Enhancing Connections-Palliative Care: A Cancer Parenting Program for Patients with Advanced Cancer and Their Children

项目摘要/摘要 这项研究的目的是测试癌症父母教育的短期效果。 为被诊断患有无法治愈的癌症的养育子女的父母提供的计划，称为增强联系-姑息 关爱计划(EC-PC)。该计划由完全脚本化的干预会议组成，将由 一位受过专门训练的耐心教育者打来的电话。EC-PC已经进行了试点测试，并已准备好投入使用 测试。如果父母被诊断出患有无法治愈的癌症[由TNM IV期确定]，他们将有资格 硬性肿瘤的癌症或2个或更多周期的治疗失败，非实体肿瘤的疾病复发]；阅读 把写英语和说英语作为他们选择的语言之一；有一个5-17岁的孩子住在 至少50%的时间与患病的父母和另一名未患病的父母或父母代孕在一起；并有权获得 电话。研究参与者将从4个研究中心招募：华盛顿大学/西雅图癌症 关爱联盟；乔治城大学/隆巴迪综合癌症中心；夏威夷大学/夏威夷 癌症中心和东南肿瘤学/南卡罗来纳大学。完成签字通知后 同意和基线措施，父母将被随机分配到试验性或替代治疗对照 一群人。试验组将每两周接受5次电话授课，时间为 受过专门训练的耐心教育者。控制组将收到邮寄的“我应该对孩子们说什么？”的邮件。 指导晚期癌症患者的父母，并由受过专门培训的患者教育者电话联系 将使用脚本来指导家长如何从小册子中获得最多的信息。主端点 对于测试效果，将在基线后3个月使用线性混合模型进行评估，意图 治疗分析和按协议分析。五个主要结果将评估疗效：父母的焦虑和 抑郁的情绪；父母帮助孩子应对癌症的能力；父母的自尊 与孩子谈论孩子与癌症相关的问题的有效性；以及孩子的焦虑/抑郁 心情。将在6个月和9个月时描述和评估变化的稳定性。估计的效果大小 对.33-81的初步结果，研究将具有大于0.80的能力来检测显著 试验组和对照组之间的差异，p=0.05(双尾)。 我们的分析样本将是492名确诊的父母及其492名未患病的同居伴侣/父母。 5-17岁儿童的代孕妈妈。除了测试有效性，拟议的研究还将测试理论 采用验证性因素分析的结构方程模型对干预效果进行评价 干预对双亲离世儿童行为情绪适应的影响 使用线性混合模型对从未患病的父母那里获得的数据进行分析；并检验 用线性混合模型研究父母症状负担和家庭环境对治疗结果的影响。

PROJECT SUMMARY/ABSTRACT The purpose of the proposed study is to test the short-term efficacy of a cancer parenting education program for child-rearing parents diagnosed with non-curable cancer, called Enhancing Connections-Palliative Care Program (EC-PC). The program consists of fully scripted intervention sessions that will be delivered by telephone by a specially trained patient educator. The EC-PC has been pilot tested and is ready for efficacy testing. Parents will be eligible if they are diagnosed with non-curable cancer [determined by TNM Stage IV cancer for hard tumors or 2 or more cycles of treatment failure with disease relapse in non-solid tumors]; read, write and speak English as one of their languages of choice; have a child between the ages of 5-17 living in the home at least 50% of the time with the ill parent and another non-ill parent or parent surrogate; and have access to a telephone. Study participants will be recruited from 4 study centers: University of Washington/ Seattle Cancer Care Alliance; Georgetown University/ Lombardi Comprehensive Cancer Center; University of Hawaii/ Hawai’i Cancer Center, and Southeast Oncology/University of South Carolina. After completing signed informed consent and baseline measures, parents will be randomized to an experimental or alternative treatment control group. The experimental group will receive 5 telephone-delivered educational sessions every 2 weeks by specially trained patient educators. The control group will be mailed “What Should I Say to the Children?”, a guide for parents with advanced cancer, and be phone contacted by a specially trained patient educator who will use a script to guide the parent on ways to gain the most information from the booklet. Primary endpoints for testing efficacy will be assessed at 3-months post-baseline using Linear Mixed Models using an intent to treat analysis and a per-protocol analysis. Five primary outcomes will assess efficacy: parents' anxiety and depressed mood; parents' skills in helping their child manage the toll of the parents' cancer; parents' self- efficacy in talking with their child about the child's cancer-related concerns; and the child's anxious/depressed mood. The stability of changes will be described and evaluated at 6- and 9-months. With estimated Effect sizes of .33-81 on the primary outcomes, the study will have greater than 0.80 power to detect a significant difference between the experimental and control group, p=.05 (2-tailed). Our sample for analysis will be 492 diagnosed parents and their 492 non-ill coinhabiting partners/parent surrogates of children ages 5-17. In addition to testing efficacy, the proposed study will test the theoretical model of the intervention using structural equation modeling with confirmatory factor analysis; evaluate the impact of the intervention on children’s behavioral-emotional adjustment whose parents die during the study using Linear Mixed Models on data obtained from the non-ill parent; and examine the moderating effects of parents' symptom burden and family environment on treatment outcomes using Linear Mixed Models.