Traditional Chinese medicine in cancer care: perspectives and experiences of patients and professionals in China
Bibliographic record
Abstract
Although traditional Chinese medicine (TCM) is widely used in Chinese cancer centres, it is a brand new area for formal scientific evaluation. As the first step of developing a research programme on clinical evaluation of TCM for cancer patients, we conducted a qualitative study to explore the perspectives and experiences of Chinese cancer patients and TCM professionals. Twenty-eight persons participated in two cancer patient focus groups and one professional focus group. Semi-structured interviews were audiotaped, transcribed and translated. Textual transcripts and field notes underwent inductive thematic analysis. We found that patients' decision to use TCM for cancer is a self-help process with a deep cultural grounding, which is related to the traditional Chinese philosophy of life. Participants perceived TCM to be an effective and harmless therapy. They highly valued the fact that TCM is tailored to patients, and believed it was the basis of an optimal and safe treatment. Participants also highlighted the long-term positive effects, the benefit of group interventions and the low cost as important features of TCM. Subjects believed that conducting clinical research would be crucial for the recognition and dissemination of TCM in Western countries. The findings of this study are expected to contribute to the knowledge base on the current TCM use for cancer in China, and to provide useful information for developing future clinical research in this area in Western countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".