Assessment of the Maya’s Beliefs and Preferences on Bonesetters and Bone Fracture Treatment in the Guatemalan Highlands: A Household Survey
Bibliographic record
Abstract
BACKGROUND: In the Lake Atitlán region of Guatemala, traditional bonesetters (hueseros) commonly treat bone fractures. The indigenous Kaqchikel population has access to biomedical care, but traditional medicine remains the preferred treatment modality for bone fracture. METHODS: Households in four villages were surveyed to assess experiences with bone fracture treatment. Of 108 households sampled, 83 met inclusion criteria and completed the survey. Responses were analyzed to assess for group demographics, bone fracture prevalence, and treatment history. Independence testing assessed for subgroup differences. RESULTS: Mean age: 40 years old. For fracture treatment, 37% (31/83) consulted with a physician/nurse whereas 75% (62/83) consulted with a bonesetter. 19% (16/83) consulted with both. Cast immobilization was utilized by only 16% (13/83) of participants. The services provided by bonesetters included massage, temazcal (sweat lodge), herbal poultice, prayer, and recommended rest. When comparing participants that used a cast (n=13) and those that used a bonesetter exclusively (n=46), the bonesetter group had lower rates of continued pain and movement limitation, higher satisfaction with treatment, and higher interest in seeking the same treatment in the future, though these findings were not statistically significant. Regarding future care, 66% (55/83) would consider consulting a doctor whereas 83% (69/83) would seek services from a bonesetter. 53% (44/83) would utilize both. If recommended, 46% (38/83) would consider using a cast. Only 22% (18/83) of participants reported previous musculoskeletal imaging. CONCLUSION: These results suggest a high preference of bonesetters for bone injury treatment, reduced acceptance of biomedical care, and limited acceptance of cast immobilization.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".