Artificial intelligence-based technologies to reduce loneliness and improve social connectedness in older people: A systematic review

Background and objectives Artificial Intelligence (AI) is undergoing a paradigm shift in its application to healthcare, particularly in the context of ageing-related care, with significant implications for disease prevention, diagnosis, and treatment. The integration of advanced machine learning, deep neural networks, and natural language processing has enabled AI to analyze datasets with remarkable accuracy, surpassing the performance of traditional methods. AI-driven approaches have the potential to facilitate early disease detection, predict progression, and personalize treatments, optimizing healthcare resources. Furthermore, AI is contributing to the development of new treatments and supporting public health strategies. The objective is to assess the effectiveness of AI-based interventions for loneliness. Research design and methods This article presents a systematic review using the PRISMA methodology. Databases searched were Pubmed, Web of Science, Scopus and PsycInfo. A total of 19 articles were identified fulfilling the inclusion criteria, and using validated tools to assess loneliness. Studies were summarized indicating: country, sample, design of the study, measures of loneliness, the IA-based technology main findings and implications. Results Findings highlight AI's potential to enhance social well-being among older adults. From a policy perspective, AI-driven analytics enable targeted interventions by identifying trends in age-related health and social issues from the psychology of social intervention. The adoption of AI in ageing policies promotes efficient, inclusive frameworks that support healthy ageing and reduce pressure on traditional healthcare systems. Discussion and implications This study contributes to the growing evidence supporting AI's role in addressing loneliness and improving overall quality of life in ageing populations.