Information processing likelihood, eHealth literacy, and complexity of seeking strategies as predictors of health decision-making quality

Yaron Connelly, Nehama Lewis, I. Talmud, Giora Kaplan
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Abstract

eHEALS is one of the most prevalent scales used to measure eHealth literacy. However, significant criticism toward its conceptualization had raised. This study tests the effects of eHEALS alongside constructs from the elaboration likelihood model and information seeking processes, within a multidimensional model to predict medical decision-making quality. We test this model using a sample of 56 participants who completed a 45-minute online simulation task, requiring them to offer recommendation for a hypothetical medical scenario. Findings revealed that neither eHealth literacy nor elaboration likelihood independently predicted decision quality. However, eHEALS was positively associated with higher decision quality, but only among participants who had greater motivation and ability to process health information, and who used more complex information seeking strategies. Findings suggest that the eHEALS measure can be examined using a multidimensional theoretical approach to illustrate the ways in which patients obtain and utilize health information to make informed decisions.
信息处理可能性、电子健康素养和寻求策略的复杂性作为健康决策质量的预测因子
eheal是用来衡量电子健康素养的最普遍的量表之一。然而,对其概念化提出了重大批评。本研究在一个多维模型中测试了eHEALS以及阐述可能性模型和信息寻求过程的结构的影响,以预测医疗决策质量。我们使用56名参与者的样本来测试这个模型,他们完成了一个45分钟的在线模拟任务,要求他们为一个假设的医疗场景提供建议。研究结果显示,电子健康素养和阐述可能性都不能独立预测决策质量。然而,eHEALS与更高的决策质量呈正相关,但仅适用于具有更大动机和处理健康信息能力的参与者,以及使用更复杂的信息寻求策略的参与者。研究结果表明,可以使用多维理论方法来检验eHEALS措施,以说明患者获取和利用健康信息做出明智决策的方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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