Exploring the lived experience of adults using prescriptions opioids to manage chronic non-cancer pain
Bibliographic record
Abstract
The use of prescription opioids for chronic non-cancer pain is complex. Opioids have the potential to alleviate discomfort and increase ones overall ability to function but, long\nterm use also has potential physical and psychological impacts. The purpose of this study was to explore the lived experience of adults who use prescription opioids to manage chronic non-cancer pain. Nine participants were recruited and interviewed. Participants were asked to describe how using prescription opioids had affected their lives. Interviews were recorded, transcribed and analyzed thematically using Interpretative phenomenological analysis (IPA). Eight themes emerged from the data: the process of decision making, physical effects of using opioids, social consequences of using opioids, Guilt, fears, ambivalence, self-protection, and acceptance. Using opioids made pain more manageable and improved function for most of the participants. Nevertheless, using opioids was also associated with stigma, guilt, fears and ambivalence about their future as persons with chronic 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".