Adjustment and Development of Health User’s Mental Model Completeness Scale in Search Engines

Document Type : Articles

Authors

Abstract

Introduction: Users’ performance and their interaction with information retrieval systems can be observed in development of their mental models. Users, especially users of health, use mental models to facilitate their interactions with these systems and incomplete or incorrect models can cause problems for them . The aim of this study was the adjustment and development of health user’s mental model completeness scale in search engines.Method: This quantitative study uses Delphi method. Among various scales for users’ mental model completeness, Li’s scale was selected and some items were added to this scale based on previous valid literature. Delphi panel members were selected using purposeful sampling method, consisting of 20 and 18 participants in the first and second rounds, respectively. Kendall’s Coefficient of Concordance in SPSS version 16 was used as basis for agreement (95% confidence).Results:The Kendall coefficient of Concordance (W) was calculated to be 0.261(P-value<0.001) for the first and 0.336 (P-value<0.001) for the second round. Therefore, the study was found to be statistically significant with 95% confidence. Since the increase in the coefficient in two consecutive rounds was very little (equal to 0.075), surveying the panel members were stopped based on second Schmidt criterion and Delphi method was stopped after the second round. Finally, the dimensions of Li’s scale (existence and nature, search characteristics and levels of interaction) were confirmed again, but “indexing of pages or websites” was eliminated and “Difference between results of different search engines”, “possibility of access to similar or related webpages”, and “possibility of search for special formats and multimedia” were added to Li’s scale.Conclusion: In this study, the scale for mental model completeness of health users was adjusted and developed; it can help the designers of information retrieval systems in systematic development of these systems and can also help librarians and informatics experts in recognizing the necessary trainings for users in order to improve their information retrieval skills. Also, as a valid and adapted scale for Iranian universities of medical sciences, it can be used for investigating completeness level of health information users’ mental models of search engines.Keywords: Mental Model Completeness Scale, Health users, Search engines

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