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Identifying the peripheral cues in the credibility assessment of online health information
Information & Management ( IF 8.2 ) Pub Date : 2024-09-08 , DOI: 10.1016/j.im.2024.104037 Jennifer L. Claggett, Brent Kitchens, Maria Paino
Information & Management ( IF 8.2 ) Pub Date : 2024-09-08 , DOI: 10.1016/j.im.2024.104037 Jennifer L. Claggett, Brent Kitchens, Maria Paino
Online health information varies, as well as what people choose to consume and believe. Previous research finds that hesitancy to follow health advice is often due to suspicion about credibility. The elaboration likelihood model suggests credibility assessments use both argument quality and source credibility. One important facet for understanding how and why people cling to misinformation about health advice is uncovering what drives their credibility assessment in the first place. Yet, little research focuses on what peripheral cues influence source credibility in online health information. Our mixed-method study, which combines an online experiment and qualitative analysis, explores how source, tone, and format affect credibility perceptions in health contexts. The results confirm ELM relationships and indicate credibility increases when information is physician-authored and objectively presented. Our findings address a gap in the literature by exploring what influences a person's credibility assessment of online health information, offering insights that could inform the design of future online health resources.
中文翻译:
识别在线健康信息可信度评估中的外围线索
在线健康信息各不相同,人们选择消费和相信的内容也各不相同。以前的研究发现,不愿遵循健康建议通常是由于对可信度的怀疑。阐述似然模型表明可信度评估同时使用论点质量和来源可信度。要了解人们如何以及为什么坚持有关健康建议的错误信息,一个重要的方面是首先揭示驱动他们可信度评估的原因。然而,很少有研究关注哪些外围线索会影响在线健康信息来源的可信度。我们的混合方法研究结合了在线实验和定性分析,探讨了来源、语气和格式如何影响健康环境中的可信度感知。结果证实了 ELM 关系,并表明当信息由医生编写并客观呈现时,可信度会增加。我们的研究结果通过探索影响一个人对在线健康信息的可信度评估的因素来解决文献中的空白,提供可以为未来在线健康资源的设计提供信息的见解。
更新日期:2024-09-08
中文翻译:
识别在线健康信息可信度评估中的外围线索
在线健康信息各不相同,人们选择消费和相信的内容也各不相同。以前的研究发现,不愿遵循健康建议通常是由于对可信度的怀疑。阐述似然模型表明可信度评估同时使用论点质量和来源可信度。要了解人们如何以及为什么坚持有关健康建议的错误信息,一个重要的方面是首先揭示驱动他们可信度评估的原因。然而,很少有研究关注哪些外围线索会影响在线健康信息来源的可信度。我们的混合方法研究结合了在线实验和定性分析,探讨了来源、语气和格式如何影响健康环境中的可信度感知。结果证实了 ELM 关系,并表明当信息由医生编写并客观呈现时,可信度会增加。我们的研究结果通过探索影响一个人对在线健康信息的可信度评估的因素来解决文献中的空白,提供可以为未来在线健康资源的设计提供信息的见解。