Integrating Users’ Perceptions to Identify Features Indicating the Quality of Cancer-Related Podcasts Provided by Non-Profit Cancer Organisations

IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Basma M. Badreddine, Yvette Blount, Alireza Amrollahi
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引用次数: 0

Abstract

While cancer podcasts are valuable for support and information, there is a significant gap in understanding their quality features from users’ perspectives. Understanding quality features from users’ perspectives is important to ensure that cancer-affected people receive the support they need. This study addresses this gap by combining multiple theoretical perspectives: a. the IQ assessment framework, source credibility theory, two-factor theory of website design to assess the quality of podcasts, and b. reception theory to highlight listeners’ perception of quality. These perspectives, together, enrich the concept of information systems quality and provide a comprehensive understanding of podcasts’ quality. Through semi-structured interviews with 17 cancer-affected individuals, the research found that credibility, content, and design were essential quality features, with the visual appearance serving as a motivational factor. The integration of Reception Theory highlights users’ active role in shaping quality perceptions, offering new insights into the effective design of cancer-related podcasts. This novel approach bridges a critical research gap, illuminating the complex interplay of technical and human factors in assessing podcast quality from the perspective of users.
整合用户感知,识别非营利癌症机构提供的癌症相关播客的质量特征
虽然癌症播客在提供支持和信息方面很有价值,但从用户的角度来了解其质量特点还存在很大差距。从用户角度了解播客的质量特征对于确保癌症患者获得所需的支持非常重要。本研究通过结合多种理论视角来弥补这一不足:a. 智商评估框架、来源可信度理论、网站设计双因素理论来评估播客的质量;b. 接收理论来强调听众对质量的感知。这些观点共同丰富了信息系统质量的概念,为全面了解播客的质量提供了依据。通过对 17 名癌症患者进行半结构式访谈,研究发现可信度、内容和设计是质量的基本特征,而视觉外观则是激励因素。接受理论的整合强调了用户在形成质量感知方面的积极作用,为有效设计癌症相关播客提供了新的见解。这种新颖的方法弥补了一项关键的研究空白,从用户的角度阐明了在评估播客质量时技术因素和人为因素之间复杂的相互作用。
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来源期刊
Australasian Journal of Information Systems
Australasian Journal of Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
4.40
自引率
4.80%
发文量
20
审稿时长
20 weeks
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