Digital technologies-enhanced older adults health management: developing a five-dimensional extension of social learning theory for community settings

Background: Against intensifying global aging, digital technologies are pivotal in supporting older adults’ health management. However, older adults often encounter significant barriers within social learning environments. Bandura’s Social Learning Theory (SLT) offers a valuable framework for enhancing older adults’ capacity to utilize digital technologies in health management within social settings. This study extends SLT by developing a novel community-based perspective, aligning it more closely with the social learning needs of older adults in digital health management. This study also responds to calls for culturally adaptable digital health frameworks by examining how Bandura’s SLT operates within Macao’s unique socio-cultural context while exploring transferability to low- and middle-income countries. Methods: 20 older adults were interviewed in semi-structured focus groups during four community health events in Macao. Guided by the core constructs of SLT, five dimensions—self-efficacy, observational learning, outcome expectations, reinforcement mechanisms, and environmental support—were predefined. Deductive thematic coding was employed to map interview data onto these dimensions, ultimately constructing a theoretical model. Results: The findings reveal that the five SLT dimensions interactively influence older adults’ adoption of digital health technologies. Younger seniors (60s) exhibit stronger observational learning tendencies than older seniors (80s). Living situation impacts environmental support utilization, as those living alone (75%) demonstrate greater reliance on community resources. Key enabling factors include technological usability, social trust-building, optimized incentive mechanisms, emotional support, and improved physical environments. These results validate and expand the applicability of SLT in the digital health domain for older adults. Conclusion: This study develops an environmentally adaptive SLT framework centered on older adults. While the model demonstrates strong contextual relevance in Macao, its core mechanisms show potential for adaptation in low- and middle-income countries through localized reinforcement strategies and infrastructure investment. The findings provide theoretical insights into the social mechanisms of digital health adoption and practical guidance for designing inclusive digital health interventions. Future research should explore personalized digital tools and conduct longitudinal studies to evaluate the long-term effectiveness of technological interventions.