Diet and Psychosis: A Scoping Review
Bibliographic record
Abstract
INTRODUCTION: Schizophrenia spectrum disorders (SSD) represent a cluster of severe mental illnesses. Diet has been identified as a modifiable risk factor and opportunity for intervention in many physical illnesses and more recently in mental illnesses such as unipolar depression; however, no dietary guidelines exist for patients with SSD. OBJECTIVE: This review sought to systematically scope the existing literature in order to identify nutritional interventions for the prevention or treatment of mental health symptoms in SSD as well as gaps and opportunities for further research. METHODS: This review followed established methodological approaches for scoping reviews including an extensive a priori search strategy and duplicate screening. Because of the large volume of results, an online program (Abstrackr) was used for screening and tagging. Data were extracted based on the dietary constituents and analyzed. RESULTS: Of 55,330 results identified by the search, 822 studies met the criteria for inclusion. Observational evidence shows a connection between the presence of psychotic disorders and poorer quality dietary patterns, higher intake of refined carbohydrates and total fat, and lower intake or levels of fibre, ω-3 and ω-6 fatty acids, vegetables, fruit, and certain vitamins and minerals (vitamin B12 and B6, folate, vitamin C, zinc, and selenium). Evidence illustrates a role of food allergy and sensitivity as well as microbiome composition and specific phytonutrients (such as L-theanine, sulforaphane, and resveratrol). Experimental studies have demonstrated benefit using healthy diet patterns and specific vitamins and minerals (vitamin B12 and B6, folate, and zinc) and amino acids (serine, lysine, glycine, and tryptophan). DISCUSSION: Overall, these findings were consistent with many other bodies of knowledge about healthy dietary patterns. Many limitations exist related to the design of the individual studies and the ability to extrapolate the results of studies using dietary supplements to dietary interventions (food). Dietary recommendations are presented as well as recommendations for further research including more prospective observational studies and intervention studies that modify diet constituents or entire dietary patterns with statistical power to detect mental health outcomes.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".