Wait-there’s evidence for that? Integrative medicine treatments for major depressive disorder
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
Depression is one of the most common mental health disorders and currently affects over 17 million Americans. Up to two-thirds of patients with depression in the United States will seek complementary and alternative or integrative medical treatments and thus medical providers who treat depression should understand that many integrative medical treatments have evidence of efficacy either as monotherapies or as add-on adjuncts to other treatments. This review references guidelines from the Canadian Network for Mood and Anxiety Treatments and Michigan Medicine, along with an updated literature review, to provide a framework for reviewing medications or herbal formulation, as well as other therapies, which have evidence in the treatment of depression. In general, St. John's Wort, Omega-3 Fatty Acids, S-adenosyl-L-methionine, and crocus sativus (saffron) have the highest levels of evidence in the treatment of mild-to-moderate depression. Acetyl-l-carnitine, l-methylfolate, DHEA, and lavender have a moderate level of evidence in treating depression, whereas Vitamin D, one of the most common supplements in the United States, does not have evidence in treating depression. Of the non-medication-based therapies, exercise, light therapy, yoga, acupuncture, and probiotics have evidence in the treatment of depression, whereas a full review of dietary modifications for depression was out of scope for this article.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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