The Wisdom of Thai Indigenous Healers for the Spiritual Healing of Fractures
Bibliographic record
Abstract
AIMS: The aim of this study was to explore the wisdom of Thai indigenous healers (IHs) for physical and spiritual healing and their treatment process for fractures. METHOD: Twelve IHs from four regions of Thailand were selected using cluster and purposive sampling. They were interviewed on their methods for treating fractures. The Colaizzi method was used for analysis, and we returned to the IHs for validity confirmation. FINDINGS: The wisdom of IHs is believed to be inherited from ancestors and from a "sixth sense," their former teacher's spirit. There are no textbooks, only one-on-one training. The annual Wai Khru ceremony, where IHs pay respect to their teachers, is believed to also impart a blessing of greater wisdom to the student healer. Their physical treatment of fractures is like that by an orthopedic physician, but their methods and materials are different because physical treatment is combined with spiritual care. CONCLUSION: Certain aspects of IH practice may have application for professional nursing. It is suggested that incorporating traditional spiritual care into nursing may improve patients' quality of life, both physically and spiritually.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".