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.
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.
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