The global phenomenon of population ageing presents significant challenges. According to the World Health Organization (WHO), by 2030, one in six people worldwide will be aged 60 years or older. During this period, the proportion of the population aged 60 and above is projected to rise from 1 billion in 2020 to 1.4 billion. By 2050, the global population of individuals aged 60 and older is expected to double, reaching 2.1 billion. Among those aged 65 and above, an increasing proportion live alone, defined as those without spouses or children for companionship. This trend is becoming more prevalent across various countries due to demographic shifts and evolving social structures.

In Australia, approximately 25.4% of individuals aged 65 and over live alone (Rodwell, 2022). Similarly, in South Korea, the number of older adults living alone surged to 1.379 million in 2015, reflecting a 1.8-fold increase since 2005, with projections estimating a rise to 3.43 million by 2035—constituting 23.2% of the older adult population (Byeon, 2021a). In Japan, more than 15% of older adults lived alone as of 2005 (Sun et al., 2007). Both cross-sectional and longitudinal studies (Blanchard et al., 2003) indicate that older adults living alone face a higher risk of disability, mental health issues, and cognitive decline compared to those living with spouses or others (Koukouli et al., 2002; van Gelder et al., 2006; You and Lee, 2006). Due to their heightened need for social support and long-term care, this specific population encounters challenges such as difficulty managing emergencies, loneliness, and daily living struggles. Consequently, developing tailored health management strategies for older adults living alone—based on their unique characteristics and needs—has become a pressing societal concern (Baines and Hollingsworth, 1955).

In recent years, the growing population of older adults living alone has attracted increasing research attention, gradually establishing this as an emerging research focus. However, a systematic and comprehensive analysis of this field remains lacking. Bibliometrics, a branch of informatics, examines document structures and quantitative characteristics to perform both quantitative and qualitative analyses (Ninkov et al., 2022). This approach enables measurement of profile distributions, relationships, and clustering within research fields while comparing contributions across authors, institutions, countries, and journals (Hassan and Duarte, 2024). Recognized as crucial for developing guidelines, identifying research hotspots, and assessing trends, bibliometrics provides valuable insights into resource management, research collaboration, developmental trajectories, and journal impacts - making it particularly suitable for analyzing research concerning older adults. For example, Hong et al. (2022) conducted a bibliometric analysis of smart home technologies for older adults, demonstrating how well-designed smart homes can support aging-in-place preferences while generating economic benefits through reduced care expenditures. Similarly, Marziali et al. (2024) performed a bibliometric review of voice assistant technologies, highlighting their potential to mitigate loneliness and social isolation among older adults. Additional applications include, Zhang et al. (2023)’s investigation of oral health’s relationship to quality of life in aging populations, and Tan et al. (2021)’s examination of cardiovascular disease’s association with sarcopenia and subsequent disability risks. Given the distinct challenges faced by older adults living alone - including reduced quality of life, increased mental health vulnerability (Park et al., 2023a; Park et al., 2023b), and limited social support networks (Yeh and Lo, 2004), - a comprehensive bibliometric analysis of this field is urgently needed. Such an analysis would provide valuable insights into current research trends and facilitate better understanding of developments concerning this vulnerable population.

The advancement of electronic technologies, including infrared wireless sensors and artificial intelligence, has led to increasing applications of smart devices such as wearable bracelets and smart speakers (Park and Kim, 2022) for monitoring older adults living alone and preventing falls and other accidents (O’Brien et al., 2020; Alharbi et al., 2023). This study employs CiteSpace (version 6.4.R1 Advanced) to examine global research trends, core research foci, and scientific frontiers concerning older adults living alone. Through analysis of recent literature and citation networks, we identify leading research institutions, their collaborative networks, and emerging thematic trends in this field. Using bibliometric methods, we systematically analyze current research progress on older adults living alone. Our study aims to establish a solid scientific foundation for future research, with the dual objectives of expanding scholarly understanding and facilitating further investigations in this important area.

Our study analyzed the literature on older adults living alone from 1965 to 2024. The increasing trend in publications reflects sustained scholarly interest and advancements in research on solitary aging. Notably, publications grew gradually from 2008 to 2017 before rising sharply after 2017, indicating heightened academic and practical engagement with this topic. This trend aligns with the earlier rapid growth in the proportion of older adults living alone, underscoring the importance of synthesizing research in this field.

Globally, South Korea and China lead in research on solitary older adults, excelling in scientific output, publication volume, and academic influence. In South Korea, institutions such as Seoul National University (SNU) and Yonsei University have laid a strong foundation for this research area. In China, the high publication output and contributions from scholars like Chen Y at Fudan University highlight the country’s significant role. Although the United Kingdom produces fewer publications, institutions like the University of London play a key role in international collaborations. Conversely, the United States and Japan have substantial publication volumes but exhibit limited cross-border collaboration, with no single institution dominating domestic output.

Researchers such as Park YH, Chang SJ, and Byeon H have made prolific contributions, demonstrating substantial influence in the field. Park YH, for instance, advocates for community-based integrated service (CBIS) models grounded in Aging-in-Place (AIP) principles to better support the health and daily living needs of solitary older adults. Additionally, the highly cited works of Lawton MP and Kharicha K exemplify the impact of influential, high-quality research in advancing this discipline.

The keyword cluster analysis yielded several significant insights. Based on these findings, we further categorized the keywords and examined their relationships across five domains: emerging technologies, disease status, research methods, intervention variables, and smart systems. This comprehensive analysis provides a holistic perspective on current research trends while offering targeted directions for future studies. In the emerging technologies category, high-frequency terms such as “machine learning,” “ambient intelligence,” “deep learning,” and “wireless sensor network” indicate the growing prominence of AI-IoT integration in health monitoring and care for older adults living alone (Rajasekaran et al., 2009; Byeon, 2021b). The disease conditions category featured prevalent terms including “depression,” “mental health,” “dementia,” and “Alzheimer’s disease,” underscoring substantial academic focus on mental health and cognitive impairment among solitary older adults - a critical concern in aging societies (Cermakova et al., 2017; Tamminen et al., 2019; Koo et al., 2021). Analysis of research paradigms revealed common keywords like “prevalence,” “association,” “risk factors,” “validity,” and “thematic analysis,” demonstrating an evolution from descriptive studies to more sophisticated correlational and empirical investigations, marking methodological maturation in the field (Yang et al., 2023; Park et al., 2025). Among intervention variables, predominant terms such as “living alone,” “social support,” “care,” and “quality of life” highlight the centrality of social support systems in enhancing wellbeing for this population (Renwick et al., 2020). The intelligent systems category featured keywords including “activity recognition,” “ambient assisted living,” “smart homes,” “fall detection,” and “assistive robotics,” illustrating the transformative potential of technology-enabled home care solutions in addressing accessibility and sustainability challenges in elder care (Daniele et al., 2019).

Keywords that experience sudden increases in citations are recognized as indicators of emerging research themes or trends. Our analysis identified multiple research streams within the field of solitary older adults, encompassing a wide array of topics. The majority of studies concentrate on enhancing quality of life, family and social support, intelligent assistive technologies, and social isolation among older adults living alone. As emerging technologies continue to advance, smart devices are expected to play an increasingly prominent role in mitigating loneliness, improving quality of life, and preventing or detecting hazardous events such as falls.

Our keyword citation trend analysis reveals that global research hotspots on solitary older adults can be categorized into five distinct phases. Phase 1 (1965–2003) is characterized by a limited number of publications and weak thematic connections, which explains its absence from the burst keyword timeline.

Phase 2 (2003–2012). Research began focusing on gender-specific studies of solitary older adults, particularly older women, as reflected in keywords such as “older women” and “home.” Health disparities by gender were evident; for instance, a cross-sectional study in Taiwan found that women aged 65 and older living alone faced a 1.6 times higher risk of depression than their male counterparts, especially those over 85 with limited social support (Lin and Wang, 2011). Gender differences also emerged in coping with memory loss, with women with Alzheimer’s disease actively reconstructing self-awareness (Frazer et al., 2012). Familial dependence was pronounced, with many older adults preferring to age and die at home, influenced by their physical environment, socioeconomic conditions, and access to care (Rolls et al., 2011). This phase thus emphasized more nuanced, gender-sensitive research.

Phase 3 (2013–2017). Research shifted toward enhancing quality of life and societal support for solitary older adults, as indicated by keywords like “support,” “quality of life,” “disability,” and “ambient assisted living.” A central focus was maintaining independence despite health challenges. Studies highlighted that depression and social isolation were more prevalent among those lacking support, leading to poorer quality of life (Lee and Kim, 2014; Parlar Kilic et al., 2014; Arslantas et al., 2015; McHugh et al., 2015). Effective interventions mitigated loneliness and improved dietary, physical, and mental health (Bilotta et al., 2012; McHugh et al., 2015). Disability research advocated for better healthcare access and non-emergency transport to prevent treatment delays (Henning-Smith et al., 2016).

Phase 4 (2018–2020). This phase was marked by the rise of electronic and wearable technologies, with keywords such as “fall detection,” “network,” “system,” and “machine learning.” Smart devices leveraging IoT, sensors, and AI enhanced safety and quality of life (Huh, 2018; Wang et al., 2019).

Phase 5 (2021–2024). Attention returned to physical and mental health, with keywords like “social isolation,” “aging in place,” and “intervention.” AI advancements enabled precise applications for improving social support and quality of life, addressing heightened risks of cognitive decline and depression (Lee et al., 2020). Technologies such as infrared sensors (Wang et al., 2022; Yang et al., 2022), IoT (Luperto et al., 2023), deep learning (Khraief et al., 2020), and wearable devices has progressed rapidly, providing tools for social support and cognitive improvement (Choi et al., 2022). AI-based home devices alleviated depression and loneliness (Park and Kim, 2022; Yan et al., 2024). while psychological and neurodegenerative issues received renewed focus (Parlar Kilic et al., 2014; Breaz, 2019; Charpentier and Kirouac, 2022). Strategies to improve life satisfaction were urged (Hou and Zhang, 2023). Non-technological factors, like pet ownership, were also explored; a cohort study found pets slowed verbal memory decline (Li et al., 2023). Another study further indicated that pet companionship may enhance wellbeing in this population, thereby mitigating feelings of loneliness and cognitive decline (Stanley et al., 2014). Notably, research employing AI-powered robotic pets has shown that integrating these companions into daily life—while iteratively refining their design based on user feedback—can effectively reduce loneliness and facilitate social engagement among isolated older adults with limited social connections (Hudson et al., 2020). Sum up this phase emphasized intelligent technologies and cognitive health in elder care.

Several crucial research hotspots—including “living arrangements,” “living alone,” “daily rhythm,” “intervention,” “climate change,” “care,” “general practitioner,” “elderly caregiving microsystem,” and “nutrient intakes”—are not prominently featured in visual maps but remain significant. Among these, studies on malnutrition, living arrangements, and daily rhythms are particularly noteworthy. Malnutrition represents a global health risk for older adults. A Norwegian cross-sectional study revealed that older adults living alone struggle to maintain adequate nutrition through self-care activities (Tomstad et al., 2012), highlighting the need for healthcare professionals to identify at-risk individuals and provide nutritional guidance. Furthermore, loneliness is a significant predictor of anorexia nervosa, malnutrition, and malnutrition risk (Ramic et al., 2011), suggesting that reducing loneliness may improve both nutritional intake and quality of life.

Consistent evidence indicates that older adults living alone have poorer nutritional intake than their married counterparts (Pequignot et al., 1967; Yamagami et al., 1998; Charlton, 1999; Hsieh et al., 2010; Tomstad et al., 2012). For instance, an Israeli policy survey found that low-income solitary men consumed fewer vegetables, fruits, and vitamin C than those with partners (Guggenheim and Margulec, 1965). Given that vitamin C deficiency increases scurvy risk, living alone emerges as an independent risk factor for poor nutrition in older adults (Oulie, 1988). Given that vitamin C deficiency increases scurvy risk, living alone emerges as an independent risk factor for poor nutrition in older adults.

Positive living arrangements and structured daily rhythms significantly influence the physical and mental health of older adults living alone. Daily activities typically encompass social interactions, physical exercise, hobbies, and community-based engagements (Cederbom et al., 2014). Research indicates that solitary older adults tend to exhibit lower physical activity levels and higher body fat percentages, increasing their susceptibility to hypertension, deep vein thrombosis, and other cardiovascular conditions (Kong and So, 2017). Implementing regular physical activity regimens, such as Tai Chi, Baduanjin, and walking, has been shown to enhance mental health, reduce loneliness and depression, and strengthen social connections, thereby fostering a greater sense of dignity among this population (Wu et al., 2024). Intervention programs like forest therapy in Korea have demonstrated dual benefits by addressing psychological loneliness while promoting healthier lifestyles, consequently reducing dementia risk (Jin and Son, 2018b; Jin and Son, 2018a). Similarly, structured community activities—including group exercises and art projects—have proven effective in improving both physical and mental wellbeing (Kil et al., 2018; Kim et al., 2018; Aydin and Kutlu, 2021; Beselt et al., 2023). Collectively, these findings underscore the critical role of maintaining positive living arrangements and consistent daily routines, which not only enhance functional independence but also facilitate meaningful social interactions. Such insights highlight daily schedules and living environments as viable targets for interventions aimed at supporting solitary older adults.

In summary, our bibliometric analysis of literature spanning 1965 to 2024 elucidates key trends and emerging themes in research on older adults living alone. This synthesis underscores the field’s evolution, advocating for multidisciplinary collaboration and innovative integration of intelligent technologies to address this population’s complex needs. By combining supportive living environments with proactive healthcare strategies, future efforts can deliver more compassionate and effective care solutions.