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Predicting User Preferences for Educational Content Based on the Results of an Automated Evalutation for Alcohol Use Problems

机译:根据对酒精使用问题的自动评估结果预测用户对教育内容的偏好

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摘要

Computer programs may be more effective than traditional self-help manuals because they are interactive, and can automatically modify their content to meet the specific needs of a user. Successfully predicting the type of information that will be most relevant to an individual may lead to greater engagement with the program and better outcomes. The current study tests the association of information obtained during an automated evaluation for alcohol use problems with subsequent preference for educational modules.
机译:计算机程序是交互式的,并且可以自动修改其内容以满足用户的特定需求,因此它们可能比传统的自助手册更有效。成功地预测与个人最相关的信息类型可能会导致与计划的更多参与和更好的结果。当前的研究测试了在自动评估饮酒问题期间获得的信息与随后对教育模块的偏好之间的关联。

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