Recherche d'information en santé sur l'internet : une analyse contextuelle des données SIRS, une cohorte parisienne

Sante Publique. 2010 Feb 16:21 Spec No 2:27-40.
[Article in French]

Abstract

From a public healthcare point of view, the Internet rapidly emerged as a potentially useful tool for providing information to patients and for promoting healthcare. While the individual factors involved in the use of online healthcare information are now well known, the effect of the area of residence has been largely ignored. The object of this study is to assess the impact of contextual characteristics associated with the neighbourhood and area of residence on the use of internet for accessing healthcare information. Analyses of multilevel logistical regression were carried out on data drawn from the SIRS cohort, a representative sample of the population in the Paris metropolitan area in 2005. Variations between neighbourhoods were observed both in the general use of internet and, more specifically, in the search for information concerning healthcare. This variability tends to decrease when individual factors are taken into account, which points to an "effect of composition", and disappears altogether when the characteristics of the area of residence are added, indicating a "contextual effect". Individual inequalities of access to internet are even greater in the most underprivileged areas. By contrast, while individual obstacles are also reflected here, the probability of using the internet for issues of healthcare is higher in neighbourhoods that include a large proportion of unqualified people. From the point of view of reducing social inequalities in the realm of healthcare, an active promotion of internet access and training of both individuals and doctors are required both at an individual and at a social level in order that the internet may constitute a medium for publicizing prevention and the promotion of useful and widely used healthcare.

MeSH terms

  • Health Services Accessibility
  • Humans
  • Logistic Models
  • Residence Characteristics
  • Socioeconomic Factors*
  • Systemic Inflammatory Response Syndrome*