Lead exposure and antisocial behavior: A systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Lead exposure remains highly prevalent worldwide despite decades of research highlighting its link to numerous adverse health outcomes. In addition to well-documented effects on cognition, there is growing evidence of an association with antisocial behavior, including aggression, conduct problems, and crime. An updated systematic review on this topic, incorporating study evaluation and a developmental perspective on the outcome, can advance the state of the science on lead and inform global policy interventions to reduce exposure. OBJECTIVES: We aim to evaluate the link between lead exposure and antisocial behavior. This association will be investigated via a systematic review of human epidemiological and experimental nonhuman mammalian studies. METHODS: The systematic review protocol presented in this publication is informed by recommendations for the conduct of systematic reviews in toxicology and environmental health research (COSTER) and follows the study evaluation approach put forth by the U.S. EPA Integrated Risk Information System (IRIS) program. DATA SOURCES: We will search the following electronic databases for relevant literature: PubMed, BIOSIS and Web of Science. Search results will be stored in EPA's Health and Environmental Research Online (HERO) database. STUDY ELIGIBILITY AND CRITERIA: Eligible human epidemiological studies will include those evaluating any population exposed to lead at any lifestage via ingestion or inhalation exposure and considering an outcome of antisocial behavior based on any of the following criteria: psychiatric diagnoses (e.g., oppositional defiant disorder (ODD), conduct disorder (CD), disruptive behavior disorders (DBD)); violation of social norms (e.g., delinquency, criminality); and aggression. Eligible experimental animal studies will include those evaluating nonhuman mammalian studies exposed to lead via ingestion, inhalation, or injection exposure during any lifestage. The following outcomes will be considered relevant: aggression; antisocial behavior; and altered fear, anxiety, and stress response. STUDY APPRAISAL AND SYNTHESIS METHODS: Screening will be conducted with assistance from an artificial intelligence application. Two independent reviewers for each data stream (human, animal) will screen studies with highest predicted relevance against pre-specified inclusion criteria at the title/abstract and full-text level. Study evaluation will be conducted using methods adapted from the U.S. EPA IRIS program. After data extraction, we will conduct a narrative review and quantitative meta-analysis on the human epidemiological studies as well as a narrative review of the experimental animal studies. We will evaluate the strength of each evidence stream separately and then will develop a summary evidence integration statement based on inference across evidence streams.
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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 | 0.068 | 0.088 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.019 | 0.014 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.093 | 0.012 |
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".