Decoding how the older adults identify misinformation: an analysis of internal mechanisms

Abstract

Introduction. This study aims to explore the key factors influencing misinformation recognition among older adults, understand the internal mechanisms of how they identify misinformation, and ultimately promote age-friendly improvements in the information environment of the AI era.

Method. Using in-depth interviews, we selected 55 misinformation recognition events as research subjects and applied content analysis and binary logistic regression methods.

Analysis. Quantitative content analysis was conducted on interview data, followed by binary logistic regression analysis on nine variables, which were later consolidated into three dimensions.

Results. The findings reveal that public information sources, interpersonal information sources, information content, information perspectives, and evidence significantly impact misinformation recognition. Information sources play a crucial role in older adults' misinformation recognition, while the influence of information dimensions is not fully realized, and the direct impact of the information users’ dimension is limited.

Conclusion. These findings reveal the mechanisms of misinformation identification by older adults, emphasizing the need for age-friendly improvements in information literacy and digital environments to enhance older adults' ability to recognize misinformation.