Comparing Transactional eHealth Literacy of Individuals With Cancer and Surrogate Information Seekers: Mixed Methods...

Area of Science:

• Oncology
• Health Informatics
• Digital Health

Background:

• Rising cancer diagnoses necessitate understanding patient and support network information-seeking behaviors.
• Individuals with cancer and their support networks (surrogate seekers) increasingly rely on the internet for health information.
• Limited research exists on the differences in eHealth literacy and information evaluation strategies between these groups.

Purpose of the Study:

• To compare the eHealth literacy of individuals with cancer and surrogate seekers.
• To investigate how each group assesses the credibility of online cancer information.
• To explore sociodemographic differences between individuals with cancer and surrogate seekers regarding eHealth literacy.

Main Methods:

• A web-based survey was administered to 282 participants (185 individuals with cancer, 97 surrogate seekers).
• Hierarchical linear regression analyzed differences in functional, communicative, critical, and translational eHealth literacy using the Transactional eHealth Literacy Instrument.
• A convergent, parallel mixed methods design included thematic content analysis of open-ended responses to understand information evaluation processes.

Main Results:

• No significant differences in overall eHealth literacy scores were found between individuals with cancer and surrogate seekers after adjusting for sociodemographics.
• Both groups prioritize the information channel (e.g., NIH) for credibility.
• Surrogate seekers more frequently evaluated the scientific references of online information, while individuals with cancer were more likely to cross-reference multiple sources.

Conclusions:

• Differences in evaluating web-based cancer information exist between individuals with cancer and surrogate seekers.
• Future web-based cancer education interventions should consider these distinct evaluation strategies.
• Further research with stratified recruitment and contextual factors is recommended to understand unique population circumstances.