Nutritional Aspects of Child and Adolescent Psychopharmacology
Bibliographic record
Abstract
One challenge faced by physicians in pharmacotherapy of children and adolescents is the management of drug-drug interactions. A second challenge, rarely addressed, is the potential interaction of drugs with nutrients. The National Health and Nutrition Examination Survey (NHANES) found 52% of adults taking a dietary supplement in the previous month. In children with autism spectrum disorders, nutrient supplementation has also been reported to be about 50%. Vitamins, minerals, amino acids, and essential fatty acids, of course, are the building blocks of neuronal structure and function, and depending on dose levels, can be expected to influence brain function per se. Additionally, supplements can affect pharmaceutical regimens prescribed for the purposes of influencing the brain, because of the possibilities for interactions. In this article, we review a) some fundamentals of nutrition and brain biochemistry shown to be important in psychiatric disorders, including the potential therapeutic benefit of nutrient supplementation, and b) what is known of drug-nutrient interactions, including nutrient stress introduced by drugs that interfere with metabolism and increase the requirement for specific nutrients. ABOUT THE AUTHORS Bonnie J. Kaplan, PhD, is Professor, Faculty of Medicine, University of Calgary, Calgary, Alberta, Canada. Scott Shannon, MD, is Medical Director, Northern Colorado Center for Holistic Medicine, Fort Collins, Colorado. Address correspondence to: Bonnie J. Kaplan, PhD, Department of Pediatrics, University of Calgary, Behavioral Research Unit, Alberta Children’s Hospital, 2888 Shaganappi Trail NW, Calgary AB T3B 6A8; fax 403-955-2772; e-mail bonnie.kaplan@calgaryhealthregion.ca. Dr. Kaplan and Dr. Shannon have disclosed no relevant financial relationships. EDUCATIONAL OBJECTIVES Describe the scope of nutrients, especially vitamins and materials, which have been studied in relationship to mood, and some of the findings. Relate the four different types of interactions between medications and nutrients/foods. Discuss the recommendations for compensatory supplementation for specific medication regimens.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".