How acceptable are innovative health-care technologies? A survey of public beliefs and attitudes in England and Wales

Soc Sci Med. 2005 May;60(9):1937-48. doi: 10.1016/j.socscimed.2004.08.058. Epub 2004 Nov 13.

Abstract

There has been a continuing debate about the extent to which the public finds health-care technological innovation acceptable. The public's ambivalence about scientific medicine may have been exacerbated, more recently, by developments such as the introduction of the 'new genetics' with their associated ethical and social implications and the claims that public trust in health care and practitioners and, more widely, in society has been eroded. The aim of this paper is to examine public attitudes to a range of innovative health-care technologies to see whether (i) certain technologies are perceived as particularly problematic, and (ii) attitudes to new health-care technologies are associated more broadly with beliefs about science, trust in health care and social trust, and perceptions of the benefits and risks of complementary and alternative medicine versus orthodox (technological) medicine. These questions are examined through a statistical analysis of data collected in a national, postal survey of the adult population (n = 1187) in England and Wales. The results showed public ambivalence about new health-care technologies, although genetic technologies, as a whole, were not seen to be problematic and their acceptability depended on their ability to control serious diseases. However, there was a level of consistency in attitude across the different technologies. Those consistently against new health-care technologies were also more likely to be suspicious of science, and doubtful about the benefits of other established, orthodox technologies (screening; medications) and to have less trust in health and health-care practitioners.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Attitude to Health*
  • Biomedical Technology*
  • England
  • Factor Analysis, Statistical
  • Female
  • Genetic Techniques
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Physician-Patient Relations
  • Socioeconomic Factors
  • Trust
  • Wales