A Decision Aid for Patients with Advanced Lung Cancer
A Decision Aid for Patients with Advanced Lung Cancer
批准号:
7140031
负责人:
PATRICIA JEAN HOLLEN
金额:
$22.14万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-09-15 至 2009-01-31
关键词:
behavioral /social science research tagbehavioral medicinecaregiversclinical researchcognitive behavior therapyconflictcounselingdecision makingexperiencehealth educationhuman subjecthuman therapy evaluationinterviewlung neoplasmsmathematical modelneoplasm /cancer chemotherapyneoplasm /cancer palliative treatmentneoplasm /cancer therapypatient care managementpatient care personnel relationspatient oriented researchpsychological aspect of cancerpsychological valuesquality of liferacial /ethnic differencesocial support networkterminal patient care
中文摘要
描述(由申请者提供):许多晚期肺癌患者和他们的照顾者都在为治疗决定而苦苦挣扎,比如什么时候说“够了”。在大多数临床实践中,患者对后续决定的准备,包括终止癌症的定向治疗,并没有得到很好的处理。这项研究的具体目的将是:1)确定为面临癌症指导治疗的晚期肺癌患者(及其照顾者)实施决策辅助(认知-行为技能干预)的可行性;以及2)收集初步数据,以验证如下假设:与通常的护理/控制组相比,接受决策援助以增强癌症治疗决策技能的晚期肺癌患者(及其照顾者)将报告:(A)提高决策质量;及(B)在决策3(终止癌症指导治疗)结束时,决策冲突减少。这项先导性研究为一项前瞻性随机临床试验做准备,将为40名IIIB或IV期肺癌患者及其40名照顾者测试一种辅助决策工具。它将在弗吉尼亚州的一家诊所进行。将使用混合方法:1)回溯性现象学设计将允许在1小时的访谈中分别探索患者和照顾者的经历;2)前测/后测设计将测量一段时间,包括在化疗过程中的三个决定(早期、中期和晚期),直到癌症指导治疗结束。将使用分层区块随机设计,其中分层由两个变量决定,即决策和种族。将分为两组:加强护理(EC)和常规护理(UC)。EC将获得包含七个组成部分的决策援助:社会支持、前瞻性指导、坚持患者参与治疗决策的偏好、高质量的决策过程教程、正常化(使用CD程序)、与肿瘤学专业人员讨论困难决策的有计划的时间,以及在整个治疗过程中对3个决策进行价值澄清。除了对与欧盟委员会的录音采访进行调查外,还将对所有参与者使用自我报告措施。结果衡量标准是决策质量和决策冲突。两个小组(决策和肺癌)将对该方案进行两次审查。该计划将包括连续筛选任命名单。决策辅助将在三次诊所就诊期间实施。数据分析将使用广义线性模型。主题的饱和度将用于定性部分。
英文摘要
DESCRIPTION (provided by applicant): Many patients with advanced lung cancer and their caregivers struggle with treatment decisions, such as when to say "enough." Patient preparation for consequential decisions, including termination of cancer directed treatment, is not well handled in most clinical practices. Specific aims for this study will be to: 1) determine the feasibility of implementing a decision-making aid (cognitive-behavioral skills intervention) for patients with advanced lung cancer (and their caregivers) facing cancer-directed treatment; and 2) gather preliminary data for testing the hypothesis that patients with advanced lung cancer (and their caregivers), who receive a decision aid to enhance decision-making skills about cancer treatment, will report (a) increased quality decision making, and (b) decreased decisional conflict at the end of Decision 3 (termination of cancer directed therapy), compared to the usual care/control group. This pilot study, in preparation for a prospective, randomized clinical trial, will test a decision-making aid for 40 patients with stage IIIB or IV lung cancer and their 40 caregivers. It will be conducted at one clinic in Virginia. A mixed-method approach will be used: 1) a retrospective phenomenological design will allow exploring the experiences of both patients and caregivers separately in a 1-hour interview; and 2) a pretest/posttest design will measure a time period including three decisions (early, midway, and late) over the course of chemotherapy until cancer-directed treatment is terminated. A stratified block randomization design will be used in which strata are determined by two variables, decision making and race. There will be two groups: enhanced care (EC) and usual care (UC). EC will receive a decision aid with seven components: social support, anticipatory guidance, adhering to the patient's preference for participation in treatment decision making, a quality decision-making process tutorial, normalization (using a CD program), structured time with oncology professionals to discuss difficult decisions, and values clarification of 3 decisions throughout treatment. Self-report measures will be used for all participants in addition to probes for the taped interviews with EC. The outcome measures are quality decision making and decisional conflict. Two panels (decision making and lung cancer) will review the protocol twice. The plan will include serially screening the appointment roster. The decision aid will be administered during three clinic visits. Generalized linear models will be used for data analysis. Saturation of themes will be used for the qualitative component.
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会议论文
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海外基金