Appl Clin Inform 2012; 03(04): 356-366
DOI: 10.4338/ACI-2012-06-RA-0021
Research Article
Schattauer GmbH

A Comparison of Usability Factors of Four Mobile Devices for Accessing Healthcare Information by Adolescents

B. Sheehan
1   Columbia University, School of Nursing, Columbia University Medical Center, New York
,
Y. Lee
1   Columbia University, School of Nursing, Columbia University Medical Center, New York
,
M. Rodriguez
1   Columbia University, School of Nursing, Columbia University Medical Center, New York
,
V. Tiase
2   Presbyterian Hospital, New York, NY
,
R. Schnall
1   Columbia University, School of Nursing, Columbia University Medical Center, New York
› Author Affiliations
Further Information

Correspondence to:

Rebecca Schnall PhD RN
Columbia University, School of Nursing
617 West 168th st.
New York, New York 10032
Phone: 212–342–6886   

Publication History

Received 10 June 2012

Accepted 21 September 2012

Publication Date:
19 December 2017 (online)

 

Summary

Background: Mobile health (mHealth) is a growing field aimed at developing mobile information and communication technologies for healthcare. Adolescents are known for their ubiquitous use of mobile technologies in everyday life. However, the use of mHealth tools among adolescents is not well described.

Objective: We examined the usability of four commonly used mobile devices (an iPhone, an Android with touchscreen keyboard, an Android with built-in keyboard, and an iPad) for accessing healthcare information among a group of urban-dwelling adolescents.

Methods: Guided by the FITT (Fit between Individuals, Task, and Technology) framework, a think-aloud protocol was combined with a questionnaire to describe usability on three dimensions: 1) task-technology fit; 2) individual-technology fit; and 3) individual-task fit.

Results: For task-technology fit, we compared the efficiency, and effectiveness of each of the devices tested and found that the iPhone was the most usable had the fewest errors and prompts and had the lowest mean overall task time For individual-task fit, we compared efficiency and learnability measures by website tasks and found no statistically significant effect on tasks steps, task time and number of errors. Following our comparison of success rates by website tasks, we compared the difference between two mobile applications which were used for diet tracking and found statistically significant effect on tasks steps, task time and number of errors. For individual-technology fit, interface quality was significantly different across devices indicating that this is an important factor to be considered in developing future mobile devices.

Conclusions: All of our users were able to complete all of the tasks, however the time needed to complete the tasks was significantly different by mobile device and mHealth application. Future design of mobile technology and mHealth applications should place particular importance on interface quality.

Citation: Sheehan B, Lee Y, Rodriguez M, Tiase V, Schnall R. A Comparison of Usability Factors of Four Mobile Devices for Accessing Healthcare Information by Adolescents. Appl Clin Inf 2012; 3: 356–366

http://dx.doi.org/10.4338/ACI-2012-06-RA-0021


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Conflicts of Interest

None of the listed authors have any financial or personal relationships with other people or organizations that may inappropriately influence or bias the objectivity of submitted content and/or its acceptance for publication in this journal.

  • References

  • 1 mHealth Alliance.. Frequently Asked Questions, 2011. 2010 [cited 2011 August 3]; Available from: http://www.mhealthalliance.org/about/frequently-asked-questions
  • 2 Istepanian R, Laxminarayan S, Pattichis CS. editors. M-health: Emerging mobile health systems. New York, N. Y.: Springer; 2006
  • 3 Kleinke JD. Dot-gov: market failure and the creation of a national health information technology system. Health Aff (Millwood)2005 Sep-Oct 24. 5 1246-62.
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  • 14 ISO/IEC FCD 25010.. Software product quality requirements and evaluation (SQuaRE)- quality models for software product and system quality in use. In: Bevan N, editor. Systems and software engineering2009.
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  • 17 Lewis JR. IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use. Int J Human Coputer Interact 1995; 7: 57-78.
  • 18 Heinonen R, Luoto R, Lindfors P, Nygard CH. Usability and feasibility of mobile phone diaries in an experimental physical exercise study. Telemed J E Health 2012; Mar 18 (Suppl. 02) 115-9.
  • 19 Whittaker R, Borland R, Bullen C, Lin RB, McRobbie H, Rodgers A. Mobile phone-based interventions for smoking cessation. Cochrane Database Syst Rev 2009; 4-CD006611.
  • 20 Mulvaney SA, Rothman RL, Dietrich MS, Wallston KA, Grove E, Elasy TA, Johnson KB. Using mobile phones to measure adolescent diabetes adherence. Health Psychol 2012; Jan 31 (Suppl. 01) 43-50.
  • 21 Lee J, Cain C, Young S, Chockley N, Burstin H. The Adoption Gap: Health Information Technology In Small Physician Practices. Health Affairs2005 September 1, 2005; 24 (Suppl. 05) 1364-6.
  • 22 Ramaiah M, Subrahmanian E, Sriram RD, Lide BB. Workflow and electronic health records in small medical practices. Perspect Health Inf Manag 2012: 9-1d.
  • 23 Honekamp W, Ostermann H. Evaluation of a prototype health information system using the FITT framework. Inform Prim Care 2011; 19 (Suppl. 01) 47-9.
  • 24 Schnall R, Smith AB, Sikka M, Gordon P, Camhi E, Kanter T, Bakken S. Employing the FITT framework to explore HIV case managers’ perceptions of two electronic clinical data (ECD) summary systems. Int J Med Inform 2012 Jul 27.
  • 25 Faulkner L. Beyond the five-user assumption: benefits of increased sample sizes in usability testing. Behav Res Methods Instrum Comput 2003; Aug 35 (Suppl. 03) 379-83.

Correspondence to:

Rebecca Schnall PhD RN
Columbia University, School of Nursing
617 West 168th st.
New York, New York 10032
Phone: 212–342–6886   

  • References

  • 1 mHealth Alliance.. Frequently Asked Questions, 2011. 2010 [cited 2011 August 3]; Available from: http://www.mhealthalliance.org/about/frequently-asked-questions
  • 2 Istepanian R, Laxminarayan S, Pattichis CS. editors. M-health: Emerging mobile health systems. New York, N. Y.: Springer; 2006
  • 3 Kleinke JD. Dot-gov: market failure and the creation of a national health information technology system. Health Aff (Millwood)2005 Sep-Oct 24. 5 1246-62.
  • 4 Lenhart A. Teens, cell phones and texting. Washington, DC: Pew Research Center; 2010
  • 5 Lenhart A. Teens and Mobile Phones Over the Past Five Years: Pew Internet Looks Back. Pew Internet and American Life Project;. 2009 [cited 2010 March 28]; Available from: http://www.pewinternet.org/Re ports/2009/14--Teens-and-Mobile-Phones-Data-Memo/1-Data-Memo/5-How-teens-use-text-mess-aging.aspx?r=1
  • 6 Lenhart A, Purcell K, Smith A, Zickuhr K. Social Media and Young Adults. Pew Internet & American Life Project. 2010 [cited 2010 March 28]; Available from: http://www.pewinternet.org/Reports/2010/Social-Media-and-Young-Adults.aspx
  • 7 Hachman M. More Kids Using Cell Phones, Study Finds Pew Internet and American Life Project;. 2009 [cited 2010 March 28]; Available from: http://www.pewinternet.org/Media-Mentions/2009/More-Kids-Using-Cell-Phones-Study-Finds.aspx
  • 8 Curioso WH, Mechael PN. Enhancing ‘M-health’ with south-to-south collaborations. Health Aff (Mill-wood)2010 Feb 29. 2 264-7.
  • 9 Lewis J. editor Psychometric evaluation of the post-study system usability questionnaire: The PSSUQ, Human Factors Society 36th Annual Meeting. 1992. Boca Raton: Fla.;
  • 10 Ammenwerth E, Iller C, Mahler C. IT-adoption and the interaction of task, technology and individuals: a fit framework and a case study. BMC Med Inform Decis Mak 2006: 6-3.
  • 11 Goodhue DL, Thompson RL. Task-Technology Fit and Individual Performance. Management Information Systems Quarterly 1995 19. 2 213-36.
  • 12 Venkatesh V, Davis FD. A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science 2000 46. 02 186-204.
  • 13 Tsiknakis M, Kouroubali A. Organizational factors affecting successful adoption of innovative eHealth services: a case study employing the FITT framework. Int J Med Inform 2009; Jan 78 (Suppl. 01) 39-52.
  • 14 ISO/IEC FCD 25010.. Software product quality requirements and evaluation (SQuaRE)- quality models for software product and system quality in use. In: Bevan N, editor. Systems and software engineering2009.
  • 15 Saffah A. editor QUIM: A framework for quantifying usability metrics in software quality models. Asia-Pacific Conference on Quality Software; 2001. Hong Kong.:
  • 16 Bevan N. editor Extending quality in use to provide a framework for usability measurement. HCI International; 2009 San Diego, Ca.:
  • 17 Lewis JR. IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use. Int J Human Coputer Interact 1995; 7: 57-78.
  • 18 Heinonen R, Luoto R, Lindfors P, Nygard CH. Usability and feasibility of mobile phone diaries in an experimental physical exercise study. Telemed J E Health 2012; Mar 18 (Suppl. 02) 115-9.
  • 19 Whittaker R, Borland R, Bullen C, Lin RB, McRobbie H, Rodgers A. Mobile phone-based interventions for smoking cessation. Cochrane Database Syst Rev 2009; 4-CD006611.
  • 20 Mulvaney SA, Rothman RL, Dietrich MS, Wallston KA, Grove E, Elasy TA, Johnson KB. Using mobile phones to measure adolescent diabetes adherence. Health Psychol 2012; Jan 31 (Suppl. 01) 43-50.
  • 21 Lee J, Cain C, Young S, Chockley N, Burstin H. The Adoption Gap: Health Information Technology In Small Physician Practices. Health Affairs2005 September 1, 2005; 24 (Suppl. 05) 1364-6.
  • 22 Ramaiah M, Subrahmanian E, Sriram RD, Lide BB. Workflow and electronic health records in small medical practices. Perspect Health Inf Manag 2012: 9-1d.
  • 23 Honekamp W, Ostermann H. Evaluation of a prototype health information system using the FITT framework. Inform Prim Care 2011; 19 (Suppl. 01) 47-9.
  • 24 Schnall R, Smith AB, Sikka M, Gordon P, Camhi E, Kanter T, Bakken S. Employing the FITT framework to explore HIV case managers’ perceptions of two electronic clinical data (ECD) summary systems. Int J Med Inform 2012 Jul 27.
  • 25 Faulkner L. Beyond the five-user assumption: benefits of increased sample sizes in usability testing. Behav Res Methods Instrum Comput 2003; Aug 35 (Suppl. 03) 379-83.