Complementary and Alternative Medicine Use and Benefit Finding Among Cancer Patients
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: An increasing number of cancer patients are choosing Complementary and Alternative Medicine (CAM) as an active way to manage the physical, psychological, and spiritual consequences of cancer. This trend parallels a movement to understand how a difficult experience, such as a cancer diagnosis, may help facilitate positive growth, also referred to as benefit finding. Little is known about the associations between the use of CAM and the ability to find benefit in the cancer experience. METHODS: We conducted a cross-sectional survey of medical oncology outpatients in an urban academic cancer center. Patients completed measures of CAM use and benefit finding following a diagnosis of cancer. A hierarchical regression, adjusting for covariates, was performed to evaluate the unique contribution of CAM use on benefit finding. The relationship between specific CAM modalities and benefit finding was explored. RESULTS: Among 316 participants, 193 (61.3%) reported CAM use following diagnosis. Factors associated with CAM use were female gender (p=0.005); college, or higher, education (p=0.09); breast cancer diagnosis (p=0.016); and being 12 to 36 months post-diagnosis (p=0.017). In the hierarchical regression, race contributed the greatest unique variance to benefit finding (23%), followed by time from diagnosis (18%), and age (14%). Adjusting for covariates, CAM use uniquely accounted for 13% of the variance in benefit finding. Individuals using energy healing and healing arts reported significantly more benefit than nonusers. Special diet, herbal remedies, vitamin use, and massage saw a smaller increase in benefit finding, while acupuncture, chiropractic, homeopathy, relaxation, yoga, and tai chi were not significantly associated with benefit finding. CONCLUSIONS: Patients who used CAM following a cancer diagnosis reported higher levels of benefit finding than those who did not. More research is required to evaluate the causal relationship between CAM use, benefit finding, and better psychosocial well-being.
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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 | 0.001 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it