Building evidence to reduce inequities in management of pain for Indigenous Australian people
Bibliographic record
Abstract
OBJECTIVES: Pain is a universal experience which each person encounters differently, guided by the psycho-socio-environmental context in which it occurs. Although more research is underway yet very little is known about pain from Indigenous Australian perspective. Therefore, this study aims to examine, experience of pain and coping, and utility of three measures: Brief Pain Inventory short form, McGill Pain Questionnaire and Numerical rating scale, from Indigenous South Australian people perspective. METHODS: Thirteen in-person interviews were conducted which lasted around 90 min and were audio-recorded. The transcripts were coded and analysed thematically with NVivo. RESULTS: Six key themes were identified; 1: Spiritual conceptualisation of pain; 2: Frequent experience of trauma and injury; 3: Influence of familial history of pain; 4: Acceptance of pain as normal; 5: Outlook on biomedical management of pain; 6: Preference for non-pharmacological management of pain. Also, the three measures did not fully capture pain from an Indigenous Australian perspective which is more deeply rooted in a bio-psycho-socio-spiritual context which is cardinal to conceptualization of health and wellbeing in Indigenous Australian communities. CONCLUSIONS: Findings highlight some commonalities as well as unique differences between Indigenous experiences of pain as compared to non-Indigenous. Factors such as spiritual connection with pain, grief and loss, history of trauma and injury, fear of addiction to pain medication and exposure to pain from early childhood had important implications for how participants viewed 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 | 0.054 | 0.150 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".