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Information Architects: Using Community-Engaged and Qualitative Methods to Design a Technology-Based Nutrition and Cancer Risk Intervention for Rural Adults. | LitMetric

Background: Nearly half of all cancer deaths are preventable through modification or avoidance of key risk factors. As such, there is a growing urgency to identify effective, low-resource, and scalable technologies that support clinical care and patient self-management of health behaviors.

Purpose: Informed by theories of cognitive load and user-centered design approaches, we develop a culturally tailored, multicomponent digital intervention to engage rural adults between 50-73 years old with their personalized nutrition risk factors for colorectal cancer (CRC) prevention.

Method: A total of 48 adults tested a Virtual Health Assistant (VHA) prototype during focus groups in individual think-aloud interviews to facilitate iterative adaptations to a web-based CRC prevention intervention. Qualitative data was analyzed to identify user needs and preferences related to information and with a focus on avoiding cognitive overload.

Results: The VHA serves as a conceptual pre-training for users helping them understand CRC prevention key concepts and engendering motivation to act on the promoted behavior. A website was identified as a strategy to fill information gaps and present actionable information, after the VHA interaction. Cognitive load reducing strategies were used including segmenting where information is presented in learner-controlled segments rather than continuously.

Conclusions: Findings indicate potential benefits of designing CRC prevention information technologies with the rural older adults. Integrating patient-centered needs before launching health information web content will be important as the rapid growth of telemedicine aims to reach traditionally marginalized and underserved populations. Theoretically informed considerations for potential adverse outcomes (eg, information overload) are discussed.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10017944PMC
http://dx.doi.org/10.1177/10732748221130162DOI Listing

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