title: An evaluation of patients' experienced usability of a diabetes mHealth system using a multi-method approach.
abstract: OBJECTIVE
  mHealth systems are becoming more common to aid patients in their diabetes self-management, but recent studies indicate a need for thorough evaluation of patients' experienced usability. Current evaluations lack a multi-method design for data collection and structured methods for data analyses. The purpose of this study was to provide a feasibility test of a multi-method approach for both data collection and data analyses for patients' experienced usability of a mHealth system for diabetes type 2 self-management.
  
  
  METHODS
  A random sample of 10 users was selected from a larger clinical trial. Data collection methods included user testing with eight representative tasks and Think Aloud protocol, a semi-structured interview and a questionnaire on patients' experiences using the system. The Framework Analysis (FA) method and Usability Problem Taxonomy (UPT) were used to structure, code and analyze the results. A usability severity rating was assigned after classification.
  
  
  RESULTS
  The combined methods resulted in a total of 117 problems condensed into 19 usability issues with an average severity rating of 2.47 or serious. The usability test detected 50% of the initial usability problems, followed by the post-interview at 29%. The usability test found 18 of 19 consolidated usability problems while the questionnaire uncovered one unique issue. Patients experienced most usability problems (8) in the Glucose Readings View when performing complex tasks such as adding, deleting, and exporting glucose measurements. The severity ratings were the highest for the Glucose Diary View, Glucose Readings View, and Blood Pressure View with an average severity rating of 3 (serious). Most of the issues were classified under the artifact component of the UPT and primary categories of Visualness (7) and Manipulation (6). In the UPT task component, most issues were in the primary category Task-mapping (12).
  
  
  CONCLUSIONS
  Multiple data collection methods yielded a more comprehensive set of usability issues. Usability testing uncovered the largest volume of usability issues, followed by interviewing and then the questionnaire. The interview did not surface any unique consolidated usability issues while the questionnaire surfaced one. The FA and UPT were valuable in structuring and classifying problems. The resulting descriptions serve as a communication tool in problem solving and programming. We recommend the usage of multiple methods in data collection and employing the FA and UPT in data analyses for future usability testing.
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA; Faculty of Computing, Blekinge Institute of Technology, Karlskrona, Sweden. Electronic address: mattias.georgsson@bth.se.
authors.forename: Mattias
authors.initials: M
authors.lastname: Georgsson
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA; College of Nursing, University of Utah, Salt Lake City, UT, USA.
authors.forename: Nancy
authors.initials: N
authors.lastname: Staggers
mesh_terms: D000328:Adult; D000368:Aged; D003924:Diabetes Mellitus, Type 2 / Q000628:therapy*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D017060:Patient Satisfaction / Q000706:statistics & numerical data*; D011795:Surveys and Questionnaires; D017216:Telemedicine / Q000706:statistics & numerical data*
keywords: Diabetes; Framework analysis; Multi-method evaluation; Usability; Usability Problem Taxonomy; mHealth