Visual Causal Models in Clinical Explanation

描述（由申请人提供）：心理健康临床医生每天面临的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化视觉因果模型是否可以帮助临床医生更有效地向客户传递有关疾病及其治疗的信息。根据最近的研究表明，双模式陈述减少了学习者的认知负荷（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理解和增加临床信息的保留。我们对非专业人士和心理健康客户的研究将检验他们在听了临床医生的口头解释和听了带有视觉因果模型的相同解释后的理解和回忆。我们的实验使用了我们开发的一个新的软件程序，使临床医生能够在临床实践中轻松地创建和显示因果模型。这个名为Conceptbuilder的程序，以及一个配套的软件Conceptanalysis，都是基于当前关于心理表征和解释性知识使用的认知理论（Kim, 2005）。我们建议，该软件将有助于改善临床实践和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（国际移民组织，2004年）。这个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。该程序本身已经免费提供给公众用于研究或临床设置。

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.