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Accepted for/Published in: JMIR Human Factors

Date Submitted: Mar 19, 2017
Open Peer Review Period: Mar 19, 2017 - Apr 27, 2017
Date Accepted: Sep 18, 2017
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Enhancing Home Health Mobile Phone App Usability Through General Smartphone Training: Usability and Learnability Case Study

Harte R, Hall T, Glynn L, Rodríguez-Molinero A, Scharf T, Quinlan LR, ÓLaighin G

Enhancing Home Health Mobile Phone App Usability Through General Smartphone Training: Usability and Learnability Case Study

JMIR Hum Factors 2018;5(2):e18

DOI: 10.2196/humanfactors.7718

PMID: 29699969

PMCID: 5945986

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Enhancing Home Health Mobile Phone App Usability Through General Smartphone Training: Usability and Learnability Case Study

  • Richard Harte; 
  • Tony Hall; 
  • Liam Glynn; 
  • Alejandro Rodríguez-Molinero; 
  • Thomas Scharf; 
  • Leo R Quinlan; 
  • Gearóid ÓLaighin

Background:

Each year, millions of older adults fall, with more than 1 out of 4 older people experiencing a fall annually, thereby causing a major social and economic impact. Falling once doubles one’s chances of falling again, making fall prediction an important aspect of preventative strategies. In this study, 22 older adults aged between 65 and 85 years were trained in the use of a smartphone-based fall prediction system. The system is designed to continuously assess fall risk by measuring various gait and balance parameters using a smart insole and smartphone, and is also designed to detect falls. The use case of the fall prediction system in question required the users to interact with the smartphone via an app for device syncing, data uploads, and checking system status.

Objective:

The objective of this study was to observe the effect that basic smartphone training could have on the user experience of a group that is not technically proficient with smartphones when using a new connected health system. It was expected that even short rudimentary training could have a large effect on user experience and therefore increase the chances of the group accepting the new technology.

Methods:

All participants received training on how to use the system smartphone app; half of the participants (training group) also received extra training on how to use basic functions of the smartphone, such as making calls and sending text messages, whereas the other half did not receive this extra training (no extra training group). Comparison of training group and no extra training group was carried out using metrics such as satisfaction rating, time taken to complete tasks, cues required to complete tasks, and errors made during tasks.

Results:

The training group fared better in the first 3 days of using the system. There were significant recorded differences in number of cues required and errors committed between the two groups. By the fourth and fifth day of use, both groups were performing at the same level when using the system.

Conclusions:

Supplementary basic smartphone training may be critical in trials where a smartphone app–based system for health intervention purposes is being introduced to a population that is not proficient with technology. This training could prevent early technology rejection and increase the engagement of older participants and their overall user experience with the system.


 Citation

Please cite as:

Harte R, Hall T, Glynn L, Rodríguez-Molinero A, Scharf T, Quinlan LR, ÓLaighin G

Enhancing Home Health Mobile Phone App Usability Through General Smartphone Training: Usability and Learnability Case Study

JMIR Hum Factors 2018;5(2):e18

DOI: 10.2196/humanfactors.7718

PMID: 29699969

PMCID: 5945986

Per the author's request the PDF is not available.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.