Simulation-Based Caregiving Skills Training for Family Members of High Grade Glioma Patients

项目概要/摘要 与其他癌症患者相比，脑肿瘤患者经历更多使人衰弱的后遗症，因此， 在病程早期往往依赖家人的照顾和支持。当你- 一般来说，脑肿瘤患者的家庭照顾者面临着独特的挑战， 患者认知能力下降，神经和运动缺陷，以及由于疾病过程引起的个性变化 和治疗。随着典型的快速疾病进展和随后的患者功能下降，护理人员 越来越多地帮助患者进行日常生活活动（例如，洗澡，喂食，穿衣）以及协调 护理，症状和药物管理，以及决策。基本上，护理人员提供基本的 没有技能培训的护理。此外，尽管有明确的证据表明，照顾者的痛苦和负担很重， 这可能会影响他们照顾病人的能力，照顾者报告说，他们的支持需求往往是 多学科肿瘤学团队无人照顾事实上，神经肿瘤学文献通常缺乏 为这一弱势群体提供基于证据的支持性护理干预措施。为了解决这些关键的知识 差距，我们建议试点测试一种新的模拟为基础的技能干预，以针对独特的需求 照顾者。考虑到癌症家庭在痛苦和生活质量方面的相互依赖，我们预计， 这种以照顾者为重点的干预措施不仅将改善照顾者，而且将改善病人的结果。使用 随机对照试验（RCT）设计，患者-护理人员配对将被随机分配至干预组或 干预内容将通过三种方式提供：教育材料（即， 练习册和视频），两个基于模拟的学习技能培训课程，以及两个心理教育课程 讨论如何应对与工作有关的角色变化的会议。这四个人工操作的会议将是护士- 采用需求评估驱动的方法，根据家庭现状的需求进行引导和调整。患者 护理人员将在基线（随机分组前）和6周和12周后完成自我报告测量。 我们将评估病人和照顾者的心理症状，照顾者的效能和角色调整， 患者癌症相关症状作为干预结果。因为照顾者的心理困扰 与可预防的医疗保健利用增加相关，我们将抽象急诊科就诊， 入院情况和患者病历中的非计划性肿瘤医生访视。我们将整合定性 照顾者的经验与多模式干预组件的帐户。可行性数据， 将记录同意、保留、遵守和程序评估。这项工作将提供丰富的 试点数据将为后续更大规模的试验提供信息，以进行这种创新干预措施的正式有效性测试， 改善这一脆弱但研究不足的患者-护理人员人群的癌症相关负担。

PROJECT SUMMARY/ABSTRACT Patients with brain tumors experience more debilitating sequelae compared to other cancer patients and thus, often dependent on their family members for care and support early on in the disease course. While caregiving- related activities are taxing in general, family caregivers of brain tumor patients face unique challenges related to patient cognitive decline, neurological and motor deficits, and personality changes due to the disease process and treatment. With the typical rapid disease progression and subsequent patient functional decline, caregivers increasingly assist patients with activities of daily living (e.g., bathing, feeding, dressing) as well as coordination of care, symptom and medication management, and decision-making. Essentially, caregivers provide basic nursing care without skill-based training. Moreover, despite clear evidence of high caregiver distress and burden, which may impact their ability to care for the patient, caregivers report that their support needs are often unattended to by multi-disciplinary oncology teams. In fact, the neuro-oncology literature generally lacks evidence-based supportive care interventions for this vulnerable population. To address these critical knowledge gaps, we propose to pilot-test a novel simulation-based caregiving skills intervention to target the unique needs of caregivers. Given interdependence in distress and quality of life in families coping with cancer, we expect that this caregiver-focused intervention will improve not only caregiver but also patient outcomes. Using a randomized controlled trial (RCT) design, patient-caregiver dyads will be randomized to the intervention or a waitlist control (WLC) arm. The intervention content will be delivered via three modes: education materials (i.e., workbook and video), two simulation-based caregiving skills training sessions, and two psychoeducation sessions addressing coping with caregiving-related role changes. The four manualized sessions will be nurse- led and tailored to the needs of the family’s current situation using a needs assessment driven approach. Patients and caregivers will complete self-report measures at baseline (prior to randomization) and 6 and 12 weeks later. We will assess patient and caregiver psychological symptoms, caregiver efficacy and role adjustment, and patient cancer-related symptoms as intervention outcomes. Because psychological distress in caregivers is associated with increased preventable healthcare utilization, we will abstract emergency department visits, hospital admissions, and unplanned oncologist visits from patients’ medical records. We will integrate qualitative accounts of the caregivers’ experiences with the multi-model intervention components. Feasibility data regarding consent, retention, adherence, and program evaluation will be recorded. The proposed work will provide rich pilot data that will inform a subsequent larger trial for formal efficacy testing of this innovative intervention seeking to improve cancer-related burden in this vulnerable yet understudied patient-caregiver population.