<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vogel, Taylor</style></author><author><style face="normal" font="default" size="100%">Riley, Kylie W</style></author><author><style face="normal" font="default" size="100%">Samon, Sam</style></author><author><style face="normal" font="default" size="100%">Anderson, Kim A</style></author><author><style face="normal" font="default" size="100%">Armstrong, Georgina</style></author><author><style face="normal" font="default" size="100%">Barton, Michael</style></author><author><style face="normal" font="default" size="100%">Bondy, Melissa</style></author><author><style face="normal" font="default" size="100%">Bramer, Lisa</style></author><author><style face="normal" font="default" size="100%">Calero, Lehyla</style></author><author><style face="normal" font="default" size="100%">Cassidy-Bushrow, Andrea E</style></author><author><style face="normal" font="default" size="100%">Dixon, Holly M</style></author><author><style face="normal" font="default" size="100%">Herbstman, Julie</style></author><author><style face="normal" font="default" size="100%">Leach, Carrie</style></author><author><style face="normal" font="default" size="100%">Oluyomi, Abiodun</style></author><author><style face="normal" font="default" size="100%">Straughen, Jennifer K</style></author><author><style face="normal" font="default" size="100%">Waters, Katrina</style></author><author><style face="normal" font="default" size="100%">Rohlman, Diana</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparative Analysis of Report-back of Research Results Strategies for Personal Chemical Exposure Data.</style></title><secondary-title><style face="normal" font="default" size="100%">J Expo Sci Environ Epidemiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Expo Sci Environ Epidemiol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2026</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2026 Jun 09</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;strong&gt;BACKGROUND: &lt;/strong&gt;Report-back of research results (RBRR) is ethically supported and highly requested by participants, yet lacks broadly transferable guidelines for RBRR. Effective RBRR must be responsive to target audience needs and may not be addressed by a &#039;one-size-fits-all&#039; approach.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;OBJECTIVE: &lt;/strong&gt;Within a subset of our 19 studies on RBRR, we had the unique opportunity to carry out a comparative analysis of RBRR strategies across cohorts with similar development and evaluation methods, yet distinct in life stage, geography, number and type of chemicals assessed, and community contexts.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;METHODS: &lt;/strong&gt;We highlight key outcomes from three environmental health studies: an ongoing New York, NY cohort (Fair Start; n = 486) and a Detroit, MI cohort (CLEAR; n = 34) assessing exposure to ambient urban pollution during pregnancy, and a longitudinal cohort in Houston, TX (Houston-3H; n = 312) following Hurricane Harvey. Focus group and survey data were analyzed to identify lessons learned and explore how RBRR supports understanding of environmental health.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;RESULTS: &lt;/strong&gt;Commonalities emerged in RBRR development, design, organization, and data visualization, as well as in how RBRR can contribute to an understanding of health-environment connections. Differences included preferences for individual versus community level findings, as well as distinguishable contextual considerations. For pregnancy cohorts, messaging was framed with cultural sensitivity, and to avoid unintended consequences of parental guilt due to prenatal exposures. In the post-disaster Houston-3H study, participants requested additional transparency regarding sampling design and study rationale.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;SIGNIFICANCE: &lt;/strong&gt;All RBRR case studies reported chemicals without known regulatory or health guidelines, so results were contextualized within the study population. Participants across cohorts requested multi-study comparisons to better understand their results beyond their communities. While foundational RBRR elements (e.g. plain language, graphic organizers) may supersede cohort-specific differences, RBRR should be personalized to encompass perceptions of health across different life-stage, cultural, and environmental contexts.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;IMPACT: &lt;/strong&gt;We had the unique opportunity to compare different studies, accounting for different exposure experiences, life stages, chemicals assessed, and RBRR evaluation methods. To our knowledge, this is the first multi-state study reporting back wristband data, used to assess transferable strategies across populations, and how RBRR supports participant understanding of environmental influences on health. Due to the differences between disaster-impacted and peripartum individuals in this subset of case studies, comparisons can inform transferable characteristics of developing RBRR as well as study specific attributes that are responsive to unique contexts.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bramer, Lisa M</style></author><author><style face="normal" font="default" size="100%">Dixon, Holly M</style></author><author><style face="normal" font="default" size="100%">Degnan, David J</style></author><author><style face="normal" font="default" size="100%">Rohlman, Diana</style></author><author><style face="normal" font="default" size="100%">Herbstman, Julie B</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author><author><style face="normal" font="default" size="100%">Waters, Katrina M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration.</style></title><secondary-title><style face="normal" font="default" size="100%">Pac Symp Biocomput</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Pac Symp Biocomput</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Data Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Environmental Monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Silicones</style></keyword><keyword><style  face="normal" font="default" size="100%">Wearable Electronic Devices</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">29</style></volume><pages><style face="normal" font="default" size="100%">170-186</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Wearable silicone wristbands are a rapidly growing exposure assessment technology that offer researchers the ability to study previously inaccessible cohorts and have the potential to provide a more comprehensive picture of chemical exposure within diverse communities. However, there are no established best practices for analyzing the data within a study or across multiple studies, thereby limiting impact and access of these data for larger meta-analyses. We utilize data from three studies, from over 600 wristbands worn by participants in New York City and Eugene, Oregon, to present a first-of-its-kind manuscript detailing wristband data properties. We further discuss and provide concrete examples of key areas and considerations in common statistical modeling methods where best practices must be established to enable meta-analyses and integration of data from multiple studies. Finally, we detail important and challenging aspects of machine learning, meta-analysis, and data integration that researchers will face in order to extend beyond the limited scope of individual studies focused on specific populations.&lt;/p&gt;
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