Accepted for/Published in: JMIR Serious Games
Date Submitted: Oct 19, 2023
Date Accepted: Feb 11, 2025
Warning: This is an author submission that is not peer-reviewed or edited.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.
Utilizing Gamification, Artificial Intelligence and mHealth for the professional development of maternal care providers: Assessing Providers' Satisfaction in Primary Healthcare Centers in Lebanon
ABSTRACT
Background:
The significantly high maternal morbidity and mortality rates witnessed globally and predominantly in low and lower middle-income countries (LLMICs) emphasize the critical role of skilled healthcare providers in preventing pregnancy-related complications, particularly among disadvantaged populations. Lebanon, a middle eastern country hosting more than 1.5 million refugees is no exception. Healthcare providers face significant challenges including resource constraints and limited access to professional development opportunities, highlighting the importance of continuous learning and innovative educational interventions. Artificial intelligence and gamification emerge as promising approaches to enhance clinical performance and evidence-based practice among healthcare providers.
Objective:
Considering the limited evidence on the effectiveness of integrating gamification and artificial intelligence in a mobile application for professional development of healthcare providers providing maternal heath services, this pilot study aims to assess the satisfaction and acceptability of healthcare providers with a novel mLearning tool, titled the ‘GAIN MHI’ App, at selected primary healthcare centers (PHCs) in Lebanon.
Methods:
This is a cross-sectional study that presents data collected from twelve participating healthcare providers, primarily obstetricians and midwives who have been using the GAIN MHI Mobile App for professional development and learning. The survey used included Likert scale questions to assess healthcare providers' satisfaction, engagement and evaluation of the Gamification and the Artificial Intelligence components of the App. Open-ended questions gathered qualitative feedback on App preferences and potential improvements. Statistical analysis was performed to derive insights from the quantitative data collected. Subsequently, a descriptive analysis was performed, presenting the frequencies and percentages of various participant characteristics, as well as responses to the survey across all sections.
Results:
Eighty five percent of the healthcare providers, including midwives and doctors, were satisfied with the GAIN MHI mobile app, the user interface and various content features. Engagement levels were robust (64.58% ± 6.2), notably impacting clinical routines and theoretical knowledge. The gamification and AI components garnered strong positive feedback, enhancing learning enjoyment (91.67%). From a qualitative perspective, users expressed appreciation for the App's diverse content, user-friendliness, and motivation for continuous learning. Suggestions for expanding the content included a wide range of health topics, highlighting the App's potential applicability in various healthcare fields.
Conclusions:
Healthcare providers, especially those practicing in remote and underserved areas, face challenges in accessing professional development opportunities, highlighting the need for innovative pedagogical approaches such as personalized learning and gamification using mobile technologies. This pilot study underlines the potential of using AI-based digital solutions for professional development with the aim of improving the quality of health services - in this case, maternal health services through continuous learning and update on most recent evidence-based clinical guidelines. Future research should investigate the feasibility and impact of applying similar solutions at larger scale to reach a wider range of healthcare providers and to cover other health topics. The applicability of such solutions in different contexts and low-resource settings should also be explored. Clinical Trial: N/A
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