Reasons for and Characteristics Associated With Complementary and Alternative Medicine Use Among Adult Cancer Patients: A Systematic Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To conduct a systematic review of reasons for and sociodemographic and disease characteristics associated with complementary and alternative medicine (CAM) use in cancer patients. METHODS: Eligible studies were identified by searching the following databases: Alt Health Watch, AMED, CINAHL, CancerLit, PremMEDLINE, MEDLINE, Pub-Med, Ingenta, EMBASE, and Health Star, as well as reference lists in review articles. Only English-language articles published between 1994 and 2004 were included. Search terms included CAM and oncology/cancer, decision making and CAM and oncology/cancer, treatment decision making and CAM and oncology/cancer, and health care choices and CAM and oncology/cancer. RESULTS: Fifty-two eligible studies were identified and summarized. These studies were conducted in 14 different countries, with the largest number of studies being completed in the United States (34.6%). A therapeutic response, wanting control, a strong belief in CAM, CAM as a last resort, and finding hope were the most commonly cited reasons for using CAM. Age, socioeconomic status, and gender were the dominant characteristics associated with CAM use. CONCLUSION: Reasons for and characteristics associated with CAM use among cancer patients have been studied extensively. Future CAM research among cancer patients should focus on identifying decision-making processes and building theoretical decision-making models. These can be used in the development of decisional aids for patients when confronted with the choice to use CAM as part of their cancer treatment.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 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) | 0.000 | 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 it