24 research outputs found

    Application of US EPA IRIS systematic review methods to the health effects of phthalates:Lessons learned and path forward

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    This special issue presents several systematic reviews of the potential human health effects associated with exposure to phthalates and addresses some of the considerations and challenges that were encountered over the course of performing these reviews. This editorial presents the views of the lead U.S. Environmental Protection Agency (EPA) researchers on the project and the Special Issue Editors with regard to lessons learned, implications of methods, and the path forward for systematic reviews to support human health assessment

    Improving the quality of toxicology and environmental health systematic reviews:What journal editors can do

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    Systematic reviews are fast increasing in prevalence in the toxicology and environmental health literature. However, how well these complex research projects are being conducted and reported is unclear. Since editors have an essential role in ensuring the scientific quality of manuscripts being published in their journals, a workshop was convened where editors, systematic review practitioners, and research quality control experts could discuss what editors can do to ensure the systematic reviews they publish are of sufficient scientific quality. Interventions were explored along four themes: setting standards; reviewing protocols; optimizing editorial workflows; and measuring the effectiveness of editorial interventions. In total, 58 editorial interventions were proposed. Of these, 26 were shortlisted for being potentially effective, and 5 were prioritized as short-term actions that editors could relatively easily take to improve the quality of published systematic reviews. Recent progress in improving systematic reviews is summarized, and outstanding challenges to further progress are highlighted

    Student public commitment in a school-based diabetes prevention project: impact on physical health and health behavior

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    <p>Abstract</p> <p>Background</p> <p>As concern about youth obesity continues to mount, there is increasing consideration of widespread policy changes to support improved nutritional and enhanced physical activity offerings in schools. A critical element in the success of such programs may be to involve students as spokespeople for the program. Making such a public commitment to healthy lifestyle program targets (improved nutrition and enhanced physical activity) may potentiate healthy behavior changes among such students and provide a model for their peers. This paper examines whether student's "public commitment"--voluntary participation as a peer communicator or in student-generated media opportunities--in a school-based intervention to prevent diabetes and reduce obesity predicted improved study outcomes including reduced obesity and improved health behaviors.</p> <p>Methods</p> <p>Secondary analysis of data from a 3-year randomized controlled trial conducted in 42 middle schools examining the impact of a multi-component school-based program on body mass index (BMI) and student health behaviors. A total of 4603 students were assessed at the beginning of sixth grade and the end of eighth grade. Process evaluation data were collected throughout the course of the intervention. All analyses were adjusted for students' baseline values. For this paper, the students in the schools randomized to receive the intervention were further divided into two groups: those who participated in public commitment activities and those who did not. Students from comparable schools randomized to the assessment condition constituted the control group.</p> <p>Results</p> <p>We found a lower percentage of obesity (greater than or equal to the 95<sup>th </sup>percentile for BMI) at the end of the study among the group participating in public commitment activities compared to the control group (21.5% vs. 26.6%, p = 0.02). The difference in obesity rates at the end of the study was even greater among the subgroup of students who were overweight or obese at baseline; 44.6% for the "public commitment" group, versus 53.2% for the control group (p = 0.01). There was no difference in obesity rates between the group not participating in public commitment activities and the control group (26.4% vs. 26.6%).</p> <p>Conclusions</p> <p>Participating in public commitment activities during the HEALTHY study may have potentiated the changes promoted by the behavioral, nutrition, and physical activity intervention components.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov number, <a href="http://www.clinicaltrials.gov/ct2/show/NCT00458029">NCT00458029</a></p

    Using Machine-Learning to Facilitate Data Extraction for Human Health Chemical Assessments: Protocol for a case application

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    &lt;p&gt;Artificial intelligence (AI) methods including natural language processing, active learning, and large language models are expected to provide workflow advances to reduce risk assessors&#39; time and effort while maintaining the accuracy necessary to meet demand for chemical assessments. A growing suite of modular software applications that integrate AI methods and leverage human-in-the-loop workflows are making operationalization of these advancements feasible. The case application in this protocol supports development of a Provisional Peer-Reviewed Toxicity Value (PPRTV) assessment for 1,3-dinitrobenzene (1,3-DNB). The protocol describes methods to develop a literature inventory and systematic evidence map (SEM) for 1,3-DNB. Along with typical systematic review methods, the protocol applies an active learning approach to screen records at the title and abstract level using AI methods. While active learning has been a routine method used to reduce the resources required to screen records at the title and abstract level, automated processes for data extraction with user verification have evolved slowly. The slow evolution of AI for data extraction continues to be a challenge primarily because the resources required to develop appropriate training datasets for model development are limited, leading to immature models with poor performance, or the lack of models for many domain-specific data extraction fields. This protocol showcases how software applications like Dextr can be used to address both challenges with the potential to make progress toward a modern workflow stack including data extraction.&lt;/p&gt

    Development of outcome-specific criteria for study evaluation in systematic reviews of epidemiology studies

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    Introduction and objectiveSystematic review tools that provide guidance on evaluating epidemiology studies are receiving increasing attention and support because their application facilitates improved quality of the review, consistency across reviewers, and transparency for readers. The U.S. Environmental Protection Agency's Integrated Risk Information System (IRIS) Program has developed an approach for systematic review of evidence of health effects from chemical exposures that includes structured approaches for literature search and screening, study evaluation, data extraction, and evidence synthesis and integration. This approach recognizes the need for developing outcome-specific criteria for study evaluation. Because studies are assessed at the outcome level, a study could be considered high quality for one investigated outcome, and low quality for another, due to differences in the outcome measures, analytic strategies, how relevant a certain bias is to the outcome, and how the exposure measure relates to the outcome. The objective of this paper is to illustrate the need for outcome-specific criteria in study evaluation or risk of bias evaluation, describe the process we used to develop the criteria, and summarize the resulting criteria.MethodsWe used a process of expert consultation to develop several sets of outcome-specific criteria to guide study reviewers, improve consistency, and ensure consideration of critical issues specific to the outcomes. The criteria were developed using the following domains: outcome assessment, exposure measurement (specifically timing of exposure in relation to outcome; other exposure measurement issues would be addressed in exposure-specific criteria), participant selection, confounding, analysis, and sensitivity (the study's ability to detect a true effect or hazard).ResultsWe discuss the application of this process to pregnancy-related outcomes (preterm birth, spontaneous abortion), other reproductive-related outcomes (male reproductive hormones, sperm parameters, time to pregnancy, pubertal development), chronic disease (diabetes, insulin resistance), and acute or episodic conditions (asthma, allergies), and provide examples of the criteria developed. For each outcome the most influential methodological considerations are highlighted including biological sample collection and quality control, sensitivity and specificity of ascertainment tools, optimal timing for recruitment into the study (e.g., preconception, specific trimesters), the etiologically relevant window for exposure assessments, and important potential confounders.ConclusionsOutcome-specific criteria are an important part of a systematic review and will facilitate study evaluations by epidemiologists with experience in evaluating studies using systematic review methods who may not have extensive discipline-specific experience in the outcomes being reviewed

    Dengue Outbreak in Key West, Florida, USA, 2009

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    After 3 dengue cases were acquired in Key West, Florida, we conducted a serosurvey to determine the scope of the outbreak. Thirteen residents showed recent infection (infection rate 5%; 90% CI 2%–8%), demonstrating the reemergence of dengue in Florida. Increased awareness of dengue among health care providers is needed
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