Literature DB >> 12435560

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

Sanjay K Pandey1, John J Hart, Sheela Tiwary.   

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.

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Year:  2003        PMID: 12435560     DOI: 10.1016/s0277-9536(02)00019-9

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  23 in total

1.  Health information-seeking behaviors, health indicators, and health risks.

Authors:  James B Weaver; Darren Mays; Stephanie Sargent Weaver; Gary L Hopkins; Dogan Eroglu; Jay M Bernhardt
Journal:  Am J Public Health       Date:  2010-06-17       Impact factor: 9.308

2.  Profiling characteristics of internet medical information users.

Authors:  James B Weaver; Darren Mays; Gregg Lindner; Dogan Eroglu; Frederick Fridinger; Jay M Bernhardt
Journal:  J Am Med Inform Assoc       Date:  2009-06-30       Impact factor: 4.497

3.  Online health information seeking behavior in Hong Kong: an exploratory study.

Authors:  Yuk Yee Yan
Journal:  J Med Syst       Date:  2010-04       Impact factor: 4.460

4.  Constructing illness: how the public in eight Western nations respond to a clinical description of "schizophrenia".

Authors:  Sigrun Olafsdottir; Bernice A Pescosolido
Journal:  Soc Sci Med       Date:  2011-07-13       Impact factor: 4.634

5.  Adapting the content of cancer web sites to the information needs of patients: reliability and readability.

Authors:  Ruben Alba-Ruiz; Clara Bermúdez-Tamayo; Jaime Jiménez Pernett; Jose Francisco Garcia-Gutierrez; José Manuel Cózar-Olmo; Beatriz Valero-Aguilera
Journal:  Telemed J E Health       Date:  2013-09-27       Impact factor: 3.536

6.  Determinants of the frequency of online health information seeking: results of a web-based survey conducted in France in 2007.

Authors:  Emilie Renahy; Isabelle Parizot; Pierre Chauvin
Journal:  Inform Health Soc Care       Date:  2010-01       Impact factor: 2.439

7.  The potential of the internet for alternative caring practices for health.

Authors:  Sarah Atkinson; Andrew Ayers
Journal:  Anthropol Med       Date:  2010-04

8.  Health-related internet use by lupus patients in southern Spain.

Authors:  José-Luis Callejas-Rubio; Raquel Ríos-Fernández; Ana-Celia Barnosi-Marín; Francisco-José García-Hernández; José-Antonio Vargas-Hitos; María-Teresa Camps-García; José-Antonio González-Nieto; Julio Sánchez-Román; Juan Jiménez-Alonso; Enrique de Ramón Garrido; Norberto Ortego-Centeno; Norberto Otego-Centeno
Journal:  Clin Rheumatol       Date:  2013-10-06       Impact factor: 2.980

9.  Antecedent characteristics of online cancer information seeking among rural breast cancer patients: an application of the Cognitive-Social Health Information Processing (C-SHIP) model.

Authors:  Bret R Shaw; Lori L Dubenske; Jeong Yeob Han; Ludmila Cofta-Woerpel; Nigel Bush; David H Gustafson; Fiona McTavish
Journal:  J Health Commun       Date:  2008-06

10.  Not all patients want to participate in decision making. A national study of public preferences.

Authors:  Wendy Levinson; Audiey Kao; Alma Kuby; Ronald A Thisted
Journal:  J Gen Intern Med       Date:  2005-06       Impact factor: 5.128

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