Visual Causal Models in Clinical Explanation

临床解释中的视觉因果模型

基本信息

批准号：
7895781
负责人：
NANCY S. KIM
金额：
$ 7.8万
依托单位：
NORTHEASTERN UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-08-01 至 2012-07-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): One of the mental health clinician's daily challenges is to adequately explain disorders and prescribed treatment regimens to clients of varying levels of health literacy while optimizing clients' comprehension and memory in a time-limited situation. We propose to test whether computerized visual causal models can assist clinicians in more effectively transmitting information about disorders and their treatments to clients. In accord with recent research indicating that dual-mode presentations reduce the learner's cognitive load (Ginns, 2005; Mayer, 2001; Reed, 2006), we predict that when a visual causal model is paired with a verbal explanation, it will help enhance client understanding and increase retention of clinical information. Our proposed study of lay people and mental health clients will examine their understanding and recall after listening to a clinician's verbal explanation versus listening to the same explanation accompanied by a visual causal model. Our experiment makes use of a new software program that we have developed to allow clinicians to easily create and display causal models in clinical practice. This program, entitled Conceptbuilder, and a companion piece of software, Conceptanalysis, have been grounded in current cognitive theory regarding the mental representation and use of explanatory knowledge (Kim, 2005). We suggest that this software will be useful both for improving clinical practice and for facilitating research on the effectiveness with which clinicians explain disorders and treatments to clients of varying levels of health literacy. PUBLIC HEALTH RELEVANCE: People who cannot understand what their doctor tells them about their disorder or treatment generally tend to have poorer health (IOM, 2004). This application draws upon past research in education and learning to test whether using visual aids, created by a computer program developed in our lab, can help doctors explain clinical information more clearly to their clients. The program itself has been made freely available to the public for use in research or clinical settings.

描述（由申请人提供）：心理健康临床医生的日常挑战之一是向不同健康素养水平的客户充分解释疾病和规定的治疗方案，同时在有限的时间内优化客户的理解和记忆。我们建议测试计算机视觉因果模型是否可以帮助临床医生更有效地将有关疾病及其治疗的信息传递给客户。根据最近的研究表明，双模式演示会减少学习者的认知负担（Ginns，2005；Mayer，2001；Reed，2006），我们预测，当视觉因果模型与口头解释配对时，它将有助于增强客户的认知能力。了解并加强对临床信息的保留。我们提出的针对非专业人士和心理健康客户的研究将检查他们在听临床医生的口头解释后的理解和回忆，以及听带有视觉因果模型的相同解释。我们的实验利用了我们开发的新软件程序，使临床医生能够在临床实践中轻松创建和显示因果模型。该程序名为 Conceptbuilder，以及配套软件 Conceptanalysis，均以当前有关心理表征和解释性知识使用的认知理论为基础（Kim，2005）。我们建议该软件将有助于改善临床实践，并促进临床医生向不同健康素养水平的客户解释疾病和治疗的有效性的研究。公共卫生相关性：无法理解医生告诉他们的疾病或治疗方法的人通常健康状况较差（IOM，2004）。该应用程序借鉴了过去在教育和学习方面的研究，以测试使用由我们实验室开发的计算机程序创建的视觉辅助工具是否可以帮助医生更清楚地向客户解释临床信息。该程序本身已免费向公众开放，用于研究或临床环境。

项目成果

期刊论文数量（1）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Visual causal models enhance clinical explanations of treatments for generalized anxiety disorder.

视觉因果模型增强了广泛性焦虑症治疗的临床解释。

DOI：
发表时间：
2013
期刊：
影响因子：
4.4
作者：
Kim, Nancy S;Khalife, Danielle;Judge, Kelly A;Paulus, Daniel J;Jordan, Jake T;Yopchick, Jennelle E
通讯作者：
Yopchick, Jennelle E