Health and Justice最新文献

{"title":"Peer support services for individuals with health-related needs reentering the community after incarceration: a scoping review of program elements and outcomes.","authors":"Peter Treitler, Vincent DiGioia-Laird, Brooke Long","doi":"10.1186/s40352-025-00358-0","DOIUrl":"10.1186/s40352-025-00358-0","url":null,"abstract":"<p><strong>Background: </strong>Peer support services (PSS) have become increasingly formalized in many healthcare settings. While use of PSS in the criminal-legal space is expanding, no comprehensive reviews of program designs and outcomes are available to characterize current approaches. This scoping review sought to identify PSS models for individuals with health-related needs transitioning from incarceration to the community and summarize key features and outcomes related to the models.</p><p><strong>Results: </strong>A search of PubMed, PsycInfo, Web of Science, National Criminal Justice Reference Service, Criminal Justice Abstracts, Criminal Justice Database, Embase, CINAHL, and Social Services Abstracts databases resulted in a total of 66 studies that described 49 unique PSS programs delivered at re-entry. Fifty-six of these studies also reported on implementation factors and program outcomes. Programs varied in terms of target populations, staffing, services offered, setting, and duration. Quantitative outcomes most commonly surrounded linkage to services, substance use, mental health, HIV, and recidivism. Lived experience of peers, extensive engagement with participants, participant-centered support, and collaboration between agencies were highlighted as key factors that supported program implementation, while challenges largely related to staffing and participant outreach.</p><p><strong>Conclusions: </strong>The heterogeneity in program design and the mixed results in both quantitative and qualitative outcomes likely reflect the need for programs to be responsive to the specific communities served. This review highlights innovative approaches within the growing use of PSS to support the health-related needs of individuals reentering the community after incarceration and may guide future research, design, implementation, and evaluation of such programs in the criminal-legal space.</p>","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"51"},"PeriodicalIF":2.6,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12357432/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144859745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A longitudinal mixed methods social network analysis to evaluate a peer-led housing program for older men returning from incarceration: Study protocol & pre-implementation results.","authors":"Brandy F Henry, Derek A Kreager, Joy Gray, Kristina Brant, Gary Zajac, Divine Lipscomb, Sarah Brothers, David R Schaefer, Nicolette Bardele, Andrea Hazelwood","doi":"10.1186/s40352-025-00362-4","DOIUrl":"10.1186/s40352-025-00362-4","url":null,"abstract":"<p><strong>Background: </strong>We describe a longitudinal mixed methods program evaluation protocol for a novel peer-led housing program for older men transitioning from prison to the community after completing long sentences of incarceration. The program departs from traditional community corrections models by providing peer-run housing designed to build and enhance peer and community social ties. This previously untested program relies on the principles of network alteration and provides a case study for examining interpersonal mechanisms underlying behavioral health and justice related outcomes.</p><p><strong>Methods: </strong>We use mixed methods and longitudinal social network analysis to evaluate the program, while also applying implementation science to document program development. We focus our evaluation on key health and social outcomes, including mental health, substance use, stress, health risk behaviors, well-being, financial security, housing, and recidivism. With longitudinal surveys, we collect (1) dynamic network data of resident and staff relationships and (2) behavioral health/social data of participants. We also administer longitudinal resident and staff interviews. Resident interviews focus on interpersonal relationships and reentry experiences, while staff interviews describe program implementation. We apply longitudinal statistical models to complete (i.e., sociocentric) network data within the house to examine how dynamic network properties connect to changes in residents' health, behavioral, and social outcomes. We integrate longitudinal survey, individual-level (i.e., egocentric) network, and qualitative data to understand how the program works. To evaluate program impacts for long-term health and social outcomes, we use an untreated matched sample to compare 6- and 12-months post-prison release outcomes using administrative data related to rearrest/reincarceration and behavioral health.</p><p><strong>Pre-implementation results: </strong>We use a logic model to present and organize pre-implementation results from interviews with program staff and peer mentors. Our results describe program design and intended goals, while highlighting how the program is rooted in principles of peer support, trauma-informed care, and restorative justice to address unique stressors of incarceration to foster responsibility and facilitate reintegration.</p><p><strong>Discussion: </strong>Community program evaluation research allows us to document real-world contextual factors that may drive intervention effectiveness. Results of the mixed methods evaluation will provide a comprehensive understanding of one network-based program's ability to support health and social outcomes of older, previously incarcerated men. Results may inform future reentry services.</p>","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"52"},"PeriodicalIF":2.6,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12357394/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144859744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health & justice 10th anniversary: looking ahead after a decade of progress.","authors":"Faye S Taxman, Lauren Brinkley-Rubinstein, Lior Gideon, Wendy P Guastaferro","doi":"10.1186/s40352-025-00357-1","DOIUrl":"10.1186/s40352-025-00357-1","url":null,"abstract":"","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"50"},"PeriodicalIF":2.6,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12323283/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144785522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Outcomes of a community sector model of reintegration for people with complex needs: a mixed-methods study.","authors":"Ruth McCausland, Rebecca Reeve, Mindy Sotiri, Lucy Phelan, Vendula Belackova, Sophie Russell","doi":"10.1186/s40352-025-00352-6","DOIUrl":"10.1186/s40352-025-00352-6","url":null,"abstract":"","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"49"},"PeriodicalIF":2.6,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12323006/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144785523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The undercounting of Indigenous Māori imprisoned by the New Zealand carceral state: a national record study.","authors":"Paula Toko King, Frederieke Sanne Petrović-van der Deen, Melissa McLeod, Ricci Harris, Cheryl Davies, Donna Cormack, Tristram Ingham, Bernadette Jones, Bridget Robson, Natalie Paki Paki, Gabrielle Baker, Belinda Tuari-Toma, Jeannine Stairmand, Marama Cole, Tīria Pehi, Julia Carr, Christopher Kemp, Marshall H Chin, Ruth Cunningham","doi":"10.1186/s40352-025-00355-3","DOIUrl":"10.1186/s40352-025-00355-3","url":null,"abstract":"<p><strong>Background: </strong>Indigenous Māori are imprisoned on a mass scale by the nation-state currently known as New Zealand, driven by racialised inequities that occur across the criminal legal system and a rapidly expanding carceral state. Lack of reliable data limits the ability to monitor and evaluate the health and disability impacts of imprisonment on Māori. We examined ethnicity data quality; specifically, potential miscounting of Māori in prison. All individuals who experienced at least one night of imprisonment between 2018 and 2021 were selected from the Department of Corrections (Corrections) data in the Stats NZ Integrated Data Infrastructure (IDI). We compared counts and proportions of Māori using two sources of ethnicity information; Corrections and IDI's core data. Within this cohort, we compared self-identified ethnicity from the 2018 Census with ethnicity recorded in Corrections data available in the IDI (via individual linkage), to assess levels of match between datasets and calculate net undercount.</p><p><strong>Results: </strong>Lesser numbers of Māori were recorded in the Corrections data compared to the IDI's core data (52% versus 57% of the study cohort), a pattern observed across all age and gender groups, and amongst those sentenced and on remand. For the linked analysis, only one third (34%) of the cohort linked to the IDI central spine had self-identified ethnicity from the 2018 Census. Of this group, 46% self-identified as Māori ethnicity. When this information was compared to ethnicity information reported by Corrections for the same individuals, there was a 12% undercount of Māori in Corrections data. The net undercount of Māori was 6%, equating to at least an extra 405 Māori imprisoned than what is publicly reported by government.</p><p><strong>Conclusions: </strong>Reliable data inclusive of high-quality ethnicity data are critical for understanding and monitoring Māori health in terms of resource allocation, policy decisions, and performance of health and disability services for Māori imprisoned in NZ. Systemic undercounting of Māori in prisons is a breach of Indigenous rights to monitor and evaluate impacts of government actions and inactions for Māori. We do not accept the inevitability of prisons but whilst prisons exist, and until there are no prisons left on Māori whenua (lands), an all-of-government approach to prioritisation of high-quality ethnicity data across the criminal legal system that meets obligations to Te Tiriti o Waitangi and international human rights instruments is urgently required.</p>","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"48"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12315448/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144761618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An experimental investigation of federal messaging on public support for enforcement- and treatment-based approaches for opioid overdose prevention in South Carolina.","authors":"Lídia Gual-Gonzalez, Hunter M Boehme, Peter Leasure, Pieter A Baker, Melissa S Nolan","doi":"10.1186/s40352-025-00356-2","DOIUrl":"10.1186/s40352-025-00356-2","url":null,"abstract":"<p><strong>Background: </strong>As the opioid overdose crisis continues to produce excessive morbidity and mortality in the United States, government agencies have applied various approaches to prevent overdoses, including law-enforcement efforts (e.g., arresting people who use drugs, interrupting drug traffickers, etc.) and treatment-based approaches (e.g., naloxone, medications for opioid use disorder, etc.). Public perception and support of these approaches are relevant for informing policy, allocating resources, and effectively implementing community interventions to prevent drug-related harms.</p><p><strong>Methods: </strong>Using an embedded informational survey design, we experimentally assessed whether public support for strategies to prevent overdose in South Carolina is influenced by language from federal agencies describing treatment- or enforcement-based approaches. Respondents were randomly assigned to one of three groups: (1) enforcement -based approach, (2) treatment-based approach, or (3) the control condition. Those assigned to experimental groups were presented with statistics on drug overdose deaths, followed by an informational prompt with language about overdose prevention approaches from either DEA (enforcement) or NIH (treatment), while the control group received no informational prompt.</p><p><strong>Results: </strong>Findings from a sample of 4,675 respondents indicated that those assigned the DEA prompt were significantly more likely to support enforcement-based approaches in arresting drug traffickers and people who use drugs (AME = 0.060, p < 0.001). On the other hand, those assigned to the NIH prompt were significantly more likely to agree that both law enforcement (AME = 0.065, p < 0.0001) and clinicians (AME = 0.044, p < 0.05) are capable of preventing drug overdose deaths.</p><p><strong>Conclusions: </strong>These findings shed light on public perceptions of approaches to addressing the opioid epidemic and limited modifiability when presented with language from federal agencies. This may inform future research, practice, and/or policy aiming to maintain public safety while also providing treatment options to people who use drugs in order to reduce overdose deaths.</p>","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"46"},"PeriodicalIF":2.6,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12291324/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144709271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overdose education and naloxone distribution in jails: Examining the impact of the Communities That HEAL intervention in 4 states.","authors":"Timothy Hunt, Carrie B Oser, Peter D Friedmann, Nicole Mack, Peter Balvanz, Bridget Freisthler, Redonna K Chandler, Karli Hochstatter, Daniel R Harris, LaShawn Glasgow, Lauren D'Costa, Mary R Russo, Barry Eggleston, Arnie Aldridge, Paul Bellair, Allyson G Cogan, James L David, Nabila El-Bassel, Dawn Goddard-Eckrich, Steve Gomori, Holly Hagan, Steve Hanson, JaNae Holloway, Elizabeth N Kinnard, Charlie Knott, Michael W Konstan, Sharon L Walsh, Patricia A LeBaron, Michael S Lyons, Margaret McGladrey, Joan Papp, Sean M Murphy, Sandra Springer, Emmanuel Oga, Michele Staton, Elizabeth Schady, Fernando Montero, Hilary L Surratt, Danelle Stevens-Watkins, John Winhusen, Gary A Zarkin, Greer A Hamilton, Joel G Sprunger","doi":"10.1186/s40352-025-00353-5","DOIUrl":"10.1186/s40352-025-00353-5","url":null,"abstract":"","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"47"},"PeriodicalIF":2.6,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12296605/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144709272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing antiracist research: addressing health inequities among juvenile legal system-impacted youth using Public Health Critical Race Praxis.","authors":"Emily Dauria, Johanna Folk, Sarah Godoy, Evan Holloway, Jeanne McPhee, David Hoskins, Ali Yurasek, Katharine Galbraith, Sheridan Sweet, Eraka Bath, Marina Tolou-Shams","doi":"10.1186/s40352-025-00346-4","DOIUrl":"10.1186/s40352-025-00346-4","url":null,"abstract":"<p><p>Youth impacted by the juvenile legal system (JLS) disproportionately experience health and healthcare inequities, including those related to substance use, mental health, and sexual and reproductive health. Structural racism is a primary driver of JLS systems contact and health inequities, interacting with other forms of oppression to negatively impact minoritized youth at every step of the JLS process. Despite the growing unmet need for tailored, empirically-driven programmatic and policy solutions, research focused on this multiply marginalized group often fails to explore or address racism as a factor shaping these inequities and identifying relevant health solutions. We use the Public Health Critical Race Praxis to offer recommendations for improving data collection and quality in longitudinal research addressing health inequities among JLS-impacted youth and families. Recommendations stem from a team of federally funded researchers and clinicians representing different career development stages, training backgrounds, and lived experiences, all of whom are working to address health inequities. Given the challenges JLS-impacted youth face and the significant need for rigorous research illuminating their health outcome and service needs, clinical and translational researchers would benefit from guidance on how to apply antiracist principles and research strategies to successfully engage JLS-impacted youth and families in longitudinal studies.</p>","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"45"},"PeriodicalIF":3.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12243205/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144592534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Site engagement in implementation research: Introducing SEAMLIS as a conceptual and measurement framework.","authors":"Sarah D Jones, John P Bartkowski, Steven Belenko, Jennifer E Becan, Faye S Taxman, Gail A Wasserman, Gregory A Aarons, Larkin S McReynolds, Cheyenne Dolbear, Xiaohe Xu","doi":"10.1186/s40352-025-00349-1","DOIUrl":"10.1186/s40352-025-00349-1","url":null,"abstract":"<p><strong>Background: </strong>Multisite implementation research in justice and health settings often does not systematically assess differential degrees of project involvement among participating sites, despite its implications for both research and the intervention. Tracking organization and participant involvement across sites, when attempted, has typically entailed the use of discrete and sometimes disjointed fidelity measures that may not accurately reflect engagement with a project. This article advances a more comprehensive and sophisticated conceptual model for measuring and monitoring site engagement. This conceptual model was developed from a literature review of the implementation science and related disciplines while being informed by multisite project implementation experience. We propose the Site Engagement Activity Model Leveraging Implementation Science (SEAMLIS), a conceptual model that holistically identifies the breadth of agency participation (diverse activities such as trainings, meetings, etc.) and duration of site engagement (participation levels from inception to completion) to be measured, assessed, and reported.</p><p><strong>Case presentation: </strong>We also describe Juvenile Justice Translational Research on Interventions for Adolescents in the Legal System (JJ-TRIALS), a 36-site implementation research project, as an illustrative case example of our proposed model. We then operationalize all proposed domains and subdomains and specify key measures from the project.</p><p><strong>Conclusions: </strong>We provide analytical recommendations for the application and future research of the proposed model in health and justice settings. In multisite implementation research, site engagement could be fruitfully used as an independent, dependent, or intervening (moderating or mediating) variable.</p><p><strong>Trial registration: </strong>NCT02672150, February 3, 2016.</p>","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"44"},"PeriodicalIF":3.0,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12228212/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144567956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personality predicts internalizing symptoms and quality of life in police cadets: a comparison of artificial intelligence and parametric approaches.","authors":"Macià Buades-Rotger, Ana Martínez Catena, Guillermo Recio, Mireia Cano Gallent, Jordi Niñerola I Maymí, Anna Figueras Masip, David Gallardo-Pujol","doi":"10.1186/s40352-025-00351-7","DOIUrl":"10.1186/s40352-025-00351-7","url":null,"abstract":"<p><strong>Background: </strong>Police cadets undergo persistent and elevated stress due to continuous training and evaluation. Identifying resilience and risk factors in this population can thus crucially inform management decisions within the police force. Here, in two large cohorts of police cadets (n = 1069, 30% women and n = 1377, 35% women) we investigated whether broad personality traits could predict internalizing symptoms (somatization, depression, and anxiety) as well as mental health-related quality of life (MHRQoL). Moreover, we compared seven popular artificial intelligence and linear regression models (Elastic Net, General Linear Model, Lasso Regression, Neural Networks, Random Forests, and Support Vector Regression) in predicting MHRQoL as a function of all other variables.</p><p><strong>Results: </strong>A Random Forest accounted for about half of the observed variance in MHRQoL, and outperformed all other models by up to 12% in an out-of-sample cross-validation. In all analyses, emotional stability emerged as the primary personality trait linked to MHRQoL, with anxiety and somatization symptoms partially mediating this relationship.</p><p><strong>Conclusions: </strong>Our findings delineate the personality factors that best predict internalizing symptoms and MHRQoL among cadets, and tentatively suggest that Random Forest models might be a powerful forecasting tool in police management.</p>","PeriodicalId":37843,"journal":{"name":"Health and Justice","volume":"13 1","pages":"43"},"PeriodicalIF":3.0,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12228195/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144561434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}