Compulsive smartphone use among older adults may be linked to a greater risk of depression, according to a new study led by researchers at Rutgers University. While smartphones are often promoted as tools for staying connected, the findings suggest their effects on mental health depend less on the technology itself than on how it is used. Researchers found that smartphones can strengthen relationships when they encourage meaningful communication, but may contribute to isolation when they become a substitute for real-world social interaction. “It comes down to purposeful interaction versus compulsive escapism,” said senior author Chien-Chung Huang, a professor at the Rutgers School of Social Work. “The same device can bridge the gap to loved ones and community or serve as a wall to shut them out.”
Published in JMIR Aging, the study analysed survey data from 2,585 adults aged 60 and older living in Guangzhou, China. Participants reported their smartphone habits, communication preferences and levels of offline social participation, while researchers also collected demographic and health information and assessed depressive symptoms using a validated screening tool. The research team, including collaborators from Guangdong University of Foreign Studies, applied machine learning techniques to identify the factors most strongly associated with depression and uncover patterns that traditional statistical methods might overlook.
Limited social participation emerged as the strongest predictor of depression, followed closely by smartphone addiction, defined as excessive or compulsive phone use that interferes with daily life. Older adults who rarely used interactive smartphone features, such as messaging or video calls, appeared particularly vulnerable. In contrast, using smartphones to maintain relationships through video chats, text messaging and photo sharing was associated with better well-being. Long periods spent scrolling, watching videos or playing games alone, however, were linked to social withdrawal and higher levels of depressive symptoms. “When an older adult uses their phone as a shield to substitute or displace real-life social participation, it acts as a major red flag for depression,” Huang said.
The researchers also identified two groups that appeared especially vulnerable. One included older men with lower levels of education who showed signs of smartphone addiction. Huang suggested that limited digital literacy may make it harder for some older adults to use communication-focused applications, increasing reliance on passive entertainment instead. Men who depend heavily on a spouse for social connection may be particularly at risk if they later experience bereavement or isolation, leaving smartphones to become “an isolating crutch rather than a bridge.”
A second high-risk group consisted of older adults with higher incomes and education levels who also exhibited problematic smartphone use. The findings suggest that financial resources, educational attainment and access to technology alone do not protect against depression when screen time replaces meaningful face-to-face relationships. However, the researchers cautioned that the study cannot determine whether excessive smartphone use contributes to depression, whether depression encourages greater phone use, or whether both reinforce one another over time.
Huang believes the relationship is likely cyclical, with lonely older adults turning to their phones for distraction while gradually replacing the social interactions that help protect mental health. Rather than discouraging smartphone use, he said families, community organisations and healthcare providers should encourage older adults to use technology in ways that strengthen relationships. Activities such as participating in family group chats, sharing photos and scheduling regular video calls can help transform smartphones from tools of passive entertainment into platforms for meaningful social connection and healthier ageing.
More information: Sheng Chen et al, Smartphone Addiction, Use Preferences, and Depression Among Older Adults in the Digital Context: Machine Learning Analysis of Survey Data, JMIR Aging. DOI: 10.2196/84703
Journal information: JMIR Aging Provided by Rutgers University
