Evidence map›Paper›PMID 42358683›Full record

ArticleDigital health

Can digital prompting and the engagement of the husband influence the satisfaction of disadvantaged women with their reproductive health journey? A cross-sectional study from Lebanon.

Shadi Saleh, Nadine Sabra, Nour El Arnaout, Asmaa El Dakdouki, Khaled El Iskandarani, Zahraa Chamseddine, Mohamad Alameddine

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Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Shadi SalehGlobal Health Institute, American University of Beirut, Beirut, Lebanon.
Nadine SabraGlobal Health Institute, American University of Beirut, Beirut, Lebanon.
Nour El ArnaoutGlobal Health Institute, American University of Beirut, Beirut, Lebanon.ORCID https://orcid.org/0000-0002-3638-5905
Asmaa El DakdoukiGlobal Health Institute, American University of Beirut, Beirut, Lebanon.
Khaled El IskandaraniGlobal Health Institute, American University of Beirut, Beirut, Lebanon.ORCID https://orcid.org/0009-0009-5285-3914
Zahraa ChamseddineGlobal Health Institute, American University of Beirut, Beirut, Lebanon.
Mohamad AlameddineCollege of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Maternal health in Lebanon is severely impacted by the country's ongoing socioeconomic crisis, disproportionately affectivng disadvantaged Lebanese and refugee women due to limited healthcare access. Digital prompting interventions have improved antenatal and postnatal care utilization, particularly when the husband of the pregnant woman is also engaged. This study aims to assess the influence of digital prompting and husband engagement on the satisfaction of disadvantaged pregnant women in Lebanon with their reproductive health journeys, using the artificial intelligence (AI)-based gamified mHealth intervention titled "Gamification and Artificial Intelligence and mHealth Network for Maternal Health Improvement" (GAIN MHI). Methods: This study was conducted across seven primary healthcare centers in Lebanon, targeting pregnant women up to 16 weeks of gestation with mobile phone access. The intervention included digital messages for both pregnant women and their husbands, alongside the GAIN MHI App for healthcare providers. Over 11 months, data was collected to assess maternal satisfaction, antenatal care (ANC) attendance, and the role of husband engagement in supporting maternal wellbeing. Results: A total of 1028 pregnant women participated. Husband involvement significantly improved support for ANC visit, reminder's frequency, and psychological support. Women receiving mobile health support were more likely to report better physical health (odds ratio (OR) = 2.16; p = 0.03) and mental health (OR = 2.12; p = 0.03). Increased ANC visits were associated with higher likelihood of satisfaction with baby health (OR = 1.35; p = 0.05) and with service quality (OR = 2.68; p = 0.01). Husband support for ANC visits improved satisfaction both predelivery (OR = 2.15; p < 0.01) and postdelivery (OR = 2.05; p < 0.01). The combined effect of all support factors significantly boosted satisfaction with self-care predelivery (OR = 2.07; p < 0.01) and postdelivery (OR = 3.82; p < 0.01). Conclusion: The findings emphasize the importance of hybrid digital health models integrating mobile-based education, spousal support, and healthcare provider engagement to enhance maternal satisfaction and health outcomes. Future programs should adopt this approach to ensure comprehensive maternal care.

Indexed as

antenatal care (ANC)artificial intelligencedigital promptingdisadvantaged womengamificationhealthcare providerMaternal healthmHealthreproductive health

Identifiers

PMID42358683
PMCPMC13291574

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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.