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Smart Normal Labor: Healthcare Providers' Experience With an AI-Based Mobile App

NCT07720531 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 427

Last updated 2026-07-22

No results posted yet for this study

Summary

Pregnancy and childbirth are uniquely important events in women's lives because they are accompanied by major physical, emotional, and psychological changes. Maternal satisfaction, emotional well-being, and perceptions of childbirth are strongly influenced by the quality of labor management. A woman's childbirth experience is shaped by multiple factors, including communication, autonomy, and active participation in the decision-making process. These factors are widely recognized as important indicators of the quality of maternity care. \[1\]

Recent demographic changes and global population growth have placed increasing demands on healthcare systems, particularly maternal health services. High birth rates in some regions, combined with shortages of trained healthcare professionals, have created a need for scalable, adaptable, and innovative models of care. In response to these challenges, digital health technologies have emerged as promising tools to enhance the quality of maternity care and support both healthcare providers and pregnant women. \[2\]

Conditions

  • Normal Labor

Interventions

OTHER

The intervention group

participants who actively use the AI application during labor management,

Sponsors & Collaborators

  • Delta University for Science and Technology

    lead OTHER

Study Design

Allocation
NON_RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE
Model
PARALLEL

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-05-06
Primary Completion
2026-07-21
Completion
2026-07-30

Countries

  • Egypt

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07720531 on ClinicalTrials.gov