Living successfully with chronic pain: Identifying the pivotal conditions needed to make it happen
Bibliographic record
Abstract
Chronic pain is associated with many negative consequences for individuals and society. Given the burden it represents, many studies have focused on the risk factors involved, but very few have aimed to explain why some people live well with chronic pain, beyond the psychological realm. Thus, this study collected and analyzed different individual experiences to identify the pivotal conditions that help some individuals achieve quality of life despite chronic pain, with an emphasis on social considerations. We conducted a qualitative study using a narrative inquiry approach to unpack the participants' stories on these pivotal conditions. We carried out 25 individual interviews with persons who considered they had been living well with their pain for a minimum of 6 months. Data were analyzed using the inductive narrative method. Most participants were women (64%), White (88%), with a high level of education, and having low back or generalized pain (56%). Three main themes were identified: 1) a care partnership, 2) a nurturing environment, and 3) breaking free from previous life to move forward. These themes were then divided into 11 sub-themes, providing an in-depth understanding of the pivotal conditions needed to live well with chronic pain. The data collected suggest that to enable people to have a favorable evolution in the presence of chronic pain, a socio-ecological approach could be necessary to counteract painogenic environments. However, these results need to be validated and adapted to different populations. Perspective This study highlights the importance of a socio-ecological approach to living well with chronic pain, emphasizing that care partnerships, a nurturing environment and the ability to break with the past are essential to improve the quality of life of those affected.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 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".