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Record W4289778755 · doi:10.1016/j.envint.2022.107438

Lead exposure and antisocial behavior: A systematic review protocol

2022· review· en· W4289778755 on OpenAlexaff
Rachel M. Shaffer, Jenna E. Forsyth, Gregory L. Ferraro, Christine Till, Laura M. Carlson, Kirstin Hester, Amanda Haddock, Jenna Strawbridge, Charles C. Lanfear, Howard Hu, Ellen Kirrane

Bibliographic record

VenueEnvironment International · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsYork University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUniversity of Washington
KeywordsProtocol (science)Lead exposurePsychologyLead (geology)Environmental healthEnvironmental scienceMedicineBiology

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0320.001

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.

Opus teacher head0.040
GPT teacher head0.335
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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