June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Educational and vision-assistive smartphone Apps for patients: a quantitative evaluation
Author Affiliations & Notes
  • Stephanie Kletke
    Medicine, McMaster University, Hamilton, ON, Canada
  • Sourabh Arora
    Ophthalmology, University of Alberta, Edmonton, AB, Canada
  • Feisal Adatia
    Ophthalmology, University of Calgary, Calgary, AB, Canada
  • Footnotes
    Commercial Relationships Stephanie Kletke, None; Sourabh Arora, None; Feisal Adatia, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 5322. doi:
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      Stephanie Kletke, Sourabh Arora, Feisal Adatia; Educational and vision-assistive smartphone Apps for patients: a quantitative evaluation. Invest. Ophthalmol. Vis. Sci. 2013;54(15):5322.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose
 

To identify and quantitatively evaluate high quality patient educational and vision assistive Apps.

 
Methods
 

Webstores of major smartphone platforms, including iPhone (App Store) and Android (Market) were searched to identify vision assistive and educational Apps targeting patients. Quantitative evaluation was performed using the Quality Component Scoring system (QCS), which assessed for: ownership, purpose, authorship, author qualification, attribution, interactivity, and currency (maximum score of 13). For vision assistive Apps, usability parameter assessment included: interface design, ease of use/user feedback, navigation, terminology, and low vision accessibility (maximum score of 10). The Technical Component Score System (TCS) was used for educational Apps only (maximum score of 16). Average user ratings, App cost, and links to other resources were also considered.

 
Results
 

Thirty-four (23 vision assistive, 11 educational) smartphone Apps were included for analysis. Amongst all Apps’ QCS, the mean attribution score (indicating use of references) was the lowest (0.15+/-0.4), while the currency score (indicating dates of latest updates are listed) was the highest (1.7+/-0.5, p<0.001). For assistive Apps, the mean usability total was 6.4+/- 1.7, and the combined QCS and usability total was 17.6+/- 2.9 (maximum possible score = 23). Patient-appropriate terminology scored the highest (2.0) and low-vision accessibility scored the lowest (0.78+/-0.52, p<0.001). Number of ratings for an App was significantly correlated with its usability score (Spearman’s rho=0.513, p=0.012) and combined total score (Spearman’s rho=0.422, p=0.045). Amongst educational Apps, the mean TCS total was 8.1+/- 5.3 and the combined QCS and TCS total was 18.6+/- 7.4 (maximum possible score = 29). The most common learning methods were text-based (82%) and video/audio-based (18%). The TCS scores were significantly higher for text-based Apps (9.3+/-5.1) compared to video/audio-based (2.5+/-0.7, p=0.004).

 
Conclusions
 

This study has provided a list of patient educational and vision assistive Apps, ranked by order of quality and categorized by their purpose/learning method. This will allow patients to access Apps most suited to their needs, and physicians to make recommendations.

 
 
Figure 1. Assessment of quality component parameters
 
Figure 1. Assessment of quality component parameters
 
 
Figure 2: Usability parameters for ophthalmology smartphone Apps targeting patients
 
Figure 2: Usability parameters for ophthalmology smartphone Apps targeting patients
 
Keywords: 584 low vision • 579 learning  
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