Exploring pain in the Andes – learning from the Quichua (Inca) people experience
Bibliographic record
Abstract
There is a mounting recognition that culture profoundly shapes human pain experience. The 28 million indigenous people of the Andes in South America, mainly the Quichua (Inca) people, share a distinctive culture. However, little is known about their pain experience and suffering. The aim of the present study was to explore how Quichua adults perceive, describe, and cope with the pain. An exploratory qualitative/descriptive study was conducted with a convenience sample of 40 Quichua adults, including 15 women and 25 men, in the Northern Highlands of Ecuador. Data were collected through structured interviews of approximately 3 h, using a Quichua questionnaire called "The Nature of Pain" [Nanay Jahua Tapuicuna]. The interviews covered the notions of causation of pain, vulnerability to pain, responses to pain, aggravating factors, frequent locations of pain, types of pain, duration, characteristics of pain, control of pain, pathways to care, and preventive measures of pain. Basic descriptive analyses were performed. The Quichuas' pain experience is complex and their strategies to cope with it are sophisticated. According to the Quichuas, emotions, life events, co-morbid conditions, and spirits, among others factors play an important role in the origin, diagnosis, and treatment of pain. They strongly embrace biomedicine and physicians as well as Quichua traditional medicine and traditional healers. Family members and neighbors are also valuable sources of health care and pain control. The pathway to pain care that the Quichua people prefer is inclusive and pluralistic. The knowledge of the Quichua ethnographic "emic" details of their belief system and coping strategies to control pain are clinically useful not only for the health professional working in the Andes, some Quichua cultural characteristics related to pain could be useful to the culturally competent health practitioner who is making efforts to provide high-quality medical care in rural and multicultural societies around the world.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".