Applying item response theory and computer adaptive testing: The challenges for health outcomes assessment

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Objectives We review the papers presented at the NCI/ DIA conference, to identify areas of controversy and uncertainty, and to highlight those aspects of item response theory (IRT) and computer adaptive testing (CAT) that require theoretical or empirical research in order to justify their application to patient reported outcomes (PROs).

Background IRT and CAT offer exciting potential for the development of a new generation of PRO instruments. However, most of the research into these techniques has been in non-healthcare settings, notably in education. Educational tests are very different from PRO instruments, and consequently problematic issues arise when adapting IRT and CAT to healthcare research.

Results Clinical scales differ appreciably from educational tests, and symptoms have characteristics distinctly different from examination questions. This affects the transferring of IRT technology. Particular areas of concern when applying IRT to PROs include inadequate software, difficulties in selecting models and communicating results, insufficient testing of local independence and other assumptions, and a need of guidelines for estimating sample size requirements. Similar concerns apply to diffrential item functioning (DIF), which is an important application of IRT. Multidimensional IRT is likely to be advantageous only for closely related PRO dimensions.

Conclusions Although IRT and CAT provide appreciable potential benefits, there is a need for circumspection. Not all PRO scales are necessarily appropriate targets for this methodology. Traditional psychometric methods, and especially qualitative methods, continue to have an important role alongside IRT. Research should be funded to address the specific concerns that have been identified.

Original languageEnglish
Pages (from-to)187-194
Number of pages8
JournalQuality of Life Research
Issue numberSupplement 1
Early online date7 Apr 2007
Publication statusPublished - Aug 2007


  • quality of life
  • item response theory
  • patient reported outcomes
  • health outcomes measurement
  • quality-of-life
  • measurement precision
  • regression-models
  • indicators
  • trials
  • scales


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