Application of the IDEAS Framework in Adapting a Web-Based Physical Activity Intervention for Young Adult College Students.
Kimberly R HartsonLindsay J DellaKristi M KingSam LiuPaige N NewquistRyan E RhodesPublished in: Healthcare (Basel, Switzerland) (2022)
User-centered developmental processes are critical to ensuring acceptability of e-health behavioral interventions, and yet physical activity research continues to be inundated with top-down developmental approaches. The IDEAS (Integrate, Design, Assess, and Share) framework outlines a user-centered process for development of e-health interventions. The purpose of this manuscript is to describe the application of the IDEAS framework in adapting a web-based physical activity intervention for young adult college students. Steps 1-3 emphasized integrating insights from users and theory and Steps 4-7 focused on iterative and rapid design with user feedback . Data were collected via repeat qualitative interviews with young adult college students ( N = 7). Resulting qualitative metathemes were engagement, accountability, and cultural fit. Therefore, intervention modifications focused on strategies to foster ongoing engagement with the program (e.g., increase interactivity), support personal and social accountability (e.g., private social media group), and provide a cultural fit within the college lifestyle (e.g., images relevant to student life). The resulting web-based intervention included eight weekly lessons, an expanded resource library, "how-to" videos, step and goal trackers, and a private social media group to be led by a wellness coach. In conclusion, the IDEAS framework guided an efficient, user-centered adaptation process that integrated empirical evidence and behavior change theory with user preferences and feedback. Furthermore, the process allowed us to address barriers to acceptability during the design and build stages rather than at later stages of pilot and efficacy testing.
Keyphrases
- social media
- physical activity
- health information
- young adults
- healthcare
- randomized controlled trial
- public health
- mental health
- body mass index
- cardiovascular disease
- sleep quality
- study protocol
- childhood cancer
- deep learning
- metabolic syndrome
- type diabetes
- climate change
- convolutional neural network
- big data
- magnetic resonance
- health promotion
- medical education
- artificial intelligence
- data analysis