Reasons to Use and Disclose Use of Complementary Medicine Use – An Insight from Cancer Patients
Bibliographic record
Abstract
Studies have shown a high prevalence (40-83%) of complementary and alternative medicine (CAM) use among cancer patients in the U.S.A cross-sectional, mixed-methods pilot study was completed. This paper focuses on the quantitative analysis conducted on demographic predictors of complementary medicine (CM) use, reasons to use CM, and disclosure to healthcare provider data. Surveys were interview-administered at the Loma Linda University Medical Center Cancer Center. Participants, 18 years or older, were selected from a convenient sample. Eighty-seven percent (87.9%) of participants reported to have used CM as a cancer treatment and most reported to have used it "to help fight the cancer." Women were eight-times more likely to use prayer. All non-Caucasian and Hispanic participants reported to use CM as a cancer therapy and none reported to use a CM provider. More women (72%) disclosed their CM use than men (53.3%). Different prevalences and predictors exist when differentiating CM modalities, reasons to use CM vary by gender, and disclosure proportions vary by gender.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".