To enhance adherence to cognitive training and improve intervention outcomes through a community-based social embedding implementation strategy.

Research purposes

To enhance adherence to cognitive training and improve intervention outcomes through a community-based social embedding implementation strategy.

Research content

1. Collaborate with stakeholders to design social embedded implementation strategies
2. Sequential multiple allocation randomized trials were used to individually verify the effectiveness of the implementation strategy

1. Collaborate with stakeholders to design social embedded implementation strategies ; for the obstacles and promotion factors of digital cognitive training for the elderly identified by the project team, collaborate with community health service center healthcare workers, social workers and elderly volunteers, mild cognitive impairment The elderly and their families, and multiple stakeholders based on behavior change technology to jointly design, develop and implement strategies.
2. Using sequential multi-allocation randomized trials, individualized verification of the effectiveness of the implementation strategy; according to the participants’ compliance with digital cognitive training at different stages, individualized and adaptive adjustment of the implementation strategy to evaluate the differences in the compliance of different strategies to improve the elderly’s digital cognitive training and improve cognitive function.

Wu, M., Feng, J., Sun, R., Zhang, S., Zhang, Y., Yang, F., Zhang, X., Ye, Y., Gong, N., and Liao, J. *, 2025. Validity and usability for digital cognitive assessment tools to screen for mild cognitive impairment: a randomized crossover trial. Journal of NeuroEngineering and Rehabilitation, 22, pp.132

Zhang, S., Wu, M., Sun, R., Cui, C., Zhang, Z., Liao, J.* and Gong, N., 2025. Exploring the discontinuous usage behavior of digital cognitive training among older adults with mild cognitive impairment and their family members: qualitative study using the extended model of IT continuance. Journal of Medical Internet Research, 27, pp.e66393