conceptualise the lived experiences of acceptance of chronic pain in adults. Methods: We conducted a systematic search and screening process, followed by qualitative, interpretive, literature synthesis using Meta-ethnography. We included qualitative studies using chronic pain as the primary condition, where the study included an aim to research the acceptance concept. We conducted each stage of the synthesis with co-researchers of differing disciplinary backgrounds, and with lived experiences of chronic pain. Findings: We included 10 qualitative studies from Canada, Sweden, The Netherlands, Ireland, UK, Australia and New Zealand. Our 'lines of argument' include a fluid and continuous journey with fluctuating states of acceptance; language and meaning of acceptance and chronic pain, a challenge to identity in a capitalist, ableist society and the limits to individualism; a caring, supportive and coherent system. The conceptual framework of the meta-ethnography is represented by a rosebush with interconnected branches, holding both roses and thorns, such is the nature of accepting life with chronic pain. Conclusion: Our findings broaden conceptualisation of 'acceptance of chronic pain' beyond an individual factor, to a fluid and continuous journey, interconnected with our socio-cultural-political worlds; an ecosystem.
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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 | 0.036 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".