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

Authors

  • Basma Badreddine Macquarie Business School, Sydney, Australia
  • Yvette Blount Deakin University, Melbourne, Australia
  • Alireza Amrollahi Macquarie Business School, Sydney, Australia

DOI:

https://doi.org/10.3127/ajis.v27i0.4435

Keywords:

Cancer Podcasts, Information Systems’ Quality, Content, Credibility, Design, Reception Theory

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.

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Published

2023-12-26

How to Cite

Badreddine, B., Blount, Y. ., & Amrollahi, A. (2023). Integrating Users’ Perceptions to Identify Features Indicating the Quality of Cancer-Related Podcasts Provided by Non-Profit Cancer Organisations. Australasian Journal of Information Systems, 27. https://doi.org/10.3127/ajis.v27i0.4435

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Selected Papers from the Australasian Conference on Information Systems (ACIS)