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American Indian and Alaska Native (AIAN) individuals are diverse culturally and geographically but share a high prevalence of chronic illness, largely because of obstacles to high-quality health care. The authors comprehensively examined cancer incidence and mortality among non-Hispanic AIAN individuals, compared with non-Hispanic White individuals for context, using population-based data from the National Cancer Institute, the Centers for Disease Control and Prevention, and the North American Association of Central Cancer Registries. Overall cancer rates among AIAN individuals were 2% higher than among White individuals for incidence (2014 through 2018, confined to Purchased/Referred Care Delivery Area counties to reduce racial misclassification) but 18% higher for mortality (2015 through 2019). However, disparities varied widely by cancer type and geographic region. For example, breast and prostate cancer mortality rates are 8% and 31% higher, respectively, in AIAN individuals than in White individuals despite lower incidence and the availability of early detection tests for these cancers. The burden among AIAN individuals is highest for infection-related cancers (liver, stomach, and cervix), for kidney cancer, and for colorectal cancer among indigenous Alaskans (91.3 vs. 35.5 cases per 100,000 for White Alaskans), who have the highest rates in the world. Steep increases for early onset colorectal cancer, from 18.8 cases per 100,000 Native Alaskans aged 20–49 years during 1998 through 2002 to 34.8 cases per 100,000 during 2014 through 2018, exacerbated this disparity. Death rates for infection-related cancers (liver, stomach, and cervix), as well as kidney cancer, were approximately two-fold higher among AIAN individuals compared with White individuals. These findings highlight the need for more effective strategies to reduce the prevalence of chronic oncogenic infections and improve access to high-quality cancer screening and treatment for AIAN individuals. Mitigating the disparate burden will require expanded financial support of tribal health care as well as increased collaboration and engagement with this marginalized population.  相似文献   
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目的调查上海市2022年3月以来新一波新型冠状病毒肺炎(COVID-19)疫情期间方舱医院新冠肺炎患者心理健康状况,并分析影响因素,为开展针对性的心理干预和治疗提供科学依据。方法于2022年4月6日—5月11日,采用横断面研究、方便抽样法,应用微信小程序“同心守沪”对上海市3所方舱医院新冠肺炎患者采用突发性公共卫生事件心理问卷,调查心理健康状况,并初步分析影响因素。结果共268例患者完成问卷调查,心理症状检出者261例(97.4%),其中抑郁、神经衰弱、恐惧、强迫-焦虑、疑病症状检出率分别为80.6%、69.8%、89.6%、75.4%、41%。心理健康总评分影响因素有年龄(P=0.008)、躯体疾病(P=0.03)、既往是否有精神心理问题(P<0.001)、疫情对心身的影响程度(P<0.001);抑郁评分(P=0.019)和神经衰弱评分(P=0.021)还受教育程度影响;神经衰弱评分还受性别影响(P=0.024);疑病评分还受新冠肺炎认知程度影响(P=0.007)。结论上海市方舱医院集中隔离治疗点内患者恐惧、抑郁、强迫-焦虑症状多见,心理异常症状严重程度以轻、中度为主。随年龄越小、受教育程度越高、女性患者、有躯体疾病、既往存在精神心理问题、对新冠肺炎认知程度低、疫情对心身影响程度越大,心理症状总分越高,症状越严重。  相似文献   
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目的:探讨基于虚拟教研室的公共卫生安全素养培育课程构建及实践。方法:选取某医学院校专科护理专业学生(护生)为研究对象,将护理1班45人作为试验组,将护理2班43人作为对照组,对照组对公共卫生安全知识实施线上与线下的常规教学,试验组实施基于虚拟教研室的公共卫生安全素养培育课程。比较两组护生内容掌握情况及学习满意度。结果:试验组护生的学习成绩明显高于对照组(P<0.01),试验组护生对教学的满意度为95.6%(43/45),明显高于对照组(P<0.05)。结论:基于虚拟教研室的公共卫生安全素养培育课程构建既可以广泛促进不同专业教师进行教学研究交流,全面提高教师教书育人能力,又可以使护生在学习过程中接触不同专业、不同领域的知识与技能,注重护生主体作用,提高学习效果和学习满意度。  相似文献   
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目的 基于《国际功能、残疾和健康分类》(ICF)构建智力和发展性残疾儿童青少年身体活动效益系统综述的范畴和PICO架构,探讨智力和发展性残疾儿童和青少年参加身体活动的健康效益。  相似文献   
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目的 探索护士、医务社工、志愿者“三位一体”护理服务模式在先天性心脏病患儿中的应用效果。 方法 护士、医务社工、志愿者组成护理团队,对住院先天性心脏病患儿及家庭开展游戏治疗服务、心理关爱服务、慈善救助服务、健康宣讲服务及主题活动服务。 结果 2018年1月至2021年12月,游戏辅导2 897例患儿,心理关爱服务764个家庭,慈善救助1 897例患儿,健康宣讲服务2 149例次。2018~2021年住院患者体验与满意度调查满意率分别为98.47%、98.59%、98.67%、98.79%。护士、医务社工、志愿者均认为提高了沟通能力。 结论 护士、医务社工、志愿者“三位一体”护理服务模式从心理、经济、健康教育等方面为患儿及家属提供服务,有效提高了服务对象满意度。  相似文献   
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《Value in health》2022,25(3):331-339
ObjectivesClinical artificial intelligence (AI) is a novel technology, and few economic evaluations have focused on it to date. Before its wider implementation, it is important to highlight the aspects of AI that challenge traditional health technology assessment methods.MethodsWe used an existing broad value framework to assess potential ways AI can provide good value for money. We also developed a rubric of how economic evaluations of AI should vary depending on the case of its use.ResultsWe found that the measurement of core elements of value—health outcomes and cost—are complicated by AI because its generalizability across different populations is often unclear and because its use may necessitate reconfigured clinical processes. Clinicians’ productivity may improve when AI is used. If poorly implemented though, AI may also cause clinicians’ workload to increase. Some AI has been found to exacerbate health disparities. Nevertheless, AI may promote equity by expanding access to medical care and, when properly trained, providing unbiased diagnoses and prognoses. The approach to assessment of AI should vary based on its use case: AI that creates new clinical possibilities can improve outcomes, but regulation and evidence collection may be difficult; AI that extends clinical expertise can reduce disparities and lower costs but may result in overuse; and AI that automates clinicians’ work can improve productivity but may reduce skills.ConclusionsThe potential uses of clinical AI create challenges for health technology assessment methods originally developed for pharmaceuticals and medical devices. Health economists should be prepared to examine data collection and methods used to train AI, as these may impact its future value.  相似文献   
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The aim of this study was to examine if citizen science contributes to gaining insight into community health and to the health of the citizen scientists themselves. Therefore, thirteen citizens in four deprived neighbourhoods were trained as citizen scientists to conduct research in their own communities. Results showed that the citizen scientists identified forty (health related) themes in their communities. The citizen scientists reported an increase in their overall self-perceived health which, however, was not significantly demonstrated in the prequestionnaire and postquestionnaire.  相似文献   
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