Evidence map›Paper›PMID 42031992›Full record

Observational studyScientific reports2026

The impact of artificial intelligence-based emotional support tools on anxiety and stress levels in high-risk pregnant women.

Mirfat Mohamed Labib Elkashif, Mohammed Rahmath, Sally Abd-Elrahman Mohamed, Samia Gamal Awad Hamed, Doaa Mostafa Sheashaa, Mohamed Sayed Abdellatif

Abstract readObservational Study
In one paragraph

Observational study in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Mirfat Mohamed Labib ElkashifDepartment of Nursing Sciences, College of Applied Medical Sciences in Wadi Aldawaser,18616, Prince Sattam Bin Abdul-Aziz University, Al-Kharj, Saudi Arabia. m.alkashif@psau.edu.sa.ORCID http://orcid.org/0000-0001-6079-2511
Mohammed RahmathDepartment of Computer Engineering and Information, College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Sally Abd-Elrahman MohamedLecturer of Obstetric and Gynecological Nursing, Faculty of Nursing, Delta University for Science and Technology, Gamasa, Egypt.
Samia Gamal Awad HamedLecturer of psychiatric and mental health Nursing, Faculty of Nursing, Mansoura University, Mansoura, Egypt.
Doaa Mostafa SheashaaLecturer of Obstetric and Gynecological Nursing, Faculty of Nursing, Delta University for Science and Technology, Gamasa, Egypt.
Mohamed Sayed AbdellatifDepartment of Psychology, College of Education in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.

Funding

Prince Sattam Bin Abdulaziz University (PSAU/2025/00/0000)
6 · The paper itself

Abstract

High-risk pregnancies are associated with increased anxiety and stress. These elevated stress levels can negatively impact both maternal and fetal health. This study aims to explore the impact of artificial intelligence as emotional support tool in reducing anxiety and stress among high-risk pregnant women. The study employed a quasi-experimental design with pre- and post-intervention. A convenient sample of 300 high-risk pregnancies women participated in this study . This study was conducted at Al-Zahraa Hospital in New Damietta, Damietta Governorate, Egypt. Three tools were used for data collection, socio demographic data and Obstetric Data, Stress and Anxiety Scale and AI Usability and Perceived Emotional Support Scale.

resultsresults demonstrated a statistically significant decrease in pregnancy-related anxiety and stress scores following the four-week intervention period. Specifically, the mean total score dropped from 54.05 ± 5.99 before the intervention to 10.15 ± 3.82 after using the AI chatbot (p < 0.001).

conclusionThe present study concluded that AI emotional support tools can effectively reduce stress and anxiety in women with high-risk pregnancies and chatbot achieved high usability scores, indicating that participants found it easy to access, functional, and responsive. RECOMMENDATIONS: Based on our findings, we recommend integrating AI emotional support tools into standard prenatal care for high-risk pregnancies. Future efforts should focus on developing ethical guidelines and adapting these technologies to meet diverse patient needs across different healthcare settings.

trial registrationClinical trial registration number (PACTR202601891625550), the date of registration (05/1/2026).

Indexed as

AnxietyArtificial IntelligencePregnancy ComplicationsPregnancy, High-RiskPregnant PeopleStress, PsychologicalAdultFemaleHumansPregnancySocial SupportYoung AdultAI emotional supportDigital health interventionHigh-risk pregnancyMaternal mental healthPregnancy anxiety and stress reduction

Identifiers

PMID42031992
PMCPMC13462083

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.