What Older Adults Read: Data Mining of Patterns and Types of Reading among the Elderly

Document Type : Original Article

Authors

• Mostafa Ahangar ¹
• Davoud Haseli ²
• Nosrat Riahinia ³

¹ PhD Candidate in Knowledge and Information Science, Faculty of Psychology and Education, Kharazmi University, Tehran, Iran.

² Assistant Professor, Department of Knowledge and Information Science, Faculty of Psychology and Education, Kharazmi University, Tehran, Iran

³ Professor, Department of Knowledge and Information Science, Faculty of Psychology and Education, Kharazmi University, Tehran, Iran.

10.22067/infosci.2025.88480.1210

Abstract

Introduction: Older adults encounter a range of challenges associated with the aging process, including loneliness, diminished social support, and cognitive decline. Engaging in reading as a leisure activity has been shown to play a significant role in alleviating these challenges by fostering mental stimulation, enhancing overall health, and improving the quality of life. Public libraries, as hubs of information and culture, are well-positioned to address the informational needs of older adults and promote their engagement in reading activities. In light of demographic shifts and the growing population of older adults in Iran, this study seeks to examine their reading habits and informational requirements, while offering strategies to optimize public library services for this demographic.
Methodology: This quantitative study utilized data mining techniques to investigate its research questions. The dataset comprised 918,324 book loan records from public libraries in Iran, representing older adults (aged 60 and above) during the period from 2015 to January 2023. Data were retrieved from the Iranian Public Library Management System (Saman software) and subjected to a rigorous six-stage cleaning process to remove irrelevant records, including children’s books, short-term loans, and incomplete data. The final dataset consisted of 30,000 older adults, each with an average of 30 loan records. The collected user data were categorized based on demographic characteristics, including age (young-elder, middle-elder, and old-elder), education level (ranging from elementary to postgraduate), and occupation (homemaker, employee, self-employed, and other). Borrowed books were classified into three main categories: non-literature, Iranian literature, and non-Iranian literature. Data analysis was performed using Excel, SPSS version 27, and Clementine version 18. The CS5.0 classification algorithm was employed to predict book topics, while the K-Means clustering algorithm was utilized to identify user profiles.
Findings: The study found that older men borrowed more than twice as many books as women, while young-elder adults (aged 60–74 years) borrowed approximately six times more books than individuals in other age groups. Borrowing rates were highest among individuals with secondary and undergraduate levels of education. In terms of occupation, employees and those classified in the "other" category exhibited the most frequent borrowing activity. Regarding subject preferences, literature accounted for the largest proportion of loans (50.17%), followed by history and geography (17.91%) and religion (12.76%). Compared to the general population, older adults demonstrated a heightened interest in history, literature, and religion, alongside a relatively lower interest in the pure sciences, social sciences, and philosophy.
The CS5.0 classification algorithm identified gender (67%) as the most significant predictor of book topics, followed by education (23%), age (5%), and occupation (4%). Among older women, Iranian literature emerged as the primary preference, with education and occupation significantly influencing their reading choices. Women with elementary education showed a tendency toward non-literature topics, whereas those with secondary education or higher exhibited a preference for Iranian literature. Conversely, older men predominantly favored non-literature topics, with this inclination being particularly pronounced among the younger subset of older adults.
The K-Means clustering algorithm identified five distinct reading profiles. The largest clusters, consisting primarily of men with secondary and associate degrees, demonstrated a predominant interest in non-literary works and Iranian literature. Clusters associated with women exhibited preferences for Iranian literature, non-Iranian literature, and non-literary works, with variations influenced by their educational attainment and occupational roles.
Discussion and conclusion: This study investigated the reading habits of older adults in Iran by analyzing public library book loan data, with the aim of identifying their reading behaviors and topic preferences. The findings indicated that young-old adults (aged 60–74) constituted the largest proportion of book borrowers. This trend may be attributed to their comparatively better physical and cognitive health, higher motivation for lifelong learning and social participation, and greater access to library resources. Furthermore, the analysis revealed that older men utilized library services more frequently than older women, a pattern likely influenced by cultural norms, traditional gender roles, and disparities in educational opportunities experienced by earlier generations. 
The thematic analysis revealed that older adults exhibited a pronounced preference for subjects such as history, literature, and religion, while demonstrating comparatively lower interest in disciplines such as the pure sciences, social sciences, philosophy, and psychology. These preferences are likely shaped by their life experiences, emotional and psychological needs, and a tendency to gravitate toward topics that hold personal significance and are deeply connected to the past. 
Data mining techniques identified five distinct reading profiles among older adults. These profiles were associated with demographic variables such as gender, age, education level, and occupation, providing a basis for optimizing library services to meet the specific needs of this group. The results of this research demonstrate that the reading behaviors of older adults are shaped by a complex interplay of social, cultural, and individual factors. These findings can guide librarians, publishers, and cultural policymakers in designing tailored services, programs, and collections to enhance the reading experiences of older adults and increase their engagement with library activities.
Originality: This study employed a data mining methodology to examine the reading patterns of older adults in Iran, a topic that has received limited scholarly attention. By analyzing extensive datasets from the Public Library Management System and applying advanced classification and clustering algorithms, the research identified distinct reading profiles and informational needs among older adults. The findings offer valuable insights into their reading behaviors and hold potential to enhance library services and publishing practices in Iran.

Keywords

• Older adults
• elderly
• reading
• public libraries
• data mining

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