Impact of Artificial Intelligence (AI) on Antenatal Care Services’ (ANCS) Adherence Among Multiparous
An increasing number of pregnant women are utilizing AI-based tools for health-related purposes as these technologies become more accessible. This study aims to explore the relationship between the use of digital platforms for health purposes and maternal adherence to prenatal healthcare services. A mixed-method design was employed, including a quantitative component with 320 pregnant multiparous women recruited through convenience sampling, and a qualitative component with 25 pregnant women selected through purposive sampling until data saturation. Data collection involved the Pregnancy Demographic Data Questionnaire and the Antenatal Care Scale (ANCS). The Results showed that 93.7% of participants had smartphones with internet access, and 84% used AI tools for 2-5 hours daily. Google was the most frequently used platform (57.9%), followed by mobile applications and YouTube (42.1%), while ChatGPT was used by 5.3%. AI tool usage was significantly associated with participants’ ANCS scores (p=0.001). However, 62.2% of participants demonstrated poor attitudes and intentions toward antenatal care adherence. The study identified multiple barriers to antenatal care adherence, including issues related to the healthcare system, users, and social support systems. In conclusion, the findings suggest that integrating respectful maternity care information into AI tools may encourage pregnant women to seek prenatal care. Future research should consider the diverse socioeconomic backgrounds of expectant mothers to better understand their attitudes and challenges in accessing prenatal services.
Authors
- Niven Basyouni (ORCID: https://orcid.org/0000-0002-7116-5625)
- Dua’a Al-Maghaireh (ORCID: https://orcid.org/0000-0001-5106-2381)
- Khitam Alsaqer (ORCID: https://orcid.org/0000-0002-2180-0432)
- Alaa Ali Yousef Bsoul
Publication Details
- Journal
- Palestinian medical and pharmaceutical journal/Palestinian medical & pharmaceutical journal
- Published
- 2025-05-01
- DOI
- https://doi.org/10.59049/2790-0231.10.4.2514
- Primary Topic
- Assisted Reproductive Technology and Twin Pregnancy
- Type
- article
- Field-Weighted Citation Impact
- 0.00