Efficacy of Vitamin D Supplementation in Depression in Adults: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Randomized controlled trials (RCTs) investigating the efficacy of vitamin D (Vit D) in depression provided inconsistent results. OBJECTIVE: We aim to summarize the evidence of RCTs to assess the efficacy of oral Vit D supplementation in depression compared to placebo. DATA SOURCES: We searched electronic databases, two conference proceedings, and gray literature by contacting authors of included studies. STUDY SELECTION: We selected parallel RCTs investigating the effect of oral Vit D supplementation compared with placebo on depression in adults at risk of depression, with depression symptoms or a primary diagnosis of depression. DATA EXTRACTION: Two reviewers independently extracted data from relevant literature. DATA SYNTHESIS: Classical and Bayesian random-effects meta-analyses were used to pool relative risk, odds ratio, and standardized mean difference. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation tool. RESULTS: Six RCTs were identified with 1203 participants (72% females) including 71 depressed patients; five of the studies involved adults at risk of depression, and one trial used depressed patients. Results of the classical meta-analysis showed no significant effect of Vit D supplementation on postintervention depression scores (standardized mean difference = -0.14, 95% confidence interval = -0.41 to 0.13, P = .32; odds ratio = 0.93, 95% confidence interval = 0.54 to 1.59, P = .79). The quality of evidence was low. No significant differences were demonstrated in subgroup or sensitivity analyses. Similar results were found when Bayesian meta-analyses were applied. CONCLUSIONS: There is insufficient evidence to support the efficacy of Vit D supplementation in depression symptoms, and more RCTs using depressed patients are warranted.
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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 | 0.022 | 0.089 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".