• Glyn Elwyn, Annette M O'Connor, Carol Bennett, Robert G Newcombe, Mary Politi, Marie-Anne Durand, Elizabeth Drake, Natalie Joseph-Williams, Sara Khangura, Anton Saarimaki, Stephanie Sivell, Mareike Stiel, Steven J Bernstein, Nananda Col, Angela Coulter, Karen Eden, Martin Härter, Margaret Holmes Rovner, Nora Moumjid, Dawn Stacey, Richard Thomson, Tim Whelan, Trudy van der Weijden, and Adrian Edwards.
• Department of Primary Care and Public Health, School of Medicine and the School of Psychology, Cardiff University, Cardiff, United Kingdom. elwyng@cardiff.ac.uk
• Plos One. 2009 Jan 1; 4 (3): e4705.

ObjectivesTo describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids).DesignScale development study, involving construct, item and scale development, validation and reliability testing.SettingThere has been increasing use of decision support technologies--adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation.MethodsScale development study, involving construct, item and scale development, validation and reliability testing.ParticipantsTwenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi). In the fourth Stage (reliability study), eight raters assessed thirty randomly selected decision support technologies.ResultsIPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100) for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30), enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68). Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items) was also developed that had very similar mean scores to IPDASi and high correlation between short score and overall score 0.87 (CI 0.79 to 0.92).ConclusionsThis work demonstrates that IPDASi has the ability to assess the quality of decision support technologies. The existing IPDASi provides an assessment of the quality of a DST's components and will be used as a tool to provide formative advice to DSTs developers and summative assessments for those who want to compare their tools against an existing benchmark.

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