Journal of Inherited Metabolic Disease

, Volume 35, Issue 1, pp 169–176 | Cite as

Putting a value on the avoidance of false positive results when screening for inherited metabolic disease in the newborn

  • Simon DixonEmail author
  • Phil Shackley
  • Jim Bonham
  • Rachel Ibbotson
Original Article


Despite the increase in the number of inherited metabolic diseases that can be detected at birth using a single dried blood spot sample, the impact of false positive results on parents remains a concern. We used an economic approach - the contingent valuation method – which asks parents to give their maximum willingness to pay for an extension in a screening programme and the degree to which the potential for false positive results diminishes their valuations. 160 parents of a child or children under the age of 16 years were surveyed and given descriptions of the current screening programme in the UK, an extended programme and an extended programme with no false positives. 148 (92.5%) respondents said they would accept the screen for the five extra conditions in an expanded screening programme whilst 10 (6.3%) said they would not and two were unsure. When asked to indicate if they would choose to be screened under an expanded screening programme with no false positive results, 152 (95%) said they would, five (3.1%) said they would not, two were unsure, and there was one non-response. 151 (94.4%) said they preferred the hypothetical test with no false-positives. The mean willingness to pay for the expanded programme was £178 compared to £219 for the hypothetical expanded programme without false positives (p > 0.05). The results suggest that there is widespread parental support for extended screening in the UK and that the number of false-positives is a relatively small issue.


Screening Programme False Positive Result Congenital Hypothyroidism Neonatal Screening Extended Programme 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The research was funded by the South Yorkshire Collaboration for Leadership in Applied Health Research and Care (CLAHRC), which in turn is funded by the National Institute for Health Research (NIHR).The authors confirm independence from the sponsors; the content of the article has not been influenced by the sponsors.


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Copyright information

© SSIEM and Springer 2011

Authors and Affiliations

  • Simon Dixon
    • 1
    Email author
  • Phil Shackley
    • 1
  • Jim Bonham
    • 2
  • Rachel Ibbotson
    • 3
  1. 1.School of Health and Related ResearchUniversity of SheffieldSheffieldUK
  2. 2.Sheffield Children’s Hospital NHS Foundation TrustSheffieldUK
  3. 3.Centre for Health and Social Care ResearchSheffield Hallam UniversitySheffieldUK

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