Defining a recovery-oriented cascade of care for opioid use disorder: A community-driven, statewide cross-sectional assessment

Background In light of the accelerating and rapidly evolving overdose crisis in the United States (US), new strategies are needed to address the epidemic and to efficiently engage and retain individuals in care for opioid use disorder (OUD). Moreover, there is an increasing need for novel approaches to using health data to identify gaps in the cascade of care for persons with OUD. Methods and findings Between June 2018 and May 2019, we engaged a diverse stakeholder group (including directors of statewide health and social service agencies) to develop a statewide, patient-centered cascade of care for OUD for Rhode Island, a small state in New England, a region highly impacted by the opioid crisis. Through an iterative process, we modified the cascade of care defined by Williams et al. for use in Rhode Island using key national survey data and statewide health claims datasets to create a cross-sectional summary of 5 stages in the cascade. Approximately 47,000 Rhode Islanders (5.2%) were estimated to be at risk for OUD (stage 0) in 2016. At the same time, 26,000 Rhode Islanders had a medical claim related to an OUD diagnosis, accounting for 55% of the population at risk (stage 1); 27% of the stage 0 population, 12,700 people, showed evidence of initiation of medication for OUD (MOUD, stage 2), and 18%, or 8,300 people, had evidence of retention on MOUD (stage 3). Imputation from a national survey estimated that 4,200 Rhode Islanders were in recovery from OUD as of 2016, representing 9% of the total population at risk. Limitations included use of self-report data to arrive at estimates of the number of individuals at risk for OUD and using a national estimate to identify the number of individuals in recovery due to a lack of available state data sources. Conclusions Our findings indicate that cross-sectional summaries of the cascade of care for OUD can be used as a health policy tool to identify gaps in care, inform data-driven policy decisions, set benchmarks for quality, and improve health outcomes for persons with OUD. There exists a significant opportunity to increase engagement prior to the initiation of OUD treatment (i.e., identification of OUD symptoms via routine screening or acute presentation) and improve retention and remission from OUD symptoms through improved community-supported processes of recovery. To do this more precisely, states should work to systematically collect data to populate their own cascade of care as a health policy tool to enhance system-level interventions and maximize engagement in care

Behavioral responses of terrestrial mammals to COVID-19 lockdowns

DATA AND MATERIALS AVAILABILITY : The full dataset used in the final analyses (33) and associated code (34) are available at Dryad. A subset of the spatial coordinate datasets is available at Zenodo (35). Certain datasets of spatial coordinates will be available only through requests made to the authors due to conservation and Indigenous sovereignty concerns (see table S1 for more information on data use restrictions and contact information for data requests). These sensitive data will be made available upon request to qualified researchers for research purposes, provided that the data use will not threaten the study populations, such as by distribution or publication of the coordinates or detailed maps. Some datasets, such as those overseen by government agencies, have additional legal restrictions on data sharing, and researchers may need to formally apply for data access. Collaborations with data holders are generally encouraged, and in cases where data are held by Indigenous groups or institutions from regions that are under-represented in the global science community, collaboration may be required to ensure inclusion.COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals’ 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.The Radboud Excellence Initiative, the German Federal Ministry of Education and Research, the National Science Foundation, Serbian Ministry of Education, Science and Technological Development, Dutch Research Council NWO program “Advanced Instrumentation for Wildlife Protection”, Fondation Segré, RZSS, IPE, Greensboro Science Center, Houston Zoo, Jacksonville Zoo and Gardens, Nashville Zoo, Naples Zoo, Reid Park Zoo, Miller Park, WWF, ZCOG, Zoo Miami, Zoo Miami Foundation, Beauval Nature, Greenville Zoo, Riverbanks zoo and garden, SAC Zoo, La Passarelle Conservation, Parc Animalier d’Auvergne, Disney Conservation Fund, Fresno Chaffee zoo, Play for nature, North Florida Wildlife Center, Abilene Zoo, a Liber Ero Fellowship, the Fish and Wildlife Compensation Program, Habitat Conservation Trust Foundation, Teck Coal, and the Grand Teton Association. The collection of Norwegian moose data was funded by the Norwegian Environment Agency, the German Ministry of Education and Research via the SPACES II project ORYCS, the Wyoming Game and Fish Department, Wyoming Game and Fish Commission, Bureau of Land Management, Muley Fanatic Foundation (including Southwest, Kemmerer, Upper Green, and Blue Ridge Chapters), Boone and Crockett Club, Wyoming Wildlife and Natural Resources Trust, Knobloch Family Foundation, Wyoming Animal Damage Management Board, Wyoming Governor’s Big Game License Coalition, Bowhunters of Wyoming, Wyoming Outfitters and Guides Association, Pope and Young Club, US Forest Service, US Fish and Wildlife Service, the Rocky Mountain Elk Foundation, Wyoming Wild Sheep Foundation, Wild Sheep Foundation, Wyoming Wildlife/Livestock Disease Research Partnership, the US National Science Foundation [IOS-1656642 and IOS-1656527, the Spanish Ministry of Economy, Industry and Competitiveness, and by a GRUPIN research grant from the Regional Government of Asturias, Sigrid Rausing Trust, Batubay Özkan, Barbara Watkins, NSERC Discovery Grant, the Federal Aid in Wildlife Restoration act under Pittman-Robertson project, the State University of New York, College of Environmental Science and Forestry, the Ministry of Education, Youth and Sport of the Czech Republic, the Ministry of Agriculture of the Czech Republic, Rufford Foundation, an American Society of Mammalogists African Graduate Student Research Fund, the German Science Foundation, the Israeli Science Foundation, the BSF-NSF, the Ministry of Agriculture, Forestry and Food and Slovenian Research Agency (CRP V1-1626), the Aage V. Jensen Naturfond (project: Kronvildt - viden, værdier og værktøjer), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy, National Centre for Research and Development in Poland, the Slovenian Research Agency, the David Shepherd Wildlife Foundation, Disney Conservation Fund, Whitley Fund for Nature, Acton Family Giving, Zoo Basel, Columbus, Bioparc de Doué-la-Fontaine, Zoo Dresden, Zoo Idaho, Kolmården Zoo, Korkeasaari Zoo, La Passarelle, Zoo New England, Tierpark Berlin, Tulsa Zoo, the Ministry of Environment and Tourism, Government of Mongolia, the Mongolian Academy of Sciences, the Federal Aid in Wildlife Restoration act and the Illinois Department of Natural Resources, the National Science Foundation, Parks Canada, Natural Sciences and Engineering Research Council, Alberta Environment and Parks, Rocky Mountain Elk Foundation, Safari Club International and Alberta Conservation Association, the Consejo Nacional de Ciencias y Tecnología (CONACYT) of Paraguay, the Norwegian Environment Agency and the Swedish Environmental Protection Agency, EU funded Interreg SI-HR 410 Carnivora Dinarica project, Paklenica and Plitvice Lakes National Parks, UK Wolf Conservation Trust, EURONATUR and Bernd Thies Foundation, the Messerli Foundation in Switzerland and WWF Germany, the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Actions, NASA Ecological Forecasting Program, the Ecotone Telemetry company, the French National Research Agency, LANDTHIRST, grant REPOS awarded by the i-Site MUSE thanks to the “Investissements d’avenir” program, the ANR Mov-It project, the USDA Hatch Act Formula Funding, the Fondation Segre and North American and European Zoos listed at http://www.giantanteater.org/, the Utah Division of Wildlife Resources, the Yellowstone Forever and the National Park Service, Missouri Department of Conservation, Federal Aid in Wildlife Restoration Grant, and State University of New York, various donors to the Botswana Predator Conservation Program, data from collared caribou in the Northwest Territories were made available through funds from the Department of Environment and Natural Resources, Government of the Northwest Territories. The European Research Council Horizon2020, the British Ecological Society, the Paul Jones Family Trust, and the Lord Kelvin Adam Smith fund, the Tanzania Wildlife Research Institute and Tanzania National Parks. The Eastern Shoshone and Northern Arapahoe Fish and Game Department and the Wyoming State Veterinary Laboratory, the Alaska Department of Fish and Game, Kodiak Brown Bear Trust, Rocky Mountain Elk Foundation, Koniag Native Corporation, Old Harbor Native Corporation, Afognak Native Corporation, Ouzinkie Native Corporation, Natives of Kodiak Native Corporation and the State University of New York, College of Environmental Science and Forestry, and the Slovenia Hunters Association and Slovenia Forest Service. F.C. was partly supported by the Resident Visiting Researcher Fellowship, IMéRA/Aix-Marseille Université, Marseille. This work was partially funded by the Center of Advanced Systems Understanding (CASUS), which is financed by Germany’s Federal Ministry of Education and Research (BMBF) and by the Saxon Ministry for Science, Culture and Tourism (SMWK) with tax funds on the basis of the budget approved by the Saxon State Parliament. This article is a contribution of the COVID-19 Bio-Logging Initiative, which is funded in part by the Gordon and Betty Moore Foundation (GBMF9881) and the National Geographic Society.https://www.science.org/journal/sciencehj2023Mammal Research InstituteZoology and Entomolog

Increasing Autonomy in the Homeless Veteran Population Through Education-Based Occupational Therapy Intervention: A Critically Appraised Topic

The focus for this critically appraised topic (CAT) is increasing the autonomy of homeless veterans through life-skills-based education programs. A review of existing literature found a gap of published research on this topic within occupational therapy and interdisciplinary research communities. There is a lack of experimentally designed research studies focusing on autonomy and community assistance programs utilizing life skills education training for or including the homeless veteran population. The level of evidence presented in the literature relating to this topic has been predominantly found to include non-experimental descriptive quantitative studies (Jones et al., 2021; Kline et al., 2021; Laan et al., 2020; Nichter et al., 2023; Tsai & Byrne, 2023), non-experimental correlational studies (Holder et al., 2023), and qualitative studies (Doris & Löfstrand, 2020; Greenberg et al., 2019) indicating a need for experimental and more rigorous studies. Additionally, many existing research utilizes the same national data set, The National Health and Resilience in Veterans Study (NHRVS), as a basis for statistical analysis (Nichter et al., 2023; Kline et al., 2021). Although the national data set yielded multiple avenues of analysis, the data was collected from two cohorts most recently surveyed in 2019 and 2020 indicating a need for a broader and more current sample

Abstract PD1-01: The Impact of Structural Racism on Breast Cancer Stage at Presentation

Abstract Background: Despite advances in diagnosis and treatment, racial and economic disparities in breast cancer-specific survival persist and this is exacerbated by later stage at presentation. It is essential to assess the factors that contribute to later stage at presentation to target racial and socioeconomic disparities in breast cancer mortality. The objective of this study was to analyze the effect of neighborhood socioeconomic status (SES) and race/ethnicity, as measured by the Index of Concentration at the Extremes (ICE), on breast cancer stage at presentation in a diverse metropolitan area that mirrors the projected demographics of many US regions. Methods: Patients treated at our medical campus, comprised of a safety-net hospital and an academic cancer center, with stage I-IV breast cancer from 2005-2017 were identified from our tumor registry. Census tracts were used as neighborhood proxies. Using 5-year estimates from the American Community Survey, 5 ICE variables were computed: economic (high vs. low), race/ethnicity (non-Hispanic White (NHW) vs. non-Hispanic Black (NHB) and NHW vs. Hispanic) and racialized economic (low-income NHB vs high-income NHW and low-income Hispanics vs. high-income NHW) segregation. ICE uniquely captures spatial economic and racial/ethnic segregation by mapping social inequality not otherwise captured by evaluating a population of a specific socioeconomic level or belonging to a particular racial/ethnic group. We used five separate models based on each of the ICE variables to evaluate economic and racial/ethnic segregation. Model 1 captures economic segregation (high vs. low), Model 2 captures racial segregation (NHB vs. NHW), Model 3 evaluates racialized economic segregation (low-income NHB vs high-income NHW), Model 4 captures segregation by Hispanic ethnicity (Hispanic vs. Non-Hispanic), and Model 5 captures ethnic and economic segregation (low-income Hispanics vs. high-income NHW). Our main outcome was breast cancer stage at presentation categorized as early (Stage I and II) vs. late (Stage III and IV) disease. All models controlled for the following covariates: race/ethnicity, age, insurance status, tumor subtype, and comorbidities including hypertension, diabetes, coronary artery disease, and hyperlipidemia. Results: The study population included 6,145 breast cancer patients. 52.6% were Hispanic, 26.3% were NHW, and 17.2% were NHB. Those living in the most economically marginalized neighborhoods (Quartiles 1 and 2) had significantly increased odds of presenting with later stage disease [ORQ1 1.36 (1.13-1.64), ORQ2 1.43 (1.18-1.75); p&amp;lt; 0.05]. Those living in the most racial/ethnic and economically marginalized neighborhoods (Quartile 1 of Models 3 and 5) had statistically significantly increased odds of presenting with later stage after controlling for all covariates compared to a NHW living in more economically advantaged neighborhoods [ORModel3 1.55 (1.21-1.99), ORModel5 1.43 (1.11-1.85); p&amp;lt; 0.05]. Conclusions: This study is the first to evaluate stage at presentation by ICE, which allows us to uniquely evaluate how residential racial and economic segregation may influence breast cancer disparities. Our study shows that patients in the most economically and racial/ethnically marginalized neighborhoods were more likely to present with later stage disease. This suggests that structural racism is influencing stage at presentation, and therefore effecting racial and economic disparities in breast cancer, even when accounting for demographics and tumor characteristics. To address these disparities, effective interventions are needed that account for the social and environmental contexts in which cancer patients live and can access care. Table 1: Odds Ratios for Later Stage at Presentation with Breast Cancer by Different Types of Residential Segregation Model 1: Economic segregation (high-income vs low-income) Model 2: NHB vs NHW segregation Model 3: NHB and economic segregation (low-income NHB vs high-income NHW) Model 4: Hispanic vs NHW segregation Model 5: Hispanic and economic segregation (low-income Hispanics vs. high-income NHW) Q1: Most disadvantaged neighborhoods; Q4: Reference: most advantaged neighborhoods. *p &amp;lt; 0.05 Citation Format: Alexandra Hernandez, Brianna L Cohen, Ashly Westrick, Cheyenne Thompson, Susan Kesmodel, Neha Goel. The Impact of Structural Racism on Breast Cancer Stage at Presentation [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD1-01.</jats:p

Abstract PD1-01: The Impact of Structural Racism on Breast Cancer Stage at Presentation

Abstract Background: Despite advances in diagnosis and treatment, racial and economic disparities in breast cancer-specific survival persist and this is exacerbated by later stage at presentation. It is essential to assess the factors that contribute to later stage at presentation to target racial and socioeconomic disparities in breast cancer mortality. The objective of this study was to analyze the effect of neighborhood socioeconomic status (SES) and race/ethnicity, as measured by the Index of Concentration at the Extremes (ICE), on breast cancer stage at presentation in a diverse metropolitan area that mirrors the projected demographics of many US regions. Methods: Patients treated at our medical campus, comprised of a safety-net hospital and an academic cancer center, with stage I-IV breast cancer from 2005-2017 were identified from our tumor registry. Census tracts were used as neighborhood proxies. Using 5-year estimates from the American Community Survey, 5 ICE variables were computed: economic (high vs. low), race/ethnicity (non-Hispanic White (NHW) vs. non-Hispanic Black (NHB) and NHW vs. Hispanic) and racialized economic (low-income NHB vs high-income NHW and low-income Hispanics vs. high-income NHW) segregation. ICE uniquely captures spatial economic and racial/ethnic segregation by mapping social inequality not otherwise captured by evaluating a population of a specific socioeconomic level or belonging to a particular racial/ethnic group. We used five separate models based on each of the ICE variables to evaluate economic and racial/ethnic segregation. Model 1 captures economic segregation (high vs. low), Model 2 captures racial segregation (NHB vs. NHW), Model 3 evaluates racialized economic segregation (low-income NHB vs high-income NHW), Model 4 captures segregation by Hispanic ethnicity (Hispanic vs. Non-Hispanic), and Model 5 captures ethnic and economic segregation (low-income Hispanics vs. high-income NHW). Our main outcome was breast cancer stage at presentation categorized as early (Stage I and II) vs. late (Stage III and IV) disease. All models controlled for the following covariates: race/ethnicity, age, insurance status, tumor subtype, and comorbidities including hypertension, diabetes, coronary artery disease, and hyperlipidemia. Results: The study population included 6,145 breast cancer patients. 52.6% were Hispanic, 26.3% were NHW, and 17.2% were NHB. Those living in the most economically marginalized neighborhoods (Quartiles 1 and 2) had significantly increased odds of presenting with later stage disease [ORQ1 1.36 (1.13-1.64), ORQ2 1.43 (1.18-1.75); p< 0.05]. Those living in the most racial/ethnic and economically marginalized neighborhoods (Quartile 1 of Models 3 and 5) had statistically significantly increased odds of presenting with later stage after controlling for all covariates compared to a NHW living in more economically advantaged neighborhoods [ORModel3 1.55 (1.21-1.99), ORModel5 1.43 (1.11-1.85); p< 0.05]. Conclusions: This study is the first to evaluate stage at presentation by ICE, which allows us to uniquely evaluate how residential racial and economic segregation may influence breast cancer disparities. Our study shows that patients in the most economically and racial/ethnically marginalized neighborhoods were more likely to present with later stage disease. This suggests that structural racism is influencing stage at presentation, and therefore effecting racial and economic disparities in breast cancer, even when accounting for demographics and tumor characteristics. To address these disparities, effective interventions are needed that account for the social and environmental contexts in which cancer patients live and can access care. Table 1: Odds Ratios for Later Stage at Presentation with Breast Cancer by Different Types of Residential Segregation Model 1: Economic segregation (high-income vs low-income) Model 2: NHB vs NHW segregation Model 3: NHB and economic segregation (low-income NHB vs high-income NHW) Model 4: Hispanic vs NHW segregation Model 5: Hispanic and economic segregation (low-income Hispanics vs. high-income NHW) Q1: Most disadvantaged neighborhoods; Q4: Reference: most advantaged neighborhoods. *p < 0.05 Citation Format: Alexandra Hernandez, Brianna L Cohen, Ashly Westrick, Cheyenne Thompson, Susan Kesmodel, Neha Goel. The Impact of Structural Racism on Breast Cancer Stage at Presentation [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD1-01

Structural racism and breast cancer stage at presentation in a South Florida majority-minority population: a retrospective studyResearch in context

Background: Residential segregation, both economic, racial and ethnic, is a social determinant of health that contributes to disparities in breast cancer outcomes. The objective of this study was to examine the association of economic and racial and ethnic residential segregation, as measured by the Index of Concentration at the Extremes (ICE), with breast cancer stage at presentation. Methods: In this retrospective two-institution study, we included patients with stage I-IV breast cancer from 2005 to 2017. Using five-year estimates from the American Community Survey (2009–2013), five ICE variables were computed to create five models, controlling for economic segregation, Non-Hispanic Black (NHB) segregation, NHB/economic segregation, Hispanic segregation, and Hispanic/economic segregation. Multi-level logistic regression models determined the association between economic and racial segregation on breast cancer stage at presentation. Findings: 4898 patients were included: 56% Hispanic, 27% Non-Hispanic White, 17% NHB. Those living in the most economically marginalised neighbourhoods [by quartiles (Q)] [ORQ1 1.38 (95% CI: 1.14–1.68), p < 0.05, majority NHB neighbourhoods [ORQ11.51 (95% CI: 1.01–2.27)], majority Hispanic neighbourhoods [ORQ1 1.29 (95% CI: 1.06–1.56)], the most NHB and economically segregated neighbourhoods [NHB and economic: ORQ1 1.64 (95% CI: 1.28–2.09), and the most Hispanic and economically segregated neighbourhoods [Hispanic and economic: ORQ1 1.60 (95% CI: 1.24–1.68)] had significantly increased odds of presenting with later stage disease compared to the reference group in each category. Interpretation: This study, to our knowledge, is the first to evaluate stage at presentation by ICE, which allows us to evaluate the association between racial and economic residential segregation and breast cancer disparities. Our findings suggest that structural racism influences stage at presentation. To address these disparities, effective interventions are needed to account for the social and environmental contexts in which cancer patients live and can access care. Funding: Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R37CA288502. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The research was also supported by a University of Miami School of Medicine DREAM Scholar Award, a NIH/NCI T32CA211034, an American Surgical Association Fellowship Award, a Breast Cancer Research Foundation, an ASCO Career Development Award, a Florida Department of Health Bankhead Cole Cancer Research Program, a NIH/NCI 5P30 240139-02 Sylvester Cancer Control Support Grant Transdisciplinary Pilot Grant, and a NIH/NCI K12CA226330