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Bridging the Digital Divide for Older Adults via Observational Training: Effects of Model Identity from a Generational Perspective

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  • Qi Ma

    (School of Public Administration, Beihang University, Beijing 100191, China)

  • Alan H. S. Chan

    (Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon Tong, Hong Kong)

  • Pei-Lee Teh

    (School of Business, Gerontechnology Laboratory, Monash University Malaysia, Selangor Darul Ehsan 47500, Malaysia)

Abstract

The proliferation of technology offers potential solutions for enhancing the well-being of older adults. However, older adults often have low digital literacy and are disengaged from the digital world. With age-appropriate training, older adults are expected to acquire a wide range of technological skills and bridge the digital divide. Through the lens of social cognitive theory, this study aims to investigate the effectiveness of observational training through behavior modeling in enhancing technology acceptance in older adults. The moderating effects of model identity on training outcomes from a generational perspective are examined. An empirical training experiment was completed with 59 community-dwelling older adults. Training outcomes were measured using cognitive knowledge, affective variables, and meta-cognition. The results ascertain the effectiveness of observational training in improving their technological knowledge, self-efficacy, outcome expectations, and sense of social connectedness when using technologies. From a generational perspective, the older adult behavior model is more effective than the young or child behavior models in increasing self-efficacy and willingness to use technology. The model identity further enhances the positive outcomes of training. The results of this study contribute to designing educational interventions to bridge the digital divide.

Suggested Citation

  • Qi Ma & Alan H. S. Chan & Pei-Lee Teh, 2020. "Bridging the Digital Divide for Older Adults via Observational Training: Effects of Model Identity from a Generational Perspective," Sustainability, MDPI, vol. 12(11), pages 1-24, June.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:11:p:4555-:d:366753
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    References listed on IDEAS

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    Cited by:

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    3. Hao Cheng & Keyi Lyu & Jiacheng Li & Hoiyan Shiu, 2021. "Bridging the Digital Divide for Rural Older Adults by Family Intergenerational Learning: A Classroom Case in a Rural Primary School in China," IJERPH, MDPI, vol. 19(1), pages 1-16, December.
    4. Milad Shahvaroughi Farahani, 2024. "Applications of Artificial Intelligence in Social Science Issues: a Case Study on Predicting Population Change," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 3266-3296, March.
    5. Sonia Casillas-Martín & Marcos Cabezas-González & Ana García-Valcárcel Muñoz-Repiso, 2020. "DigiCraft: A Pedagogical Innovative Proposal for the Development of the Digital Competence in Vulnerable Children," Sustainability, MDPI, vol. 12(23), pages 1-15, November.
    6. Kwok-kin Fung & Shirley Suet-lin Hung & Daniel W. L. Lai & Michelle H. Y. Shum & Hong-wang Fung & Langjie He, 2023. "Access to Information and Communication Technology, Digital Skills, and Perceived Well-Being among Older Adults in Hong Kong," IJERPH, MDPI, vol. 20(13), pages 1-11, June.
    7. Marielle Schirmer & Katharina Dalko & Dietrich Stoevesandt & Denny Paulicke & Patrick Jahn, 2023. "Educational Concepts of Digital Competence Development for Older Adults—A Scoping Review," IJERPH, MDPI, vol. 20(13), pages 1-18, June.

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