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Women's health and the internet: understanding emerging trends and implications

Author

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  • Pandey, Sanjay K.
  • Hart, John J.
  • Tiwary, Sheela

Abstract

Internet has become a major information source, yet little is known about why women use the internet for obtaining health information. In this paper, we propose and test three exploratory models to explain internet use for obtaining health information: health and wellness model, health needs model, and search costs model. The health and wellness model is based on the notion that internet has become such an integral part of daily life that health-conscious women use the internet in a pro-active manner for health promotion. The health needs model posits that women with greater health needs or concerns are more likely to use the internet. Finally, the search costs model explores the idea that women may view the internet as a resource for reducing high information search costs. These models were tested using data collected through telephone surveys of women in three southern New Jersey counties in the USA. Consistent with expectations, our findings show that internet use to search for health information is greater among women with higher levels of income and education. There is support for all three models, with surprisingly strong support for the health and wellness model. We conclude that women increasingly rely on the internet to supplement health information received from traditional sources and discuss the implications of our findings for policymakers and health professions.

Suggested Citation

  • Pandey, Sanjay K. & Hart, John J. & Tiwary, Sheela, 2003. "Women's health and the internet: understanding emerging trends and implications," Social Science & Medicine, Elsevier, vol. 56(1), pages 179-191, January.
  • Handle: RePEc:eee:socmed:v:56:y:2003:i:1:p:179-191
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    Cited by:

    1. Wu, Haitao & Ba, Ning & Ren, Siyu & Xu, Lu & Chai, Jingxia & Irfan, Muhammad & Hao, Yu & Lu, Zhi-Nan, 2022. "The impact of internet development on the health of Chinese residents: Transmission mechanisms and empirical tests," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    2. Seale, Clive & Ziebland, Sue & Charteris-Black, Jonathan, 2006. "Gender, cancer experience and internet use: A comparative keyword analysis of interviews and online cancer support groups," Social Science & Medicine, Elsevier, vol. 62(10), pages 2577-2590, May.
    3. Olafsdottir, Sigrun & Pescosolido, Bernice A., 2011. "Constructing illness: How the public in eight Western nations respond to a clinical description of "schizophrenia"," Social Science & Medicine, Elsevier, vol. 73(6), pages 929-938, September.
    4. Ningyuan Guo & Ziqiu Guo & Shengzhi Zhao & Sai Yin Ho & Daniel Yee Tak Fong & Agnes Yuen Kwan Lai & Sophia Siu-chee Chan & Man Ping Wang & Tai Hing Lam, 2021. "Digital inequalities in health information seeking behaviors and experiences in the age of web 2.0: A population-based study in Hong Kong," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-16, March.
    5. Sillence, Elizabeth & Briggs, Pam & Harris, Peter Richard & Fishwick, Lesley, 2007. "How do patients evaluate and make use of online health information?," Social Science & Medicine, Elsevier, vol. 64(9), pages 1853-1862, May.
    6. Rao, Amar & Talan, Amogh & Abbas, Shujaat & Dev, Dhairya & Taghizadeh-Hesary, Farhad, 2023. "The role of natural resources in the management of environmental sustainability: Machine learning approach," Resources Policy, Elsevier, vol. 82(C).
    7. Slauson-Blevins, Kathleen S. & McQuillan, Julia & Greil, Arthur L., 2013. "Online and in-person health-seeking for infertility," Social Science & Medicine, Elsevier, vol. 99(C), pages 110-115.
    8. Farah, Maya F. & Ramadan, Zahy B., 2017. "Disruptions versus more disruptions: How the Amazon dash button is altering consumer buying patterns," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 54-61.

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