目的·系统整合晚期癌症患者预立医疗照护计划(advance care planning,ACP)参与行为的相关影响因素。方法·系统检索中国知网、万方、中国生物医学文献数据库(Sinomed)、PubMed、Cochrane Library、Embase、CINAHL、PsycINFO等...目的·系统整合晚期癌症患者预立医疗照护计划(advance care planning,ACP)参与行为的相关影响因素。方法·系统检索中国知网、万方、中国生物医学文献数据库(Sinomed)、PubMed、Cochrane Library、Embase、CINAHL、PsycINFO等数据库从建库至2022年12月有关晚期癌症患者ACP参与行为影响因素的中英文文献。由2名研究者对最终纳入的文献进行文献质量评价、内容提取和汇总,将定量研究与定性研究分别提取数据后进行整合,得到晚期癌症患者ACP参与行为的最终影响因素。并借助理论域框架,将其逐级映射至能力、机会、动机-行为(capability,opportunity,motivation-behavior,COM-B)模型。结果·共纳入21项研究,整合归纳出27个影响因素,涉及9个理论域。映射至COMB模型中的因素包括能力因素9个(ACP知识、文化程度、准确了解预后知识、知晓疾病诊断时间、先前经历、主观预期寿命、年龄、肿瘤部位、疾病症状负担)、机会因素13个(性别、婚姻状况、种族/民族、宗教信仰、未成年子女、家庭经济收入、居住地点、房屋居住类型、家庭支持、社会支持、医患关系、文化适应、是否设立临终关怀服务中心)和动机因素5个(ACP态度、ACP信念、ACP动机、焦虑抑郁、死亡态度)。其中,医患关系、宗教信仰、ACP态度、文化程度、婚姻状况、家庭支持、ACP知识、准确了解预后知识、年龄、居住地点、死亡态度、先前经历、种族/民族是对患者ACP参与行为影响较多的因素。结论·基于COM-B模型可全面归纳总结晚期癌症患者ACP参与行为的影响因素。未来研究可以上述因素为切入点,基于COM-B模型设计连续化、多方面的综合性干预措施,促进晚期癌症患者ACP参与行为实践。展开更多
This paper is to examine the impact of satellite data on the systematic error of operational B-model in China.Em- phasis is put on the study of the impact of satellite sounding data on forecasts of the sea level press...This paper is to examine the impact of satellite data on the systematic error of operational B-model in China.Em- phasis is put on the study of the impact of satellite sounding data on forecasts of the sea level pressure field and 500 hPa height.The major findings are as follows. (1)The B-model usually underforecasts the strength of features in the sea level pressure(SLP)field,i.e.pressures are too low near high pressure systems and too high near low pressure systems. (2)The nature of the systematic errors found in the 500 hPa height forecasts is not as clear cut as that of the SLP forecasts,but most often the same type of pattern is seen,i.e.,the heights in troughs are not low enough and those in ridges are not high enough. (3)The use of satellite data in the B-model analysis/forecast system is found to have an impact upon the model's forecast of SLP and 500 hPa height.Systematic errors in the vicinity of surface lows/500 hPa troughs over the oceans are usually found to be significantly reduced.A less conclusive mix of positive and negative impacts was found for all other types of features.展开更多
文摘目的·系统整合晚期癌症患者预立医疗照护计划(advance care planning,ACP)参与行为的相关影响因素。方法·系统检索中国知网、万方、中国生物医学文献数据库(Sinomed)、PubMed、Cochrane Library、Embase、CINAHL、PsycINFO等数据库从建库至2022年12月有关晚期癌症患者ACP参与行为影响因素的中英文文献。由2名研究者对最终纳入的文献进行文献质量评价、内容提取和汇总,将定量研究与定性研究分别提取数据后进行整合,得到晚期癌症患者ACP参与行为的最终影响因素。并借助理论域框架,将其逐级映射至能力、机会、动机-行为(capability,opportunity,motivation-behavior,COM-B)模型。结果·共纳入21项研究,整合归纳出27个影响因素,涉及9个理论域。映射至COMB模型中的因素包括能力因素9个(ACP知识、文化程度、准确了解预后知识、知晓疾病诊断时间、先前经历、主观预期寿命、年龄、肿瘤部位、疾病症状负担)、机会因素13个(性别、婚姻状况、种族/民族、宗教信仰、未成年子女、家庭经济收入、居住地点、房屋居住类型、家庭支持、社会支持、医患关系、文化适应、是否设立临终关怀服务中心)和动机因素5个(ACP态度、ACP信念、ACP动机、焦虑抑郁、死亡态度)。其中,医患关系、宗教信仰、ACP态度、文化程度、婚姻状况、家庭支持、ACP知识、准确了解预后知识、年龄、居住地点、死亡态度、先前经历、种族/民族是对患者ACP参与行为影响较多的因素。结论·基于COM-B模型可全面归纳总结晚期癌症患者ACP参与行为的影响因素。未来研究可以上述因素为切入点,基于COM-B模型设计连续化、多方面的综合性干预措施,促进晚期癌症患者ACP参与行为实践。
文摘This paper is to examine the impact of satellite data on the systematic error of operational B-model in China.Em- phasis is put on the study of the impact of satellite sounding data on forecasts of the sea level pressure field and 500 hPa height.The major findings are as follows. (1)The B-model usually underforecasts the strength of features in the sea level pressure(SLP)field,i.e.pressures are too low near high pressure systems and too high near low pressure systems. (2)The nature of the systematic errors found in the 500 hPa height forecasts is not as clear cut as that of the SLP forecasts,but most often the same type of pattern is seen,i.e.,the heights in troughs are not low enough and those in ridges are not high enough. (3)The use of satellite data in the B-model analysis/forecast system is found to have an impact upon the model's forecast of SLP and 500 hPa height.Systematic errors in the vicinity of surface lows/500 hPa troughs over the oceans are usually found to be significantly reduced.A less conclusive mix of positive and negative impacts was found for all other types of features.
