Literature DB >> 22132037

Improving Clinical Trial Participant Tracking Tools Using Knowledge-anchored Design Methodologies.

Philip R O Payne1, Peter J Embi, Stephen B Johnson, Eneida Mendonca, Justin Starren.   

Abstract

OBJECTIVE: Rigorous human-computer interaction (HCI) design methodologies have not traditionally been applied to the development of clinical trial participant tracking (CTPT) tools. Given the frequent us of iconic HCI models in CTPTs, and prior evidence of usability problems associated with the use of ambiguous icons in complex interfaces, such approaches may be problematic. Presentation Discovery (PD), a knowledge-anchored HCI design method, has been previously demonstrated to improve the design of iconic HCI models. In this study, we compare the usability of a CTPT HCI model designed using PD and an intuitively designed CTPT HCI model.
METHODS: An iconic CPTP HCI model was created using PD. The PD-generated and an existing iconic CTPT HCI model were subjected to usability testing, with an emphasis on task accuracy and completion times. Study participants also completed a qualitative survey instrument to evaluate subjective satisfaction with the two models.
RESULTS: CTPT end-users reliably and reproducibly agreed on the visual manifestation and semantics of prototype graphics generated using PD. The performance of the PD-generated iconic HCI model was equivalent to an existing HCI model for tasks at multiple levels of complexity, and in some cases superior. This difference was particularly notable when tasks required an understanding of the semantic meanings of multiple icons.
CONCLUSION: The use of PD to design an iconic CTPT HCI model generated beneficial results and improved end-user subjective satisfaction, while reducing task completion time. Such results are desirable in information and time intensive domains, such as clinical trials management.

Entities:  

Year:  2010        PMID: 22132037      PMCID: PMC3225206          DOI: 10.4338/ACI-2010-02-RA-0012

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


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