Evidence map›Paper›PMID 40929508›Full record

ArticleJMIR serious games2025

Utilizing Gamification, Artificial Intelligence, and mHealth for the Professional Development of Maternal Care Providers: Exploratory Pilot Cross-Sectional Study Assessing Providers' Satisfaction in Primary Health Care Centers in Lebanon.

Mohamad Alameddine, Nadine Sabra, Nour El Arnaout, Asmaa El Dakdouki, Mahmoud El Jaouni, Randa Hamadeh, Abed Shanaa, Shadi Saleh

Abstract read
In one paragraph

Article in JMIR serious games, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Perceptions of Artificial Intelligence in Gynecologic Oncology Education: Insights from a Qualitative Study Using Semi-Structured Interviews.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Mohamad AlameddineCollege of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates.ORCID http://orcid.org/0000-0002-2299-1242
Nadine SabraGlobal Health Institute, American University of Beirut, PO Box 11-0236, Riad El Solh, Beirut, 1107 2020, Lebanon, 961 3047578.ORCID http://orcid.org/0009-0002-9441-5719
Nour El ArnaoutGlobal Health Institute, American University of Beirut, PO Box 11-0236, Riad El Solh, Beirut, 1107 2020, Lebanon, 961 3047578.ORCID http://orcid.org/0000-0002-3638-5905
Asmaa El DakdoukiGlobal Health Institute, American University of Beirut, PO Box 11-0236, Riad El Solh, Beirut, 1107 2020, Lebanon, 961 3047578.ORCID http://orcid.org/0009-0005-7803-0853
Mahmoud El JaouniFaculty of Health Sciences, American University of Beirut, Beirut, Lebanon.ORCID http://orcid.org/0009-0000-7710-0999
Randa HamadehMinistry of Public Health, Beirut, Lebanon.ORCID http://orcid.org/0000-0002-3091-9750
Abed ShanaaThe United Nations Relief and Works Agency for Palestine Refugees in the Near East, Beirut, Lebanon.ORCID http://orcid.org/0009-0006-2854-4001
Shadi SalehGlobal Health Institute, American University of Beirut, PO Box 11-0236, Riad El Solh, Beirut, 1107 2020, Lebanon, 961 3047578.ORCID http://orcid.org/0000-0001-8689-4030

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: High maternal morbidity and mortality rates globally, especially in low-income and lower-middle-income countries, highlight the critical role of skilled health care providers (HCPs) in preventing pregnancy-related complications among disadvantaged populations. Lebanon, hosting over 1.5 million refugees, is no exception. HCPs face significant challenges, including resource constraints and limited professional development opportunities, underscoring the need for continuous learning and innovative educational interventions. Artificial intelligence (AI) and gamification show promise in enhancing clinical performance and evidence-based practice. Objective: Considering the limited evidence on the effectiveness of integrating gamification and AI in a mobile app for professional development of HCPs providing maternal health services, this pilot study aims to assess the satisfaction and acceptability of HCPs with a novel mLearning tool, titled the "GAIN MHI" app (gamification, artificial intelligence, and mHealth network for maternal health improvement), at selected primary health care centers in Lebanon. Methods: This is a cross-sectional study that presents data collected from 12 participating HCPs, 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 HCPs' satisfaction, engagement, and evaluation of the gamification and AI 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: A total of 85% (n=10) of the HCPs, including midwives and doctors, were satisfied with the GAIN MHI mobile app, the user interface, and various content features. Engagement levels were robust (64.6%, SD 6.2%), notably impacting clinical routines and theoretical knowledge. The gamification and AI components garnered strong positive feedback, enhancing learning enjoyment (11/12, 92%). 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 health care fields. Conclusions: HCPs, especially those practicing in underserved areas, face challenges in accessing professional development opportunities, highlighting the need for innovative pedagogical approaches 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 updates on the most recent evidence-based clinical guidelines. Future research should investigate the feasibility of applying similar solutions on a larger scale to reach a wider range of HCPs and cover other health topics. The applicability of such solutions in different contexts and low-resource settings should also be explored.

Indexed as

artificial intelligencegamificationhealth providermaternal healthmedical knowledgemHealthprofessional development

Identifiers

PMID40929508
PMCPMC12422396

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.