Investigating Factors Associated with Digital Inclusion Among Older Adults in China: A Latent Profile Analysis

Abstract

This study aimed to investigate the impact mechanism and diversity of digital inclusion among elderly people in China. As digital technologies become ubiquitous, older adults face varying degrees of challenges in adapting to digital life, yet research in this area remains insufficient. The study utilized data from the 2020 China Longitudinal Aging Social Survey (CLASS), including 10,198 participants aged 60 and above. Latent Profile Analysis (LPA) was employed to identify different types of digital inclusion, and multinomial logistic regression was used to analyze the influence of various factors on digital inclusion types. LPA identified four types of digital inclusion: Class 1(utilitarian type ,14.4%), Class 2(social type, 18.1%), Class 3(digital disabled type, 35.4%), and Class 4(highly adaptive type, 32.1%). Multinomial logistic regression analysis revealed that factors such as age, education level, family annual income, hukou status, living alone status, cognitive ability, Internet access, and age-friendly design significantly influenced different types of digital inclusion. Notably, cognitive ability and Internet access negatively affected all classes. Age-friendly design negatively impacted Classes 1 and 2 but positively influenced Class 3. Regarding psychosocial variables, self-efficacy had a slight but significant negative effect on Class 3, while social support positively influenced Class 2 but negatively affected Class 3. This study reveals the complex factors influencing digital adaptability among elderly Chinese people, highlighting the diverse needs and challenges faced by different groups when engaging with digital technology. These findings have important implications for developing targeted digital inclusion policies and interventions to better integrate older adults into the digital society.