Developing a short-form of the Genetic Counselling Outcome Scale: The Genomics Outcome Scale.

Grant PE1, Pampaka M2, Payne K3, Clarke A4, McAllister M5.

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Abstract

The Genetic Counselling Outcome Scale (GCOS-24) is a 24-item patient reported outcome measure for use in evaluations of genetic counselling and testing services. The aim of this study was to develop a short form of GCOS-24. The study comprised three phases. Phase I: Cognitive interviews were used to explore interpretability of GCOS-24 items and which GCOS-24 items were most valued by the target population. Phase II: The Graded Response Model was used to analyse an existing set of GCOS-24 responses (n = 395) to examine item discrimination. Phase III: Item Selection. Three principles guided the approach to item selection (i) Items with poor discriminative properties were not selected; (ii) To avoid redundancy, items capturing a similar outcome were not selected together; item information curves and cognitive interview findings were used to establish superior items. (iii) Rasch analysis was then used to determine the optimal scale. In Phase I, ten cognitive interviews were conducted with individuals affected by or at risk for a genetic condition, recruited from patient support groups. Analysis of interview transcripts identified twelve GCOS-24 items which were highly valued by participants. In Phase II, Graded Response Model item characteristic curves and item information curves were produced. In Phase III, findings from Phases I and II were used to select ten highly-valued items that perform well. Finally, items were iteratively removed and permutated to establish optimal fit statistics under the Rasch model. A six-item questionnaire with a five-point Likert Scale was produced (The Genomics Outcome Scale (GOS)). Correlation between GCOS-24 and GOS scores is high (r = 0.838 at 99% confidence), suggesting that GOS maintains the ability of GCOS-24 to capture empowerment, whilst providing a less burdensome scale for respondents. This study represents the first step in developing a preference-based measure which could be used in the evaluation of technologies and services used in genomic medicine.