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ScanLag: High-throughput Quantification of Colony Growth and Lag Time
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Published on: July 15, 2014

Lead versus lag-time trade-off variants: does it make any difference?

Federico Augustovski1, Lucila Rey-Ares, Vilma Irazola

  • 1Institute of Clinical Effectiveness and Health Policy, IECS, Dr Emilio Ravignani 2024, C1414CPV Buenos Aires, Argentina. faugustovski@iecs.org.ar

The European Journal of Health Economics : HEPAC : Health Economics in Prevention and Care
|August 1, 2013
PubMed
Summary
This summary is machine-generated.

This study compared lead-time and lag-time time trade-off (TTO) methods for valuing health states worse than dead. No significant differences were found between these TTO variants, suggesting potential equivalence for health state valuation.

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Area of Science:

  • Health Economics
  • Patient-Reported Outcomes
  • Psychometrics

Background:

  • The traditional time trade-off (TTO) method faces challenges in valuing health states perceived as worse than death.
  • Lead-time and lag-time TTO are variants designed to address these valuation challenges.

Purpose of the Study:

  • To compare the performance of lead-time TTO and lag-time TTO in valuing EQ-5D-5L health states.
  • To assess the equivalence of these two TTO variants for health state valuation.

Main Methods:

  • A study involving 387 participants in Buenos Aires utilized quota sampling.
  • Respondents were randomly assigned to either lead-time or lag-time TTO using a web-based digital aid (EQ-VT).
  • Two blocks of five EQ-5D-5L health states were valued by participants.

Main Results:

  • Mean values for health states were generally similar between lead-time and lag-time TTO groups.
  • No statistically significant differences were observed between the TTO variants, except for one specific health state (33133).
  • Both methods showed peaks around a value of 0, with ordering effects potentially influencing responses.

Conclusions:

  • The lead-time and lag-time TTO variants appear to be equivalent for valuing EQ-5D-5L health states.
  • Potential study design factors may have influenced the results, possibly obscuring subtle differences between the methods.