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To Do or Not to Do: How Socio-demographic Characteristics of Older Adults Are Associated with Online Activities

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 12209)

Abstract

Older adults use the Internet for a broad range of purposes including interpersonal communication, errands, and leisure. Although barriers towards physical access to the digital world have diminished, relevant subgroups of older adults still lack the digital skills required for diverse online activities. While understanding this second-level digital divide is an active field of research, the results of previous studies are less conclusive in the factors that explain whether one belongs to the group of users or nonusers. We posit that the accumulation of knowledge from empirical quantitative studies is undermined by considerable heterogeneity in the reporting of logistic regression analysis, for which we provide evidence in the extant literature. We then explore the usefulness of socio-demographic characteristics in explaining various online activities. Our results (1) highlight different roles of education and living arrangement in explaining informational, social, and instrumental online activities, and (2) underscore the need to provide contextualized information when conducting logistic regression analysis. Taken together, our findings contribute to understanding differentiated online activities in older adults and provide methodological guidance for future studies.

Keywords

Cross-sectional data Digital divide Internet use Logistic regression analysis Older adults Online activities Survey Technology adoption 

Notes

Acknowledgments

The work by Joerg Leukel and Barbara Schehl has been supported by the Federal Ministry of Education and Research, Germany, under grant 16SV7438K. The work by Vijayan Sugumaran has been partially supported by a 2019 School of Business Administration Spring/Summer Research Fellowship at Oakland University. We thank Susanne Wallrafen (Sozial-Holding der Stadt Mönchengladbach GmbH) for her support in conducting the survey.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Faculty of Business, Economics and Social SciencesUniversity of HohenheimStuttgartGermany
  2. 2.Department of Decision and Information SciencesOakland UniversityRochesterUSA

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