Informed Consent: Advising Patients and Parents About Complementary and Alternative Medicine Therapies
Bibliographic record
Abstract
Although research on complementary and alternative medicine (CAM) therapies is still limited, systematic reviews have revealed sufficient evidence to conclude that CAM can be effective for certain conditions. In this article we discuss clinicians' responsibilities to inform parents/patients about CAM alternatives and use the example of acupuncture for chemotherapy-induced nausea and vomiting. Chemotherapy-induced nausea and vomiting remain significant adverse effects of cancer therapy, and some patients cannot find relief with standard therapies. When making decisions for a child with a life-threatening illness, parents must consider all reasonable options and decide what is in the child's best interests. A physician's failure to provide parents with relevant information regarding therapies with the prospect of therapeutic benefit impedes their ability to make an informed decision. Physicians have the ethical duty of beneficence; they must be aware of current research in pain and symptom management and other aspects of care. A physician's duty of care does not necessarily include the obligation to provide information about therapies outside the range of conventional treatment or those not yet supported in the medical literature. However, as CAM therapies such as acupuncture become better studied and their safety and efficacy are established, the scope of disclosure required may expand to include them. The legal and ethical obligation to obtain informed consent to treatment requires disclosure and discussion of therapies when there is reliable evidence of potential therapeutic benefit. At the same time, the more limited state of knowledge regarding effects of a particular therapy in the pediatric population must be factored into decision-making when treating a child.
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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 | 0.082 | 0.274 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.022 | 0.020 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".