JAMA Network Open最新文献

{"title":"Adherence to Follow-Up Lung Cancer Screening-A Critical Target for Intervention.","authors":"Francesca C Duncan, Matthew Triplette","doi":"10.1001/jamanetworkopen.2025.0949","DOIUrl":"https://doi.org/10.1001/jamanetworkopen.2025.0949","url":null,"abstract":"","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e250949"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lifetime and Past-Year Defensive Gun Use.","authors":"Michael D Anestis, Kimberly Burke, Sultan Altikriti, Daniel Semenza","doi":"10.1001/jamanetworkopen.2025.0807","DOIUrl":"10.1001/jamanetworkopen.2025.0807","url":null,"abstract":"<p><strong>Importance: </strong>Defensive gun use (DGU) is cited as a rationale for permissive firearm-carrying policies; however, no consensus exists on how frequently DGU occurs.</p><p><strong>Objective: </strong>To examine the frequency of DGU relative to gun violence exposure (GVE) in a sample of firearm owners drawn from a nationally representative sample of US adults.</p><p><strong>Design, setting, and participants: </strong>This survey study used data from a cross-sectional, self-reported survey administered via KnowledgePanel, a probability-based panel, between May 15 and May 28, 2024. Eligible participants were adults residing within the US reporting current firearm access who responded to DGU survey items. Data were analyzed from July to September 2024.</p><p><strong>Main outcomes and measures: </strong>Primary outcomes were 4 forms of DGU: telling a perceived threat about a firearm, showing a firearm to a perceived threat, firing in the vicinity of but not at a perceived threat, and firing at a perceived threat.</p><p><strong>Results: </strong>Among 12 822 adults invited to participate, 8647 (67.4%) read the informed consent, 8009 (92.6%) consented to participate, and 3000 (37.7%; 532 [51.1%] male; 982 [32.7%] aged ≥60 years) endorsed firearm access and responded to DGU items, including 295 Black, non-Hispanic participants (9.8%); 365 Hispanic participants (12.2%); and 2178 White, non-Hispanic participants (72.6%). DGU was rare, with 91.7% (95% CI, 90.6%-92.7%) of participants reporting no lifetime history of DGU. The most reported form of DGU was showing a firearm to a perceived threat (lifetime: 4.7%; 95% CI, 4.0%-5.5%). Less than 1% of the sample reported any form of past-year DGU. GVE was more pervasive for lifetime (eg, loss of a friend or loved one to firearm suicide: 34.4%; 95% CI, 32.7%-36.1%; hearing gunshots in neighborhood: 51.8%; 95% CI, 50.0%-53.6%) and past-year exposure (eg, loss of a friend or loved one to firearm suicide: 3.2%; 95% CI, 2.6%-3.9%; hearing gunshots in neighborhood: 32.7%; 95% CI, 31.0%-34.4%).</p><p><strong>Conclusions and relevance: </strong>In this survey of adults with firearm access, DGU was rare relative to GVE. Perceived threats may not necessitate DGU, and given the association between DGU and GVE, the consequences of DGU may be substantial. Narratives centering DGU as a consideration in firearm policies may misstate the risk profile of firearm access.</p>","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e250807"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11909608/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adherence to Annual Lung Cancer Screening and Rates of Cancer Diagnosis.","authors":"Roger Y Kim, Katharine A Rendle, Nandita Mitra, Christine Neslund-Dudas, Robert T Greenlee, Stacey A Honda, Marilyn M Schapira, Michael J Simoff, Jihyoun Jeon, Rafael Meza, Debra P Ritzwoller, Anil Vachani","doi":"10.1001/jamanetworkopen.2025.0942","DOIUrl":"10.1001/jamanetworkopen.2025.0942","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Importance: &lt;/strong&gt;Adherence to annual lung cancer screening (LCS) is a proposed quality metric for LCS programs, but data linking annual adherence to lung cancer outcomes are lacking.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;To investigate annual LCS adherence rates across 2 subsequent LCS rounds among adults undergoing baseline LCS and examine the association of adherence with lung cancer diagnosis rates.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design, setting, and participants: &lt;/strong&gt;This retrospective cohort study included adults aged 55 to 75 years who formerly or currently smoked and underwent baseline LCS between January 1, 2015, and December 31, 2018, across 5 US health care systems in the Population-Based Research to Optimize the Screening Process-Lung Consortium. Participants with missing Lung Computed Tomography Screening Reporting & Data System scores or a lung cancer diagnosis prior to LCS initiation were excluded. Data were analyzed from October 2023 to October 2024.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Exposures: &lt;/strong&gt;For negative baseline screening results, T1 and T2 screening adherence was defined as chest computed tomography (CT) between 10 and 18 months and 22 and 30 months after baseline, respectively. For positive baseline screening results, T1 and T2 adherence was defined as chest CT between 11 and 21 months and 28 and 36 months after baseline, respectively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main outcomes and measures: &lt;/strong&gt;The main outcomes were annual T1 and T2 LCS adherence rates and associations between T1 and T2 screening adherence; annual incident lung cancer diagnoses in rounds T0 (0-12 months after baseline), T1 (&gt;12 to 24 months after baseline), and T2 (&gt;24 to 36 months after baseline); and cancer stage distribution.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 10 170 individuals received baseline LCS (median age, 65 years [IQR, 60-69 years]; 5415 [53.2%] male). During round T1, 6141 of 10 033 eligible patients (61.2% [95% CI, 60.2%-62.2%]) were adherent, and during round T2, 5028 of 9966 eligible patients (50.5% [95% CI, 49.5%-51.4%]) were adherent. T1 adherence was significantly associated with T2 adherence (adjusted relative risk, 2.40; 95% CI, 2.06-2.79). Across 36 months of follow-up, 279 patients (2.7%; 95% CI, 2.4%-3.1%) were diagnosed with lung cancer. Incident lung cancer diagnosis rates were 1.3% (95% CI, 1.1%-1.6%), 0.7% (95% CI, 0.5%-0.8%), and 0.8% (95% CI, 0.6%-0.9%) during rounds T0, T1, and T2, respectively. Lung cancer diagnosis rates were higher among individuals who were LCS adherent vs nonadherent during both rounds T1 (59 of 6141 [1.0%; 95% CI, 0.7%-1.2%] vs 8 of 3892 [0.2%; 95% CI, 0.1%-0.4%]; P &lt; .001) and T2 (63 of 5028 [1.3%; 95% CI, 1.0%-1.6%] vs 12 of 4938 [0.2%; 95% CI, 0.1%-0.4%]; P &lt; .001). A greater proportion of early-stage lung cancers were diagnosed among individuals adherent to screening at T2 compared with those who were not (46 of 63 [73.0%] vs 3 of 12 [25.0%]; P = .006).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions and relevance: &lt;/strong&gt;In this mul","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e250942"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11920840/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Food and Water Insecurity and Functional Disability in Adults.","authors":"Yankun Wang, Rodrigo X Armijos, Sarah Commodore, Aurelian Bidulescu, M Margaret Weigel","doi":"10.1001/jamanetworkopen.2025.1271","DOIUrl":"10.1001/jamanetworkopen.2025.1271","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Importance: &lt;/strong&gt;Evidence from diverse global populations suggests that household food insecurity (HFI) is associated with adult disability, but the association between household water insecurity (HWI) and disability remains understudied. Examinations of the joint association of dual HFI and HWI with disability are lacking.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;To explore independent and joint associations of HFI and HWI with functional disability in Ecuadorian adults.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design, setting, and participants: &lt;/strong&gt;This cross-sectional study used data from the 2018 Ecuadorian National Health and Nutrition Survey, a nationally representative, population-based survey conducted in Ecuador. The study included adults (aged 18-99 years) with information on sociodemographic characteristics, household food and water security, and functional disability status. Data were collected in 2 waves of the survey, from November 2018 to January 2019 and June to July 2019. Statistical analysis was performed from May to December 2024.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Exposures: &lt;/strong&gt;HFI, WFI, or both.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main outcomes and measures: &lt;/strong&gt;The primary outcome was self-reported functional disability, assessed using the Washington Group Short Set on Functioning, a tool that uses a set of 6 questions to measure activity limitations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among 42 071 participants (mean [SE] age, 48.0 [0.1] years; 31 683 male [75.3%]; 1840 African descendant [4.4%], 5184 Indigenous [12.3%], and 35 047 Mestizo ethnic majority group [83.3%]), most lived in urban areas (26 164 participants [62.2%]). Exposure to HFI only was associated with an increased risk for any functional disability (adjusted relative risk [aRR], 1.44; 95% CI, 1.37-1.52), as well as sensory (aRR, 1.43; 95% CI, 1.35-1.52), physical (aRR, 1.56, 95% CI, 1.42-1.72), and cognitive (aRR, 1.78; 95% CI, 1.61-1.98) disabilities. HWI exposure only was associated with increased risk for any functional disability (aRR, 1.12; 95% CI, 1.06-1.20), as well as sensory (aRR, 1.17; 95% CI, 1.09-1.25), physical (aRR, 1.15; 95% CI, 1.05-1.26), and cognitive (aRR, 1.17; 95% CI, 1.03-1.34) disabilities. Exposure to dual HFI and HWI was associated with a greater increase in risk than HFI or HWI alone of any functional disability (aRR, 1.61; 95% CI, 1.50-1.72), as well as sensory (aRR, 1.65; 95% CI, 1.52-1.79), physical (aRR, 1.72; 95% CI, 1.59-1.87), and cognitive (aRR, 2.01; 95% CI, 1.76-2.29) disabilities.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion and relevance: &lt;/strong&gt;In this study, dual exposure to HFI and HWI was associated with a greater increase in risk of any and specific functional disabilities compared with independent contributions of HFI and HWI alone. These findings highlight the importance of addressing HFI and HWI jointly rather than independently when conducting research on disability and other health outcomes and in designing policies and programs to protect at-risk adults and their households.&lt;/","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e251271"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143663512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Exome Sequencing for Neurodevelopmental Disorders.","authors":"Seth I Berger","doi":"10.1001/jamanetworkopen.2025.1818","DOIUrl":"https://doi.org/10.1001/jamanetworkopen.2025.1818","url":null,"abstract":"","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e251818"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143700343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Five-Year Functional Outcomes Among Patients Surviving Aneurysmal Subarachnoid Hemorrhage.","authors":"Ho Seok Lee, Min Kyun Sohn, Jongmin Lee, Deog Young Kim, Yong-Il Shin, Gyung-Jae Oh, Yang-Soo Lee, Min Cheol Joo, So Young Lee, Min-Keun Song, Junhee Han, Jeonghoon Ahn, Young-Hoon Lee, Dae Hyun Kim, Young-Taek Kim, Yun-Hee Kim, Won Hyuk Chang","doi":"10.1001/jamanetworkopen.2025.1678","DOIUrl":"10.1001/jamanetworkopen.2025.1678","url":null,"abstract":"<p><strong>Importance: </strong>Longitudinal changes in functional levels can provide valuable information about disability. However, longitudinal outcomes in aneurysmal subarachnoid hemorrhage (aSAH) have not been well reported, which could provide insight into appropriate management and information for patients experiencing disability.</p><p><strong>Objective: </strong>To investigate the 5-year prognosis and functional outcomes of patients with aSAH.</p><p><strong>Design, setting, and participants: </strong>This retrospective cohort study used data of patients with aSAH from the Korean Stroke Cohort for Functioning and Rehabilitation study up to 5 years after onset. Data were collected from August 2012 through May 2015 in 9 different hospitals in Korea. Data were analyzed from September 2023 through January 2024.</p><p><strong>Exposure: </strong>Patients with aSAH surviving at least 7 days after onset.</p><p><strong>Main outcomes and measures: </strong>Assessments were performed serially from 7 days to 5 years after onset. Prognosis, measured by the modified Rankin scale (mRS) in terms of positive outcome (mRS score of 0 or 1), and mortality were analyzed. In addition, sequential functional outcomes were assessed using the Functional Independence Measure (FIM) in survivors of aSAH at 5 years after onset. Multiple imputation method was used to handle missing data. Wilcoxon signed-rank test and paired t test were used to analyze differences in functional measurements between each follow-up period. Additionally, a generalized mixed-effects model was used to analyze the longitudinal trajectory of the FIM.</p><p><strong>Results: </strong>A total of 338 patients with aSAH (mean [SD] age, 56.3 [13.0] years; 207 female [61.2%]) were included. Among survivors of aSAH at 7 days, the 5-year mortality rate was 8.3% (28 participants). The distribution of mRS significantly improved until 4 years and then plateaued, with 180 (53.3%) and 77 (22.8%) patients reporting an mRS score of 0 and 1, respectively. FIM showed a significant improvement up to 4 years (mean [SD] score, 118.9 [18.7]) and then plateaued.</p><p><strong>Conclusions and relevance: </strong>In this cohort study, the functional outcomes in patients with aSAH continued to improve up to 4 years after onset, with the majority of participants showing favorable outcomes without significant disability, suggesting that proper long-term assessment is needed and appropriate management should be emphasized to maximize potential outcomes of patients with aSAH.</p>","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e251678"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11937949/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143700342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kidney Transplant Wait Times Under Waiting List Expansion Scenarios.","authors":"Jillian S Caldwell, Xingxing S Cheng, Glenn M Chertow, Jeremy D Goldhaber-Fiebert","doi":"10.1001/jamanetworkopen.2025.1665","DOIUrl":"10.1001/jamanetworkopen.2025.1665","url":null,"abstract":"<p><strong>Importance: </strong>Kidney transplantation offers survival benefits and superior quality of life compared with maintenance dialysis for patients with end-stage kidney disease (ESKD), but it is limited to approximately 25 000 patients annually in the United States. Expanding access to transplant could be accomplished by allowing more patients to join the waiting list or by increasing organ supply.</p><p><strong>Objective: </strong>To estimate how these interventions could affect transplant wait times.</p><p><strong>Design, setting, and participants: </strong>This decision-analytic study used a Markov model with a simulated cohort of transplant-eligible US patients over 10 years (2022-2032).</p><p><strong>Exposures: </strong>Three expansion strategies: waiting list expansion alone, waiting list expansion with deceased-donor transplant (DDT) expansion, and waiting list expansion with living-donor transplant (LDT) expansion. Relative 10%, 25%, 50%, and 100% expansions of the current deceased-donor organ supply and 25%, 50%, 100%, and 200% expansions of current living donation rates were simulated, modeling 2 degrees of waiting list expansion (10% and 50%) for each strategy.</p><p><strong>Main outcomes and measures: </strong>Median wait time to kidney transplant using Kaplan-Meier survival analysis.</p><p><strong>Results: </strong>There were a total of 662 190 transplant-eligible patients in the simulated cohort, with a mean (SD) age of 58.7 (14.7) years; 327 126 (49%) female individuals; and 269 082 (41%) Black, 163 028 (25%) Hispanic, 233 739 (35%) non-Hispanic White, and 78 496 (12%) Asian individuals and individuals with another race or ethnicity. Under the baseline strategy, median (IQR) wait time was 32.8 (13.1-66.4) months and increased to 36.8 (14.7-74.7) months and 52.6 (21.0-107.9) months for 10% and 50% waiting list expansion alone. DDT and LDT expansion strategies added 1911 to 20 035 organs. For 10% waiting list expansion, median (IQR) wait times ranged from 23.7 (9.3-47.8) months to 34.5 (13.9-74.7) months. For 50% waiting list expansion, median (IQR) wait times ranged from 34.2 (13.6-69.4) months to 49.4 (19.7-101.0) months.</p><p><strong>Conclusions and relevance: </strong>In this decision-analytic model, expansion strategies without additional organ supply increased the median time to kidney transplant by nearly 2 years; 10% waiting list expansion required at least 2850 additional organs to shorten wait times. However, 50% waiting list expansion required at least 11 000 additional organs to approximate current wait times. Reduction in the deceased-donor organ nonuse rate alone is unlikely to meet the shortfall. Systems-level efforts to significantly increase deceased and living donation should be prioritized alongside increased access to the transplant waiting list.</p>","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e251665"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11933994/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of Hearing Test Software Applications to Detect Hearing Loss.","authors":"Meaghan Lunney, Natasha Wiebe, Tanis Howarth, Lorienne Jenstad, Alex DeBusschere, Gillian Crysdale, Sharon Straus, Kara Schick-Makaroff, Maoliosa Donald, Stephanie Thompson, Jayna Holroyd-Leduc, Marcello Tonelli","doi":"10.1001/jamanetworkopen.2025.2166","DOIUrl":"10.1001/jamanetworkopen.2025.2166","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Importance: &lt;/strong&gt;Hearing loss is common and may impact health and quality of life if not properly managed. It is diagnosed following formal audiological assessment, which may not be available or practical. Hearing test software applications (apps) may help identify people who might benefit from audiological assessment, but their diagnostic accuracy has been incompletely studied.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;To measure and compare the validity and reliability of 2 commonly recommended apps (hearWHO and SHOEBOX) to detect moderately severe or greater hearing loss. Secondary objectives were to evaluate the apps' ability to detect less severe hearing loss and the diagnostic performance of 2 questionnaires for detecting both severities of hearing loss.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design, setting, and participants: &lt;/strong&gt;This prospective diagnostic accuracy study compared the hearWHO and SHOEBOX apps with a 4-frequency pure-tone average audiological assessment reference standard. All consenting English-speaking patients aged 18 years or older and referred for routine audiological assessment at a publicly funded health center in Calgary, Canada, were included between May 17, 2023, and March 12, 2024.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main outcome and measures: &lt;/strong&gt;The main outcome was the validity and reliability of 4 index tests, including the hearWHO app, SHOEBOX app, Revised Hearing Handicap Inventory-Screening (RHHI-S) questionnaire, and the Single-Item Self-Assessment (SISA) questionnaire, to detect moderate to severe hearing loss. All index test results were compared with an audiological assessment reference standard (hearing loss defined by a better ear hearing threshold of ≥50 dB [more severe denoted as HL50] or ≥20 dB [less severe denoted as HL20]). Test-retest reliability of the 2 apps and C statistics, sensitivity, specificity, and positive and negative predicted values of all index tests were measured.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 130 participants were recruited (median [IQR] age, 58 [47-67] years; 82 female [63.1%]). Complete data for each comparison ranged from 123 to 129 participants. The prevalence of HL50 was 16.3% (21 or 130 participants). Neither the hearWHO nor the SHOEBOX app had high test-retest reliability (all κ-values &lt;0.80), with the SHOEBOX having a κ of 0.64 (95% CI, 0.48-0.79) and hearWHO having a κ of 0.32 (95% CI, 0.18-0.46). All C statistics for HL50 were less than 0.80. When testing for HL50, diagnostic performance for both apps was better for the second measurement than the first measurement or the mean. Sensitivity and specificity for the second measurement of SHOEBOX were 0.26 (95% CI, 0.09-0.51) and 1.00 (95% CI, 0.97-1.00), respectively, and for the second measurement of hearWHO, 0.67 (95% CI, 0.43-0.85) and 0.71 (95% CI, 0.62-0.79), respectively. Sensitivity and specificity for the RHHI-S were 0.76 (95% CI, 0.53-0.92) and 0.42 (95% CI, 0.32-0.52), respectively, and for SISA, 0.10 (95% CI, 0.01-0.30) and 0.9","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e252166"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11950885/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143719137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Affording Childcare on a Surgical Resident's Salary.","authors":"Margaret G Mercante, Emily G Tocco, Nidhi Kuchimanchi, Mohamad El Moheb, Maria F Nunez, Mackenzie M Mayhew, Susan J Kim, Allan Tsung, Lily S Cheng, Russell G Witt","doi":"10.1001/jamanetworkopen.2025.0708","DOIUrl":"10.1001/jamanetworkopen.2025.0708","url":null,"abstract":"<p><strong>Importance: </strong>Previously published literature found that 28.6% of surgical residents have or are expecting children, yet little information exists regarding the financial demands of childcare during residency.</p><p><strong>Objective: </strong>To evaluate surgical residents' net financial balance after childcare costs at various postgraduate years and child ages.</p><p><strong>Design, setting, and participants: </strong>This cross-sectional study, conducted from June 14 to August 2, 2024, examined surgical residency programs across the US using publicly available data. Programs were categorized into US regions based on the Association of American Medical Colleges classifications: Northeast, Midwest, South, and West. Childcare costs were obtained from the National Database of Childcare Prices, and annual expenditure data came from the Bureau of Labor Statistics.</p><p><strong>Main outcomes and measures: </strong>The primary outcome was residents' net income by year of residency, calculated using salaries and expenditures. To compare costs by region and child age, net income was determined by subtracting mean expenditures and childcare costs from residency salaries. Calculations were validated using the Massachusetts Institute of Technology Living Wage Calculator.</p><p><strong>Results: </strong>Of 351 US surgical residency programs, 295 with publicly available salaries for postgraduate years 1 through 5 met inclusion criteria. A total of 290 programs (98.3%) showed a negative net income when expenditures and childcare costs were deducted. This finding held true across all child age groups and US regions. The West had the most negative mean net income (-$18 852 [range, -$35 726 to $766]), followed by the Northeast (-$15 878 [range, -$37 310 to $3589]), Midwest (-$12 067 [range, -$26 111 to $1614]), and South (-$8636 [range, -$18 740 to $4826]). Parents of school-aged children in the South had the lowest mean negative net income (-$8453 [range, -$16 377 to $3417]), while parents of infants in the West had the highest mean negative net income (-$21 278 [range, -$35 726 to -$5112]).</p><p><strong>Conclusions and relevance: </strong>This cross-sectional study of surgical residents' net income found that, after accounting for mean annual expenditures and childcare costs, a surgical resident's salary was insufficient to cover living expenses and childcare costs for single resident parents. This financial obstacle may deter individuals from pursuing surgical residency or from starting families as surgical residents.</p>","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e250708"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11907318/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health Care Contact Days for Older Adults Enrolled in Cancer Clinical Trials.","authors":"Arjun Gupta, Cathee Till, Riha Vaidya, Dawn L Hershman, Joseph M Unger","doi":"10.1001/jamanetworkopen.2025.0778","DOIUrl":"10.1001/jamanetworkopen.2025.0778","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Importance: &lt;/strong&gt;Contact days-days with health care contact outside the home-are a measure of how much of a patient's life is consumed by health care. Clinical trials, with a more uniform patient mix and protocolized care, provide a unique opportunity to assess whether burdens differ by individuals' sociodemographic backgrounds.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;To characterize patterns of contact days for older adults with cancer participating in clinical trials.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design, setting, and participants: &lt;/strong&gt;In this cohort study, data from 6 SWOG Cancer Research Network trials across prostate, lung, and pancreatic cancers that recruited patients aged 65 years or older from 1999 to 2014 were linked with Medicare claims data. Data were analyzed from December 14, 2023, to September 26, 2024.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Exposures: &lt;/strong&gt;Demographic variables, including age, sex, self-reported race and ethnicity, and insurance status; clinical factors, such as cancer type and study-specific prognostic risk score; and social factors, such as neighborhood socioeconomic deprivation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main outcomes and measures: &lt;/strong&gt;Number of contact days, defined as number of days with contact with the health care system, percentage of health care contact days (number of contact days divided by follow-up), and sources of contact days (eg, ambulatory or inpatient) in the first 12 months after trial enrollment. Sociodemographic and clinical factors associated with contact days were examined using negative binomial regression, including an offset variable for duration of observation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The study included 1429 patients (median age, 71 years [range, 65-91 years]; 1123 men [78.6%]; and 332 patients [23.5%] with rural residence). The median number of contact days was 48 (IQR, 26-71), of a median of 350 days (IQR, 178-365 days) of observation; the median percentage of contact days was 19% (IQR, 13%-29%). The most common sources of contact days were ambulatory clinician visits (median, 17 [IQR, 7-25]), tests (median, 12 [IQR, 3-24]), and treatments (median, 11 [IQR, 3-22]). A median of 70% (IQR, 50%-88%) of ambulatory contact days had only a single service performed on that day (eg, only tests). In multivariable regression, factors associated with increased contact days included age (relative risk [RR] per year, 1.02 [95% CI, 1.01-1.02]), insurance type (Medicare alone or with Medicaid or private insurance vs other: RR, 2.47 [95% CI, 2.16-2.83]), prognostic risk score (above the median vs at or below the median: RR, 1.14 [95% CI, 1.04-1.25]), and type of cancer (pancreatic vs prostate cancer: RR, 1.69 [95% CI, 1.51-1.89]; lung vs prostate cancer: RR, 1.69 [95% CI, 1.54-1.85]).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions and relevance: &lt;/strong&gt;In this cohort study of older adults with advanced stage cancer participating in phase 3 randomized clinical trials, patients spent nearly 1 in 5 days with health care contact. These findings h","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 3","pages":"e250778"},"PeriodicalIF":10.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11907310/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}