Abstract

Obesity and overweight are considered a health threat globally. Saudi Arabia is a country that has a high percentage of people suffering from obesity. These people can be helped to lose weight through the usage of mobile apps as these apps can collect users’ personal information. These collected data is used to provide precise and personalized weight loss advices. However, weight loss apps must be user friendly, provide data security and user privacy protection. In this paper, we analyze the usability, security, and privacy of a weight loss app. Our main aim to clarify the data privacy and security procedure and test the usability level of the new Arabic weight loss app ‘Akser Waznk’ that is developed considering the social and cultural norms of Saudi users.

Highlights

  • Obesity means storing extra energy in the shape of fat [1]

  • We have analyzed the usability for the Arabic weight loss app “Akser Waznk” which is designed for Saudi obese users

  • The usability testing for Akser Waznk is performed following the same techniques and procedures that were used in our previous work to test the usability level of two Arabic weight loss apps (Twazon and Aded Surat) [19, 20]

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Summary

INTRODUCTION

Obesity means storing extra energy in the shape of fat [1]. It can lead to many health problems, such as diabetes and cardiovascular issues [2, 3]. The unique features within weight loss apps can motivate users to improve their behavior and start to lose weight [5, 6]. Though, users want such apps to have a high level of usability and can provide data privacy and security [7]. There is a dire need of such apps that are easy to use and preserve user privacy along with security. We have analyzed the usability for the Arabic weight loss app “Akser Waznk” which is designed for Saudi obese users. We discuss the procedures that need to be implemented in order to provide data privacy and security protection.

DATA PRIVACY AND SECURITY
Usability Attributes
Procedure and Participations
The Tasks
Effectiveness
Satisfaction
Cognitive Load
Errors
USABILITY LEVEL BETWEEN USERS
Deep Navigation
Option Location
VIII. CONCLUSION
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