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ALBA: a model-driven framework for the automatic generation of android location-based apps

Author(s): Gharaat M; Sharbaf M; Zamani B; Hamou-Lhadj A;

In recent years, the number of smartphone users has increased dramatically. These users download millions of apps and use them for various services. Due to the significant demand for mobile apps, developers often seek faster development methods and more eff ...

Article GUID: 38624616


Design Principles in mHealth Interventions for Sustainable Health Behavior Changes: Protocol for a Systematic Review

Author(s): Yang L; Kuang A; Xu C; Shewchuk B; Singh S; Quan H; Zeng Y;

Background: In recent years, mHealth has increasingly been used to deliver behavioral interventions for disease prevention and self-management. Computing power in mHealth tools can provide unique functions beyond conventional interventions ...

Article GUID: 36811938


Smartphone apps for menstrual pain and symptom management: A scoping review

Author(s): Trépanier LCM; Lamoureux É; Bjornson SE; Mackie C; Alberts NM; Gagnon MM;

The past decade marks a surge in the development of mobile apps used to digitally track and monitor aspects of personal health, including menstruation. Despite a plethora of menstruation-related apps, pain and symptom management content available in apps ha ...

Article GUID: 36761398


Evaluation of the Diet Tracking Smartphone Application Keenoa™: A Qualitative Analysis

Author(s): Bouzo V; Plourde H; Beckenstein H; Cohen TR;

Keenoa™ is a novel Canadian diet application (app) currently used by Canadian dietitians to collect diet-related data from clients. The goal of this study was to evaluate Keenoa™ based on user feedback and compare it to a conventional pen and paper method. ...

Article GUID: 34582258


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