Journal of Rural Health最新文献

{"title":"Employing Collaborative Survey Development and Mixed-Mode Strategies to Facilitate Data Collection Among Those Living in Rural Communities","authors":"Lisa A. Brenner,&nbsp;Nazanin Bahraini,&nbsp;Christina R. LaValle,&nbsp;Molly E. Penzenik,&nbsp;Kelly A. Stearns-Yoder,&nbsp;Alexandra L. Schneider,&nbsp;Joanna R. Sells,&nbsp;Vincent Welch,&nbsp;Claire Hoffmire","doi":"10.1111/jrh.70232","DOIUrl":"https://doi.org/10.1111/jrh.70232","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Among those living in rural areas, knowledge regarding best community-based strategies to prevent negative health outcomes, including suicide, remains limited. A survey was collaboratively developed regarding individual- and community-based suicide risk and protective factors, and Veterans and non-Veterans living in rural communities were outreached. Mixed-mode strategies were employed to improve response rates and reduce non-response bias.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Recruitment letters were mailed to a random address-based sample of 45,000 households in rural Mississippi (MS), New Mexico (NM), and Oregon (OR) to achieve 3,600 responses assuming an 8% yield rate. Recruitment prioritized survey completion by Veterans. Letters encouraged survey completion online, however, paper-and-pencil surveys were also mailed. Enhanced recruitment efforts to increase yield included weekly emails, telephone reminders, increased incentives, letters to those who started but did not complete, and Spanish language paper-and-pencil surveys to members of NM households.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Completed surveys totaled 3,864 across the three communities; an 8.6% yield rate; resulting in a 21.7% American Association for Public Opinion Research (AAPOR) response rate. Approximately, 77% of surveys were completed online and 23% by paper-and-pencil, respectively. The distribution of completion modes was similar across communities. Increasing email frequency and post-incentives were most effective for boosting survey completion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Input from rural communities is needed to facilitate innovative, community-driven suicide-prevention. Mixed-mode strategies enabled successful recruitment to obtain vital information regarding community-specific suicide risk and protective factors. Using paper-based methods may be important in rural areas to account for limited internet infrastructure and accommodate traditional communication preferences.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149259136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rural Hospital AI Use and Evaluation","authors":"Josiah A. Cruikshank,&nbsp;Brian E. Whitacre,&nbsp;Alison F. Davis","doi":"10.1111/jrh.70237","DOIUrl":"https://doi.org/10.1111/jrh.70237","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Hospital use of predictive artificial intelligence (AI) is increasing. This study examines rural–urban differences in the adoption, use, and evaluation of predictive AI by US hospitals in 2023. It then assesses the characteristics associated with AI adoption and evaluation among all rural hospitals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyze the 2023 American Hospital Association's Information Technology Supplement, which was the first to include questions on predictive model use. Adjusted Wald tests assess differences in AI adoption between rural and urban hospitals, and in categories of use and evaluation of such models for those that do adopt. We then use weighted multivariate logistic regressions on a subset of rural-only hospitals to document associations between predictive model adoption/evaluation and hospital characteristics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Rural hospitals adopted and used predictive AI at substantially lower rates than urban hospitals (51% vs. 81%) in 2023. Among hospitals that adopted AI, rural facilities were less likely to evaluate their models for accuracy (59% vs. 65%) and bias (39% vs. 47%). They also relied more heavily on AI tools developed by their electronic health record vendor. Regression analyses show that system membership and stronger financial performance were positively associated with AI adoption, while Critical Access Hospital and for-profit status were negatively associated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Rural hospitals remain constrained in their ability to adopt, use, and evaluate AI tools, driven largely by resource limitations. Targeted policies may be needed to ensure rural hospitals appropriately implement and evaluate AI systems as they become increasingly integral to hospital operation and clinical care.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149259461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rural–Urban Differences in Out-of-Pocket Spending Associated With Colonoscopies Among US Residents Aged 40 and Older","authors":"Ingrid Jacobson,&nbsp;Sean Kelso,&nbsp;Anika Eldien,&nbsp;Brooke Gully,&nbsp;Kenneth Huang,&nbsp;Aquino Williams","doi":"10.1111/jrh.70236","DOIUrl":"https://doi.org/10.1111/jrh.70236","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Colorectal cancer (CRC) remains the second most common cause of death in the United States. Morbidity and mortality of CRC are significantly reduced by early detection through colonoscopy, but rural screening rates are lower (and mortality rates higher) than urban rates. Understanding factors influencing screening adherence in rural populations is crucial for reducing disparities in cancer mortality. This study examines differences in out-of-pocket colonoscopy payment category between rural and urban populations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This cross-sectional study used data from the National Health Interview Survey 2019 and 2021. Our main exposure was rurality, and our main outcome was how much the individual paid out of pocket for the most recent colonoscopy: none, part, or all of the cost. We estimated a multinomial logistic regression model, adjusted for sociodemographic covariates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Rural residents were more likely than urban residents to report paying all of the cost (4.12% vs. 3.01%, <i>p</i> = 0.042). Sociodemographic covariates were differentially associated with out-of-pocket colonoscopy spending levels; compared to non-Hispanic whites, significantly more Hispanic individuals reported paying all of the cost (OR: 1.54, 95% CI: 1.03–2.30), and being uninsured or having other or unknown insurance status versus having private insurance was a strong predictor of higher out-of-pocket cost.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We found a modest but statistically significant rural–urban difference in patient-reported out-of-pocket colonoscopy payment. Variation in patient financial responsibility may represent part of the broader access barriers experienced by rural populations. Initiatives directed towards reducing the financial burden of colonoscopies and improving access to alternative screening modalities may help reduce disparities and improve rural outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149259462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"People Living With Dementia in Rural Areas are Most Likely to Report Unmet Service Needs in Home- and Community-Based Services in the United States","authors":"Romil R. Parikh,&nbsp;Eric Jutkowitz,&nbsp;Jack M. Wolf,&nbsp;Benjamin W. Langworthy,&nbsp;Chanee D. Fabius,&nbsp;Stephanie Giordano,&nbsp;Tetyana P. Shippee","doi":"10.1111/jrh.70230","DOIUrl":"https://doi.org/10.1111/jrh.70230","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Most older adults prefer aging in place, for which home- and community-based services (HCBS) play an essential role. However, it is unknown whether rural-urban differences in unmet HCBS needs differ by dementia status, which is an important evidence gap to develop targeted interventions to improve HCBS access. Therefore, we evaluated associations of rural-urban continuum (RUCA classification) with consumer-reported unmet HCBS needs by dementia status.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyzed data from the National Core Indicators- Aging &amp; Disability survey (2016-2019; 14,645 community-dwelling consumers; age, ≥65years; 23 states) using logistic regression, comparing adjusted odds ratios (OR) of consumer-reported unmet HCBS needs across rural-urban continuum, stratified by dementia.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Among people living with dementia (PLWD, n = 2438), compared to metropolitan areas, prevalence of unmet HCBS needs was greater in micropolitan areas (35.4% versus 30.7% consumers; OR, 1.32, 95% CI, 0.98–1.77), small towns (36.3% consumers; OR, 1.44, 95% CI, 0.97–2.13), and rural areas (44.8% consumers; OR, 1.83, 95% CI, 1.11–3.04). These associations were reversed in those without dementia (n = 12,207). Compared with metropolitan areas, prevalence of unmet HCBS needs was lower among those in micropolitan areas (28.7% vs 31.4% consumers; OR, 0.82; 95% CI 0.72–0.93), small towns (29.3%; OR 0.85; 95% CI 0.73–1.00) and rural areas (25.4%; OR, 0.73, 95% CI, 0.58-0.90).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Among PLWD, unmet HCBS needs are significantly greater in rural areas. These findings highlight the critical need for dementia-capable HCBS in rural areas to improve equitable access to these essential services among PLWD.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70230","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149258969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Snapshots From the “Edge” of Recovery: Using Photovoice for Community-Based Participatory Research on Addictions in Rural Areas","authors":"Marissa D. Abram,&nbsp;Courtney Swinkels,&nbsp;Kari Bail,&nbsp;Chrisann Newransky,&nbsp;Dalton Barrett,&nbsp;Lemuel Scott,&nbsp;Devon Noonan","doi":"10.1111/jrh.70233","DOIUrl":"10.1111/jrh.70233","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To examine how multilevel factors shape substance use recovery in a rural North Carolina county and influence access and engagement with treatment and recovery services.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This qualitative participatory study used Photovoice and semi-structured interviews with adults with lived experience of substance use recruited through local harm reduction and recovery organizations in rural North Carolina.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Four interrelated themes emerged: (1) place-based safety, in which rural environments functioned as both protective and constraining; (2) trust-centered care as foundational to engagement; (3) recovery as self-determined and sustained through supportive relationships; and (4) punitive and fragmented systems that destabilized recovery trajectories.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Recovery in rural contexts is relational, place-based, and structurally mediated. Strengthening rural recovery systems requires community-informed approaches that reduce structural barriers and expand accessible, person-centered care.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149247170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rethinking Rurality in Graduate Medical Education","authors":"Mukesh Adhikari,&nbsp;Raquel Davis,&nbsp;George M. Holmes,&nbsp;Lori Rodefeld,&nbsp;Emily M. Hawes","doi":"10.1111/jrh.70238","DOIUrl":"10.1111/jrh.70238","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Graduate medical education policy relies on rural classification to determine eligibility for rural training programs. This study aimed to assess whether hospitals classified by the Federal Office of Rural Health Policy (FORHP) as rural, but located in metropolitan counties, more closely resemble hospitals in non-metropolitan counties than other hospitals in metropolitan counties in terms of hospital and community characteristics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This was a cross-sectional, observational study. Our study sample consisted of 4686 acute general hospitals in the United States from a 2024 publicly available hospital list. We conducted pairwise comparisons of hospital characteristics from 2024 Medicare cost report data and community characteristics from the Agency for Healthcare Research and Quality 2020 Social Determinants of Health Database and the 2024 American Medical Association Master file between FORHP-rural metropolitan hospitals and each comparison group: metropolitan non-FORHP-rural hospitals and non-metropolitan hospitals. Our main similarity analysis estimated pairwise logistic regression models predicting FORHP-rural metropolitan classification using community characteristics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>We classified 459 hospitals as FORHP-rural metropolitan hospitals. Our pairwise comparisons showed that hospital and community characteristics are similar to non-metropolitan hospital characteristics but significantly differ from metropolitan non-rural hospital characteristics. Predicted probability distributions for FORHP-rural metropolitan and non-metropolitan hospitals showed substantially greater overlap than distributions for FORHP-rural metropolitan and metropolitan non-FORHP-rural hospitals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>FORHP's tract-level rural definition identifies a distinct group of hospitals. Expanding the definition of rural could unlock federal funding for physician training for nearly 500 additional US hospitals.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149247191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rural Versus Urban Distribution of Obstetrics and Gynecology Residency Training and Associated Rural Community Characteristics","authors":"Ryan Spencer,&nbsp;Mukesh Adhikari,&nbsp;Lori Rodefeld,&nbsp;Laney McDougal,&nbsp;AnnaMarie Connolly,&nbsp;Emily M. Hawes","doi":"10.1111/jrh.70231","DOIUrl":"10.1111/jrh.70231","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To assess the distribution of OB/GYN residency program training sites and compare community characteristics in rural counties with and without training sites.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Using data from the Accreditation Council for Graduate Medical Education (ACGME), the locations of all accredited obstetrician/gynecologist (OB/GYN) residency training sites for the 2023–2024 academic year (AY 23–24) were geocoded. They were classified as rural or urban according to the Federal Office of Rural Health Policy and Core-Based Statistical Area categories. The percentage of time spent training in rural areas was calculated for each program. Programs with at least 50% rural training were also identified. Bivariate analyses, including Pearson's chi-square tests and Wilcoxon rank-sum tests, were conducted using the Area Health Resource File (AHRF, 2022–23) to compare community characteristics between rural counties with and without OB/GYN residency training sites.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;In AY 23–24, there were 294 OB/GYN residency programs utilizing 1052 training sites. There were 19 programs (6.5% of programs) offering a total of 25 training sites in rural areas (2.4% of all training sites). In programs that offered rural training sites, the rural experience accounted for an average of 4.8% of total training time in those programs. Regarding community characteristics, rural counties that did not have a residency training site were less populated than rural counties with a training site (15,742 vs. 50,886; &lt;i&gt;p&lt;/i&gt; &lt; 0.001). Compared with rural counties that had an OB/GYN training site, rural counties without a training site had a higher proportion of uninsured people less than 65 years old (8.0% vs. 11.5%; &lt;i&gt;p&lt;/i&gt; &lt; 0.001), a higher proportion of uninsured people less than 19 years old (3.8% vs. 6.4%; &lt;i&gt;p&lt;/i&gt; &lt; 0.001), lower median number of primary care physicians (40.6 vs. 55.1 per 100,000; &lt;i&gt;p&lt;/i&gt; = 0.005), fewer median number of psychiatrists (0.0 vs. 2.5 per 100,000; &lt;i&gt;p&lt;/i&gt; &lt; 0.001), and were more likely for the entire county be a mental Health Professional Shortage Area (HPSA; 35.3% vs. 69.0%; &lt;i&gt;p&lt;/i&gt;&lt;0.001).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;OB/GYN residency training is highly urbanized. There are significantly less favorable health care access characteristics in rural counties without an OB/GYN residency training site compared to those with residency training sites. The findings identify rural communities without OB/GYN training sites t","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13678571/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149221063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population-Based Rates of Youth Suicide-Related Emergency Department Encounters by Rural-Urban Status","authors":"Laura M. Prichett,&nbsp;Yurika Tarui,&nbsp;Susan De Luca","doi":"10.1111/jrh.70235","DOIUrl":"10.1111/jrh.70235","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To compare population-based rates and mechanisms of suicide-related emergency department (ED) encounters among rural and urban youth in Kentucky and Arkansas.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a population-based cross-sectional study using 2018–2021 Healthcare Cost and Utilization Project State Emergency Department Databases linked with U.S. Census population estimates. Suicide-related ED encounters among youth aged 10–19 years were identified using diagnosis codes for suicidal ideation, suicide attempt, and intentional self-harm. Counties were classified using the National Center for Health Statistics urban-rural classification scheme. We calculated rates per 10,000 youth and rural-to-urban incidence rate ratios (IRRs) with 95% confidence intervals (CIs).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Among 27,098 suicide-related ED encounters, 11,243 (41.5%) occurred among rural youth. Rural youth had a 14% higher population-based encounter rate than urban youth (IRR = 1.14; 95% CI, 1.12–1.17). Rural–urban differences were greatest among youth aged 10–14 years (IRR = 1.26; 95% CI, 1.21–1.31), White youth (IRR = 1.21; 95% CI, 1.18–1.24), and females (IRR = 1.17; 95% CI, 1.13–1.20). Rates were lower among rural than urban Black youth (IRR = 0.86; 95% CI, 0.80–0.92). Mechanisms were similar across settings; suicidal ideation without self-harm accounted for approximately 72% of encounters in both groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Rural youth experienced higher rates of suicide-related ED encounters, particularly younger adolescents and females. Strengthening early identification and access to crisis and outpatient mental health services may help prevent rural youth from progressing to psychiatric emergencies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149221042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Breast Tomosynthesis Use, Facility Mammography Volume, and Timely Follow-Up After Abnormal Screening Mammograms in Appalachia, United States","authors":"Silas Selorm Daniels-Donkor,&nbsp;Fabian T. Camacho,&nbsp;Gloribel Bonilla,&nbsp;Emma M. Mitchell,&nbsp;Chris Louis,&nbsp;Roger T. Anderson","doi":"10.1111/jrh.70229","DOIUrl":"10.1111/jrh.70229","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Diagnostic follow-up times after abnormal screening mammography vary widely across facilities. However, whether the use of digital breast tomosynthesis (DBT) is associated with follow-up timeliness, independent of facility context factors, remains unclear.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objective&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To evaluate the extent to which facility mammography volume accounts for the association between facility-level DBT use proportion and recall delay after abnormal screening mammography in Appalachia.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We linked 2016–2018 Medicare fee-for-service claims to facility survey data from screening facilities in five Appalachian states (KY, OH, PA, VA, and WV). Recall delay was modeled using linear mixed-effects models with random intercepts for facility and beneficiary. The models adjusted for DBT use proportion, capacity score, age, race, dual Medicare–Medicaid eligibility, deprivation, rurality, and stand-alone status. To assess whether facility mammography volume accounted for the association between DBT use proportion and recall delay, we compared two models fitted to the same analytic sample with the same covariates. The models differed only in whether facility mammography volume was included. We estimated 95% confidence intervals for the difference in the DBT coefficient using 5000 bootstrap resamples. Facility-level models and exploratory mediation analyses were conducted as complementary analyses.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;DBT use proportion was associated with higher facility mammography volume after adjustment for capacity score and facility covariates (&lt;i&gt;β&lt;/i&gt; = 0.614, 95% CI [0.170, 1.058], &lt;i&gt;p&lt;/i&gt; = 0.007). After adjustment for capacity score, a 1-SD higher facility mammography volume was associated with shorter recall delay (&lt;i&gt;β&lt;/i&gt; = −1.103 days, 95% CI [−2.074, −0.132], &lt;i&gt;p&lt;/i&gt; = 0.028). The DBT coefficient changed from −0.970 days before adding facility volume to −0.402 days after volume adjustment, corresponding to a raw coefficient change of 0.568 days (95% bootstrap CI [0.130, 1.088]). The complementary facility-level model estimated a corresponding raw coefficient change of 0.620 days (95% bootstrap CI [0.149, 1.143]). An exploratory mediation analysis adjusted for capacity score and facility covariates estimated an indirect estimate through facility mammography volume of −0.620 days (95% CI [−1.111, −0.146], &lt;i&gt;p&lt;/i&gt; = 0.004). The direct and total estimates were not statistically significant.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 ","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13656888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149170395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adult Community Perspectives on Improving Rural Youth Access to Mental Health Services: A Participatory Group Concept Mapping Study","authors":"Janessa M. Graves,&nbsp;Demetrius A. Abshire,&nbsp;Jessica L. Mackelprang,&nbsp;Kailee Parrott","doi":"10.1111/jrh.70227","DOIUrl":"10.1111/jrh.70227","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Rural youth face barriers to mental health service access, including provider shortages, stigma, geographic isolation, and financial constraints. Community-engaged approaches are essential for developing contextually appropriate solutions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used Group Concept Mapping, a participatory research method, to identify strategies for improving mental health service access for rural youth in three counties in northeastern Washington State. Adult community members participated in brainstorming, sorting, and rating potential solutions. Statements were rated on perceived impact and perceived equity dimensions and analyzed to identify thematic clusters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Analysis yielded eight thematic clusters: Youth Life Skills Development, Community-Based Training &amp; Education, Community Support Systems, Community Awareness &amp; Engagement, Mental Health Services Delivery &amp; Access, Affordability, School-Based Mental Health Services, and Capacity-Building in Schools. The Affordability cluster received the highest ratings for both impact and equity. Notably, 72.7% of statements in the Capacity-Building in Schools cluster fell in the “go-zone” (above the overall mean for both perceived impact and perceived equity). Strategies related to de-stigmatization, mental health education, and workforce development were highly rated across clusters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Rural stakeholders prioritized school-based interventions, affordability, and mental health education as key strategies to improve access to youth mental health services. Findings highlight the importance of leveraging existing community infrastructure, particularly schools, and addressing mental health workforce shortages. Ratings reflect adult perceptions; youth were not participants. Future research should include youth perspectives and evaluate the feasibility of implementing these community-identified strategies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":50060,"journal":{"name":"Journal of Rural Health","volume":"42 4","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jrh.70227","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149139041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}