Using Likert-type and ipsative/forced choice items in sequence to generate a preference

Collaboration and implementation of a minimum, standardized set of core global educational and professional competencies seems appropriate given the expanding international evolution of pharmacy practice. However, winnowing down hundreds of competencies from a plethora of local, national and international competency frameworks to select the most highly preferred to be included in the core set is a daunting task. The objective of this paper is to describe a combination of strategies used to ascertain the most highly preferred items among a large number of disparate items. In this case, the items were >100 educational and professional competencies that might be incorporated as the core components of new and existing competency frameworks. Panelists (n = 30) from the European Union (EU) and United States (USA) were chosen to reflect a variety of practice settings. Each panelist completed two electronic surveys. The first survey presented competencies in a Likert-type format and the second survey presented many of the same competencies in an ipsative/forced choice format. Item mean scores were calculated for each competency, the competencies were ranked, and non-parametric statistical tests were used to ascertain the consistency in the rankings achieved by the two strategies. This exploratory study presented over 100 competencies to the panelists in the beginning. The two methods provided similar results, as indicated by the significant correlation between the rankings (Spearman's rho = 0.30, P