Unlocking the Power of Peer Support in Digital Use and Digital Health Interventions for Older Adults: A Scoping...

To summarise peer support in digital use and digital health interventions for older adults.

The following databases were searched (from 2010 to 2024): PubMed, Embase, Web of Science, the Cochrane Library and EBSCOhost.

This review is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. All articles selected and extracted were double-checked. The data were analysed using the inductive descriptive approach and presented in table and narrative form.

This review included 21 studies involving adults aged 60 or older, primarily from developed countries, and focused on the post-21st century. Peer support included peer digital support through face-to-face or online, peer-led or coached in digital intervention, peer motivation and companionship in digital health interventions, group-based mutual support through social media and online health platforms through websites or apps. The social cognitive theory was the common theoretical framework. Most studies indicate high feasibility, acceptability and effectiveness in six health domains. It facilitated information and behaviour exchange, improved mental health, enhanced social support, increased cost-effectiveness and adherence. However, some studies have shown ineffectiveness, influenced by peer support design issues, negative social norms, technological issues, network size and study design limitations. Besides, qualitative results indicated positive experiences enhanced personal worth and social connection, while negative experiences involved technological barriers, emotional burdens, privacy issues and lack of recognition.

Peer support represents a valuable complement to existing digital use and digital health interventions for older adults, with important implications for practices in healthcare and outcomes.

Further research should optimise peer support, maintain bi-directional relationships, explore mechanisms of influence, analyse cost-effectiveness, utilise machine-learning algorithms, apply digital peer support to more health domains and call for healthcare providers to develop relevant policies or strategies.

No patient or public contribution.