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Measuring the Impact of Bedroom Privacy on Social Networks in a Long-Term Care Facility for Hong Kong Older Adults: A Spatio-Social Network Analysis Approach

Author

Listed:
  • Aria C. H. Yang

    (School of Design, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China)

  • Habib Chaudhury

    (Department of Gerontology, Simon Fraser University, 8888 University Drive Burnaby, Vancouver, BC V5A 1S6, Canada)

  • Jeffrey C. F. Ho

    (School of Design, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China)

  • Newman Lau

    (School of Design, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China)

Abstract

This study aims to measure the impact of bedroom privacy on residents’ social networks in a long-term care (LTC) facility for older adults. Little is known about how the architectural design of bedrooms affects residents’ social networks in compact LTC facilities. Five design factors affecting privacy were examined: bedroom occupancy, visual privacy, visibility, bedroom adjacency, and transitional space. We present a spatio-social network analysis approach to analyse the social network structures of 48 residents. Results show that residents with the highest bedroom privacy had comparatively smaller yet stronger groups of network partners in their own bedrooms. Further, residents who lived along short corridors interacted frequently with non-roommates in one another’s bedrooms. In contrast, residents who had the least privacy had relatively diverse network partners, however, with weak social ties. Clustering analyses also identified five distinct social clusters among residents of different bedrooms, ranging from diverse to restricted. Multiple regressions showed that these architectural factors are significantly associated with residents’ network structures. The findings have methodological implications for the study of physical environment and social networks which are useful for LTC service providers. We argue that our findings could inform current policies to develop LTC facilities aimed at improving residents’ well-being.

Suggested Citation

  • Aria C. H. Yang & Habib Chaudhury & Jeffrey C. F. Ho & Newman Lau, 2023. "Measuring the Impact of Bedroom Privacy on Social Networks in a Long-Term Care Facility for Hong Kong Older Adults: A Spatio-Social Network Analysis Approach," IJERPH, MDPI, vol. 20(8), pages 1-19, April.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:8:p:5494-:d:1122268
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    References listed on IDEAS

    as
    1. Li, Ting & Zhang, Yanlong, 2015. "Social network types and the health of older adults: Exploring reciprocal associations," Social Science & Medicine, Elsevier, vol. 130(C), pages 59-68.
    2. Debra Street & Stephanie Burge & Jill Quadagno & Anne Barrett, 2007. "The Salience of Social Relationships for Resident Well-Being in Assisted Living," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 62(2), pages 129-134.
    3. Katherine L. Fiori & Toni C. Antonucci & Kai S. Cortina, 2006. "Social Network Typologies and Mental Health Among Older Adults," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 61(1), pages 25-32.
    4. Judith M. Mitchell & Bryan J. Kemp, 2000. "Quality of Life in Assisted Living Homes," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 55(2), pages 117-127.
    5. Xinyue Ye & Xingjian Liu, 2018. "Integrating social networks and spatial analyses of the built environment," Environment and Planning B, , vol. 45(3), pages 395-399, May.
    6. Yiqi Tao & Stephen Siu Yu Lau & Zhonghua Gou & Jiayan Fu & Boya Jiang & Xiaowei Chen, 2018. "Privacy and Well-Being in Aged Care Facilities with a Crowded Living Environment: Case Study of Hong Kong Care and Attention Homes," IJERPH, MDPI, vol. 15(10), pages 1-14, October.
    7. Sheung-Tak Cheng & Coty K. L. Lee & Alfred C. M. Chan & Edward M. F. Leung & Jik-Joen Lee, 2009. "Social Network Types and Subjective Well-being in Chinese Older Adults," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 64(6), pages 713-722.
    8. Philip D. Sloane & C. Madeline Mitchell & Gerald Weisman & Sheryl Zimmerman & Kristie M. Long Foley & Mary Lynn & Margaret Calkins & M. Powell Lawton & Jeanne Teresi & Leslie Grant & David Lindeman & , 2002. "The Therapeutic Environment Screening Survey for Nursing Homes (TESS-NH)," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 57(2), pages 69-78.
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